{ "schemaVersion": 1, "revisionDate": "2026-10-19", "pursuitsUrl": "https://semiaifoundry.com/agents/pursuits.json", "items": [ { "id": "intelligence-2026-10-19", "title": "Semiconductor Executive Intelligence - October 19, 2026", "category": "intelligence", "format": "Briefing", "description": "TSMC and ASML results, divided end markets, compute implementation choices, specialty manufacturing, and financing and policy. A weekly review distinguishing reported results, project milestones and unresolved risks.", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-10-19/", "publishedDate": "2026-10-19", "revisionDate": "2026-10-19", "author": "F. M. Cinnor", "topic": "Semiconductors", "series": "Semiconductor Executive Intelligence", "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ed5e74b105c0b7a785f2e62f4a3343789216ca1938edcb78cfb4d844da369352", "contentLength": 39641, "jsonUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-10-19.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-10-19.md", "sections": [ { "id": "section-1", "title": "Top Five Executive Takeaways" }, { "id": "section-2", "title": "Pricing & Utilization" }, { "id": "section-3", "title": "Market & Company Prints" }, { "id": "section-4", "title": "Technology & Roadmap" }, { "id": "section-5", "title": "CapEx & Footprint" }, { "id": "section-6", "title": "Policy & Regulation" }, { "id": "section-7", "title": "Strategic Implications & Risk Heat Map" }, { "id": "section-8", "title": "Explore further" }, { "id": "section-9", "title": "Disclaimer" } ], "citations": [ { "title": "TSMC", "url": "https://investor.tsmc.com/english/encrypt/files/encrypt_file/reports/2026-10/9f58506f6f114f91cefbf86820cc63297b39b130/3Q26%20Presentation%20%28E%29.pdf" }, { "title": "Nanya", "url": "https://www.nanya.com/Content/InvestorCalendar/6729_20261012_3Q26_Investor%20Conference_CN.pdf" }, { "title": "Micron", "url": "https://d18rn0p25nwr6d.cloudfront.net/CIK-0000723125/5dafce68-38e8-4cad-a8f3-ab56d04d73fd.pdf" }, { "title": "ASML", "url": "https://www.investor.asml.com/news-releases/news-release-details/asml-reports-eu11.7-billion-total-net-sales-and-eu5.0-billion-net-income-q3-2026" }, { "title": "TSMC filing", "url": "https://www.sec.gov/Archives/edgar/data/1046179/000104617926000726/a3q26e_withguidancexfinal.htm" }, { "title": "ASML Q2 results", "url": "https://www.investor.asml.com/news-releases/news-release-details/q2-2026-financial-results" }, { "title": "ASML", "url": "https://www.investor.asml.com/static-files/40c56a6b-1460-4f69-9340-6a869560d24b" }, { "title": "Schneider Electric", "url": "https://www.se.com/ww/en/assets/pdf/release-Q3-revenues-2026" }, { "title": "National Bureau of Statistics", "url": "https://www.stats.gov.cn/sj/zxfb/202610/t20261019_1965617.html" }, { "title": "CXMT disclosure", "url": "https://vip.stock.finance.sina.com.cn/corp/view/vCB_AllBulletinDetail.php?id=12647223" }, { "title": "CoreWeave", "url": "https://investors.coreweave.com/financials/quarterly-results/" }, { "title": "Reuters", "url": "https://www.reuters.com/business/coreweave-shares-bonds-headed-steep-weekly-losses-ai-borrowing-concerns-mount-2026-10-16/" }, { "title": "Reuters", "url": "https://www.reuters.com/business/finance/anthropics-q3-revenue-surges-45-nearly-17-billion-2026-10-14/" }, { "title": "Microsoft", "url": "https://blogs.microsoft.com/blog/2026/10/12/microsoft-to-expand-azure-maia-system-to-multi-gigawatt-deployments/" }, { "title": "AMD", "url": "https://newsroom.amd.com/news/open-rack-blueprint-scale-agentic-ai/" }, { "title": "Cisco", "url": "https://newsroom.cisco.com/c/r/newsroom/en/us/a/y2026/m10/cisco-advances-scalability-and-openness-at-ocp-2026.html" }, { "title": "Reuters", "url": "https://www.reuters.com/business/retail-consumer/amazon-says-its-ai-chips-will-work-with-popular-coding-language-challenging-2026-10-19/" }, { "title": "AWS Neuron", "url": "https://awsdocs-neuron.readthedocs-hosted.com/en/latest/frameworks/torch/pytorch-native-overview.html" }, { "title": "NVIDIA", "url": "https://blogs.nvidia.com/blog/ocp-global-summit-vera-rubin-scale-ai-factories/" }, { "title": "Reuters", "url": "https://www.reuters.com/world/asia-pacific/samsung-use-tsmc-technology-nvidias-next-generation-memory-chips-seoul-newspaper-2026-10-18/" }, { "title": "Reuters", "url": "https://www.reuters.com/business/besi-shares-fall-report-asml-is-working-rival-hybrid-bonding-product-2026-10-16/" }, { "title": "ASML", "url": "https://www.investor.asml.com/static-files/44d4bee1-b2f9-41b7-b3f8-1bf28f993fe6" }, { "title": "GlobalFoundries", "url": "https://gf.com/news-and-events/news/gf-unveils-roadmap-to-deliver-worlds-most-advanced-platform-for-physical-ai/" }, { "title": "Anthropic", "url": "https://www.anthropic.com/research/designing-efficient-quantum-circuits" }, { "title": "SEMI", "url": "https://www.semi.org/en/semi-press-release/global-300mm-fab-equipment-spending-to-reach-227-billion-in-2029-as-buildout-accelerates-semi-projects" }, { "title": "GlobalFoundries", "url": "https://gf.com/news-and-events/news/globalfoundries-selected-to-operate-two-new-semiconductor-fabs-in-new-york-under-landmark-us-japan-initiative/" }, { "title": "TSMC", "url": "https://investor.tsmc.com/english/encrypt/files/encrypt_file/reports/2026-10/eba4fac72873bf546b669bd2b5d973df5c93215d/TSMC%203Q26%20Transcript.pdf" }, { "title": "Nanya", "url": "https://www.nanya.com/en/IR/16?IRId=14188" }, { "title": "Tokyo Ohka Kogyo", "url": "https://www.tok.co.jp/news/2026/261008" }, { "title": "Sumitomo Bakelite", "url": "https://www.sumibe.co.jp/topics/2026/it-materials/1007_01/index.html" }, { "title": "Constellation", "url": "https://www.constellationenergy.com/news/2026/10/google-and-constellation-announce-landmark-agreement-to-bring-890-mw-of-new-nuclear-capacity-to-pjm-grid.html" }, { "title": "Qualcomm", "url": "https://www.qualcomm.com/news/releases/2026/10/qualcomm-statement-on-trial-verdict-win" }, { "title": "Reuters", "url": "https://www.reuters.com/legal/litigation/qualcomm-says-jury-found-arm-breached-license-agreement-2026-10-13/" }, { "title": "Reuters", "url": "https://www.reuters.com/world/asia-pacific/sk-hynix-conditions-new-us-factory-more-us-chip-equipment-exports-china-sources-2026-10-15/" }, { "title": "Yonhap", "url": "https://www.yna.co.kr/view/AKR20261019091151002" }, { "title": "Utility Dive", "url": "https://www.utilitydive.com/news/ferc-pjm-large-load-interconnection-iras-byonc/832716/" }, { "title": "Texas Instruments", "url": "https://www.ti.com/about-ti/newsroom/news-releases/2026/2026-10-01-texas-instruments-to-webcast-q3-2026-earnings-conference-call.html" }, { "title": "Explore AI Machinery Atlas", "url": "https://semiaifoundry.com/ai-atlas/" }, { "title": "Explore Semiconductor Pulse", "url": "https://semiaifoundry.com/semiconductor-pulse/" } ], "recordHash": "36584e872068bab4f65e8108b864489f034274614288d90281b4879b5c66729e" }, { "id": "semiconductor-pulse", "title": "Semiconductor Pulse", "category": "intelligence", "format": "Interactive analysis", "description": "Taiwan monthly signals, global quarterly context, and an integrated executive readout. Inspect company disclosures, segment-level evidence, and a fixed published edition.", "canonicalUrl": "https://semiaifoundry.com/semiconductor-pulse/", "publishedDate": "2026-10-13", "revisionDate": "2026-10-19", "author": null, "topic": "Semiconductors", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "2026-10-13-r2", "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [ { "id": "intelligence-2026-10-19", "relationship": "Executive intelligence", "description": "A dated assessment of industry developments, operating implications, and the evidence that changes the decision.", "title": "Semiconductor Executive Intelligence - October 19, 2026", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-10-19/" }, { "id": "atlas", "relationship": "Engineering context", "description": "Follow the systems beneath semiconductor markets, from materials and fabrication to accelerators and data centers.", "title": "AI Machinery Atlas v1.3.0", "canonicalUrl": "https://semiaifoundry.com/ai-atlas/" } ], "supersedes": [], "supersededBy": [], "contentHash": "131da031edcd72d868a8dc22105b1430fe8f113f27851d905f07eb8fb415839d", "contentLength": 36610, "jsonUrl": "https://semiaifoundry.com/agents/publications/semiconductor-pulse.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/semiconductor-pulse.md", "sections": [ { "id": "section-1", "title": "Semiconductor Pulse" }, { "id": "section-2", "title": "Growth is widespread across the selected cohort." }, { "id": "section-3", "title": "Participation narrowed on the same roster" }, { "id": "section-4", "title": "Growth reaches distinct corporate exposures" }, { "id": "section-5", "title": "Durability needs sustained growth and better economics" }, { "id": "section-6", "title": "What changed since August 2026" }, { "id": "section-7", "title": "Outliers and contrary signals" }, { "id": "section-8", "title": "September: a strong quarter with narrower participation" }, { "id": "section-9", "title": "A strong quarter ends with fewer companies growing" }, { "id": "section-10", "title": "Design and IP loses participation despite a growing quarter" }, { "id": "section-11", "title": "Equipment strengthens while foundries remain positive" }, { "id": "section-12", "title": "System assembly outpaces power, cooling and interconnect" }, { "id": "section-13", "title": "Lower annual growth still accompanies exceptional revenue levels" }, { "id": "section-14", "title": "Company explanations distinguish stock-building from final demand" }, { "id": "section-15", "title": "What the combined evidence reveals" }, { "id": "section-16", "title": "Optical chips & components: broad participation accompanies faster growth" }, { "id": "section-17", "title": "Memory is growing on a different scale" }, { "id": "section-18", "title": "Revenue growth is reaching margins unevenly" }, { "id": "section-19", "title": "Systems & ODM and power, cooling & interconnect: an unusually wide growth gap" }, { "id": "section-20", "title": "An earlier monthly report is useful before a forecasting lead is proven" }, { "id": "section-21", "title": "Evidence and interpretation" }, { "id": "section-22", "title": "Why Taiwan illuminates the global cycle" }, { "id": "section-23", "title": "69% of sub-10nm capacity" }, { "id": "section-24", "title": "From smaller chips to integrated systems" }, { "id": "section-25", "title": "Front end to far back end" }, { "id": "section-26", "title": "From front end to far back end" }, { "id": "section-27", "title": "Global implications" }, { "id": "section-28", "title": "Context sources" }, { "id": "section-29", "title": "Trace the changes across the ecosystem." }, { "id": "section-30", "title": "Segment changes since August 2026" }, { "id": "section-31", "title": "Quarterly evidence across the value chain." }, { "id": "section-32", "title": "NVIDIA" }, { "id": "section-33", "title": "TSMC" }, { "id": "section-34", "title": "Micron" }, { "id": "section-35", "title": "Tokyo Electron" }, { "id": "section-36", "title": "Advantest" }, { "id": "section-37", "title": "Renesas" }, { "id": "section-38", "title": "Synopsys Inc" }, { "id": "section-39", "title": "Entegris" }, { "id": "section-40", "title": "Arrow Electronics, Inc." }, { "id": "section-41", "title": "What to watch next" }, { "id": "section-42", "title": "Next monthly print · participation" }, { "id": "section-43", "title": "Next two prints · durability" }, { "id": "section-44", "title": "Next quarterly disclosures · economics" }, { "id": "section-45", "title": "Coverage & interpretation" }, { "id": "section-46", "title": "About this analysis" }, { "id": "section-47", "title": "Selected source credits" }, { "id": "section-48", "title": "Disclaimer" }, { "id": "section-49", "title": "Usage & rights" } ], "citations": [ { "title": "Explore live Pulse", "url": "https://semiaifoundry.com/semiconductor-pulse/" }, { "title": "Published editions", "url": "https://semiaifoundry.com/semiconductor-pulse/releases/" }, { "title": "Edition 2026-10-13-r2", "url": "https://semiaifoundry.com/semiconductor-pulse/releases/2026-10-13-r2/index.html" }, { "title": "Official Taiwan monthly disclosures", "url": "https://mops.twse.com.tw/" }, { "title": "MediaTek and design-company September disclosures", "url": "https://mopsov.twse.com.tw/nas/t21/sii/t21sc03_115_9_0.html" }, { "title": "TSMC September revenue", "url": "https://pr.cld.tsmc.com/english/news/3343" }, { "title": "TSMC financial calendar", "url": "https://investor.tsmc.com/english/financial-calendar" }, { "title": "Micron fiscal Q4 2026 actual results", "url": "https://www.sec.gov/Archives/edgar/data/723125/000072312526000018/a2026q4ex991-pressrelease.htm" }, { "title": "PCL September consolidation note", "url": "https://mopsov.twse.com.tw/nas/t21/sii/t21sc03_115_9_1.html" }, { "title": "Synopsys Inc · company disclosure", "url": "https://www.sec.gov/edgar/browse/?CIK=883241" }, { "title": "Veeco Instruments Inc · company disclosure", "url": "https://www.sec.gov/edgar/browse/?CIK=103145" }, { "title": "Acm Research, Inc. · company disclosure", "url": "https://www.sec.gov/edgar/browse/?CIK=1680062" }, { "title": "SIA / BCG · capacity benchmark", "url": "https://www.semiconductors.org/wp-content/uploads/2024/05/Report_Emerging-Resilience-in-the-Semiconductor-Supply-Chain.pdf#page=14" }, { "title": "TSMC · CoWoS", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm" }, { "title": "TSMC · 3DFabric", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/3DFabric.htm" }, { "title": "Source disclosure ↗", "url": "https://www.sec.gov/edgar/browse/?CIK=1045810" }, { "title": "Source disclosure ↗", "url": "https://investor.tsmc.com/english/quarterly-results/2026/q2" }, { "title": "Source disclosure ↗", "url": "https://www.tel.com/ir/library/report/i242su0000000goz-att/fy27q1tanshin-e.pdf" }, { "title": "Source disclosure ↗", "url": "https://www.advantest.com/document/en/investors/ir-library/result/E_FR_FY2026_1Q.pdf" }, { "title": "Source disclosure ↗", "url": "https://www.renesas.com/document/rep/earnings-report-2nd-quarter-ended-june-30-2026" }, { "title": "Source disclosure ↗", "url": "https://www.sec.gov/edgar/browse/?CIK=1101302" }, { "title": "Source disclosure ↗", "url": "https://www.sec.gov/edgar/browse/?CIK=7536" }, { "title": "Request additional information →", "url": "https://semiaifoundry.com/contact/?subject=semiconductor-pulse#contact-form" }, { "title": "Taipei Exchange: company disclosures", "url": "https://www.tpex.org.tw/" }, { "title": "Historical archive: FinMind (attribution)", "url": "https://finmind.github.io/" }, { "title": "SEC: company financial disclosures", "url": "https://www.sec.gov/edgar/search/" } ], "recordHash": "2305142b090cff9a9b9cbefbec571d08f7b8b00caf5d3d049ecb721c40b5411a" }, { "id": "intelligence-2026-10-12", "title": "Semiconductor Executive Intelligence - October 12, 2026", "category": "intelligence", "format": "Briefing", "description": "Memory contract repricing, PC shipment weakness, custom silicon, packaging agreements, financing, and policy. A revised weekly review separating reported results, company plans, and conditional forecasts.", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-10-12/", "publishedDate": "2026-10-12", "revisionDate": "2026-10-12", "author": "F. M. Cinnor", "topic": "Semiconductors", "series": "Semiconductor Executive Intelligence", "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "d5958d9ba4525b0b030b4ad1df260067656267d5435f04546433037506e67aaf", "contentLength": 42624, "jsonUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-10-12.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-10-12.md", "sections": [ { "id": "section-1", "title": "Top Five Executive Takeaways" }, { "id": "section-2", "title": "Pricing & Utilization" }, { "id": "section-3", "title": "Market & Company Prints" }, { "id": "section-4", "title": "Technology & Roadmap" }, { "id": "section-5", "title": "CapEx & Footprint" }, { "id": "section-6", "title": "Policy & Regulation" }, { "id": "section-7", "title": "Strategic Implications & Risk Heat Map" }, { "id": "section-8", "title": "Explore further" }, { "id": "section-9", "title": "Disclaimer" } ], "citations": [ { "title": "Nanya", "url": "https://www.nanya.com/en/Activity?Action=IR_investorcalendar_FileName&Id=5298&column=Presentation" }, { "title": "IDC", "url": "https://www.idc.com/resource-center/press-releases/idc-pc-tracker-3q26/" }, { "title": "DMASS", "url": "https://www.dmass.com/press-releases?catid=8&id=68%3Aeuropean-components-market-shows-strong-growth-in-2026-q2&view=article" }, { "title": "Dell’Oro", "url": "https://www.delloro.com/news/worldwide-telecom-capex-rises-5-percent-in-1h26/" }, { "title": "CNA", "url": "https://www.cna.com.tw/news/afe/202610060270.aspx" }, { "title": "Microsoft", "url": "https://blogs.microsoft.com/blog/2026/10/12/microsoft-to-expand-azure-maia-system-to-multi-gigawatt-deployments/" }, { "title": "GlobalFoundries", "url": "https://gf.com/news-and-events/news/globalfoundries-reaches-agreement-to-establish-us-based-supply-of-silicon-interposers-for-advanced-ai-packaging/" }, { "title": "Reuters", "url": "https://www.reuters.com/world/asia-pacific/broadcom-ceo-says-biggest-hurdle-ai-fuelled-tech-growth-is-capital-not-memory-2026-10-12/" }, { "title": "Micron", "url": "https://s25.q4cdn.com/621799436/files/doc_financials/2026/q4/Q4-FY26-Prepared-Remarks.pdf" }, { "title": "TrendForce spot update", "url": "https://www.trendforce.com/news/2026/10/07/insights-memory-spot-price-update-dram-spot-largely-sideways-as-holidays-month-end-effects-weigh/" }, { "title": "TrendForce contract outlook", "url": "https://www.trendforce.com.tw/presscenter/news/20260930-13256.html" }, { "title": "Omdia", "url": "https://omdia.tech.informa.com/pr/2026/oct/global-pc-shipments-fall-21percent-in-3q26-as-pull-forward-demand-subsides" }, { "title": "SIA", "url": "https://www.semiconductors.org/year-to-date-global-semiconductor-sales-top-1-trillion-through-august/" }, { "title": "TSMC", "url": "https://pr.tsmc.com/english/news/3343" }, { "title": "Samsung", "url": "https://news.samsung.com/global/samsung-electronics-announces-earnings-guidance-for-third-quarter-2026" }, { "title": "Hon Hai", "url": "https://www.foxconn.com/en-us/investor-relations/financial-information/reports?category=monthly" }, { "title": "CNA", "url": "https://www.cna.com.tw/news/afe/202610080279.aspx" }, { "title": "Dell’Oro", "url": "https://www.delloro.com/news/data-center-capex-grew-92-percent-in-2q-2026-driven-by-surging-ai-demand-and-memory-costs/" }, { "title": "PTC/Schneider", "url": "https://www.ptc.com/en/news/2026/schneider-electric-to-acquire-ptc" }, { "title": "Reuters", "url": "https://www.reuters.com/world/asia-pacific/australian-nvidia-backed-ai-data-centre-operator-firmus-shelves-ipo-2026-10-08/" }, { "title": "Bain", "url": "https://www.bain.com/insights/new-innovation-is-required-to-fund-ais-6-trillion-buildout-technology-report-2026/" }, { "title": "Synopsys", "url": "https://news.synopsys.com/2026-09-30-Synopsys-and-Amazon-Announce-Strategic%2C-Multi-year-IP-Agreement-for-Custom-Silicon-Collaboration-Also-Extends-to-Cloud-and-AI-Powered-Engineering" }, { "title": "Synopsys", "url": "https://investor.synopsys.com/news/news-details/2026/OpenAI-and-Synopsys-Announce-GPT-Synopsys-Frontier-Intelligence-to-Revolutionize-Chip-Design/default.aspx" }, { "title": "DeepSeek", "url": "https://github.com/deepseek-ai/DeepEP-Ascend" }, { "title": "Nvidia", "url": "https://docs.nvidia.com/cuda/cublas/index.html" }, { "title": "Microchip", "url": "https://www.microchip.com/en-us/about/news-releases/products/the-data-center-is-moving-to-800v-microchip-and-navitas-are-enabling-transition" }, { "title": "Infineon", "url": "https://www.infineon.com/press-release/2026/infpr202610-002" }, { "title": "TrendForce", "url": "https://www.trendforce.com.tw/presscenter/news/20261008-13259.html" }, { "title": "ficonTEC", "url": "https://www.ficontec.com/ficontec-and-htsi-announce-strategic-cooperation-to-scale-advanced-cpo-test-solutions-in-taiwan/" }, { "title": "Applied Materials", "url": "https://www.appliedmaterials.com/us/en/newsroom/press-releases/100626-applied-intel-collaborate-chipmaking-innovations-ai-driven-computing.html" }, { "title": "AlixLabs", "url": "https://www.alixlabs.com/2026/10/01/alixlabs-begins-aps-technology-evaluation-within-the-nanoic-pilot-line/" }, { "title": "SEMI", "url": "https://www.semi.org/en/products-services/market-data/300mm-fab-outlook" }, { "title": "Nanya earnings release", "url": "https://www.nanya.com/en/IR/16?IRId=14188" }, { "title": "China Securities Journal", "url": "https://epaper.cs.com.cn/zgzqb/html/2026-10/08/nw.D110000zgzqb_20261008_4-B014.htm" }, { "title": "Sangyo Times", "url": "https://www.sangyo-times.jp/article.aspx?ID=15225" }, { "title": "Infineon", "url": "https://www.infineon.com/press-release/2026/infpr202610-144" }, { "title": "SEAJ", "url": "https://www.seaj.or.jp/statistics/" }, { "title": "Chinese government portal", "url": "https://english.www.gov.cn/policies/latestreleases/202610/09/content_WS6ac8d93ec6d00ca5f9a0d95c.html" }, { "title": "Reuters", "url": "https://www.reuters.com/world/asia-pacific/us-fcc-vote-ban-chinese-labs-testing-us-electronics-2026-10-07/" }, { "title": "Reuters", "url": "https://www.reuters.com/legal/government/super-micro-contractor-pleads-guilty-scheme-divert-ai-servers-with-nvidia-chips-2026-10-09/" }, { "title": "IRS", "url": "https://www.irs.gov/credits-deductions/advanced-manufacturing-investment-credit" }, { "title": "SEMI", "url": "https://www.semi.org/en/semi-press-release/semi-brings-semiconductor-industry-tax-leaders-to-capitol-hill-to-urge-congress-to-extend-section-48d-semiconductor-investment-tax-credit" }, { "title": "EU Council", "url": "https://www.consilium.europa.eu/en/meetings/mpo/2026/10/att-wp-on-competitiveness-and-growth-compgro-industry-%28370246%29/" }, { "title": "SIA", "url": "https://www.semiconductors.org/sia-report-highlights-strategies-for-strengthening-supply-chains-supporting-the-u-s-chip-ecosystem/" }, { "title": "Explore AI Machinery Atlas", "url": "https://semiaifoundry.com/ai-atlas/" }, { "title": "Explore Semiconductor Pulse", "url": "https://semiaifoundry.com/semiconductor-pulse/" } ], "recordHash": "d6cd692de5b9636d21dbc1336b6036ed40309ec769c31c269edc297a0ef80ba0" }, { "id": "crg-options-exploration", "title": "Which options must survive?", "category": "learning", "format": "Guided exploration", "description": "Inspect how changing prices and decision classes expose the cost of discarded realization choices, then connect the example to CRG theory, published validation, and the released system.", "canonicalUrl": "https://semiaifoundry.com/learn/crg/preserving-options/", "publishedDate": "2026-10-07", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Computation and realization", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [ { "id": "crg-theory", "relationship": "Formal foundations", "description": "The Safe-Commitment Law characterizes which geometry must survive for each declared class of future decisions.", "title": "A Communication Theory of Computation Realization", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/" }, { "id": "crg-system", "relationship": "Operational realization", "description": "The released system carries options, scoped evidence, and commitment into replayable engineering workflows.", "title": "The commitment layer for AI-native chip design", "canonicalUrl": "https://semiaifoundry.com/updates/the-commitment-layer-for-ai-native-chip-design/" }, { "id": "atlas", "relationship": "Engineering context", "description": "Connected lessons explain the computational and physical machinery behind the realization question.", "title": "AI Machinery Atlas v1.3.0", "canonicalUrl": "https://semiaifoundry.com/ai-atlas/" } ], "supersedes": [], "supersededBy": [], "contentHash": "4d17814e7734a7ef42b0685d76288d383a5613d5b4c2d0f9929684466efd0600", "contentLength": 7433, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-options-exploration.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-options-exploration.md", "sections": [ { "id": "section-1", "title": "Which options must survive?" }, { "id": "section-2", "title": "Optimization cannot recover an option that has disappeared." }, { "id": "section-3", "title": "One computation. Three possible realizations." }, { "id": "section-4", "title": "The decision" }, { "id": "section-5", "title": "The retained family" }, { "id": "section-6", "title": "Change the price." }, { "id": "section-7", "title": "Change the decision class." }, { "id": "section-8", "title": "Safe for which future decisions?" }, { "id": "section-9", "title": "From a small example to a declared Transformer co-design case." }, { "id": "section-10", "title": "Keep the question connected to the machinery." }, { "id": "section-11", "title": "Inspect the formal contribution" }, { "id": "section-12", "title": "Explore the engineering context" }, { "id": "section-13", "title": "Examine the built system" } ], "citations": [ { "title": "Read the Safe-Commitment Law", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=8" }, { "title": "Geometry and decision classes, PDF pages 24–27", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=24" }, { "title": "Inspect the experiment and its boundaries", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=13" }, { "title": "Read the manuscripts ↗", "url": "https://semiaifoundry.com/research/computation-realization-geometry/#manuscripts" }, { "title": "The computation-to-realization gap ↗", "url": "https://semiaifoundry.com/learn/atlas/crg-problem-statement/" }, { "title": "Communication is the realization medium ↗", "url": "https://semiaifoundry.com/learn/atlas/crg-communication-graph/" }, { "title": "Architecture is a contract between computation and silicon ↗", "url": "https://semiaifoundry.com/learn/atlas/crg-architecture-contract/" }, { "title": "Explore CRG System ↗", "url": "https://semiaifoundry.com/updates/the-commitment-layer-for-ai-native-chip-design/" }, { "title": "Our complete Research in the Open commitment", "url": "https://semiaifoundry.com/research/#research-commitment" } ], "recordHash": "f9b8a6f53289a32aa56cfb6afa53f2fa310134d2bbbb68331703f4c7097098d3" }, { "id": "intelligence-2026-10-05", "title": "Semiconductor Executive Intelligence - October 5, 2026", "category": "intelligence", "format": "Briefing", "description": "Memory and compute pricing, AI-native design, manufacturing readiness, financing, and policy. The operating implications of the latest evidence across the semiconductor value chain.", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-10-05/", "publishedDate": "2026-10-05", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Semiconductors", "series": "Semiconductor Executive Intelligence", "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c73062f5f33fc085fbbbf454fa480e653086642d057a775aa880def16ba8db63", "contentLength": 49227, "jsonUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-10-05.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-10-05.md", "sections": [ { "id": "section-1", "title": "Top Five Executive Takeaways" }, { "id": "section-2", "title": "Pricing & Utilization" }, { "id": "section-3", "title": "Market & Company Prints" }, { "id": "section-4", "title": "Technology & Roadmap" }, { "id": "section-5", "title": "CapEx & Footprint" }, { "id": "section-6", "title": "Policy & Regulation" }, { "id": "section-7", "title": "Strategic Implications & Risk Heat Map" }, { "id": "section-8", "title": "Explore further" }, { "id": "section-9", "title": "Disclaimer" } ], "citations": [ { "title": "Micron prepared remarks, Sept. 30 — fiscal Q4", "url": "https://s25.q4cdn.com/621799436/files/doc_financials/2026/q4/Q4-FY26-Prepared-Remarks.pdf" }, { "title": "TrendForce, Sept. 30 — Q4 2026 outlook", "url": "https://www.trendforce.com/presscenter/news/20260930-13258.html" }, { "title": "TrendForce DRAMeXchange, Oct. 2", "url": "https://www.trendforce.com/price/dram/dram_spot" }, { "title": "TrendForce daily spot notes, Sept. 29–Oct. 2", "url": "https://www.trendforce.com/presscenter" }, { "title": "Parameter, Oct. 3", "url": "https://parameter.io/coreweave-crwv-raises-gpu-prices-35-as-104-billion-backlog-signals-tight-ai-capacity/" }, { "title": "VideoCardz/DIGITIMES, Sept. 8", "url": "https://videocardz.com/newz/intel-reportedly-plans-another-10-pc-cpu-price-increase-for-october-5" }, { "title": "Startup Fortune", "url": "https://startupfortune.com/amd-is-raising-ai-chip-prices-10-this-quarter-while-sparing-ryzen-gamers/" }, { "title": "ThinkComputers", "url": "https://thinkcomputers.org/amd-reportedly-preparing-10-q4-price-increase-for-gpus-chipsets-and-possibly-ryzen-cpus" }, { "title": "24/7 Wall St., Sept. 21", "url": "https://247wallst.com/investing/2026/09/21/rothschild-redburn-downgrades-nebius-coreweave-to-sell-on-lower-gpu-prices/" }, { "title": "SIA/WSTS, Oct. 5 — August data", "url": "https://www.semiconductors.org/year-to-date-global-semiconductor-sales-top-1-trillion-through-august/" }, { "title": "Korea Times, Oct. 1", "url": "https://www.koreatimes.co.kr/economy/20261001/koreas-sept-exports-hit-record-1209-bil-on-robust-chip-sales" }, { "title": "Seoul Economic Daily, Oct. 1", "url": "https://en.sedaily.com/finance/2026/10/01/koreas-september-exports-hit-record-1209-billion-on-chip" }, { "title": "Reuters via US News, Oct. 1", "url": "https://money.usnews.com/investing/news/articles/2026-09-30/south-korea-september-exports-rise-83-5-y-y-to-monthly-record" }, { "title": "Economic Daily News, Oct. 5 — Foxconn", "url": "https://money.udn.com/money/story/5710/9795876?from=edn_related_storybottom" }, { "title": "CNA, Oct. 5 — Chicony Power", "url": "https://money.udn.com/money/story/5612/9795814?from=edn_editorrelated_story" }, { "title": "Reuters, Oct. 1 — Mate 90 launch", "url": "https://www.reuters.com/business/retail-consumer/huawei-unveils-mate-90-phones-leans-homegrown-chip-design-offset-us-curbs-2026-10-01/" }, { "title": "Bloomberg via Deccan Chronicle, Oct. 5", "url": "https://www.deccanchronicle.com/technology/qualcomm-licenses-patents-on-huaweis-logicfolding-chip-tech-1993272" }, { "title": "AskTraders, Oct. 5", "url": "https://www.asktraders.com/analysis/qualcomm-and-huawei-agree-patent-cross-licence-with-no-terms-disclosed/" }, { "title": "Financial News, Oct. 5", "url": "https://www.financial-news.co.uk/qualcomm-to-pay-huawei-in-reversal-of-25-year-patent-deal/" }, { "title": "TechJuice, Oct. 5", "url": "https://www.techjuice.pk/qualcomm-licenses-huawei-logicfolding-chip-patents-cross-license-deal/" }, { "title": "ACM Shanghai disclosure, Oct. 1, via Sina", "url": "https://money.finance.sina.com.cn/corp/view/vCB_AllBulletinDetail.php?id=12630151&stockid=688082" }, { "title": "Reuters, Oct. 1; updated Oct. 2", "url": "https://www.reuters.com/business/broadcom-lend-anthropic-up-42-billion-lease-its-chips-filing-says-2026-10-01/" }, { "title": "Schneider Electric regulated release, Oct. 5", "url": "https://www.webdisclosure.com/press-release/schneider-electric-epa-su-schneider-electric-to-acquire-ptc-creating-the-next-level-of-energy-and-industrial-intelligence-dGRqi6qds3p" }, { "title": "Evertiq, Oct. 1 — Global Electronics Association August data", "url": "https://evertiq.com/news/2026-10-01-north-american-pcb-shipments-up-235-in-august-as-orders-pull-back" }, { "title": "Counterpoint, Sept. 29", "url": "https://counterpointresearch.com/en/insights/global-foundry-20-revenue-rises-25-yoy-to-a-record-966-billion-in-as-advanced" }, { "title": "Communications Today, Sept. 29", "url": "https://www.communicationstoday.co.in/global-foundry-2-0-revenue-jumps-25-yoy-to-96-6b-in-q2-2026/" }, { "title": "Synopsys, Sept. 30", "url": "https://www.prnewswire.com/news-releases/synopsys-details-growth-strategy-and-long-term-financial-model-at-2026-investor-day-302894684.html" }, { "title": "Futurum, Oct. 2", "url": "https://futurumgroup.com/insights/synopsys-investor-day-2026-turns-eda-into-a-royalty-and-ai-model-revenue-share-business/" }, { "title": "Yahoo Finance, Oct. 1", "url": "https://finance.yahoo.com/markets/stocks/articles/synopsys-shares-rise-2-5-122851662.html" }, { "title": "Bits&Chips, Sept. 29", "url": "https://bits-chips.com/article/mckinsey-raises-2030-chip-market-forecast-to-2-3t/" }, { "title": "Synopsys–OpenAI, Sept. 30", "url": "https://news.synopsys.com/2026-09-30-OpenAI-and-Synopsys-Announce-GPT-Synopsys-Frontier-Intelligence-to-Revolutionize-Chip-Design" }, { "title": "DeepSeek deployment documentation, reviewed Oct. 5", "url": "https://github.com/deepseek-ai/DeepEP-Ascend" }, { "title": "Benzinga/The Information, Sept. 27", "url": "https://www.benzinga.com/markets/tech/26/09/62013860/nvidia-chips-for-alibaba-bytedance-china-reportedly-green-lights-rtx-pro-5500-amid-us-curbs" }, { "title": "Cryptopolitan, Sept. 28", "url": "https://www.cryptopolitan.com/nvidia-rtx-pro-5500-us-export-curbs-beijing/" }, { "title": "ExplainX", "url": "https://explainx.ai/blog/china-bytedance-alibaba-nvidia-rtx-pro-5500-approval-2026" }, { "title": "NVIDIA cuBLAS 13.4 documentation, reviewed Oct. 5", "url": "https://docs.nvidia.com/cuda/cublas/index.html#floating-point-emulation" }, { "title": "FANUC–Hitachi, Sept. 30", "url": "https://www.fanuc.co.jp/ja/profile/pr/newsrelease/2026/news20260930.html" }, { "title": "Semiconductor Engineering, Oct. 1", "url": "https://semiengineering.com/the-hidden-challenges-of-edge-ai-design/" }, { "title": "Applied Materials–Besi, Oct. 1", "url": "https://www.appliedmaterials.com/us/en/newsroom/press-releases/100126-applied-besi-expand-partnership.html" }, { "title": "The Elec, Oct. 5", "url": "https://www.thelec.kr/news/articleView.html?idxno=63232" }, { "title": "Semiconductor Engineering, Sept. 10 — context", "url": "https://semiengineering.com/validation-gets-tested-at-1kw/" }, { "title": "ficonTEC–HTSI, Oct. 1", "url": "https://www.ficontec.com/cn/ficontec-and-htsi-announce-strategic-cooperation-to-scale-advanced-cpo-test-solutions-in-taiwan/" }, { "title": "JEDEC, Oct. 1", "url": "https://www.jedec.org/news/pressreleases/jedec%C2%AE-publishes-first-industry-wide-silicon-photonics-reliability-standard-ai" }, { "title": "Converge Digest, Oct. 5", "url": "https://convergedigest.com/jedec-jesd264-silicon-photonics-reliability-standard/" }, { "title": "AlixLabs partner announcement hosted by imec, Oct. 1", "url": "https://www.imec-int.com/en/press/alixlabs-begins-apstm-technology-evaluation-within-nanoic-pilot-line" }, { "title": "SemiAnalysis, Sept. 26", "url": "https://newsletter.semianalysis.com/p/intel-panther-lake-teardown" }, { "title": "TechPowerUp", "url": "https://www.techpowerup.com/353161/panther-lake-teardown-shows-intel-18a-near-tsmc-n3e-newer-tsmc-nodes-still-ahead" }, { "title": "The Elec, May 2026", "url": "https://www.thelec.net/news/articleView.html?idxno=10625" }, { "title": "FinanceFeeds", "url": "https://financefeeds.com/intel-foundry-1-million-high-na-wafers-customer-question/" }, { "title": "DIGITIMES, Oct. 5", "url": "https://www.digitimes.com/news/a20261005VL205/rapidus-silicon-design-manufacturing-automation.html" }, { "title": "SEMI, Q3 2026 300mm Fab Outlook", "url": "https://www.semi.org/en/products-services/market-data/300mm-fab-outlook" }, { "title": "Economic Daily News, Oct. 3", "url": "https://money.udn.com/money/story/5612/9791716" }, { "title": "Economic Daily News interview, Oct. 1", "url": "https://money.udn.com/money/story/5612/9788376" }, { "title": "CNA, Oct. 1; updated the same day", "url": "https://www.cna.com.tw/news/afe/202610010250.aspx" }, { "title": "Shinko’s Japanese disclosure, Sept. 30", "url": "https://www.shinko.co.jp/news/docs/20260930-01_jp.pdf" }, { "title": "Infineon, Oct. 1", "url": "https://www.infineon.com/press-release/2026/infpr202610-144" }, { "title": "LG Electronics, Oct. 1", "url": "https://www.lg.com/global/newsroom/news/eco-solution/lg-electronics-expands-chiller-production-for-ai-data-centers-to-three-factories/" }, { "title": "Bits&Chips, Oct. 5", "url": "https://bits-chips.com/article/xiver-secures-e28m-for-production-expansion/" }, { "title": "Reuters/Bloomberg via Yahoo Finance, Oct. 1", "url": "https://finance.yahoo.com/technology/articles/tsmc-mulls-multibillion-dollar-chip-135354924.html" }, { "title": "The Next Web, Oct. 2", "url": "https://thenextweb.com/news/tsmc-texas-fabs-europe-gap" }, { "title": "SEMI", "url": "https://www.semi.org/en/semi-press-release/semi-brings-semiconductor-industry-tax-leaders-to-capitol-hill-to-urge-congress-to-extend-section-48d-semiconductor-investment-tax-credit" }, { "title": "Thomson Reuters Tax", "url": "https://tax.thomsonreuters.com/news/bipartisan-push-for-semiconductor-credit-extension-expansion/" }, { "title": "Drive Tesla Canada, Oct. 5", "url": "https://driveteslacanada.ca/news/elon-musk-confirms-tsmc-terafab-talks/" }, { "title": "Crypto Briefing, Oct. 5", "url": "https://cryptobriefing.com/tsmc-terafab-talks-intel-shares-fall" }, { "title": "CNBC, Sept. 16", "url": "https://www.cnbc.com/2026/09/16/intel-sk-hynix-us-memory-chips.html" }, { "title": "The Standard/Reuters, Sept. 16", "url": "https://www.thestandard.com.hk/innovation/article/342998/SK-Hynix-in-talks-with-Intel-about-deal-to-make-memory-chips-in-US-for-the-first-time-sources-say" }, { "title": "TrendForce/Economic Daily News, Sept. 29", "url": "https://www.trendforce.com/news/2026/09/29/news-tsmc-reportedly-eyes-texas-expansion-that-could-top-us265b-vis-nxp-mulls-second-singapore-fab/" }, { "title": "Bits&Chips, Sept. 29", "url": "https://bits-chips.com/article/nxp-vis-joint-venture-weighs-second-singapore-fab/" }, { "title": "Entrepreneur APAC", "url": "https://apac.entrepreneur.com/business-news/vis-nxp-opens-6-7-bn-singapore-fab-as-physical-ai-broadens-chip-demand" }, { "title": "Hello Entrepreneurs, Oct. 3", "url": "https://helloentrepreneurs.com/technology/indias-semiconductor-fab-100460/" }, { "title": "IMARC Engineering", "url": "https://www.imarcengineering.com/news/india-semiconductor-manufacturing-infrastructure" }, { "title": "U.S. Department of Justice, Oct. 1", "url": "https://www.justice.gov/usao-cdca/pr/san-gabriel-man-arrested-federal-charges-alleging-he-smuggled-china-more-300-million" }, { "title": "Bloomberg, Oct. 1", "url": "https://www.bloomberg.com/news/features/2026-10-01/nvidia-faces-questions-over-china-ai-chip-smuggling-cases" }, { "title": "Original CTS report, September 2026", "url": "https://techstatecraft.org/duv/" }, { "title": "Bits&Chips, Oct. 5", "url": "https://bits-chips.com/article/report-calls-for-blanket-ban-on-duv-immersion-exports-to-china/" }, { "title": "Sen. Banks/Punchbowl, July", "url": "https://www.banks.senate.gov/news/in-the-news/tech-chips-bills-poised-for-ndaa-ride/" }, { "title": "CNAS", "url": "https://www.cnas.org/publications/commentary/cnas-insights-matching-policy-to-strategy-the-bill-to-control-chipmaking-equipment" }, { "title": "Sen. Banks, AI OVERWATCH", "url": "https://www.banks.senate.gov/news/press-releases/banks-secures-ai-overwatch-act-in-senate-ndaa/" }, { "title": "ITI letter, Sept. 3", "url": "https://www.itic.org/documents/NDAAExportControlsLetter.pdf" }, { "title": "CRS, Sept. 1", "url": "https://www.everycrsreport.com/reports/IN12704.html" }, { "title": "InvestorNews, Oct. 4", "url": "https://investornews.com/critical-minerals-rare-earths/technology-metals-report-10-04-2026-a-summit-without-a-rare-earth-deal-leaves-the-west-buying-its-way-to-supply" }, { "title": "Foreign Policy, Sept. 22", "url": "https://foreignpolicy.com/2026/09/22/china-rare-earth-xi-trump-meeting-summit/" }, { "title": "GMF", "url": "https://www.gmfus.org/news/trump-xi-summit-scorecard" }, { "title": "Asia Times, Oct. 2", "url": "https://asiatimes.com/2026/10/us-bans-chinese-data-center-gear-as-beijing-grounds-its-ai-talent" }, { "title": "Sen. McCormick, Sept. 25", "url": "https://www.mccormick.senate.gov/news/press-releases/senators-mccormick-gallego-cornyn-fetterman-introduce-bill-to-keep-chinese-transceivers-out-of-u-s-national-security-systems/" }, { "title": "AI Weekly, Sept. 26", "url": "https://aiweekly.co/alerts/senate-bill-would-bar-chinese-optical-transceivers-from-sensitive-us-national" }, { "title": "Reuters via US News, Sept. 25", "url": "https://www.usnews.com/news/politics/articles/2026-09-25/us-lawmakers-aim-to-keep-chinas-datacenter-tech-out-of-sensitive-government-systems" }, { "title": "TechCrunch, Oct. 3", "url": "https://techcrunch.com/2026/10/03/amazon-responds-to-data-center-backlash-says-it-no-longer-uses-ndas/" }, { "title": "Spotlight on America, Oct. 1", "url": "https://nbcmontana.com/news/spotlight-on-america/data-centers-emerge-as-flashpoint-in-2026-races-as-opposition-rises-take-the-power-back-documentary-economy-politics-midterms-virginia-protests-water-supply-electricity-cost-tax-credits-election" }, { "title": "NBC News", "url": "https://www.nbcnews.com/tech/tech-news/data-center-opposition-sharply-rising-2026-study-finds-rcna349728" }, { "title": "CNBC, Oct. 3", "url": "https://www.cnbc.com/2026/10/03/data-center-backlash-europe-asia-africa.html" }, { "title": "NYT via Inquirer, Oct. 4", "url": "https://inquirer.com/business/data-centers-wall-street-backlash-skepticism-investors-build-20261004.html" }, { "title": "Explore AI Machinery Atlas", "url": "https://semiaifoundry.com/ai-atlas/" }, { "title": "Explore Semiconductor Pulse", "url": "https://semiaifoundry.com/semiconductor-pulse/" } ], "recordHash": "022809064453e35178bdc17bfc67ec83f6c59193b7598640365796aab662f39d" }, { "id": "agentic-brain", "title": "The Agentic Brain", "category": "research", "format": "Paper", "description": "Dual-process metacognition, evidence-gated authority, and runtime governance. A control-plane framework for how AI agents reason, acquire evidence, and make consequential commitments.", "canonicalUrl": "https://semiaifoundry.com/research/the-agentic-brain/", "publishedDate": "2026-10-03", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Agentic intelligence", "series": null, "pursuitIds": [ "intelligent-agency-and-control" ], "license": "https://creativecommons.org/licenses/by/4.0/", "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "1.0.0", "status": "Preprint", "evidenceScope": "Formal results and executable finite-model validation under declared assumptions; not certification of arbitrary agents or production deployments.", "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [ { "id": "crg-theory", "relationship": "Decision preservation", "description": "CRG examines which implementation options must survive for future decisions, and when commitment preserves the required geometry.", "title": "A Communication Theory of Computation Realization", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/" }, { "id": "when-discovery-becomes-abundant", "relationship": "Founding perspective", "description": "The larger question of what becomes possible when intellectual exploration is no longer bounded by human attention alone.", "title": "When Discovery Becomes Abundant", "canonicalUrl": "https://semiaifoundry.com/publications/perspectives/when-discovery-becomes-abundant/" }, { "id": "atlas", "relationship": "The machinery of intelligence", "description": "The physical and computational foundations beneath learning systems, inference, and agent architectures.", "title": "AI Machinery Atlas v1.3.0", "canonicalUrl": "https://semiaifoundry.com/ai-atlas/" } ], "supersedes": [], "supersededBy": [], "contentHash": "768087e8c087afd8b51e9e58f410ffd7180c75f59eb2e2a82c892d2ac8dbc5c4", "contentLength": 7802, "jsonUrl": "https://semiaifoundry.com/agents/publications/agentic-brain.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/agentic-brain.md", "sections": [ { "id": "section-1", "title": "The Agentic Brain" }, { "id": "section-2", "title": "The agent optimizes part of the process that governs its own authority." }, { "id": "section-3", "title": "Two control questions. One coupled system." }, { "id": "section-4", "title": "Allocate cognition" }, { "id": "section-5", "title": "Preserve evidence" }, { "id": "section-6", "title": "Control effects" }, { "id": "section-7", "title": "An incentive-and-assurance framework for evidence-gated agency." }, { "id": "section-8", "title": "Price what evidence changes." }, { "id": "section-9", "title": "Explain acquisition, avoidance, and gaming." }, { "id": "section-10", "title": "Make evidence valid under selection." }, { "id": "section-11", "title": "Bind permission to what actually runs." }, { "id": "section-12", "title": "Complete logging can still leave a verifier blind spot fully exploitable." }, { "id": "section-13", "title": "A fully enumerated control environment" }, { "id": "section-14", "title": "Permission foresight changes the tradeoffs" }, { "id": "section-15", "title": "Evidence reaches a checked executor" }, { "id": "section-16", "title": "Calibration has a measurable price" }, { "id": "section-17", "title": "The scope of the result" }, { "id": "section-18", "title": "Read, inspect, and build on the work." }, { "id": "section-19", "title": "Research across the intelligence continuum." } ], "citations": [ { "title": "Open diagram ↗", "url": "https://semiaifoundry.com/assets/research/agentic-brain/control-plane.svg" }, { "title": "10.5281/zenodo.23125976", "url": "https://doi.org/10.5281/zenodo.23125976" }, { "title": "Creative Commons Attribution 4.0", "url": "https://creativecommons.org/licenses/by/4.0/" } ], "recordHash": "db163d3b6967994692862750ac58c862b99e25d28ddffd0e8b711540306b383d" }, { "id": "intelligence-2026-09-30", "title": "Semiconductor Executive Intelligence - 30 Sept, 2026", "category": "intelligence", "format": "Briefing", "description": "Foundry concentration, HBM scarcity, qualified packaging, and the financing behind AI infrastructure. What the signals establish—and what still requires evidence.", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-09-30/", "publishedDate": "2026-09-30", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Semiconductors", "series": "Semiconductor Executive Intelligence", "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "af3dae98628ee562cde58a2cb003287f1048743dcdd2406f8ece167dfbacd67e", "contentLength": 17276, "jsonUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-30.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-30.md", "sections": [ { "id": "section-1", "title": "Top Five Executive Takeaways" }, { "id": "section-2", "title": "Pricing & Utilization" }, { "id": "section-3", "title": "Market & Company Prints" }, { "id": "section-4", "title": "Technology & Roadmap" }, { "id": "section-5", "title": "CapEx & Footprint" }, { "id": "section-6", "title": "Policy & Regulation" }, { "id": "section-7", "title": "Strategic Implications & Risk Heat Map" }, { "id": "section-8", "title": "Explore further" } ], "citations": [ { "title": "Reuters, Sept. 29", "url": "https://www.reuters.com/world/asia-pacific/samsung-electronics-says-hbm-account-nearly-30-industry-dram-capacity-next-year-2026-09-29/" }, { "title": "TrendForce, Sept. 29", "url": "https://www.trendforce.com/presscenter/news/20260929-13255.html" }, { "title": "Micron Investor Relations", "url": "https://investors.micron.com/news/press-release/2026/Micron-Technology-to-Report-Fiscal-Fourth-Quarter-Results-on-September-30-2026/default.aspx" }, { "title": "Economic Daily News", "url": "https://money.udn.com/money/story/5612/9782072?from=edn_subcatelist_cate" }, { "title": "Semiconductor Engineering", "url": "https://semiengineering.com/tsmc-oip-chip-industry-growth-blows-past-forecast/" }, { "title": "Reuters", "url": "https://www.reuters.com/world/asia-pacific/australias-megaport-wins-687-million-ai-infrastructure-deals-raises-2027-2026-09-28/" }, { "title": "Dell’Oro Group, Sept. 10", "url": "https://www.delloro.com/news/wi-fi-7-surpasses-50-percent-of-the-market-with-wi-fi-8-on-the-horizon/" }, { "title": "International Federation of Robotics, Sept. 24", "url": "https://ifr.org/ifr-press-releases/news/five-million-robots-now-operate-in-factories-globally" }, { "title": "Scanfil, Sept. 29", "url": "https://www.scanfil.com/newsroom/stock_release/scanfil-raises-its-long-term-financial-targets" }, { "title": "Semiconductor Today, Sept. 28", "url": "https://www.semiconductor-today.com/news_items/2026/sep/riber-280926.shtml" }, { "title": "Cerebras/Gimlet", "url": "https://www.cerebras.ai/press-release/gimlet-labs-adds-cerebras-to-deliver-ultrafast-ai-inference-through-gimlet-cloud-deployment" }, { "title": "General Compute/Cerebras", "url": "https://www.generalcompute.com/blog/general-compute-cerebras-multi-year-agreement" }, { "title": "AMD/GlobeNewswire, Sept. 28", "url": "https://www.globenewswire.com/news-release/2026/09/28/3370256/0/en/amd-to-acquire-world-labs-to-advance-the-future-of-ai-compute.html" }, { "title": "EE Times, Sept. 25", "url": "https://www.eetimes.com/podcasts/can-disaggregated-memory-reshape-ai-inference/" }, { "title": "Montage Technology, Sept. 28", "url": "https://www.montage-tech.com/cn/Press_Releases/20260928" }, { "title": "The Elec, Sept. 29", "url": "https://www.thelec.kr/news/articleView.html?idxno=62979" }, { "title": "EE Times Japan, Sept. 29", "url": "https://eetimes.itmedia.co.jp/ee/articles/2609/29/news073.html" }, { "title": "EE Times Japan, Sept. 30", "url": "https://eetimes.itmedia.co.jp/ee/articles/2609/30/news065.html" }, { "title": "Economic Daily News/UDN, Sept. 28", "url": "https://money.udn.com/money/story/5612/9781570" }, { "title": "The Elec, Sept. 29", "url": "https://www.thelec.kr/news/articleView.html?idxno=62922" }, { "title": "Samsung Global Newsroom, Sept. 29", "url": "https://news.samsung.com/global/samsung-to-invest-usd-1-billion-in-ai-infrastructure-company-helix" }, { "title": "PicoJool, Sept. 24", "url": "https://www.picojool.com/news/picojool-raises-27-5-million-series-a-to-scale-optical-connectivity-for-ai-infrastructure" }, { "title": "Tata Electronics, Sept. 17", "url": "https://www.tataelectronics.com/w/tata-electronics-and-besi-enter-strategic-partnership-to-strengthen-advanced-packaging-capabilities" }, { "title": "Reuters, Sept. 29", "url": "https://www.reuters.com/legal/litigation/netlist-seeks-us-import-ban-micron-chips-used-google-nvidia-ai-computing-2026-09-29/" }, { "title": "USTR, Sept. 27", "url": "https://ustr.gov/about/policy-offices/press-office/press-releases/2026/september/ambassador-greer-issues-statement-announcement-recommendations-us-china-board-trade" }, { "title": "Explore AI Machinery Atlas", "url": "https://semiaifoundry.com/ai-atlas/" }, { "title": "Explore Semiconductor Pulse", "url": "https://semiaifoundry.com/semiconductor-pulse/" } ], "recordHash": "683173f5a50b3ab6e5a8108d62fc482be2706a31e9167078bf8d6ead57de7d0b" }, { "id": "intelligence-2026-09-25", "title": "Semiconductor Executive Intelligence - 25 Sept, 2026", "category": "intelligence", "format": "Briefing", "description": "Price-led growth versus physical demand, qualified alternatives, AI-enabled design flows, and the contractual consequences of infrastructure readiness.", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-09-25/", "publishedDate": "2026-09-25", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Semiconductors", "series": "Semiconductor Executive Intelligence", "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0cd3248c40e7a92c4911a37e97e166cb11538c693345d4e159e7dbc3600f6cc0", "contentLength": 21891, "jsonUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-25.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-25.md", "sections": [ { "id": "section-1", "title": "Top Five Executive Takeaways" }, { "id": "section-2", "title": "Pricing & Utilization" }, { "id": "section-3", "title": "Market & Company Prints" }, { "id": "section-4", "title": "Technology & Roadmap" }, { "id": "section-5", "title": "CapEx & Footprint" }, { "id": "section-6", "title": "Policy & Regulation" }, { "id": "section-7", "title": "Strategic Implications & Risk Heat Map" }, { "id": "section-8", "title": "Explore further" } ], "citations": [ { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260921-13246.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260924-13252.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260921-13247.html" }, { "title": "Ministry of Economic Affairs", "url": "https://www.moea.gov.tw/MNS/populace/news/News.aspx?kind=1&menu_id=40&news_id=124026" }, { "title": "McKinsey & Company", "url": "https://www.mckinsey.com/industries/semiconductors/our-insights/the-2-point-3-trillion-dollar-horizon-how-ai-is-rewriting-the-semiconductor-story" }, { "title": "ACEA", "url": "https://www.acea.auto/pc-registrations/new-car-registrations-5-3-in-august-2026-year-to-date-battery-electric-21-7-market-share/" }, { "title": "Cognex Investor Relations", "url": "https://investor.cognex.com/news/news-details/2026/Cognex-to-Acquire-RealSense-Expanding-Machine-Vision-Leadership-into-High-Growth-Robotic-Perception-Market/default.aspx" }, { "title": "Cadence Newsroom", "url": "https://newsroom.cadence.com/press-releases/press-release-details/2026/Cadence-Collaborates-With-TSMC-to-Deliver-Certified-Tool-Solutions-and-Industry-Leading-Silicon-Proven-UALink-IP-on-TSMC-Advanced-Processes/default.aspx" }, { "title": "Cadence Newsroom", "url": "https://newsroom.cadence.com/press-releases/press-release-details/2026/Cadence-Expands-ChipStack-AI-Super-Agent-with-a-New-Agent-for-RTL-Generation-and-Early-PPA-Optimization/default.aspx" }, { "title": "imec", "url": "https://www.imec-int.com/en/press/ic-link-imec-expands-collaboration-tsmc-accelerate-customer-access-advanced-node-chip-design" }, { "title": "AlibabaCloud", "url": "https://www.alibabacloud.com/en/press-room/alibaba-unveils-roadmap-on-full-stack-ai-strategy?_p_lc=1" }, { "title": "Cxmt", "url": "https://www.cxmt.com/news/info_97.html" }, { "title": "imec", "url": "https://www.imec-int.com/en/press/imec-debuts-100-ghz-gesi-avalanche-photodiode-apd-enabling-net-400-gbps-data-reception-just-5" }, { "title": "ATS", "url": "https://ats.net/en/press/ats-and-marvell-technology-expand-collaboration-to-support-next-generation-ai-infrastructure" }, { "title": "Yonhap News Agency", "url": "https://www.yna.co.kr/view/AKR20260922054000003" }, { "title": "The Business Times", "url": "https://www.businesstimes.com.sg/singapore/singapore-launches-national-semicon-brand-initiative-inks-rd-deals" }, { "title": "The Star", "url": "https://www.thestar.com.my/business/business-news/2026/09/21/kelington-partners-tata-electronics-on-dholera-semiconductor-fab" }, { "title": "Reuters", "url": "https://www.reuters.com/business/oracle-cites-force-majeure-shield-itself-controversial-data-center-bloomberg-2026-09-24/" }, { "title": "Texas.gov", "url": "http://texas.gov/" }, { "title": "Reuters", "url": "https://www.reuters.com/world/china/us-japanese-officials-discussed-chinas-yttrium-curbs-ahead-trump-xi-meeting-2026-09-24/" }, { "title": "Explore AI Machinery Atlas", "url": "https://semiaifoundry.com/ai-atlas/" }, { "title": "Explore Semiconductor Pulse", "url": "https://semiaifoundry.com/semiconductor-pulse/" } ], "recordHash": "9237e4344b6873277a794fe1c9349c2a8652038fc848a81b8575d87c0926cfb0" }, { "id": "fabqed", "title": "FabQED", "category": "company", "format": "Product platform", "description": "Fab-grade orchestration for semiconductor suppliers. One governed response connects fab-impacting escalations to containment, investigation, accountable action, reviewed customer updates, and signed closure.", "canonicalUrl": "https://semiaifoundry.com/portfolio/#fabqed-heading", "publishedDate": "2026-09-25", "revisionDate": "2026-10-07", "author": null, "topic": "Semiconductors", "series": null, "pursuitIds": [ "domain-native-execution" ], "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f3d3284d067165ee53cf9025686f469a60ab51f8e11db2a1183b204163aab722", "contentLength": 1297, "jsonUrl": "https://semiaifoundry.com/agents/publications/fabqed.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/fabqed.md", "sections": [ { "id": "section-1", "title": "FabQEDTM" } ], "citations": [ { "title": "Explore FabQED ↗", "url": "https://fabqed.com/" }, { "title": "Watch the FabQED introduction ↗", "url": "https://www.youtube.com/watch?v=BHn2kLv7bHo" } ], "recordHash": "5f6e85e184726e0209e593a4e0f1c29934c0b86aca89cce114761fff2f62ceb3" }, { "id": "intelligence-2026-09-22", "title": "Semiconductor Executive Intelligence - 22 Sept, 2026", "category": "intelligence", "format": "Briefing", "description": "Selective physical recovery, unequal memory economics, software-driven hardware decisions, and investments moving on different readiness clocks.", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-09-22/", "publishedDate": "2026-09-22", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Semiconductors", "series": "Semiconductor Executive Intelligence", "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "04af9233970a5357552064a254ec2d3a958ff41a30f3d94efbfb33e886ec5cde", "contentLength": 33399, "jsonUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-22.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-22.md", "sections": [ { "id": "section-1", "title": "Top Five Executive Takeaways" }, { "id": "section-2", "title": "Pricing & Utilization" }, { "id": "section-3", "title": "Market & Company Prints" }, { "id": "section-4", "title": "Technology & Roadmap" }, { "id": "section-5", "title": "CapEx & Footprint" }, { "id": "section-6", "title": "Policy & Regulation" }, { "id": "section-7", "title": "Strategic Implications & Risk Heat Map" }, { "id": "section-8", "title": "Explore further" } ], "citations": [ { "title": "UMC", "url": "https://www.umc.com/upload/media/08_Investors/Financials/Quarterly_Results/Quarterly_2020-2029_English_pdf/2026/Q2_2026/UMC26Q2_report.pdf" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260907-13219.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260914-13235.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260921-13246.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260922-13249.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260921-13247.html" }, { "title": "Ministry of Economic Affairs", "url": "https://www.moea.gov.tw/MNS/populace/news/News.aspx?kind=1&menu_id=40&news_id=124026" }, { "title": "Semiconductor Industry Association", "url": "https://www.semiconductors.org/global-semiconductor-sales-increase-6-4-month-to-month-in-july/" }, { "title": "DMASS", "url": "https://www.dmass.com/press-releases?catid=8&id=68%3Aeuropean-components-market-shows-strong-growth-in-2026-q2&view=article" }, { "title": "Samsung Global Newsroom", "url": "https://news.samsung.com/global/samsung-electronics-announces-second-quarter-2026-results" }, { "title": "Broadcom Inc.", "url": "https://investors.broadcom.com/news-releases/news-release-details/broadcom-inc-announces-third-quarter-fiscal-year-2026-financial" }, { "title": "株式会社アドバンテスト", "url": "https://www.advantest.com/ja/news/2026/qnpuno0000000cmx-att/J_Info_20260729.pdf" }, { "title": "Sina Finance", "url": "https://vip.stock.finance.sina.com.cn/corp/view/vCB_AllBulletinDetail.php?id=12505777&stockid=688012" }, { "title": "Infineon Technologies", "url": "https://www.infineon.com/press-release/2026/infpr202609-140" }, { "title": "NVIDIA Blog", "url": "https://blogs.nvidia.com/blog/vera-rubin-nvl72-mlperf-inference/" }, { "title": "Cadence Community", "url": "https://community.cadence.com/cadence_blogs_8/b/corporate-news/posts/accelerate-chip-design-with-arm-architecture-cadence-eda-tools-on-aws-graviton" }, { "title": "Qualcomm", "url": "https://www.qualcomm.com/news/releases/2026/09/qualcomm-announces-multi-generational-product-collaboration-with" }, { "title": "Semiconductor Engineering", "url": "https://semiengineering.com/how-robotics-and-intelligent-equipment-control-drive-next-gen-fab-productivity/" }, { "title": "SK hynix Newsroom", "url": "https://news.skhynix.com/en/ai-infra-summit-2026/" }, { "title": "Huawei", "url": "https://www.huawei.com/en/news/2026/9/hc-wang-keynote" }, { "title": "MediaTek", "url": "https://www.mediatek.com/press-room/mediatek-dimensity-9600-pro-sets-new-standard-for-flagship-smartphone-chips" }, { "title": "ST Newsroom", "url": "https://newsroom.st.com/media-center/press-item.html/stmicroelectronics-delivers-advanced-context-aware-sensors-in-st-sustainable-technology-framework-n4791.html" }, { "title": "onsemi", "url": "https://www.onsemi.com/company/newsroom/news-and-insights/onsemi-introduces-the-embedded-power-platform-a-breakthrough-architecture-for-the-ai-era" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260918-13241.html" }, { "title": "SEMI", "url": "https://www.semi.org/en/semi-press-release/global-semiconductor-equipment-billings-increased-23-percent-year-over-year-in-q2-2026-semi-reports" }, { "title": "EIR Parts", "url": "https://ssl4.eir-parts.net/doc/285A/tdnet/2878649/00.pdf" }, { "title": "Amkor Technology", "url": "https://ir.amkor.com/news-releases/news-release-details/amkor-technology-announces-phase-2-arizona-advanced-packaging" }, { "title": "GlobalFoundries", "url": "https://gf.com/news-and-events/news/globalfoundries-and-marvell-expand-collaboration-fornext-generation-optical-connectivity/" }, { "title": "Bits&Chips", "url": "https://bits-chips.com/article/tno-looks-to-double-photonic-chip-pilot-capacity/" }, { "title": "Evertiq", "url": "https://evertiq.com/design/2026-09-22-navitas-takes-5-million-stake-in-magnachip-to-deepen-sic-partnership" }, { "title": "CoreWeave", "url": "https://www.coreweave.com/news/coreweave-brings-up-multi-rack-nvidia-vera-rubin-nvl72-cluster" }, { "title": "Nexperia", "url": "https://www.nexperia.com/about/news-events/press-releases/Nexperia-and-Tata-Electronics-announce-strategic-partnership-across-semiconductor-manufacturing-technology-and-innovation" }, { "title": "Taiwan Semiconductor", "url": "https://pr.tsmc.com/english/news/3333" }, { "title": "Taiwan Semiconductor", "url": "https://pr.tsmc.com/english/news/3338" }, { "title": "Reuters", "url": "https://www.reuters.com/business/energy/texas-gov-abbott-halts-all-state-issued-permits-data-centers-until-grid-audit-is-2026-09-21/" }, { "title": "Digital Strategy", "url": "https://digital-strategy.ec.europa.eu/en/policies/cyber-resilience-act" }, { "title": "Reuters", "url": "https://www.reuters.com/business/finance/us-treasurys-bessent-chinas-he-launch-talks-ai-trade-critical-minerals-2026-09-20/" }, { "title": "Explore AI Machinery Atlas", "url": "https://semiaifoundry.com/ai-atlas/" }, { "title": "Explore Semiconductor Pulse", "url": "https://semiaifoundry.com/semiconductor-pulse/" } ], "recordHash": "409a018a26c64ebac4dae889dbf7d92d316cb0eb410bbfedcbcfb5423534b04c" }, { "id": "intelligence-2026-09-19", "title": "Semiconductor Executive Digest - 19 Sep, 2026", "category": "intelligence", "format": "Briefing", "description": "Uneven value capture in the AI buildout, competing compute architectures, manufacturing integration, and memory placement beyond HBM.", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-09-19/", "publishedDate": "2026-09-19", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Semiconductors", "series": "Semiconductor Executive Intelligence", "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b4b6fb3de09beb4f6a825c2bcc0cfc7cc7d8f913b613cf926f4a332924d1bba8", "contentLength": 24821, "jsonUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-19.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-19.md", "sections": [ { "id": "section-1", "title": "Top Five Executive Takeaways" }, { "id": "section-2", "title": "Pricing & Utilization" }, { "id": "section-3", "title": "Market & Company Prints" }, { "id": "section-4", "title": "Technology & Roadmap" }, { "id": "section-5", "title": "CapEx & Footprint" }, { "id": "section-6", "title": "Policy & Regulation" }, { "id": "section-7", "title": "Strategic Implications & Risk Heat Map" } ], "citations": [ { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260907-13219.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260914-13235.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260818-13186.html" }, { "title": "Reuters", "url": "https://www.reuters.com/technology/nebius-hikes-ai-cloud-prices-again-demand-computing-power-soars-2026-09-17/" }, { "title": "Reuters", "url": "https://www.reuters.com/business/world-at-work/micron-taiwan-union-presses-profit-sharing-demand-keeps-strike-preparations-2026-09-15/" }, { "title": "Semiconductor Industry Association", "url": "https://www.semiconductors.org/global-semiconductor-sales-increase-6-4-month-to-month-in-july/" }, { "title": "TSMC", "url": "https://investor.tsmc.com/english/monthly-revenue/2026" }, { "title": "Broadcom Inc.", "url": "https://investors.broadcom.com/news-releases/news-release-details/broadcom-inc-announces-third-quarter-fiscal-year-2026-financial" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260908-13222.html" }, { "title": "Infineon", "url": "https://www.infineon.com/press-release/2026/infpr202609-140" }, { "title": "NVIDIA Blog", "url": "https://blogs.nvidia.com/blog/vera-rubin-nvl72-mlperf-inference/" }, { "title": "Qualcomm", "url": "https://www.qualcomm.com/news/releases/2026/09/qualcomm-announces-multi-generational-product-collaboration-with" }, { "title": "SK hynix Newsroom", "url": "https://news.skhynix.com/en/ai-infra-summit-2026/" }, { "title": "Cadence Community", "url": "https://community.cadence.com/cadence_blogs_8/b/corporate-news/posts/accelerate-chip-design-with-arm-architecture-cadence-eda-tools-on-aws-graviton" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260918-13241.html" }, { "title": "MediaTek", "url": "https://www.mediatek.com/press-room/mediatek-dimensity-9600-pro-sets-new-standard-for-flagship-smartphone-chips" }, { "title": "onsemi", "url": "https://www.onsemi.com/company/news-media/press-announcements/en/onsemi-introduces-the-embedded-power-platform-a-breakthrough-architecture-for-the-ai-era" }, { "title": "The Financial Express", "url": "https://www.financialexpress.com/business/industry-lt-semiconductor-unveils-40-products-at-semicon-india-2026-eyes-digital-sovereignty-4342252/" }, { "title": "Huawei", "url": "https://www.huawei.com/en/news/2026/9/hc-wang-keynote" }, { "title": "CoreWeave", "url": "https://www.coreweave.com/news/coreweave-brings-up-multi-rack-nvidia-vera-rubin-nvl72-cluster" }, { "title": "Business Wire", "url": "https://www.businesswire.com/news/home/20260917137088/en/CoreWeave-Prices-Upsized-%243.7-Billion-Convertible-Senior-Notes-Offering" }, { "title": "Intel", "url": "https://www.intel.com/content/www/us/en/newsroom/news/intel-foundry/intel-foundry-asml-accelerate-industry-readiness-for-high-na-euv.html" }, { "title": "Amkor Technology", "url": "https://ir.amkor.com/news-releases/news-release-details/amkor-technology-announces-phase-2-arizona-advanced-packaging" }, { "title": "GlobalFoundries", "url": "https://gf.com/news-and-events/news/globalfoundries-and-marvell-expand-collaboration-fornext-generation-optical-connectivity/" }, { "title": "Nexperia", "url": "https://www.nexperia.com/about/news-events/press-releases/Nexperia-and-Tata-Electronics-announce-strategic-partnership-across-semiconductor-manufacturing-technology-and-innovation" }, { "title": "Reuters", "url": "https://www.reuters.com/world/asia-pacific/chinas-cxmt-eyes-flash-memory-push-amid-global-shortage-firm-take-samsung-ymtc-2026-09-18/" }, { "title": "SEMI", "url": "https://www.semi.org/en/semi-press-release/global-semiconductor-equipment-billings-increased-23-percent-year-over-year-in-q2-2026-semi-reports" }, { "title": "NVIDIA Blog", "url": "https://blogs.nvidia.com/blog/ai-energy-management-alliance/" }, { "title": "Reuters", "url": "https://www.reuters.com/business/finance/us-treasurys-bessent-chinas-he-meet-sunday-jpmorgan-headquarters-2026-09-19/" }, { "title": "House Committee on Energy and Commerce", "url": "https://energycommerce.house.gov/posts/ratepayer-protection-act-passes-house-with-strong-bipartisan-support" }, { "title": "Digital Strategy", "url": "https://digital-strategy.ec.europa.eu/en/policies/cyber-resilience-act" }, { "title": "SEMI", "url": "https://www.semi.org/en/semi-press-release/semi-europe-joins-resilient-consortium-to-strengthen-europes-silicon-and-silicon-carbide-raw-material-value-chains" } ], "recordHash": "fc65679a72d9d11d30d55efff205a609104e1eb113e9150c9c6a337bab9556f0" }, { "id": "intelligence-2026-09-17", "title": "Semiconductor Executive Digest — 17 Sep, 2026", "category": "intelligence", "format": "Briefing", "description": "The AI boom is broadening its supply chain—not yet the recovery. Separate specific process opportunities, powered capacity, and software efficiency from blanket growth assumptions.", "canonicalUrl": "https://semiaifoundry.com/publications/semiconductor-executive-intelligence/2026-09-17/", "publishedDate": "2026-09-17", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Semiconductors", "series": "Semiconductor Executive Intelligence", "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "8721369faa4212c629194bfb12c4c97bcd8d0403c1155dbadb01718fc63050de", "contentLength": 12401, "jsonUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-17.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/intelligence-2026-09-17.md", "sections": [ { "id": "section-1", "title": "Semiconductor Executive Digest" }, { "id": "section-2", "title": "The AI boom is broadening its supply chain—not yet the recovery" }, { "id": "section-3", "title": "What changed—and why it matters" }, { "id": "section-4", "title": "Specialty-process exposure to AI is becoming more tangible" }, { "id": "section-5", "title": "Demand, financing, and powered capacity need separate scorecards" }, { "id": "section-6", "title": "Software gains complicate the hardware-demand equation" }, { "id": "section-7", "title": "Industry pulse" }, { "id": "section-8", "title": "Connecting the dots: upstream growth can create downstream pressure" }, { "id": "section-9", "title": "Executive implications and next signposts" } ], "citations": [ { "title": "GlobalFoundries", "url": "https://gf.com/news-and-events/news/globalfoundries-and-marvell-expand-collaboration-fornext-generation-optical-connectivity/" }, { "title": "GlobalFoundries Inc.", "url": "https://investors.gf.com/news-releases/news-release-details/globalfoundries-and-monolithic-power-systems-form-manufacturing" }, { "title": "Reuters", "url": "https://www.reuters.com/legal/transactional/coreweave-launches-3-billion-convertible-debt-sale-2026-09-17/" }, { "title": "NVIDIA Blog", "url": "https://blogs.nvidia.com/blog/ai-energy-management-alliance/" }, { "title": "NVIDIA Blog", "url": "https://blogs.nvidia.com/blog/vera-rubin-nvl72-mlperf-inference/" }, { "title": "Semiconductor Industry Association", "url": "https://www.semiconductors.org/global-semiconductor-sales-increase-6-4-month-to-month-in-july/" }, { "title": "Broadcom Inc.", "url": "https://investors.broadcom.com/news-releases/news-release-details/broadcom-inc-announces-third-quarter-fiscal-year-2026-financial" }, { "title": "TSMC", "url": "https://investor.tsmc.com/english/monthly-revenue/2026" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260907-13219.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260818-13186.html" }, { "title": "PR Newswire", "url": "https://www.prnewswire.com/news-releases/ase-technology-holding-co-ltd-announces-monthly-net-revenues-302873068.html" }, { "title": "TrendForce", "url": "https://www.trendforce.com/presscenter/news/20260908-13222.html" }, { "title": "Amkor Technology", "url": "https://ir.amkor.com/news-releases/news-release-details/amkor-technology-reports-financial-results-second-quarter-2026" }, { "title": "SEMI", "url": "https://www.semi.org/en/semi-press-release/global-semiconductor-equipment-billings-increased-23-percent-year-over-year-in-q2-2026-semi-reports" }, { "title": "Reuters", "url": "https://www.reuters.com/world/asia-pacific/chinas-huawei-launch-two-new-ai-chips-2027-2026-09-17/" }, { "title": "The Wall Street Journal", "url": "https://www.wsj.com/economy/trade/u-s-pressures-mexico-to-box-out-chinas-ai-hardware-exports-4f708103" } ], "recordHash": "7c9de7328f209dc3960a179447e81a326b8fbd5fe2cbf51c06ff70e0df0d2c65" }, { "id": "when-discovery-becomes-abundant", "title": "When Discovery Becomes Abundant", "category": "perspectives", "format": "Essay", "description": "Every tool that made us smaller made our world larger. What becomes possible when intellectual exploration is no longer bounded by the number of human minds available to pursue it?", "canonicalUrl": "https://semiaifoundry.com/publications/perspectives/when-discovery-becomes-abundant/", "publishedDate": "2026-09-11", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Intelligence and discovery", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [ { "id": "agentic-brain", "relationship": "Research contribution", "description": "Dual-process metacognition, shared evidence, and the boundary between reasoning and authorized action.", "title": "The Agentic Brain", "canonicalUrl": "https://semiaifoundry.com/research/the-agentic-brain/" }, { "id": "crg-theory", "relationship": "From possibility to commitment", "description": "A computation-first theory of preserving valid realization choices before architecture becomes definitive.", "title": "A Communication Theory of Computation Realization", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/" } ], "supersedes": [], "supersededBy": [], "contentHash": "696a5ddce84e90ca3960703977f59a70ab8f07b8df24148f33048b039d16e927", "contentLength": 4934, "jsonUrl": "https://semiaifoundry.com/agents/publications/when-discovery-becomes-abundant.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/when-discovery-becomes-abundant.md", "sections": [], "citations": [ { "title": "https://semiaifoundry.com/assets/publications/when-discovery-becomes-abundant-illustration.png", "url": "https://semiaifoundry.com/assets/publications/when-discovery-becomes-abundant-illustration.png" }, { "title": "Research in the Open", "url": "https://semiaifoundry.com/research/" }, { "title": "@semiAIfoundry", "url": "https://x.com/semiAIfoundry" } ], "recordHash": "e0460ba1f005884682534979ad3059dbc34fc505a800607d6f6ac14d0e4e3029" }, { "id": "where-the-line-was", "title": "Where the line was", "category": "perspectives", "format": "Essay and film", "description": "A 183-year ledger of artificial intelligence's moving finish line, and what changes when AI moves from passing benchmarks to producing formally checkable knowledge.", "canonicalUrl": "https://semiaifoundry.com/updates/where-the-line-was/", "publishedDate": "2026-09-08", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Intelligence and discovery", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "eed3790eb1ff747ab09a4a83ccf5066a5785af6e35283f93b55992dc4b0629e5", "contentLength": 20332, "jsonUrl": "https://semiaifoundry.com/agents/publications/where-the-line-was.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/where-the-line-was.md", "sections": [ { "id": "section-1", "title": "Where the line was" }, { "id": "section-2", "title": "The short version" }, { "id": "section-3", "title": "The tether between Lovelace’s objection and Turing’s answer" }, { "id": "section-4", "title": "Turing’s list of things a machine will never do" }, { "id": "section-5", "title": "How long each line stood" }, { "id": "section-6", "title": "Who drew the line, and what they said when it fell" }, { "id": "section-7", "title": "Always about twenty years away" }, { "id": "section-8", "title": "Why the line moves" }, { "id": "section-9", "title": "The achievement is redescribed until it no longer signifies intelligence." }, { "id": "section-10", "title": "Success exposes what the test never measured." }, { "id": "section-11", "title": "A demonstrated capability is not yet an accepted outcome." }, { "id": "section-12", "title": "The line left the benchmark." }, { "id": "section-13", "title": "Discovery clock" }, { "id": "section-14", "title": "Formal verification clock" }, { "id": "section-15", "title": "Institutional clock" }, { "id": "section-16", "title": "Provenance is part of the result." }, { "id": "section-17", "title": "Will it ever end?" }, { "id": "section-18", "title": "The line is defined by an absence, and absences refill." }, { "id": "section-19", "title": "The question stops being asked." }, { "id": "section-20", "title": "The line leaves performance and enters acceptance." }, { "id": "section-21", "title": "Consequences" }, { "id": "section-22", "title": "Reliability and control" }, { "id": "section-23", "title": "Consciousness and moral status" }, { "id": "section-24", "title": "Why it feels new and old at the same time" }, { "id": "section-25", "title": "Receipts" } ], "citations": [ { "title": "[77]", "url": "https://semiaifoundry.com/updates/where-the-line-was/#sources" }, { "title": "Announcement", "url": "https://openai.com/index/navier-stokes-solution/" }, { "title": "Analytical paper", "url": "https://cdn.openai.com/pdf/32d9f210-8b73-45e0-91bc-82a30aef8a9a/navier-stokes.pdf" }, { "title": "Lean formalization", "url": "https://github.com/openai/NavierStokesAndEuler" }, { "title": "Clay rules", "url": "https://www.claymath.org/millennium-problems/rules/" } ], "recordHash": "72f67e79df99db0c9c8c686a04b019e2fc8fc2a57d6868c7f17f493b1b53444b" }, { "id": "atlas", "title": "AI Machinery Atlas v1.3.0", "category": "company", "format": "Interactive learning", "description": "311 lessons and 28 engineering experiences connect atoms, transistors, packages, accelerators, data centers, and learning systems. Includes guided experiences, a cinematic companion, and portable downloads.", "canonicalUrl": "https://semiaifoundry.com/ai-atlas/", "publishedDate": "2026-09-07", "revisionDate": "2026-10-07", "author": null, "topic": "The machinery of intelligence", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [ { "id": "crg-theory", "relationship": "Computation and realization", "description": "Explore the formal theory alongside the Atlas’s physical and computational engineering context.", "title": "A Communication Theory of Computation Realization", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/" }, { "id": "agentic-brain", "relationship": "Cognition and governance", "description": "Research on how agent systems reason, acquire evidence, and govern consequential commitments.", "title": "The Agentic Brain", "canonicalUrl": "https://semiaifoundry.com/research/the-agentic-brain/" } ], "supersedes": [], "supersededBy": [], "contentHash": "d5f8882905743d657d070761bad7aeb22df7c470ef1f89cf5b5ab8fce4b83824", "contentLength": 206, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas.md", "sections": [], "citations": [], "recordHash": "c0f192f8b4dbb592a64b192bb60bc4669f1cd4a0b3fd8393282364230322bf35" }, { "id": "crg-system", "title": "The commitment layer for AI-native chip design", "category": "company", "format": "System release", "description": "CRG Systems v1.5.0 connects formal theory, reproducible validation, independent replay, and an agent-native boundary in one cumulative system.", "canonicalUrl": "https://semiaifoundry.com/updates/the-commitment-layer-for-ai-native-chip-design/", "publishedDate": "2026-09-03", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Computation–Realization Geometry", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "1.5.0", "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [ { "id": "crg-theory", "relationship": "Theoretical foundations", "description": "The six-manuscript program establishes realization geometry, safe commitment, scaling, and architecture selection.", "title": "A Communication Theory of Computation Realization", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/" }, { "id": "agentic-brain", "relationship": "Agent authority", "description": "A separate framework for evidence-gated authority and runtime governance in consequential agent systems.", "title": "The Agentic Brain", "canonicalUrl": "https://semiaifoundry.com/research/the-agentic-brain/" } ], "supersedes": [], "supersededBy": [], "contentHash": "e6052b34d4b4405365f53ca357b206ee3791bd9212ae54137eba5f33cd50a711", "contentLength": 14480, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-system.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-system.md", "sections": [ { "id": "section-1", "title": "The commitment layer for AI-native chip design." }, { "id": "section-2", "title": "The bottleneck has moved." }, { "id": "section-3", "title": "The layer between possibility and commitment." }, { "id": "section-4", "title": "From a formal law to an agent-native system." }, { "id": "section-5", "title": "The cost of forgetting is measurable." }, { "id": "section-6", "title": "Build the policy without seeing the test." }, { "id": "section-7", "title": "Ask whether the retained set survives new conditions." }, { "id": "section-8", "title": "Change what is legally possible." }, { "id": "section-9", "title": "Held-out conditions" }, { "id": "section-10", "title": "Technology shift" }, { "id": "section-11", "title": "Six releases. One commitment stack." }, { "id": "section-12", "title": "An integrated system, not a thin wrapper." }, { "id": "section-13", "title": "The depth of the cumulative platform is measurable in years, not feature sprints." }, { "id": "section-14", "title": "A decision travels with its proof." }, { "id": "section-15", "title": "May this distinction be discarded?" }, { "id": "section-16", "title": "Independently replayable by design." }, { "id": "section-17", "title": "Scale begins with one commitment boundary." } ], "citations": [ { "title": "Explore v1.5.0 ↗", "url": "https://github.com/SemiAIFoundry/crg-systems/releases/tag/v1.5.0" }, { "title": "Read the evidence ↓", "url": "https://semiaifoundry.com/updates/the-commitment-layer-for-ai-native-chip-design/#evidence" }, { "title": "All updates", "url": "https://semiaifoundry.com/updates/" }, { "title": "CRG research", "url": "https://semiaifoundry.com/research/computation-realization-geometry/" }, { "title": "Read the frozen protocol ↗", "url": "https://github.com/SemiAIFoundry/computation-realization-geometry/blob/bf3964f300f3142470f40e0ff9b8d0548e17dd97/validation/retention/PREREGISTRATION.json" }, { "title": "Inspect the retained results ↗", "url": "https://github.com/SemiAIFoundry/computation-realization-geometry/blob/bf3964f300f3142470f40e0ff9b8d0548e17dd97/validation/retention/expected/experiment_summary.json" }, { "title": "Download v1.5.0 ↗", "url": "https://github.com/SemiAIFoundry/crg-systems/releases/download/v1.5.0/crg-systems-v1.5.0.tar.gz" }, { "title": "Inspect the v1.5.0 distribution ↗", "url": "https://github.com/SemiAIFoundry/crg-systems/tree/v1.5.0" }, { "title": "Discuss an integration →", "url": "https://semiaifoundry.com/contact/" }, { "title": "Verify and install v1.5.0 ↗", "url": "https://github.com/SemiAIFoundry/crg-systems/blob/v1.5.0/README.md#user-content-install" } ], "recordHash": "56ca01902497c27966f400dd9816bddc1c7ac22d63873211b20fadae9002968f" }, { "id": "crg-announcement", "title": "Addressing a 55-Year Gap in Chip Design", "category": "company", "format": "Research announcement", "description": "Introducing A Communication Theory of Computation Realization and CRG System, developed through human-led collaboration with GPT-5.6 and Claude Fable 5.", "canonicalUrl": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/", "publishedDate": "2026-08-25", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Computation–Realization Geometry", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "7936efd940b8ccf86be648a16250c096aaac0f57c3063dceb0c0d37418405a16", "contentLength": 7416, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-announcement.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-announcement.md", "sections": [ { "id": "section-1", "title": "Addressing a 55-Year Gap in Chip Design" }, { "id": "section-2", "title": "The order is the point." }, { "id": "section-3", "title": "From theory to an operational system" }, { "id": "section-4", "title": "Human-led and AI-enabled" } ], "citations": [ { "title": "All updates", "url": "https://semiaifoundry.com/updates/" }, { "title": "Research page", "url": "https://semiaifoundry.com/research/computation-realization-geometry/" }, { "title": "Semiconductor Industry Association", "url": "https://www.semiconductors.org/policies/chip-design/" }, { "title": "Canonical theoryA Communication Theory of Computation Realization↗", "url": "https://zenodo.org/records/22048090" }, { "title": "Complete technical manuscript corpusPreprint publication record↗", "url": "https://zenodo.org/search?q=metadata.creators.person_or_org.name%3A%22Cinnor%2C%20Fitih%20M.%22&l=list&p=1&s=10&sort=bestmatch" }, { "title": "Research repositoryPublic benchmarks, validation, and reproducibility corpus↗", "url": "https://github.com/SemiAIFoundry/computation-realization-geometry" }, { "title": "System repositoryCRG System software, documentation, and licensing↗", "url": "https://github.com/SemiAIFoundry/crg-systems" } ], "recordHash": "0aa3e3196c8d7b87f19cbf7f97d5321946b41385d238f812b6f599fdd362918c" }, { "id": "crg-theory", "title": "A Communication Theory of Computation Realization", "category": "research", "format": "Research program", "description": "Six manuscripts connect computation, legal transformations, realization geometry, and safe commitment, with public validation and an operational system.", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/", "publishedDate": "2026-08-25", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Computation–Realization Geometry", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": "https://creativecommons.org/licenses/by/4.0/", "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "3.2.0", "status": "Published research program with public validation and an operational software release", "evidenceScope": "The public pages describe formal results and reproducible validation. These are not claims of universal correctness, physical fabrication validation, or customer deployment.", "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [ { "id": "crg-options-exploration", "relationship": "Inspect the principle", "description": "A guided finite example makes the distinction between retaining today's winner and preserving future decision classes directly inspectable.", "title": "Which options must survive?", "canonicalUrl": "https://semiaifoundry.com/learn/crg/preserving-options/" }, { "id": "crg-system", "relationship": "System realization", "description": "The operational system carries realization choices, evidence, and commitment into independently replayable engineering workflows.", "title": "The commitment layer for AI-native chip design", "canonicalUrl": "https://semiaifoundry.com/updates/the-commitment-layer-for-ai-native-chip-design/" }, { "id": "agentic-brain", "relationship": "Evidence and authority", "description": "A related research question: how an agent’s evidence and reasoning govern its authority to make consequential commitments.", "title": "The Agentic Brain", "canonicalUrl": "https://semiaifoundry.com/research/the-agentic-brain/" }, { "id": "atlas", "relationship": "Physical and computational context", "description": "Explore the machinery connecting computation, chip design, fabrication, packaging, and operating infrastructure.", "title": "AI Machinery Atlas v1.3.0", "canonicalUrl": "https://semiaifoundry.com/ai-atlas/" } ], "supersedes": [], "supersededBy": [], "contentHash": "1e120049eb1dda1097d94c98612e7d7dcee19bd91995acd38dc4d5efbb5a6665", "contentLength": 16996, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-theory.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-theory.md", "sections": [ { "id": "section-1", "title": "A Communication Theory of Computation Realization" }, { "id": "section-2", "title": "Optimization can improve the design space it receives. It cannot recover a valid path erased before search began." }, { "id": "section-3", "title": "Computation–Realization Geometry maps the valid ways a computation can become physical." }, { "id": "section-4", "title": "Computation–Realization Geometry program map" }, { "id": "section-5", "title": "Discard an option only when the decisions still ahead could not tell that it was gone." }, { "id": "section-6", "title": "The complete CRG program." }, { "id": "section-7", "title": "Six-manuscript technical corpus" }, { "id": "section-8", "title": "Public validation corpus" }, { "id": "section-9", "title": "Operational realization control" }, { "id": "section-10", "title": "The commitment layer meets the agent." }, { "id": "section-11", "title": "Six manuscripts. One research program." }, { "id": "section-12", "title": "A Communication Theory of Computation Realization" }, { "id": "section-13", "title": "Computation-Realization Geometry" }, { "id": "section-14", "title": "A Generalized Rent Law from Computation-Realization Geometry" }, { "id": "section-15", "title": "Designing with Computation-Realization Geometry" }, { "id": "section-16", "title": "Structural Theorems for Computation-Realization Geometry" }, { "id": "section-17", "title": "Certified Nonseparable Co-Design of a Long-Context Transformer Superblock" }, { "id": "section-18", "title": "Theory, evidence, and implementation." }, { "id": "section-19", "title": "Human-led and AI-enabled." } ], "citations": [ { "title": "Semiconductor Industry Association ↗", "url": "https://www.semiconductors.org/policies/chip-design/" }, { "title": "https://semiaifoundry.com/assets/images/crg-program-map-v2.webp", "url": "https://semiaifoundry.com/assets/images/crg-program-map-v2.webp" }, { "title": "Read the v1.5 announcement", "url": "https://semiaifoundry.com/updates/the-commitment-layer-for-ai-native-chip-design/" }, { "title": "Read PDF", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf" }, { "title": "BibTeX", "url": "https://semiaifoundry.com/assets/research/crg/crg-canonical-theory.bib" }, { "title": "DOI", "url": "https://doi.org/10.5281/zenodo.22048090" }, { "title": "Read PDF", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf" }, { "title": "BibTeX", "url": "https://semiaifoundry.com/assets/research/crg/crg-foundations.bib" }, { "title": "DOI", "url": "https://doi.org/10.5281/zenodo.22050676" }, { "title": "Read PDF", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf" }, { "title": "BibTeX", "url": "https://semiaifoundry.com/assets/research/crg/crg-scaling.bib" }, { "title": "DOI", "url": "https://doi.org/10.5281/zenodo.22050605" }, { "title": "Read PDF", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf" }, { "title": "BibTeX", "url": "https://semiaifoundry.com/assets/research/crg/crg-design.bib" }, { "title": "DOI", "url": "https://doi.org/10.5281/zenodo.22050638" }, { "title": "Read PDF", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf" }, { "title": "BibTeX", "url": "https://semiaifoundry.com/assets/research/crg/crg-structural-theorems.bib" }, { "title": "DOI", "url": "https://doi.org/10.5281/zenodo.22050654" }, { "title": "Read PDF", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf" }, { "title": "BibTeX", "url": "https://semiaifoundry.com/assets/research/crg/crg-transformer.bib" }, { "title": "DOI", "url": "https://doi.org/10.5281/zenodo.22058422" }, { "title": "Corpus citations", "url": "https://semiaifoundry.com/assets/research/crg/citations.bib" }, { "title": "File checksums", "url": "https://semiaifoundry.com/assets/research/crg/SHA256SUMS.txt" }, { "title": "CC BY 4.0", "url": "https://creativecommons.org/licenses/by/4.0/" }, { "title": "Canonical theoryA Communication Theory of Computation Realization↗", "url": "https://zenodo.org/records/22048090" }, { "title": "Publication recordComplete six-manuscript corpus↗", "url": "https://semiaifoundry.com/research/computation-realization-geometry/#manuscripts" }, { "title": "Research repositoryBenchmarks, validation, and reproducibility↗", "url": "https://github.com/SemiAIFoundry/computation-realization-geometry" }, { "title": "System repositoryCRG System software, documentation, and licensing↗", "url": "https://github.com/SemiAIFoundry/crg-systems" }, { "title": "Read our Research in the Open commitment →", "url": "https://semiaifoundry.com/research/" }, { "title": "Read the release announcement →", "url": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/" } ], "recordHash": "838f6c2f76d66729223a758c9577e770e5932aedc7cb3cbc7232ef6b33b109f4" }, { "id": "research-commitment", "title": "Introducing semiAIfoundry Research", "category": "company", "format": "Research commitment", "description": "Our commitment to radical transparency, open knowledge, and recognized collaboration across all forms of intelligence.", "canonicalUrl": "https://semiaifoundry.com/updates/semiaifoundry-research-launch/", "publishedDate": "2026-06-01", "revisionDate": "2026-10-05", "author": "F. M. Cinnor", "topic": "Research in the Open", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "584d7630ac1de8fbdb4a29dcd1f38ceed9349c39750651eebc456a0c53cd273f", "contentLength": 1404, "jsonUrl": "https://semiaifoundry.com/agents/publications/research-commitment.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/research-commitment.md", "sections": [ { "id": "section-1", "title": "Introducing semiAIfoundryTM Research." } ], "citations": [ { "title": "All updates", "url": "https://semiaifoundry.com/updates/" }, { "title": "Read Research in the Open →", "url": "https://semiaifoundry.com/research/" } ], "recordHash": "6202f48bb6ebb6a1fbd1eb65b04d3691da186bb23357665eeb55876b972b943a" }, { "id": "inside-machinery", "title": "Inside the machinery", "category": "learning", "format": "Guided experience", "description": "A one-minute journey through ten captured Atlas moments, following actual data, learned state, verification, and recovery. Includes captions, a transcript, and links to the interactive lessons.", "canonicalUrl": "https://semiaifoundry.com/ai-atlas/connected.html", "publishedDate": null, "revisionDate": "2026-10-05", "author": null, "topic": "AI Machinery Atlas", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f18d0220c4cbd8756e4fb4b1941b31ce8450fac2f4ef33ec0f07ab11582e8219", "contentLength": 6329, "jsonUrl": "https://semiaifoundry.com/agents/publications/inside-machinery.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/inside-machinery.md", "sections": [ { "id": "section-1", "title": "Inside the machinery." }, { "id": "section-2", "title": "Transcript and lesson links" }, { "id": "section-3", "title": "0:00 Geometry becomes behavior" }, { "id": "section-4", "title": "0:06 A read must earn trust" }, { "id": "section-5", "title": "0:12 Boundaries before batches" }, { "id": "section-6", "title": "0:18 Weights that actually learn" }, { "id": "section-7", "title": "0:24 One objective, many owners" }, { "id": "section-8", "title": "0:30 Verify before accepting" }, { "id": "section-9", "title": "0:36 A reference becomes a proposal" }, { "id": "section-10", "title": "0:42 Inspect what really happened" }, { "id": "section-11", "title": "0:48 Prediction meets consequence" }, { "id": "section-12", "title": "0:54 Keep the work that survives" }, { "id": "section-13", "title": "The Ascent" } ], "citations": [ { "title": "download the video", "url": "https://semiaifoundry.com/ai-atlas/connected/connected.mp4" }, { "title": "Read the transcript", "url": "https://semiaifoundry.com/ai-atlas/connected.html#transcript" }, { "title": "Download plain text", "url": "https://semiaifoundry.com/ai-atlas/connected/transcript.txt" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#oxide-to-cell-acceptance~v=1&studio=cell" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#hbm-channel-generation-ras~v=1&studio=memory-workload" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#training-data~v=1&studio=data" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#tiny-causal-decoder~v=1&studio=learning" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#distributed-gradient-weighting~v=1&studio=distributed" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#speculative-decoding-verification~v=1&studio=serving" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#tool-loop~v=1&studio=retrieval" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#tool-loop~v=1&studio=automation" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#robot-feedback-control~v=1&studio=control" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#checkpoint-retained-work~v=1&studio=factory" }, { "title": "Watch The Ascent ↗", "url": "https://semiaifoundry.com/ai-atlas/ascent.html" } ], "recordHash": "90b324b5c50b9d1d1e6df702a509baac8ce04def1148cd0239ef592aadf966a2" }, { "id": "follow-machinery", "title": "Follow the machinery", "category": "learning", "format": "Guided experience", "description": "Eight engineering experiences connect material transformation, memory, realization choices, retained work, application results, and orbital constraints.", "canonicalUrl": "https://semiaifoundry.com/ai-atlas/walkthrough.html", "publishedDate": null, "revisionDate": "2026-10-05", "author": null, "topic": "AI Machinery Atlas", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "8ec9303cd954a17bf7e2347402f2fdcac33e59a840cffc83dd5d862f0af7947e", "contentLength": 4854, "jsonUrl": "https://semiaifoundry.com/agents/publications/follow-machinery.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/follow-machinery.md", "sections": [ { "id": "section-1", "title": "Follow the machinery." }, { "id": "section-2", "title": "Transcript and lesson links" }, { "id": "section-3", "title": "0:00 A material transformation" }, { "id": "section-4", "title": "0:09 A bit in a memory system" }, { "id": "section-5", "title": "0:17 One operation, four organizations" }, { "id": "section-6", "title": "0:25 From a contract to hardware" }, { "id": "section-7", "title": "0:32 Work that survives a restart" }, { "id": "section-8", "title": "0:40 Test the application result" }, { "id": "section-9", "title": "0:48 Close the orbital budgets" }, { "id": "section-10", "title": "0:54 Breakthroughs and finite capacity" }, { "id": "section-11", "title": "The Ascent" } ], "citations": [ { "title": "download the video", "url": "https://semiaifoundry.com/ai-atlas/walkthrough/navigation.mp4" }, { "title": "Read the transcript", "url": "https://semiaifoundry.com/ai-atlas/walkthrough.html#transcript" }, { "title": "Download plain text", "url": "https://semiaifoundry.com/ai-atlas/walkthrough/transcript.txt" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#thermal-oxidation-interface~v=1&studio=fabrication" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#hbm-channel-generation-ras~v=1&studio=memory" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#systolic-array-dataflow~v=1&studio=architecture" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#chip-rtl-verification~v=1&studio=realization" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#retained-work-restart-boundary~v=1&studio=hall" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#evaluation~v=1&studio=applications" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#orbital-solar-storage~v=1&studio=orbital" }, { "title": "Open the experience and related lesson ↗", "url": "https://semiaifoundry.com/ai-atlas/#compatible-supply-capacity~v=1&studio=progress" }, { "title": "Watch The Ascent ↗", "url": "https://semiaifoundry.com/ai-atlas/ascent.html" } ], "recordHash": "1be75eed8df6da680a8766bf3562b79bcd21a0d994907ed914f6766a82f82923" }, { "id": "ascent", "title": "The Ascent", "category": "learning", "format": "Film", "description": "A cinematic journey through modern AI, from attention and early GPT systems toward the frontier.", "canonicalUrl": "https://semiaifoundry.com/ai-atlas/ascent.html", "publishedDate": null, "revisionDate": "2026-10-05", "author": null, "topic": "AI Machinery Atlas", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "30634d4c73551012348e51eed3b574608662f9bece37c49d270d8a0343ab6946", "contentLength": 96, "jsonUrl": "https://semiaifoundry.com/agents/publications/ascent.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/ascent.md", "sections": [], "citations": [], "recordHash": "4cf2c5e2856ac785aa17508d537a03c947f3ccc9b91c267217a89e95a55c3ca5" }, { "id": "line-film", "title": "Where the line was: the film", "category": "perspectives", "format": "Film", "description": "The companion film follows the recurring argument over machine intelligence and the shift from benchmark performance to formally checkable discovery.", "canonicalUrl": "https://semiaifoundry.com/updates/where-the-line-was/#film", "publishedDate": null, "revisionDate": "2026-10-05", "author": null, "topic": "Intelligence and discovery", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "7c106ffa1ac6247aae6177b69aea15515c1be248748287107409460cbb1c39fc", "contentLength": 1181, "jsonUrl": "https://semiaifoundry.com/agents/publications/line-film.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/line-film.md", "sections": [ { "id": "section-1", "title": "Where the line was" } ], "citations": [], "recordHash": "4b86e757ac5c222fa65f817a03ba12164a67249bdbe9ceaeacd357b4400fb287" }, { "id": "fabqed-film", "title": "Introducing FabQED", "category": "company", "format": "Introduction film", "description": "The platform introduction for fab-grade orchestration of semiconductor supplier workflows.", "canonicalUrl": "https://www.youtube.com/watch?v=BHn2kLv7bHo", "publishedDate": null, "revisionDate": "2026-10-05", "author": null, "topic": "FabQED", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "External media; full transcript not indexed", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "30364a80c43992ad5e0659bd8923ab31ae2d7355b102c2acc3dc77df65f29dab", "contentLength": 162, "jsonUrl": "https://semiaifoundry.com/agents/publications/fabqed-film.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/fabqed-film.md", "sections": [], "citations": [ { "title": "Open the original media", "url": "https://www.youtube.com/watch?v=BHn2kLv7bHo" } ], "recordHash": "8558ec7fcb59ad2634980e5a699f835d49b686ea9a468de62099ee1a432f7ce9" }, { "id": "foundry", "title": "semiAIfoundry", "category": "company", "format": "Public statement", "description": "semiAIfoundry is a research and technology development platform applying advanced AI and disciplined execution to frontier scientific and technological challenges.", "canonicalUrl": "https://semiaifoundry.com/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "2ed4d4d056cdd8602a194c532d3697e2912d66f90faa40a034472e265268e942", "contentLength": 5351, "jsonUrl": "https://semiaifoundry.com/agents/publications/foundry.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/foundry.md", "sections": [ { "id": "section-1", "title": "From frontier possibility to real-world impact." }, { "id": "section-2", "title": "Latest publications" }, { "id": "section-3", "title": "The Agentic Brain" }, { "id": "section-4", "title": "A Communication Theory of Computation Realization" }, { "id": "section-5", "title": "When Discovery Becomes Abundant" }, { "id": "section-6", "title": "The commitment layer for AI-native chip design" }, { "id": "section-7", "title": "The execution gap." }, { "id": "section-8", "title": "Domain-specific orchestration compounds execution." }, { "id": "section-9", "title": "Expanding capability" }, { "id": "section-10", "title": "Acceptance constraint" }, { "id": "section-11", "title": "Verified value throughput" }, { "id": "section-12", "title": "Have a research, technology development, or collaboration inquiry?" }, { "id": "section-13", "title": "Inside the machinery of intelligence." } ], "citations": [ { "title": "Explore our focus →", "url": "https://semiaifoundry.com/portfolio/" }, { "title": "Explore the research", "url": "https://semiaifoundry.com/research/the-agentic-brain/" }, { "title": "Explore the research", "url": "https://semiaifoundry.com/research/computation-realization-geometry/" }, { "title": "Read the essay", "url": "https://semiaifoundry.com/publications/perspectives/when-discovery-becomes-abundant/" }, { "title": "Read the update", "url": "https://semiaifoundry.com/updates/the-commitment-layer-for-ai-native-chip-design/" }, { "title": "Explore all publications", "url": "https://semiaifoundry.com/publications/" }, { "title": "Contact us", "url": "https://semiaifoundry.com/contact/" }, { "title": "Explore the AI Atlas →", "url": "https://semiaifoundry.com/ai-atlas/" }, { "title": "Watch The Ascent film", "url": "https://semiaifoundry.com/ai-atlas/ascent.html" }, { "title": "GitHub release · v1.3.0", "url": "https://github.com/SemiAIFoundry/ai-machinery-atlas/releases/tag/v1.3.0" }, { "title": "Download source", "url": "https://semiaifoundry.com/downloads/ai-atlas/ai-machinery-atlas-v1.3.0-source.zip" }, { "title": "Commercial use requires a separate license.", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" } ], "recordHash": "bbe108195822a874d8f0a26653b03ac731bfdc1447094d4fc2583128a33d05b3" }, { "id": "research-mission", "title": "Research in the Open", "category": "research", "format": "Public statement", "description": "semiAIfoundry Research’s commitment to radical transparency, open knowledge, and recognized collaboration across all forms of intelligence.", "canonicalUrl": "https://semiaifoundry.com/research/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "d92f4adc88a786f1c7883c16a69721ef15278a804788f1666042ba39758dff0f", "contentLength": 4414, "jsonUrl": "https://semiaifoundry.com/agents/publications/research-mission.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/research-mission.md", "sections": [ { "id": "section-1", "title": "Research in the Open" }, { "id": "section-2", "title": "Work placed in the public record." }, { "id": "section-3", "title": "The Agentic Brain" }, { "id": "section-4", "title": "A Communication Theory of Computation Realization" } ], "citations": [ { "title": "Explore current research →", "url": "https://semiaifoundry.com/research/#current-research-heading" }, { "title": "Read our complete research commitment ↓", "url": "https://semiaifoundry.com/research/#research-commitment" }, { "title": "Agentic intelligenceOctober 3, 2026\n \n The Agentic Brain\n A control-plane framework connecting dual-process cognition, evidence-gated authority, and runtime governance. Formal results and executable finite-model validation show how evidence changes both decision quality and permission to act.\n Explore the research →", "url": "https://semiaifoundry.com/research/the-agentic-brain/" }, { "title": "Computation–Realization GeometryAugust 2026\n \n A Communication Theory of Computation Realization\n A formal framework for preserving valid implementation choices before architecture becomes definitive—and for knowing when commitment is safe.\n Explore the research →", "url": "https://semiaifoundry.com/research/computation-realization-geometry/" }, { "title": "Explore CRG: which options must survive? ↗", "url": "https://semiaifoundry.com/learn/crg/preserving-options/" } ], "recordHash": "f7692ea473a0b33ad3048f023278ca97eefafe09b66a7c404f05ad80921b4681" }, { "id": "founder-background", "title": "About semiAIfoundry", "category": "company", "format": "Public statement", "description": "semiAIfoundry is a founder-led research and technology development platform applying advanced AI to frontier scientific and technological challenges.", "canonicalUrl": "https://semiaifoundry.com/about/", "publishedDate": null, "revisionDate": "2026-10-05", "author": null, "topic": null, "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": null, "status": "Published public page", "evidenceScope": null, "contentCoverage": "published-page", "artifactUrl": null, "interactiveUrl": null, "related": [], "supersedes": [], "supersededBy": [], "contentHash": "142a663956407ed8fdaa6e8470a85f730d67b4ac0ba2910fb41309b3ed0fbd87", "contentLength": 5117, "jsonUrl": "https://semiaifoundry.com/agents/publications/founder-background.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/founder-background.md", "sections": [ { "id": "section-1", "title": "Research, technology, and execution—brought together." }, { "id": "section-2", "title": "Why we exist" }, { "id": "section-3", "title": "Fitih “Fitz” Cinnor, Ph.D., MBA" }, { "id": "section-4", "title": "Domain depth, rigorous inquiry, disciplined execution." }, { "id": "section-5", "title": "01 / Start with the challenge" }, { "id": "section-6", "title": "02 / Make evidence operational" }, { "id": "section-7", "title": "03 / Extend expert capacity" }, { "id": "section-8", "title": "04 / Design for impact" } ], "citations": [ { "title": "Explore our focus →", "url": "https://semiaifoundry.com/portfolio/" }, { "title": "Contact semiAIfoundryTM →", "url": "https://semiaifoundry.com/contact/" } ], "recordHash": "3347271aab33b1e7515904941a914c5b3c48f67079062cd5943a9d93533f4d54" }, { "id": "crg-canonical-theory", "title": "A Communication Theory of Computation Realization: Resource-Conditioned Geometry of Legal Realizations and the Safe-Commitment Law", "category": "research", "format": "Manuscript", "description": "A computation specifies a semantic relation, not one inevitable algorithm, hierarchy, architecture, or physical implementation. This article introduces Computation–Realization Geometry (CRG), a computation-first theory of the legal ways a declared computation can become...", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/#crg-canonical-theory", "publishedDate": "2026-08-24", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Canonical theory", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": "https://creativecommons.org/licenses/by/4.0/", "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "3.2.0", "status": "Published open-access manuscript", "evidenceScope": null, "contentCoverage": "extracted-pdf-text", "artifactUrl": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf", "interactiveUrl": null, "pageCount": 87, "pageNumbering": "One-based PDF file pages, not printed manuscript page labels.", "textNotice": "Extracted PDF text; equations and layout should be checked against the original PDF.", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3ddefe3861a42a06cd6503b7acd8db057928d7e2213531b020eeecf9209884aa", "contentLength": 285193, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-canonical-theory.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-canonical-theory.md", "sections": [ { "id": "section-1", "title": "A Communication Theory of Computation Realization: Resource-Conditioned Geometry of Legal Realizations and the Safe-Commitment Law" }, { "id": "section-2", "title": "Abstract" }, { "id": "section-3", "title": "Extracted manuscript text" }, { "id": "pdf-page-1", "title": "PDF page 1" }, { "id": "pdf-page-2", "title": "PDF page 2" }, { "id": "pdf-page-3", "title": "PDF page 3" }, { "id": "pdf-page-4", "title": "PDF page 4" }, { "id": "pdf-page-5", "title": "PDF page 5" }, { "id": "pdf-page-6", "title": "PDF page 6" }, { "id": "pdf-page-7", "title": "PDF page 7" }, { "id": "pdf-page-8", "title": "PDF page 8" }, { "id": "pdf-page-9", "title": "PDF page 9" }, { "id": "pdf-page-10", "title": "PDF page 10" }, { "id": "pdf-page-11", "title": "PDF page 11" }, { "id": "pdf-page-12", "title": "PDF page 12" }, { "id": "pdf-page-13", "title": "PDF page 13" }, { "id": "pdf-page-14", "title": "PDF page 14" }, { "id": "pdf-page-15", "title": "PDF page 15" }, { "id": "pdf-page-16", "title": "PDF page 16" }, { "id": "pdf-page-17", "title": "PDF page 17" }, { "id": "pdf-page-18", "title": "PDF page 18" }, { "id": "pdf-page-19", "title": "PDF page 19" }, { "id": "pdf-page-20", "title": "PDF page 20" }, { "id": "pdf-page-21", "title": "PDF page 21" }, { "id": "pdf-page-22", "title": "PDF page 22" }, { "id": "pdf-page-23", "title": "PDF page 23" }, { "id": "pdf-page-24", "title": "PDF page 24" }, { "id": "pdf-page-25", "title": "PDF page 25" }, { "id": "pdf-page-26", "title": "PDF page 26" }, { "id": "pdf-page-27", "title": "PDF page 27" }, { "id": "pdf-page-28", "title": "PDF page 28" }, { "id": "pdf-page-29", "title": "PDF page 29" }, { "id": "pdf-page-30", "title": "PDF page 30" }, { "id": "pdf-page-31", "title": "PDF page 31" }, { "id": "pdf-page-32", "title": "PDF page 32" }, { "id": "pdf-page-33", "title": "PDF page 33" }, { "id": "pdf-page-34", "title": "PDF page 34" }, { "id": "pdf-page-35", "title": "PDF page 35" }, { "id": "pdf-page-36", "title": "PDF page 36" }, { "id": "pdf-page-37", "title": "PDF page 37" }, { "id": "pdf-page-38", "title": "PDF page 38" }, { "id": "pdf-page-39", "title": "PDF page 39" }, { "id": "pdf-page-40", "title": "PDF page 40" }, { "id": "pdf-page-41", "title": "PDF page 41" }, { "id": "pdf-page-42", "title": "PDF page 42" }, { "id": "pdf-page-43", "title": "PDF page 43" }, { "id": "pdf-page-44", "title": "PDF page 44" }, { "id": "pdf-page-45", "title": "PDF page 45" }, { "id": "pdf-page-46", "title": "PDF page 46" }, { "id": "pdf-page-47", "title": "PDF page 47" }, { "id": "pdf-page-48", "title": "PDF page 48" }, { "id": "pdf-page-49", "title": "PDF page 49" }, { "id": "pdf-page-50", "title": "PDF page 50" }, { "id": "pdf-page-51", "title": "PDF page 51" }, { "id": "pdf-page-52", "title": "PDF page 52" }, { "id": "pdf-page-53", "title": "PDF page 53" }, { "id": "pdf-page-54", "title": "PDF page 54" }, { "id": "pdf-page-55", "title": "PDF page 55" }, { "id": "pdf-page-56", "title": "PDF page 56" }, { "id": "pdf-page-57", "title": "PDF page 57" }, { "id": "pdf-page-58", "title": "PDF page 58" }, { "id": "pdf-page-59", "title": "PDF page 59" }, { "id": "pdf-page-60", "title": "PDF page 60" }, { "id": "pdf-page-61", "title": "PDF page 61" }, { "id": "pdf-page-62", "title": "PDF page 62" }, { "id": "pdf-page-63", "title": "PDF page 63" }, { "id": "pdf-page-64", "title": "PDF page 64" }, { "id": "pdf-page-65", "title": "PDF page 65" }, { "id": "pdf-page-66", "title": "PDF page 66" }, { "id": "pdf-page-67", "title": "PDF page 67" }, { "id": "pdf-page-68", "title": "PDF page 68" }, { "id": "pdf-page-69", "title": "PDF page 69" }, { "id": "pdf-page-70", "title": "PDF page 70" }, { "id": "pdf-page-71", "title": "PDF page 71" }, { "id": "pdf-page-72", "title": "PDF page 72" }, { "id": "pdf-page-73", "title": "PDF page 73" }, { "id": "pdf-page-74", "title": "PDF page 74" }, { "id": "pdf-page-75", "title": "PDF page 75" }, { "id": "pdf-page-76", "title": "PDF page 76" }, { "id": "pdf-page-77", "title": "PDF page 77" }, { "id": "pdf-page-78", "title": "PDF page 78" }, { "id": "pdf-page-79", "title": "PDF page 79" }, { "id": "pdf-page-80", "title": "PDF page 80" }, { "id": "pdf-page-81", "title": "PDF page 81" }, { "id": "pdf-page-82", "title": "PDF page 82" }, { "id": "pdf-page-83", "title": "PDF page 83" }, { "id": "pdf-page-84", "title": "PDF page 84" }, { "id": "pdf-page-85", "title": "PDF page 85" }, { "id": "pdf-page-86", "title": "PDF page 86" }, { "id": "pdf-page-87", "title": "PDF page 87" } ], "citations": [ { "title": "Read the complete manuscript (PDF)", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf" }, { "title": "Publication record", "url": "https://doi.org/10.5281/zenodo.22048090" }, { "title": "BibTeX citation", "url": "https://semiaifoundry.com/assets/research/crg/crg-canonical-theory.bib" }, { "title": "Open PDF page 1", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=1" }, { "title": "Open PDF page 2", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=2" }, { "title": "Open PDF page 3", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=3" }, { "title": "Open PDF page 4", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=4" }, { "title": "Open PDF page 5", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=5" }, { "title": "Open PDF page 6", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=6" }, { "title": "Open PDF page 7", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=7" }, { "title": "Open PDF page 8", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=8" }, { "title": "Open PDF page 9", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=9" }, { "title": "Open PDF page 10", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=10" }, { "title": "Open PDF page 11", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=11" }, { "title": "Open PDF page 12", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=12" }, { "title": "Open PDF page 13", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=13" }, { "title": "Open PDF page 14", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=14" }, { "title": "Open PDF page 15", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=15" }, { "title": "Open PDF page 16", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=16" }, { "title": "Open PDF page 17", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=17" }, { "title": "Open PDF page 18", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=18" }, { "title": "Open PDF page 19", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=19" }, { "title": "Open PDF page 20", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=20" }, { "title": "Open PDF page 21", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=21" }, { "title": "Open PDF page 22", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=22" }, { "title": "Open PDF page 23", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=23" }, { "title": "Open PDF page 24", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=24" }, { "title": "Open PDF page 25", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=25" }, { "title": "Open PDF page 26", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=26" }, { "title": "Open PDF page 27", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=27" }, { "title": "Open PDF page 28", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=28" }, { "title": "Open PDF page 29", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=29" }, { "title": "Open PDF page 30", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=30" }, { "title": "Open PDF page 31", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=31" }, { "title": "Open PDF page 32", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=32" }, { "title": "Open PDF page 33", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=33" }, { "title": "Open PDF page 34", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=34" }, { "title": "Open PDF page 35", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=35" }, { "title": "Open PDF page 36", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=36" }, { "title": "Open PDF page 37", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=37" }, { "title": "Open PDF page 38", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=38" }, { "title": "Open PDF page 39", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=39" }, { "title": "Open PDF page 40", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=40" }, { "title": "Open PDF page 41", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=41" }, { "title": "Open PDF page 42", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=42" }, { "title": "Open PDF page 43", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=43" }, { "title": "Open PDF page 44", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=44" }, { "title": "Open PDF page 45", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=45" }, { "title": "Open PDF page 46", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=46" }, { "title": "Open PDF page 47", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=47" }, { "title": "Open PDF page 48", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=48" }, { "title": "Open PDF page 49", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=49" }, { "title": "Open PDF page 50", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=50" }, { "title": "Open PDF page 51", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=51" }, { "title": "Open PDF page 52", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=52" }, { "title": "Open PDF page 53", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=53" }, { "title": "Open PDF page 54", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=54" }, { "title": "Open PDF page 55", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=55" }, { "title": "Open PDF page 56", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=56" }, { "title": "Open PDF page 57", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=57" }, { "title": "Open PDF page 58", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=58" }, { "title": "Open PDF page 59", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=59" }, { "title": "Open PDF page 60", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=60" }, { "title": "Open PDF page 61", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=61" }, { "title": "Open PDF page 62", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=62" }, { "title": "Open PDF page 63", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=63" }, { "title": "Open PDF page 64", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=64" }, { "title": "Open PDF page 65", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=65" }, { "title": "Open PDF page 66", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=66" }, { "title": "Open PDF page 67", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=67" }, { "title": "Open PDF page 68", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=68" }, { "title": "Open PDF page 69", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=69" }, { "title": "Open PDF page 70", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=70" }, { "title": "Open PDF page 71", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=71" }, { "title": "Open PDF page 72", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=72" }, { "title": "Open PDF page 73", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=73" }, { "title": "Open PDF page 74", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=74" }, { "title": "Open PDF page 75", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=75" }, { "title": "Open PDF page 76", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=76" }, { "title": "Open PDF page 77", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=77" }, { "title": "Open PDF page 78", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=78" }, { "title": "Open PDF page 79", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=79" }, { "title": "Open PDF page 80", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=80" }, { "title": "Open PDF page 81", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=81" }, { "title": "Open PDF page 82", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=82" }, { "title": "Open PDF page 83", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=83" }, { "title": "Open PDF page 84", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=84" }, { "title": "Open PDF page 85", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=85" }, { "title": "Open PDF page 86", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=86" }, { "title": "Open PDF page 87", "url": "https://semiaifoundry.com/assets/research/crg/A_Communication_Theory_of_Computation_Realization_v3.2.0.pdf#page=87" } ], "recordHash": "3dee2198819e36d226ef7bbe41298f4b0ce0b1e8f17bf59f2dc29be88953aec7" }, { "id": "crg-foundations", "title": "Computation-Realization Geometry: Semantic Interface Laws, Decision-Sufficient Abstraction, and Cost Duality", "category": "research", "format": "Manuscript", "description": "This paper introduces the foundational object of Computation–Realization Geometry (CRG). A terminalized computation and resource contract define a legal realization family P; typed signatures yield the exact attainable region R, the upper obligation region Γ, and the...", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/#crg-foundations", "publishedDate": "2026-08-25", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Foundations", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": "https://creativecommons.org/licenses/by/4.0/", "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "3.2.0", "status": "Published open-access manuscript", "evidenceScope": null, "contentCoverage": "extracted-pdf-text", "artifactUrl": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf", "interactiveUrl": null, "pageCount": 30, "pageNumbering": "One-based PDF file pages, not printed manuscript page labels.", "textNotice": "Extracted PDF text; equations and layout should be checked against the original PDF.", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "08f3f65a3689a0a8c3795928d5c9a2af3bfbe825a5d836e51835032632c33f62", "contentLength": 109613, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-foundations.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-foundations.md", "sections": [ { "id": "section-1", "title": "Computation-Realization Geometry: Semantic Interface Laws, Decision-Sufficient Abstraction, and Cost Duality" }, { "id": "section-2", "title": "Abstract" }, { "id": "section-3", "title": "Extracted manuscript text" }, { "id": "pdf-page-1", "title": "PDF page 1" }, { "id": "pdf-page-2", "title": "PDF page 2" }, { "id": "pdf-page-3", "title": "PDF page 3" }, { "id": "pdf-page-4", "title": "PDF page 4" }, { "id": "pdf-page-5", "title": "PDF page 5" }, { "id": "pdf-page-6", "title": "PDF page 6" }, { "id": "pdf-page-7", "title": "PDF page 7" }, { "id": "pdf-page-8", "title": "PDF page 8" }, { "id": "pdf-page-9", "title": "PDF page 9" }, { "id": "pdf-page-10", "title": "PDF page 10" }, { "id": "pdf-page-11", "title": "PDF page 11" }, { "id": "pdf-page-12", "title": "PDF page 12" }, { "id": "pdf-page-13", "title": "PDF page 13" }, { "id": "pdf-page-14", "title": "PDF page 14" }, { "id": "pdf-page-15", "title": "PDF page 15" }, { "id": "pdf-page-16", "title": "PDF page 16" }, { "id": "pdf-page-17", "title": "PDF page 17" }, { "id": "pdf-page-18", "title": "PDF page 18" }, { "id": "pdf-page-19", "title": "PDF page 19" }, { "id": "pdf-page-20", "title": "PDF page 20" }, { "id": "pdf-page-21", "title": "PDF page 21" }, { "id": "pdf-page-22", "title": "PDF page 22" }, { "id": "pdf-page-23", "title": "PDF page 23" }, { "id": "pdf-page-24", "title": "PDF page 24" }, { "id": "pdf-page-25", "title": "PDF page 25" }, { "id": "pdf-page-26", "title": "PDF page 26" }, { "id": "pdf-page-27", "title": "PDF page 27" }, { "id": "pdf-page-28", "title": "PDF page 28" }, { "id": "pdf-page-29", "title": "PDF page 29" }, { "id": "pdf-page-30", "title": "PDF page 30" } ], "citations": [ { "title": "Read the complete manuscript (PDF)", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf" }, { "title": "Publication record", "url": "https://doi.org/10.5281/zenodo.22050676" }, { "title": "BibTeX citation", "url": "https://semiaifoundry.com/assets/research/crg/crg-foundations.bib" }, { "title": "Open PDF page 1", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=1" }, { "title": "Open PDF page 2", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=2" }, { "title": "Open PDF page 3", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=3" }, { "title": "Open PDF page 4", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=4" }, { "title": "Open PDF page 5", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=5" }, { "title": "Open PDF page 6", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=6" }, { "title": "Open PDF page 7", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=7" }, { "title": "Open PDF page 8", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=8" }, { "title": "Open PDF page 9", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=9" }, { "title": "Open PDF page 10", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=10" }, { "title": "Open PDF page 11", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=11" }, { "title": "Open PDF page 12", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=12" }, { "title": "Open PDF page 13", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=13" }, { "title": "Open PDF page 14", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=14" }, { "title": "Open PDF page 15", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=15" }, { "title": "Open PDF page 16", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=16" }, { "title": "Open PDF page 17", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=17" }, { "title": "Open PDF page 18", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=18" }, { "title": "Open PDF page 19", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=19" }, { "title": "Open PDF page 20", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=20" }, { "title": "Open PDF page 21", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=21" }, { "title": "Open PDF page 22", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=22" }, { "title": "Open PDF page 23", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=23" }, { "title": "Open PDF page 24", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=24" }, { "title": "Open PDF page 25", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=25" }, { "title": "Open PDF page 26", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=26" }, { "title": "Open PDF page 27", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=27" }, { "title": "Open PDF page 28", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=28" }, { "title": "Open PDF page 29", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=29" }, { "title": "Open PDF page 30", "url": "https://semiaifoundry.com/assets/research/crg/Computation_Realization_Geometry_Foundations_v3.2.0.pdf#page=30" } ], "recordHash": "c0792e6b6984336eb0ef9e6788dfaa9ad42a53564185dacf3892b7a69f425e1c" }, { "id": "crg-scaling", "title": "A Generalized Rent Law from Computation-Realization Geometry: Scaling Fixed Points, Hierarchy Phase, and Finite-Scale Diagnostics", "category": "research", "format": "Manuscript", "description": "This paper develops a conditioned scaling theory for Computation–Realization Geometry. A Rent-like profile is defined as the multiscale observation of one legal realization under a declared hierarchy, accounting convention, estimator, and fit window. Stable dilation limits yield...", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/#crg-scaling", "publishedDate": "2026-08-25", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Scaling", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": "https://creativecommons.org/licenses/by/4.0/", "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "3.2.0", "status": "Published open-access manuscript", "evidenceScope": null, "contentCoverage": "extracted-pdf-text", "artifactUrl": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf", "interactiveUrl": null, "pageCount": 28, "pageNumbering": "One-based PDF file pages, not printed manuscript page labels.", "textNotice": "Extracted PDF text; equations and layout should be checked against the original PDF.", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3771a25f10b72768ffee8861905d14d169f04a91f6a36b3ba472251eb70890b8", "contentLength": 76639, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-scaling.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-scaling.md", "sections": [ { "id": "section-1", "title": "A Generalized Rent Law from Computation-Realization Geometry: Scaling Fixed Points, Hierarchy Phase, and Finite-Scale Diagnostics" }, { "id": "section-2", "title": "Abstract" }, { "id": "section-3", "title": "Extracted manuscript text" }, { "id": "pdf-page-1", "title": "PDF page 1" }, { "id": "pdf-page-2", "title": "PDF page 2" }, { "id": "pdf-page-3", "title": "PDF page 3" }, { "id": "pdf-page-4", "title": "PDF page 4" }, { "id": "pdf-page-5", "title": "PDF page 5" }, { "id": "pdf-page-6", "title": "PDF page 6" }, { "id": "pdf-page-7", "title": "PDF page 7" }, { "id": "pdf-page-8", "title": "PDF page 8" }, { "id": "pdf-page-9", "title": "PDF page 9" }, { "id": "pdf-page-10", "title": "PDF page 10" }, { "id": "pdf-page-11", "title": "PDF page 11" }, { "id": "pdf-page-12", "title": "PDF page 12" }, { "id": "pdf-page-13", "title": "PDF page 13" }, { "id": "pdf-page-14", "title": "PDF page 14" }, { "id": "pdf-page-15", "title": "PDF page 15" }, { "id": "pdf-page-16", "title": "PDF page 16" }, { "id": "pdf-page-17", "title": "PDF page 17" }, { "id": "pdf-page-18", "title": "PDF page 18" }, { "id": "pdf-page-19", "title": "PDF page 19" }, { "id": "pdf-page-20", "title": "PDF page 20" }, { "id": "pdf-page-21", "title": "PDF page 21" }, { "id": "pdf-page-22", "title": "PDF page 22" }, { "id": "pdf-page-23", "title": "PDF page 23" }, { "id": "pdf-page-24", "title": "PDF page 24" }, { "id": "pdf-page-25", "title": "PDF page 25" }, { "id": "pdf-page-26", "title": "PDF page 26" }, { "id": "pdf-page-27", "title": "PDF page 27" }, { "id": "pdf-page-28", "title": "PDF page 28" } ], "citations": [ { "title": "Read the complete manuscript (PDF)", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf" }, { "title": "Publication record", "url": "https://doi.org/10.5281/zenodo.22050605" }, { "title": "BibTeX citation", "url": "https://semiaifoundry.com/assets/research/crg/crg-scaling.bib" }, { "title": "Open PDF page 1", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=1" }, { "title": "Open PDF page 2", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=2" }, { "title": "Open PDF page 3", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=3" }, { "title": "Open PDF page 4", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=4" }, { "title": "Open PDF page 5", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=5" }, { "title": "Open PDF page 6", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=6" }, { "title": "Open PDF page 7", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=7" }, { "title": "Open PDF page 8", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=8" }, { "title": "Open PDF page 9", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=9" }, { "title": "Open PDF page 10", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=10" }, { "title": "Open PDF page 11", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=11" }, { "title": "Open PDF page 12", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=12" }, { "title": "Open PDF page 13", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=13" }, { "title": "Open PDF page 14", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=14" }, { "title": "Open PDF page 15", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=15" }, { "title": "Open PDF page 16", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=16" }, { "title": "Open PDF page 17", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=17" }, { "title": "Open PDF page 18", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=18" }, { "title": "Open PDF page 19", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=19" }, { "title": "Open PDF page 20", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=20" }, { "title": "Open PDF page 21", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=21" }, { "title": "Open PDF page 22", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=22" }, { "title": "Open PDF page 23", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=23" }, { "title": "Open PDF page 24", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=24" }, { "title": "Open PDF page 25", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=25" }, { "title": "Open PDF page 26", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=26" }, { "title": "Open PDF page 27", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=27" }, { "title": "Open PDF page 28", "url": "https://semiaifoundry.com/assets/research/crg/A_Generalized_Rent_Law_from_Computation_Realization_Geometry_v3.2.0.pdf#page=28" } ], "recordHash": "3b5f7a1f91c28adb3b59362fa27ff40aeac23e938a68505a7d3bcade574375b6" }, { "id": "crg-design", "title": "Designing with Computation-Realization Geometry: Certified Architecture Selection, Technology Matching, and Reference Physical Realization", "category": "research", "format": "Manuscript", "description": "This paper develops the design calculus of Computation–Realization Geometry. Technology enters after computation, legality, and attainability through feasible embeddings, service laws, and declared objectives. Finite algebraic registries induce semialgebraic technology phase...", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/#crg-design", "publishedDate": "2026-08-25", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Design", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": "https://creativecommons.org/licenses/by/4.0/", "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "3.2.0", "status": "Published open-access manuscript", "evidenceScope": null, "contentCoverage": "extracted-pdf-text", "artifactUrl": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf", "interactiveUrl": null, "pageCount": 29, "pageNumbering": "One-based PDF file pages, not printed manuscript page labels.", "textNotice": "Extracted PDF text; equations and layout should be checked against the original PDF.", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "08e4c8cb715e5f3395ab7a2f2c55a2b335574c65641ffc4f0692ffc1b891f5ba", "contentLength": 93799, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-design.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-design.md", "sections": [ { "id": "section-1", "title": "Designing with Computation-Realization Geometry: Certified Architecture Selection, Technology Matching, and Reference Physical Realization" }, { "id": "section-2", "title": "Abstract" }, { "id": "section-3", "title": "Extracted manuscript text" }, { "id": "pdf-page-1", "title": "PDF page 1" }, { "id": "pdf-page-2", "title": "PDF page 2" }, { "id": "pdf-page-3", "title": "PDF page 3" }, { "id": "pdf-page-4", "title": "PDF page 4" }, { "id": "pdf-page-5", "title": "PDF page 5" }, { "id": "pdf-page-6", "title": "PDF page 6" }, { "id": "pdf-page-7", "title": "PDF page 7" }, { "id": "pdf-page-8", "title": "PDF page 8" }, { "id": "pdf-page-9", "title": "PDF page 9" }, { "id": "pdf-page-10", "title": "PDF page 10" }, { "id": "pdf-page-11", "title": "PDF page 11" }, { "id": "pdf-page-12", "title": "PDF page 12" }, { "id": "pdf-page-13", "title": "PDF page 13" }, { "id": "pdf-page-14", "title": "PDF page 14" }, { "id": "pdf-page-15", "title": "PDF page 15" }, { "id": "pdf-page-16", "title": "PDF page 16" }, { "id": "pdf-page-17", "title": "PDF page 17" }, { "id": "pdf-page-18", "title": "PDF page 18" }, { "id": "pdf-page-19", "title": "PDF page 19" }, { "id": "pdf-page-20", "title": "PDF page 20" }, { "id": "pdf-page-21", "title": "PDF page 21" }, { "id": "pdf-page-22", "title": "PDF page 22" }, { "id": "pdf-page-23", "title": "PDF page 23" }, { "id": "pdf-page-24", "title": "PDF page 24" }, { "id": "pdf-page-25", "title": "PDF page 25" }, { "id": "pdf-page-26", "title": "PDF page 26" }, { "id": "pdf-page-27", "title": "PDF page 27" }, { "id": "pdf-page-28", "title": "PDF page 28" }, { "id": "pdf-page-29", "title": "PDF page 29" } ], "citations": [ { "title": "Read the complete manuscript (PDF)", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf" }, { "title": "Publication record", "url": "https://doi.org/10.5281/zenodo.22050638" }, { "title": "BibTeX citation", "url": "https://semiaifoundry.com/assets/research/crg/crg-design.bib" }, { "title": "Open PDF page 1", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=1" }, { "title": "Open PDF page 2", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=2" }, { "title": "Open PDF page 3", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=3" }, { "title": "Open PDF page 4", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=4" }, { "title": "Open PDF page 5", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=5" }, { "title": "Open PDF page 6", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=6" }, { "title": "Open PDF page 7", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=7" }, { "title": "Open PDF page 8", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=8" }, { "title": "Open PDF page 9", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=9" }, { "title": "Open PDF page 10", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=10" }, { "title": "Open PDF page 11", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=11" }, { "title": "Open PDF page 12", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=12" }, { "title": "Open PDF page 13", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=13" }, { "title": "Open PDF page 14", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=14" }, { "title": "Open PDF page 15", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=15" }, { "title": "Open PDF page 16", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=16" }, { "title": "Open PDF page 17", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=17" }, { "title": "Open PDF page 18", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=18" }, { "title": "Open PDF page 19", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=19" }, { "title": "Open PDF page 20", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=20" }, { "title": "Open PDF page 21", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=21" }, { "title": "Open PDF page 22", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=22" }, { "title": "Open PDF page 23", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=23" }, { "title": "Open PDF page 24", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=24" }, { "title": "Open PDF page 25", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=25" }, { "title": "Open PDF page 26", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=26" }, { "title": "Open PDF page 27", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=27" }, { "title": "Open PDF page 28", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=28" }, { "title": "Open PDF page 29", "url": "https://semiaifoundry.com/assets/research/crg/Designing_with_Computation_Realization_Geometry_v3.2.0.pdf#page=29" } ], "recordHash": "23b3f913debeee8dc09588207f654dc0a58cfaeb4b07cbae6fb00907ae10ec96" }, { "id": "crg-structural-theorems", "title": "Structural Theorems for Computation-Realization Geometry: Interaction, Safe Commitment, Network Embedding, Conservation, and Scaling", "category": "research", "format": "Manuscript", "description": "This paper develops selected exact deterministic fragments of Computation–Realization Geometry rather than claiming closure of the complete nonlinear, randomized, approximate, or physically embedded theory. It establishes circuit–protocol translations under named accounting...", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/#crg-structural-theorems", "publishedDate": "2026-08-25", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Structural theorems", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": "https://creativecommons.org/licenses/by/4.0/", "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "3.2.0", "status": "Published open-access manuscript", "evidenceScope": null, "contentCoverage": "extracted-pdf-text", "artifactUrl": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf", "interactiveUrl": null, "pageCount": 23, "pageNumbering": "One-based PDF file pages, not printed manuscript page labels.", "textNotice": "Extracted PDF text; equations and layout should be checked against the original PDF.", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0a3b705b65085c4bb9215008f917326e553644750eab5869f4d27100da205cd1", "contentLength": 73669, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-structural-theorems.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-structural-theorems.md", "sections": [ { "id": "section-1", "title": "Structural Theorems for Computation-Realization Geometry: Interaction, Safe Commitment, Network Embedding, Conservation, and Scaling" }, { "id": "section-2", "title": "Abstract" }, { "id": "section-3", "title": "Extracted manuscript text" }, { "id": "pdf-page-1", "title": "PDF page 1" }, { "id": "pdf-page-2", "title": "PDF page 2" }, { "id": "pdf-page-3", "title": "PDF page 3" }, { "id": "pdf-page-4", "title": "PDF page 4" }, { "id": "pdf-page-5", "title": "PDF page 5" }, { "id": "pdf-page-6", "title": "PDF page 6" }, { "id": "pdf-page-7", "title": "PDF page 7" }, { "id": "pdf-page-8", "title": "PDF page 8" }, { "id": "pdf-page-9", "title": "PDF page 9" }, { "id": "pdf-page-10", "title": "PDF page 10" }, { "id": "pdf-page-11", "title": "PDF page 11" }, { "id": "pdf-page-12", "title": "PDF page 12" }, { "id": "pdf-page-13", "title": "PDF page 13" }, { "id": "pdf-page-14", "title": "PDF page 14" }, { "id": "pdf-page-15", "title": "PDF page 15" }, { "id": "pdf-page-16", "title": "PDF page 16" }, { "id": "pdf-page-17", "title": "PDF page 17" }, { "id": "pdf-page-18", "title": "PDF page 18" }, { "id": "pdf-page-19", "title": "PDF page 19" }, { "id": "pdf-page-20", "title": "PDF page 20" }, { "id": "pdf-page-21", "title": "PDF page 21" }, { "id": "pdf-page-22", "title": "PDF page 22" }, { "id": "pdf-page-23", "title": "PDF page 23" } ], "citations": [ { "title": "Read the complete manuscript (PDF)", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf" }, { "title": "Publication record", "url": "https://doi.org/10.5281/zenodo.22050654" }, { "title": "BibTeX citation", "url": "https://semiaifoundry.com/assets/research/crg/crg-structural-theorems.bib" }, { "title": "Open PDF page 1", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=1" }, { "title": "Open PDF page 2", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=2" }, { "title": "Open PDF page 3", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=3" }, { "title": "Open PDF page 4", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=4" }, { "title": "Open PDF page 5", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=5" }, { "title": "Open PDF page 6", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=6" }, { "title": "Open PDF page 7", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=7" }, { "title": "Open PDF page 8", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=8" }, { "title": "Open PDF page 9", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=9" }, { "title": "Open PDF page 10", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=10" }, { "title": "Open PDF page 11", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=11" }, { "title": "Open PDF page 12", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=12" }, { "title": "Open PDF page 13", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=13" }, { "title": "Open PDF page 14", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=14" }, { "title": "Open PDF page 15", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=15" }, { "title": "Open PDF page 16", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=16" }, { "title": "Open PDF page 17", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=17" }, { "title": "Open PDF page 18", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=18" }, { "title": "Open PDF page 19", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=19" }, { "title": "Open PDF page 20", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=20" }, { "title": "Open PDF page 21", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=21" }, { "title": "Open PDF page 22", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=22" }, { "title": "Open PDF page 23", "url": "https://semiaifoundry.com/assets/research/crg/Structural_Theorems_for_Computation_Realization_Geometry_v3.2.0.pdf#page=23" } ], "recordHash": "b392bc409ff27855a4dadde22e3a2b9219aab7d246f6dd3a9724b8b9a8a0c81b" }, { "id": "crg-transformer", "title": "Certified Nonseparable Co-Design of a Long-Context Transformer Superblock: A Computation-Realization Geometry Case Study", "category": "research", "format": "Manuscript", "description": "This paper presents a complete evaluation within a declared finite algebraic registry and typed exclusions for a long-context Transformer superblock. The registry distinguishes dedicated, universal time-shared, split-specialist, hybrid, memory-centric, and vertical realization...", "canonicalUrl": "https://semiaifoundry.com/research/computation-realization-geometry/#crg-transformer", "publishedDate": "2026-08-25", "revisionDate": "2026-10-07", "author": "F. M. Cinnor", "topic": "Case study", "series": null, "pursuitIds": [ "computation-and-realization" ], "license": "https://creativecommons.org/licenses/by/4.0/", "rightsUrl": "https://semiaifoundry.com/terms-of-use/", "version": "3.2.0", "status": "Published open-access manuscript", "evidenceScope": null, "contentCoverage": "extracted-pdf-text", "artifactUrl": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf", "interactiveUrl": null, "pageCount": 17, "pageNumbering": "One-based PDF file pages, not printed manuscript page labels.", "textNotice": "Extracted PDF text; equations and layout should be checked against the original PDF.", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "07e51141842603885198b2aa38b46e3a268a4472b3561a4c89fefaf07372ba3d", "contentLength": 56630, "jsonUrl": "https://semiaifoundry.com/agents/publications/crg-transformer.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/crg-transformer.md", "sections": [ { "id": "section-1", "title": "Certified Nonseparable Co-Design of a Long-Context Transformer Superblock: A Computation-Realization Geometry Case Study" }, { "id": "section-2", "title": "Abstract" }, { "id": "section-3", "title": "Extracted manuscript text" }, { "id": "pdf-page-1", "title": "PDF page 1" }, { "id": "pdf-page-2", "title": "PDF page 2" }, { "id": "pdf-page-3", "title": "PDF page 3" }, { "id": "pdf-page-4", "title": "PDF page 4" }, { "id": "pdf-page-5", "title": "PDF page 5" }, { "id": "pdf-page-6", "title": "PDF page 6" }, { "id": "pdf-page-7", "title": "PDF page 7" }, { "id": "pdf-page-8", "title": "PDF page 8" }, { "id": "pdf-page-9", "title": "PDF page 9" }, { "id": "pdf-page-10", "title": "PDF page 10" }, { "id": "pdf-page-11", "title": "PDF page 11" }, { "id": "pdf-page-12", "title": "PDF page 12" }, { "id": "pdf-page-13", "title": "PDF page 13" }, { "id": "pdf-page-14", "title": "PDF page 14" }, { "id": "pdf-page-15", "title": "PDF page 15" }, { "id": "pdf-page-16", "title": "PDF page 16" }, { "id": "pdf-page-17", "title": "PDF page 17" } ], "citations": [ { "title": "Read the complete manuscript (PDF)", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf" }, { "title": "Publication record", "url": "https://doi.org/10.5281/zenodo.22058422" }, { "title": "BibTeX citation", "url": "https://semiaifoundry.com/assets/research/crg/crg-transformer.bib" }, { "title": "Open PDF page 1", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=1" }, { "title": "Open PDF page 2", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=2" }, { "title": "Open PDF page 3", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=3" }, { "title": "Open PDF page 4", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=4" }, { "title": "Open PDF page 5", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=5" }, { "title": "Open PDF page 6", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=6" }, { "title": "Open PDF page 7", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=7" }, { "title": "Open PDF page 8", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=8" }, { "title": "Open PDF page 9", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=9" }, { "title": "Open PDF page 10", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=10" }, { "title": "Open PDF page 11", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=11" }, { "title": "Open PDF page 12", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=12" }, { "title": "Open PDF page 13", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=13" }, { "title": "Open PDF page 14", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=14" }, { "title": "Open PDF page 15", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=15" }, { "title": "Open PDF page 16", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=16" }, { "title": "Open PDF page 17", "url": "https://semiaifoundry.com/assets/research/crg/Certified_Nonseparable_Transformer_Codesign_CRG_v3.2.0.pdf#page=17" } ], "recordHash": "f148e7ad58fd7fbf70bb923f2cae4e8d272bdb89c0a0026b663d890996bd685f" }, { "id": "atlas-lesson-ablation-reproduction-design", "title": "Controlled comparisons and confounded improvement", "category": "learning", "format": "Atlas lesson", "description": "Makes the design of an experiment part of the evidence for an improvement.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/ablation-reproduction-design/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "data-evidence-foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. Finite deterministic authored data with no noise and an additive constant effect. This lesson does not establish a general causal-identification method.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/ablation-reproduction-design-e3b9777cc2d5f751.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#ablation-reproduction-design", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "fdf102dfb9d9909d9a6359f7da2dd9d350a727127d03cbfde66ab3e1461fa326", "contentLength": 6484, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-ablation-reproduction-design.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-ablation-reproduction-design.md", "sections": [ { "id": "section-1", "title": "Controlled comparisons and confounded improvement" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Controlled comparisons and confounded improvement" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does the confounded contrast exceed the authored effect?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#ablation-reproduction-design" }, { "title": "Goodfellow, Bengio and Courville · Probability and information theory", "url": "https://www.deeplearningbook.org/contents/prob.html" }, { "title": "Gebru et al. · Datasheets for Datasets", "url": "https://arxiv.org/abs/1803.09010" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/ablation-reproduction-design-e3b9777cc2d5f751.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Sampling variability and independent evidence", "url": "https://semiaifoundry.com/learn/atlas/sampling-estimation-uncertainty/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Scaling laws & resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scaling-laws/" } ], "recordHash": "1e7fc15e660b43f9922518b711e50a368959dee02b21e355a2fc0b876bbc920e" }, { "id": "atlas-lesson-action-conditioned-world-model", "title": "Predict transitions conditional on actions", "category": "learning", "format": "Atlas lesson", "description": "Change an action while holding state fixed and compare predicted transitions with a held-out environment.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/action-conditioned-world-model/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-world-action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Example gain is 2 m per normalized command per step; model gain is 1.8. No clipping, noise or hidden state. This is worked arithmetic, not a trained world-model experience. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/action-conditioned-world-model-edfade0d879a1d13.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#action-conditioned-world-model", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0e12dacbd86a30943e31ead249a0725a9796ebcbbcec5785f444ab7bb5bd46bc", "contentLength": 6626, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-action-conditioned-world-model.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-action-conditioned-world-model.md", "sections": [ { "id": "section-1", "title": "Predict transitions conditional on actions" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Predict transitions conditional on actions · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What distinguishes action-conditioned prediction from an action-free continuation?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#action-conditioned-world-model" }, { "title": "V-JEPA 2", "url": "https://arxiv.org/html/2506.09985v1" }, { "title": "Mastering Diverse Domains through World Models", "url": "https://arxiv.org/html/2301.04104v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/action-conditioned-world-model-edfade0d879a1d13.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Predict temporal representations without generating pixels", "url": "https://semiaifoundry.com/learn/atlas/video-latent-prediction/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Learn behavior from a model and test in the environment", "url": "https://semiaifoundry.com/learn/atlas/imagined-rollouts-policy-learning/" }, { "title": "Translate learned representations into robot action units", "url": "https://semiaifoundry.com/learn/atlas/vision-language-action-interface/" }, { "title": "Predict action chunks and replan with feedback", "url": "https://semiaifoundry.com/learn/atlas/diffusion-action-horizon/" } ], "recordHash": "b177ff123e547575905dfcb605972815807133d72d549582b26e88596763e549" }, { "id": "atlas-lesson-adder", "title": "Full adder and carry network", "category": "learning", "format": "Atlas lesson", "description": "Combines binary operands and propagates the carry needed for exact integer addition.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/adder/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Arithmetic circuits", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The carry relations follow the linked digital-design lecture. Examples are unsigned four-bit arithmetic; signed overflow is a different condition, and gate delay is outside the truth-table calculation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/adder-b13c5aa2d36b257c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#adder", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "101260e8f1122f9c7008e90923023a9e988d43747c51ed3bf22c5cc8b96e8256", "contentLength": 4668, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-adder.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-adder.md", "sections": [ { "id": "section-1", "title": "Full adder and carry network" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Generate and propagate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why use more elaborate carry logic?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#adder" }, { "title": "University of Washington CSE 370 — Adders", "url": "https://courses.cs.washington.edu/courses/cse370/08au/Lecture%20Slides/Lec14-Adders.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/adder-b13c5aa2d36b257c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Two-input CMOS NAND gate", "url": "https://semiaifoundry.com/learn/atlas/nand/" }, { "title": "Binary multiplier and partial-product reduction", "url": "https://semiaifoundry.com/learn/atlas/multiplier/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" } ], "recordHash": "7e814f6ae9528c41a66a3fd89e1cadc16946dc774c73c93758236f5f9e2760cc" }, { "id": "atlas-lesson-ald-self-limiting-growth", "title": "ALD and self-limiting surface reactions", "category": "learning", "format": "Atlas lesson", "description": "Builds a film through separated chemical exposures and controlled surface saturation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/ald-self-limiting-growth/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Repeated operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The numbers illustrate an empirical model and are not a vendor recipe. Material-specific ALD windows and selectivity must be established experimentally.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/ald-self-limiting-growth-a831d1b62669b6de.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#ald-self-limiting-growth", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "8586a062fcbc8be245f21ff76e3f616a02f66af54f5f1606f65cd0904e9280cc", "contentLength": 5241, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-ald-self-limiting-growth.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-ald-self-limiting-growth.md", "sections": [ { "id": "section-1", "title": "ALD and self-limiting surface reactions" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Steady-cycle thickness estimate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why might a deep feature need longer exposure than a flat witness wafer?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#ald-self-limiting-growth" }, { "title": "Lam Research — Our Processes", "url": "https://www.lamresearch.com/products/our-processes/" }, { "title": "Applied Materials — New Ways to Shrink", "url": "https://ir.appliedmaterials.com/static-files/f2fbf48d-a761-4c4f-ab4c-73f312ab1ebc" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/ald-self-limiting-growth-a831d1b62669b6de.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "CVD and PVD: two ways to supply a film", "url": "https://semiaifoundry.com/learn/atlas/cvd-pvd-film-transport/" }, { "title": "Nanosheet release and replacement gates", "url": "https://semiaifoundry.com/learn/atlas/nanosheet-gate-last-integration/" }, { "title": "Thermal oxidation and the silicon interface", "url": "https://semiaifoundry.com/learn/atlas/thermal-oxidation-interface/" } ], "recordHash": "734f538325574070f17f0b0224ac6c716efb0f94ea092cf22a327d05c38561d9" }, { "id": "atlas-lesson-analog-photonic-research", "title": "Analog and photonic arithmetic research", "category": "learning", "format": "Atlas lesson", "description": "Explores physical multiply accumulation with explicit conversion and accuracy limits.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/analog-photonic-research/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The IBM and Nature sources describe particular research systems. No commercial deployment scale, universal energy advantage or precision equivalence is asserted.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/analog-photonic-research-3227848746f7ea50.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#analog-photonic-research", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "282655a87905e841926a8ba877ae0326f66d2d7cb19445fc4399c6fbb5f09fdd", "contentLength": 5375, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-analog-photonic-research.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-analog-photonic-research.md", "sections": [ { "id": "section-1", "title": "Analog and photonic arithmetic research" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Ideal conductance accumulation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What belongs in a fair analog-versus-digital energy comparison?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#analog-photonic-research" }, { "title": "An energy-efficient analog chip for AI inference", "url": "https://research.ibm.com/blog/analog-ai-chip-inference" }, { "title": "Parallel convolutional processing using an integrated photonic tensor core", "url": "https://www.nature.com/articles/s41586-020-03070-1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/analog-photonic-research-3227848746f7ea50.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" }, { "title": "Workload contract and architecture selection", "url": "https://semiaifoundry.com/learn/atlas/chip-workload-contract/" } ], "recordHash": "649a6f38d9616ac3f37afc20fefaf9f065d05b45af41296c2484f76c4c743c88" }, { "id": "atlas-lesson-astra", "title": "GPT-6 Astra", "category": "learning", "format": "Atlas lesson", "description": "Connect documented model capabilities to a larger system of context, tools, and evaluation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/astra/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Agent systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example applies the token-accounting relation already stated in the lesson. These are invented limits, not a current OpenAI specification. Actual service accounting, tools and multimodal inputs require the cited interface documentation; no parameter count, training cluster or private design is inferred.\n\nNo new private architecture, current product capability or actual-model execution claim is introduced. The existing public-service source boundary remains intact.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/astra-ee8b7a965ce793c3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#astra", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f033ad5f4add9ed648bf6c302620037aafbe8cecedaca67d007a37015ad30f9a", "contentLength": 8860, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-astra.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-astra.md", "sections": [ { "id": "section-1", "title": "GPT-6 Astra" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Visible output shares a generated-token budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does Astra’s published context limit establish?" }, { "id": "section-11", "title": "What does a recorded model tool proposal establish?" }, { "id": "section-12", "title": "Historical context" }, { "id": "section-13", "title": "2026 · GPT-6 Astra released through the OpenAI API" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#astra" }, { "title": "OpenAI API Changelog — September 3, 2026", "url": "https://developers.openai.com/api/docs/changelog" }, { "title": "OpenAI — GPT-6 Astra Model", "url": "https://developers.openai.com/api/docs/models/gpt-6-astra" }, { "title": "OpenAI — Reasoning Models: Context and Output Accounting", "url": "https://developers.openai.com/api/docs/guides/reasoning" }, { "title": "MCP tools", "url": "https://modelcontextprotocol.io/specification/2026-07-28/server/tools" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/astra-ee8b7a965ce793c3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Post-training & feedback", "url": "https://semiaifoundry.com/learn/atlas/post-training/" }, { "title": "Scaling laws & resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scaling-laws/" }, { "title": "Tool schemas and semantic validation", "url": "https://semiaifoundry.com/learn/atlas/tool-contracts-schemas/" }, { "title": "User authority and service identity", "url": "https://semiaifoundry.com/learn/atlas/tool-authority-identity/" }, { "title": "Traces connect cost, latency and results", "url": "https://semiaifoundry.com/learn/atlas/telemetry-traces-evaluation/" } ], "recordHash": "3c6ff825e0286badef57f82f340fd669aa543557754cdfba03be86f23fade545" }, { "id": "atlas-lesson-attention", "title": "Self-attention", "category": "learning", "format": "Atlas lesson", "description": "Exchange information between token representations.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/attention/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Transformer computation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The displayed equation is a model abstraction; masks and precision are explicit assumptions.\n\nMode: executable causal attention gradients. Scalar value example, softmax over the allowed set, values held fixed for the shown score derivative. Full model also differentiates values and projections. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.\n\nThe experience constructs explicit masks and arrays. It does not execute fused variable-length attention or measure packing speedups. Documents crossing blocks lose earlier-block context in this declared specimen.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/attention-ca04a2b8e0cce22b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#attention", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "fc3fc3accb8714f89fdfda9af895c77b27760534a788bb34f0a17c9df13e9821", "contentLength": 10251, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-attention.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-attention.md", "sections": [ { "id": "section-1", "title": "Self-attention" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Scaled dot-product attention" }, { "id": "section-5", "title": "Trainable attention from Q/K/V through gradients · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "What does the attention weight matrix mix?" }, { "id": "section-12", "title": "What is the derivative of output with respect to the first score?" }, { "id": "section-13", "title": "A packed query at slot7 belongs to a document starting at slot5. Which keys are allowed by this specimen?" }, { "id": "section-14", "title": "Historical context" }, { "id": "section-15", "title": "2017 · The Transformer replaces recurrent sequence processing" }, { "id": "section-16", "title": "Evidence and scope" }, { "id": "section-17", "title": "Sources" }, { "id": "section-18", "title": "Continue exploring" }, { "id": "section-19", "title": "Foundations" }, { "id": "section-20", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#attention" }, { "title": "Vaswani et al. — Attention Is All You Need", "url": "https://arxiv.org/abs/1706.03762" }, { "title": "Dao et al. — FlashAttention", "url": "https://arxiv.org/abs/2205.14135" }, { "title": "Attention Is All You Need", "url": "https://arxiv.org/html/1706.03762v7" }, { "title": "Megatron Bridge 0.3.1 · packed sequence boundaries", "url": "https://docs.nvidia.com/nemo/megatron-bridge/0.3.1/training/packed-sequences.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/attention-ca04a2b8e0cce22b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Position representation", "url": "https://semiaifoundry.com/learn/atlas/positional-encoding/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Feed-forward network", "url": "https://semiaifoundry.com/learn/atlas/feed-forward/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "A differentiable computation graph", "url": "https://semiaifoundry.com/learn/atlas/reverse-mode-autodiff/" }, { "title": "Assemble an initialized causal language model", "url": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Tokenizer", "url": "https://semiaifoundry.com/learn/atlas/tokenizer/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" } ], "recordHash": "2a95e250ab7f7566e26201ff1b766d6c3304b3910fea02f8ae784e756b5ce63d" }, { "id": "atlas-lesson-attention-io-tiling", "title": "IO-aware attention and online softmax", "category": "learning", "format": "Atlas lesson", "description": "Computes attention while reducing large intermediate transfers to outer memory.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/attention-io-tiling/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example is a storage calculation, not a promised speedup. Exactness refers to the algorithm’s attention definition; finite-precision evaluation still needs testing.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/attention-io-tiling-430677d2c8cf857a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#attention-io-tiling", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "249ed34b9273038259b4fc21799b57c19a0921955146e33690d12eee2ca1f8ea", "contentLength": 4936, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-attention-io-tiling.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-attention-io-tiling.md", "sections": [ { "id": "section-1", "title": "IO-aware attention and online softmax" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Score storage" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is the main avoided object in tiled IO-aware attention?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#attention-io-tiling" }, { "title": "FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness", "url": "https://arxiv.org/abs/2205.14135" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/attention-io-tiling-430677d2c8cf857a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Kernel tiling, fusion and operand reuse", "url": "https://semiaifoundry.com/learn/atlas/kernel-locality-fusion/" }, { "title": "Occupancy and asynchronous tile pipelines", "url": "https://semiaifoundry.com/learn/atlas/gpu-occupancy-pipeline/" } ], "recordHash": "3ebb517fa63e684df53b554119161f77a325f5f8d526c1b0bf9337a6f0194b0e" }, { "id": "atlas-lesson-audio-sampling-spectrum", "title": "Audio sampling, windows and spectra", "category": "learning", "format": "Atlas lesson", "description": "Recover a finite frequency representation and diagnose sampling ambiguity.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/audio-sampling-spectrum/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Contrasting computational structures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "One finite sampled tone and an explicitly normalized DFT; symmetric Hann window; no microphone, calibrated acoustic units, speech recognition or anti-aliasing hardware simulation. Numerical settings are original teaching fixtures. The named experience executes the stated bounded algorithm; no production performance or independent human review is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/audio-sampling-spectrum-ce756b070c8d3c91.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#audio-sampling-spectrum", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "08ff8e79759a989d6e782d0bba3c20befc3000624c07822a36bde8c12e18a1b0", "contentLength": 6500, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-audio-sampling-spectrum.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-audio-sampling-spectrum.md", "sections": [ { "id": "section-1", "title": "Audio sampling, windows and spectra" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Audio sampling, windows and spectra · governing computation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "With 32 samples at 16,000 samples/s, what is the DFT bin spacing?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#audio-sampling-spectrum" }, { "title": "SciPy DFT convention", "url": "https://docs.scipy.org/doc/scipy/reference/generated/scipy.fft.fft.html" }, { "title": "SciPy symmetric Hann window definition", "url": "https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.windows.hann.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/audio-sampling-spectrum-ce756b070c8d3c91.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Sampling variability and independent evidence", "url": "https://semiaifoundry.com/learn/atlas/sampling-estimation-uncertainty/" }, { "title": "Audio representation, alignment and transcript loss", "url": "https://semiaifoundry.com/learn/atlas/speech-audio-sequence-objectives/" }, { "title": "Speech is a timed interaction", "url": "https://semiaifoundry.com/learn/atlas/streaming-speech-turns/" }, { "title": "Floating-point range, resolution and rounding", "url": "https://semiaifoundry.com/learn/atlas/floating-number-range-resolution/" } ], "recordHash": "013ae51cc3fc22d264f4227ff687a9e9ee119be96ca02154ea9d73fb45305560" }, { "id": "atlas-lesson-aws-neuron-dataflow", "title": "Trainium and Inferentia execution paths", "category": "learning", "format": "Atlas lesson", "description": "Combines specialized engines, local buffers and a compiler-managed accelerator runtime.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/aws-neuron-dataflow/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Published memory values are retained in evidence claims. The example is synthetic and does not imply equal features or performance across Trainium2 and Inferentia2.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/aws-neuron-dataflow-a76c9fd8110a4cf1.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#aws-neuron-dataflow", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "986e8099757ff52ce94a6dfae389010bc22a3fe6404af40c2b746dc20df7cbff", "contentLength": 5280, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-aws-neuron-dataflow.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-aws-neuron-dataflow.md", "sections": [ { "id": "section-1", "title": "Trainium and Inferentia execution paths" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Engine schedule bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why must an Inf2 instance memory total be distinguished from an Inferentia2 chip value?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#aws-neuron-dataflow" }, { "title": "Trainium2 Architecture", "url": "https://awsdocs-neuron.readthedocs-hosted.com/en/latest/about-neuron/arch/neuron-hardware/trainium2.html" }, { "title": "Amazon EC2 Inf2 Architecture", "url": "https://awsdocs-neuron.readthedocs-hosted.com/en/latest/about-neuron/arch/neuron-hardware/inf2-arch.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/aws-neuron-dataflow-a76c9fd8110a4cf1.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Systolic arrays and tensor dataflow", "url": "https://semiaifoundry.com/learn/atlas/systolic-array-dataflow/" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" }, { "title": "Compiler layout, lowering and buffer planning", "url": "https://semiaifoundry.com/learn/atlas/compiler-layout-lowering/" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" } ], "recordHash": "2d898c13c8deb742c201d5031078ba23eb6a384a2924d0a423ad4d49686f59a3" }, { "id": "atlas-lesson-backside-power-dtco", "title": "Backside power and design–technology co-optimization", "category": "learning", "format": "Atlas lesson", "description": "Changes physical power routing and evaluates the device, layout and system consequences together.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/backside-power-dtco/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / BEOL and co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Intel’s brief includes announced roadmap capabilities. The lesson explains mechanisms and does not equate those announcements with a universal qualified flow.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/backside-power-dtco-5a6a59fdd09da2a1.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#backside-power-dtco", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "23aeef5f37b72468be29664abe219b9e3914530882bf1a5ce0e123854655aada", "contentLength": 5126, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-backside-power-dtco.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-backside-power-dtco.md", "sections": [ { "id": "section-1", "title": "Backside power and design–technology co-optimization" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Supply-path budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What makes a backside-power comparison meaningful?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#backside-power-dtco" }, { "title": "imec — CMOS scaling", "url": "https://www.imec-int.com/en/expertise/cmos-advanced/compute/cmos-scaling" }, { "title": "Intel Foundry — Accelerating HPC and AI", "url": "https://www.intel.com/content/dam/www/central-libraries/us/en/documents/2025-11/intel-foundry-hpc-ai-brief.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/backside-power-dtco-5a6a59fdd09da2a1.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wire resistance, low-k dielectrics and reliability", "url": "https://semiaifoundry.com/learn/atlas/interconnect-rc-materials/" }, { "title": "Voltage regulator module", "url": "https://semiaifoundry.com/learn/atlas/voltage-regulator/" }, { "title": "Temporary bonding, thinning and singulation", "url": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" } ], "recordHash": "9c64475efb36b441bd95aeb592e8b0254284b397d9d807bd30ead10288d8f50c" }, { "id": "atlas-lesson-beol-damascene-vias", "title": "BEOL layers, damascene and vias", "category": "learning", "format": "Atlas lesson", "description": "Builds a multilayer conductor network above completed device terminals.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/beol-damascene-vias/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / BEOL and co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Other BEOL routes and conductors exist. The copper example is a named representative flow, not an assertion that all levels and nodes use it.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/beol-damascene-vias-971a6a772607b650.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#beol-damascene-vias", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "437a4bcfd2710f2404f7882d3b1adddcc20180a7e50b8eb3a47c23f7cdfbc802", "contentLength": 5206, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-beol-damascene-vias.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-beol-damascene-vias.md", "sections": [ { "id": "section-1", "title": "BEOL layers, damascene and vias" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Series interconnect resistance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a small via defect matter even when a long wire is intact?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#beol-damascene-vias" }, { "title": "imec — Scaling the BEOL: a toolbox of processes and conductors", "url": "https://www.imec-int.com/en/imec-magazine/imec-magazine-september-2019/scaling-the-beol-a-toolbox-filled-with-new-processes-boosters-and-conductors" }, { "title": "Lam Research — Our Processes", "url": "https://www.lamresearch.com/products/our-processes/" }, { "title": "IBM Research — Full copper wiring in a sub-0.25 μm CMOS ULSI technology", "url": "https://research.ibm.com/publications/full-copper-wiring-in-a-sub-025-mm-cmos-ulsi-technology" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/beol-damascene-vias-971a6a772607b650.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Source/drain, spacers, contacts and MOL", "url": "https://semiaifoundry.com/learn/atlas/source-drain-contact-integration/" }, { "title": "Cleaning and CMP as interface preparation", "url": "https://semiaifoundry.com/learn/atlas/clean-planarize-surface/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Wire resistance, low-k dielectrics and reliability", "url": "https://semiaifoundry.com/learn/atlas/interconnect-rc-materials/" } ], "recordHash": "71c62940ca7332cc83699dfe1893d82aed474f754aea3d45a087609763b6cd78" }, { "id": "atlas-lesson-bump-thermocompression-assembly", "title": "Microbumps, reflow and thermocompression", "category": "learning", "format": "Atlas lesson", "description": "Forms electrical joints while controlling placement, local contact and material transformation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/bump-thermocompression-assembly/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Assembly and reliability", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No temperature, force, alloy or dwell-time recipe is specified. MR-MUF and thermocompression flows remain separate route examples.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/bump-thermocompression-assembly-f45081c93565d732.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#bump-thermocompression-assembly", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c47a446e62034c5918a3adf1affb806ba0c05855af38746a1d8b224f394375be", "contentLength": 5122, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-bump-thermocompression-assembly.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-bump-thermocompression-assembly.md", "sections": [ { "id": "section-1", "title": "Microbumps, reflow and thermocompression" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Current-density bookkeeping" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can good room-temperature alignment still leave opens after joining?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#bump-thermocompression-assembly" }, { "title": "Amkor — Flip Chip Packaging", "url": "https://amkor.com/technology/flip-chip/" }, { "title": "Besi — Scientific publications", "url": "https://www.besi.com/scientific-publications/" }, { "title": "SK hynix — Small Size, Big Impact", "url": "https://news.skhynix.com/en/small-size-big-impact/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/bump-thermocompression-assembly-f45081c93565d732.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Microbumps and bonding joints", "url": "https://semiaifoundry.com/learn/atlas/microbump/" }, { "title": "Flip-chip assembly and organic substrates", "url": "https://semiaifoundry.com/learn/atlas/flip-chip-abf-substrate/" }, { "title": "EMIB and localized die-to-die bridges", "url": "https://semiaifoundry.com/learn/atlas/emib-local-bridge/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" }, { "title": "Underfill, warpage, thermal paths and qualification", "url": "https://semiaifoundry.com/learn/atlas/package-thermomechanical-reliability/" } ], "recordHash": "25131746ec3fcddf9c1fbfbc5f9f93dc288fbc800f024c761dae6c56b89e2dca" }, { "id": "atlas-lesson-cable-cartridge", "title": "NVLink copper cable cartridge", "category": "learning", "format": "Atlas lesson", "description": "Provides dense physical signal connections between compute and switch trays.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cable-cartridge/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Rack integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Length, speed and payload rate are teaching assumptions rather than specifications for a cable cartridge. A physical cable route is distinct from the logical collective or network topology that uses it.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cable-cartridge-f4c862ca63ac4f0e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cable-cartridge", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c54c63445c468fde236fe247abb3c68ac97b41affb9549a495aaa1cadc6a6ef0", "contentLength": 5337, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cable-cartridge.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cable-cartridge.md", "sections": [ { "id": "section-1", "title": "NVLink copper cable cartridge" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Propagation and serialization" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does the atlas sample the cable paths?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cable-cartridge" }, { "title": "NVIDIA — Blackwell Rack-Scale Interconnection", "url": "https://blogs.nvidia.com/blog/blackwell-ai-inference/" }, { "title": "NVIDIA — DGX GB Rack Scale Systems Hardware Guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "NVIDIA — DGX GB200 SuperPOD Components", "url": "https://docs.nvidia.com/dgx-superpod/reference-architecture-scalable-infrastructure-gb200/latest/dgx-superpod-components.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cable-cartridge-f4c862ca63ac4f0e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "NVLink GPU interface", "url": "https://semiaifoundry.com/learn/atlas/nvlink-port/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "GB200 compute tray", "url": "https://semiaifoundry.com/learn/atlas/compute-tray/" }, { "title": "NVLink switch tray and scale-up fabric", "url": "https://semiaifoundry.com/learn/atlas/nvlink-switch/" }, { "title": "Optical transceiver and fiber link", "url": "https://semiaifoundry.com/learn/atlas/optics/" } ], "recordHash": "4bc508afd9acab7447ef5855416226e6e7c6d43637a18cd5d73266e85a97ef83" }, { "id": "atlas-lesson-capacity-phase-geography", "title": "Facility phases and geographical evidence", "category": "learning", "format": "Atlas lesson", "description": "Keeps physical sites, organizational names and development stages distinct before counting capacity.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/capacity-phase-geography/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Global AI infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This lesson supplies evidence methods and selected public cases, not a complete world census. The atlas’s facility records preserve the selected geographical examples.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/capacity-phase-geography-bdcaf4fe3d7d4285.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#capacity-phase-geography", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "224e31dc6f802f48652500969a68d0d7e12eeea65f17e6c4f3e8db16ecd03887", "contentLength": 5743, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-capacity-phase-geography.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-capacity-phase-geography.md", "sections": [ { "id": "section-1", "title": "Facility phases and geographical evidence" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Status-scoped aggregation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "How should a partly operating campus with an announced expansion be recorded?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#capacity-phase-geography" }, { "title": "Five new Stargate sites", "url": "https://openai.com/index/five-new-stargate-sites/" }, { "title": "Google AI Hub construction milestone in India", "url": "https://blog.google/intl/en-in/google-ai-hub-scaling-indias-ai-infrastructure-and-community-impact/" }, { "title": "The EuroHPC Joint Undertaking launches the AI Gigafactories Call", "url": "https://www.eurohpc-ju.europa.eu/eurohpc-joint-undertaking-launches-ai-gigafactories-call-2026-07-30_en" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/capacity-phase-geography-bdcaf4fe3d7d4285.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Commissioning a usable AI cluster", "url": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/" }, { "title": "Production ramps, inventory and allocation", "url": "https://semiaifoundry.com/learn/atlas/production-ramp-allocation/" }, { "title": "Siting, regional infrastructure and access to compute", "url": "https://semiaifoundry.com/learn/atlas/regional-siting-access/" } ], "recordHash": "ee0e5b611c259f0f8df323a4492ba8fc8de7fedc9052c59274d6a719d879b127" }, { "id": "atlas-lesson-causal-pretraining-objective", "title": "Next-token supervision from raw sequences", "category": "learning", "format": "Atlas lesson", "description": "Construct shifted next-token targets and interpret token likelihood separately from answer accuracy.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-pretraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable core. Natural logarithms, positive target probabilities and nonzero denominator. Perplexities with different tokenization/masks are not directly comparable. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/causal-pretraining-objective-0045cc6f8ca8a55b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#causal-pretraining-objective", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "2124b0d54fd316ec7657c90f8237469c28c2136852ce186edad9424cb1d0d7d5", "contentLength": 6013, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-causal-pretraining-objective.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-causal-pretraining-objective.md", "sections": [ { "id": "section-1", "title": "Next-token supervision from raw sequences" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Next-token supervision from raw sequences · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which comparison uses the same next-token objective?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#causal-pretraining-objective" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Attention Is All You Need", "url": "https://arxiv.org/html/1706.03762v7" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/causal-pretraining-objective-0045cc6f8ca8a55b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Assemble an initialized causal language model", "url": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/" }, { "title": "Packing documents and masking valid targets", "url": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/" }, { "title": "Initialization, learning rate and stable updates", "url": "https://semiaifoundry.com/learn/atlas/optimizer-schedule-stability/" }, { "title": "Gradient accumulation under a fixed global objective", "url": "https://semiaifoundry.com/learn/atlas/microbatch-equivalent-updates/" } ], "recordHash": "2c2dc50a548da67ac2e7c0f3d546a2d7c61d7bfe51191873411396f27f2bef16" }, { "id": "atlas-lesson-cdu", "title": "Coolant distribution unit and separated loops", "category": "learning", "format": "Atlas lesson", "description": "Controls the IT coolant loop and transfers collected heat to another cooling system.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cdu/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Thermal infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The model excludes pump power, exchanger approach temperature and redundancy.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cdu-ba276d9443d0bfb9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cdu", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "55091bfbdfc3d6e389970c3963d77afba99697c81b7b391d8e8ea976f1446a6c", "contentLength": 4644, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cdu.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cdu.md", "sections": [ { "id": "section-1", "title": "Coolant distribution unit and separated loops" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Sensible heat transport" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What crosses between the two separated loops?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cdu" }, { "title": "Vertiv — Understanding Coolant Distribution Units", "url": "https://www.vertiv.com/en-anz/insights/articles/educational-articles/understanding-coolant-distribution-units-cdus-for-liquid-cooling/" }, { "title": "NREL — Data-Center Heat-Balance Analysis", "url": "https://www1.eere.energy.gov/buildings/publications/pdfs/rsf/reducing_data_center_loads_large_scale_low_energy_office_building.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cdu-ba276d9443d0bfb9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Liquid-cooling coldplate", "url": "https://semiaifoundry.com/learn/atlas/coldplate/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "GB200 compute tray", "url": "https://semiaifoundry.com/learn/atlas/compute-tray/" }, { "title": "Facility cooling and final heat rejection", "url": "https://semiaifoundry.com/learn/atlas/cooling-plant/" } ], "recordHash": "9e52fe4a77a02c57a8f5c2f55e7b362b7a9b2953b56d383acd94a14179c696a1" }, { "id": "atlas-lesson-channel", "title": "Controllable semiconductor channel", "category": "learning", "format": "Atlas lesson", "description": "Forms the field-controlled conduction path inside the transistor.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/channel/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Device physics", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The channel equation is a gradual-channel teaching approximation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/channel-f59d6c3c83d50804.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#channel", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "e142089a57d57e50338b89d81f8539290daec0094217368733f98166cdb7cc64", "contentLength": 4725, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-channel.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-channel.md", "sections": [ { "id": "section-1", "title": "Controllable semiconductor channel" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Inversion-sheet charge" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What changes when an inversion channel forms?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#channel" }, { "title": "MIT 6.012 — MOS Electrostatics Under Bias", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/ba97ec0d4b75ff1049567a48e66b74a0_lec8.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/channel-f59d6c3c83d50804.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Energy bands and carriers", "url": "https://semiaifoundry.com/learn/atlas/energy-bands/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "Fin field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/finfet/" }, { "title": "Gate-all-around nanosheet transistor", "url": "https://semiaifoundry.com/learn/atlas/gaa/" } ], "recordHash": "49b9a35ade15c153d4f8e36eea50dc02e6715c619d0527f12dafcb294870db42" }, { "id": "atlas-lesson-checkpoint", "title": "Distributed checkpoint and recovery state", "category": "learning", "format": "Atlas lesson", "description": "Persists enough execution state to resume a model workflow after interruption.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/checkpoint/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "System operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The bound is an I/O boundary, not a complete recovery policy.\n\nThe local E5 journal/receipt replay is executable. It is separate from the operating hall’s retained computational-work model and from actual distributed training checkpoint formats.\n\nMode: executable full checkpoint. Exact equality is tested within one numerical implementation and operation order. Cross-device floating-point kernels can require a tolerance or different reproducibility contract. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/checkpoint-71d8146fe35d9574.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#checkpoint", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ead48a54e3ef4b971238a9058b72da897c9c0dae37c17afddf3ddc9e991a9684", "contentLength": 10523, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-checkpoint.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-checkpoint.md", "sections": [ { "id": "section-1", "title": "Distributed checkpoint and recovery state" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Checkpoint write-time floor" }, { "id": "section-5", "title": "Restart the same learning experiment · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Which statement about a training checkpoint is correct?" }, { "id": "section-12", "title": "Does restoring a training checkpoint automatically undo a committed tool reservation?" }, { "id": "section-13", "title": "What is missing from a weights-only continuation record?" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#checkpoint" }, { "title": "PyTorch — Distributed Checkpoint", "url": "https://docs.pytorch.org/docs/stable/distributed.checkpoint.html" }, { "title": "Temporal Workflow Execution", "url": "https://docs.temporal.io/workflow-execution" }, { "title": "Temporal Activities", "url": "https://docs.temporal.io/activities" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/checkpoint-71d8146fe35d9574.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Dataset and checkpoint storage hierarchy", "url": "https://semiaifoundry.com/learn/atlas/storage/" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Uninterruptible power supply and backup chain", "url": "https://semiaifoundry.com/learn/atlas/ups/" }, { "title": "Durable actions and the ambiguous timeout", "url": "https://semiaifoundry.com/learn/atlas/durable-actions-idempotency/" }, { "title": "Context, retrieval and durable memory", "url": "https://semiaifoundry.com/learn/atlas/context-memory-provenance/" }, { "title": "When completed work survives a restart", "url": "https://semiaifoundry.com/learn/atlas/retained-work-restart-boundary/" }, { "title": "Next-token supervision from raw sequences", "url": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/" }, { "title": "Initialization, learning rate and stable updates", "url": "https://semiaifoundry.com/learn/atlas/optimizer-schedule-stability/" }, { "title": "Gradient accumulation under a fixed global objective", "url": "https://semiaifoundry.com/learn/atlas/microbatch-equivalent-updates/" } ], "recordHash": "96d6d682650e8f957b0316d81c93263c3ae093a65b042908ae8eae68ad111f19" }, { "id": "atlas-lesson-checkpoint-averaging-boundaries", "title": "Compatible weight averaging and regressions", "category": "learning", "format": "Atlas lesson", "description": "Check parameter alignment before averaging and evaluate the resulting function.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/checkpoint-averaging-boundaries/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-continuation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Compatible parameter coordinates and tokenizer required. Permutation counterexample is an exact linear network; no averaging feature is executed by the lifecycle core. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/checkpoint-averaging-boundaries-6f89c616c7334d7b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#checkpoint-averaging-boundaries", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9b04028466aabf214dc6611a12e0da892b0dfe46c8f845b5cd7ed033ab80381f", "contentLength": 6198, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-checkpoint-averaging-boundaries.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-checkpoint-averaging-boundaries.md", "sections": [ { "id": "section-1", "title": "Compatible weight averaging and regressions" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Compatible weight averaging and regressions · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why do equal tensor shapes fail to guarantee a useful average?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#checkpoint-averaging-boundaries" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/checkpoint-averaging-boundaries-6f89c616c7334d7b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Describe a stage by its changed contract", "url": "https://semiaifoundry.com/learn/atlas/model-lifecycle-stage-contract/" }, { "title": "Continue language modeling on a new domain", "url": "https://semiaifoundry.com/learn/atlas/domain-adaptive-continuation/" }, { "title": "Retention, replay and transfer", "url": "https://semiaifoundry.com/learn/atlas/replay-retention-forgetting/" }, { "title": "Context extension is a learned-use test", "url": "https://semiaifoundry.com/learn/atlas/long-context-adaptation/" } ], "recordHash": "a3d22b6d4026cbd548e3ee66dfce9ae782bcbd0fcfb92b688f08a18cbcf1fe14" }, { "id": "atlas-lesson-checkpoint-retained-work", "title": "Checkpointing, failure and retained useful work", "category": "learning", "format": "Atlas lesson", "description": "Balances checkpoint overhead against lost progress and recovery delay.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/checkpoint-retained-work/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Failure rates and times are synthetic. Provider-reported speedups are not imported as defaults; real failure correlation and checkpoint durability require operational evidence.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/checkpoint-retained-work-34f5856318637549.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#checkpoint-retained-work", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "6bbd59bce61dcbf90373833a68950babeec1c66c495a21b0dbe80b2b83b272c3", "contentLength": 5042, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-checkpoint-retained-work.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-checkpoint-retained-work.md", "sections": [ { "id": "section-1", "title": "Checkpointing, failure and retained useful work" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Simple checkpoint loss fraction" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What should a useful-work metric exclude after a restart?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#checkpoint-retained-work" }, { "title": "Elastic training and optimized checkpointing improve ML Goodput", "url": "https://cloud.google.com/blog/products/ai-machine-learning/elastic-training-and-optimized-checkpointing-improve-ml-goodput" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/checkpoint-retained-work-34f5856318637549.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Dataset and checkpoint storage hierarchy", "url": "https://semiaifoundry.com/learn/atlas/storage/" }, { "title": "Storage paths for datasets and checkpoints", "url": "https://semiaifoundry.com/learn/atlas/storage-input-checkpoint-path/" } ], "recordHash": "99c02d108a1eea5277477a2d30f3ae87a311cca9f63c919a74d12dfff9e95ae1" }, { "id": "atlas-lesson-chip-physical-closure", "title": "PDKs, synthesis and physical closure", "category": "learning", "format": "Atlas lesson", "description": "Converts logical behavior into a manufacturable layout under electrical constraints.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/chip-physical-closure/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Custom silicon ecosystem", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "SKY130’s open documentation warns that the open release is not intended for production use. These examples explain the flow without implying access to commercial signoff decks.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-physical-closure-ef52421d901adf0c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#chip-physical-closure", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "40db7ae466a572f46e973fbf3a16ee458749154c85dd53523dfcc38c99ecc51d", "contentLength": 5276, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-physical-closure.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-physical-closure.md", "sections": [ { "id": "section-1", "title": "PDKs, synthesis and physical closure" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Timing closure model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A longer routed wire causes a timing failure. Why might pre-layout simulation miss it?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#chip-physical-closure" }, { "title": "SkyWater SKY130 PDK Documentation", "url": "https://skywater-pdk.readthedocs.io/en/main/" }, { "title": "OpenROAD documentation", "url": "https://openroad.readthedocs.io/en/latest/main/README.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-physical-closure-ef52421d901adf0c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "Tapeout, bring-up and productization", "url": "https://semiaifoundry.com/learn/atlas/chip-tapeout-productization/" } ], "recordHash": "3dd94fb573c876fef3b2f10c7b43d3f667b5721404ab6e43e9cda96cedb60044" }, { "id": "atlas-lesson-chip-rtl-verification", "title": "RTL and functional verification", "category": "learning", "format": "Atlas lesson", "description": "Checks that a cycle-based design obeys its specification before manufacture.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/chip-rtl-verification/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Custom silicon ecosystem", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "OpenTitan is a methodology example, not an AI accelerator design. Proprietary test coverage and signoff criteria are unknown and are not invented.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-rtl-verification-a059c32d0e186ea1.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#chip-rtl-verification", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9466d12df66133e6e56d1ebc60fd70f745b2d0b22b66bf3add8172243bbf9086", "contentLength": 4955, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-rtl-verification.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-rtl-verification.md", "sections": [ { "id": "section-1", "title": "RTL and functional verification" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "State-space growth" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What makes a test useful for a hardware handshake?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#chip-rtl-verification" }, { "title": "OpenTitan Verification Methodology, Earlgrey 1.0.0", "url": "https://opentitan.org/earlgrey_1.0.0/book/doc/contributing/dv/methodology/index.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-rtl-verification-a059c32d0e186ea1.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" }, { "title": "Workload contract and architecture selection", "url": "https://semiaifoundry.com/learn/atlas/chip-workload-contract/" }, { "title": "PDKs, synthesis and physical closure", "url": "https://semiaifoundry.com/learn/atlas/chip-physical-closure/" } ], "recordHash": "360ee2d68162f6958b9e2b2ecb7665c9f0894c7ce2fc4baeffe4e7f6e375fe62" }, { "id": "atlas-lesson-chip-tapeout-productization", "title": "Tapeout, bring-up and productization", "category": "learning", "format": "Atlas lesson", "description": "Coordinates design release, manufacturing partners and software into a usable product.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/chip-tapeout-productization/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Custom silicon ecosystem", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No confidential partnership, contract, yield or schedule is claimed. Open development stages illustrate evidence discipline, not a universal manufacturer release process.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-tapeout-productization-2cedd1fda232c638.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#chip-tapeout-productization", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "53064a382c4f5e9f26b10d3c21ce0db5d4fc9c8c307afcf469b2ed2cb2369c21", "contentLength": 5096, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-tapeout-productization.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-tapeout-productization.md", "sections": [ { "id": "section-1", "title": "Tapeout, bring-up and productization" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Dependency readiness" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which result is still missing after a successful tapeout?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#chip-tapeout-productization" }, { "title": "OpenTitan Hardware Development Stages", "url": "https://opentitan.org/book/doc/project_governance/development_stages.html" }, { "title": "OpenROAD documentation", "url": "https://openroad.readthedocs.io/en/latest/main/README.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-tapeout-productization-2cedd1fda232c638.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "PDKs, synthesis and physical closure", "url": "https://semiaifoundry.com/learn/atlas/chip-physical-closure/" }, { "title": "RTL and functional verification", "url": "https://semiaifoundry.com/learn/atlas/chip-rtl-verification/" }, { "title": "Baseboard management controller", "url": "https://semiaifoundry.com/learn/atlas/management-controller/" } ], "recordHash": "3b87351515c8dc88a4dd1c69c56cb6a01bc65af0a3791492dfa690f3bc0a0264" }, { "id": "atlas-lesson-chip-volume-economics", "title": "Custom-chip volume economics", "category": "learning", "format": "Atlas lesson", "description": "Compares lifecycle costs per useful result under explicit volume and performance assumptions.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/chip-volume-economics/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Custom silicon ecosystem", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "All money values are illustrative. Research cost coefficients are not 2026 quotes, and confidential foundry, memory and packaging contracts remain unknown.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-volume-economics-0e3c12fc0bb2b96a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#chip-volume-economics", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b4c1d976ac6abbb824ada0b260538b233c23daefe0a6c577d29a617b93435738", "contentLength": 5263, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-volume-economics.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-volume-economics.md", "sections": [ { "id": "section-1", "title": "Custom-chip volume economics" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Simplified break-even volume" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What happens to fixed development cost per unit when usable volume is halved?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#chip-volume-economics" }, { "title": "Chiplet Actuary: A Quantitative Cost Model and Multi-Chiplet Architecture Exploration", "url": "https://arxiv.org/abs/2203.12268v4" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-volume-economics-0e3c12fc0bb2b96a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Workload contract and architecture selection", "url": "https://semiaifoundry.com/learn/atlas/chip-workload-contract/" }, { "title": "GPU chiplets and memory locality", "url": "https://semiaifoundry.com/learn/atlas/gpu-chiplet-locality/" }, { "title": "Tapeout, bring-up and productization", "url": "https://semiaifoundry.com/learn/atlas/chip-tapeout-productization/" } ], "recordHash": "908490332d15fdf08af01e1d8c30ff6e1531d9f6791e77e68a986efbfe0aaaa6" }, { "id": "atlas-lesson-chip-workload-contract", "title": "Workload contract and architecture selection", "category": "learning", "format": "Atlas lesson", "description": "Turns desired service behavior into measurable hardware and software requirements.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/chip-workload-contract/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Custom silicon ecosystem", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Workload mix values are synthetic. Public co-design accounts do not reveal a provider’s complete internal traces, IP contracts or acceptance thresholds.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-workload-contract-5b9ec61ef1e7641d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#chip-workload-contract", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "32566e9f8893a06146760f57b889b24bf0471ae00cd032ee7889a83853d47579", "contentLength": 5551, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-workload-contract.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-chip-workload-contract.md", "sections": [ { "id": "section-1", "title": "Workload contract and architecture selection" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Workload-weighted demand" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which requirement most directly prevents a misleading inference performance target?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#chip-workload-contract" }, { "title": "Inside the hardware and co-design of MTIA", "url": "https://engineering.fb.com/2024/08/22/ml-applications/meta-mtia-hardware-co-design/" }, { "title": "Chiplet Actuary: A Quantitative Cost Model and Multi-Chiplet Architecture Exploration", "url": "https://arxiv.org/abs/2203.12268v4" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/chip-workload-contract-5b9ec61ef1e7641d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" }, { "title": "Custom inference silicon: Maia and MTIA", "url": "https://semiaifoundry.com/learn/atlas/inference-custom-silicon/" }, { "title": "RTL and functional verification", "url": "https://semiaifoundry.com/learn/atlas/chip-rtl-verification/" }, { "title": "Custom-chip volume economics", "url": "https://semiaifoundry.com/learn/atlas/chip-volume-economics/" } ], "recordHash": "8f7c2afec941420c4cf926f744e8efa7fa28cfc52b5fcd7b88a9a29c550bf530" }, { "id": "atlas-lesson-clean-planarize-surface", "title": "Cleaning and CMP as interface preparation", "category": "learning", "format": "Atlas lesson", "description": "Removes residues and topography while controlling loss, shape and defects.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/clean-planarize-surface/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / FEOL and MOL", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Illustrative coefficients, defect maps and acceptance ranges are not production tolerances. A spatial association does not prove a CMP root cause.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/clean-planarize-surface-b4aee2df6719e290.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#clean-planarize-surface", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f55b502488eb034aabcdb5c6c450ac29792b50782cb40c16860098ea690c3223", "contentLength": 5056, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-clean-planarize-surface.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-clean-planarize-surface.md", "sections": [ { "id": "section-1", "title": "Cleaning and CMP as interface preparation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Preston-type removal model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Average film thickness meets target, but bonding opens cluster over dense wiring. What is the next useful evidence?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#clean-planarize-surface" }, { "title": "imec — Wafer-to-wafer hybrid bonding: 400 nm interconnect pitch", "url": "https://www.imec-int.com/en/articles/wafer-wafer-hybrid-bonding-pushing-boundaries-400nm-interconnect-pitch" }, { "title": "Lam Research — Our Processes", "url": "https://www.lamresearch.com/products/our-processes/" }, { "title": "KLA — Chip Manufacturing 101", "url": "https://www.kla.com/wp-content/uploads/ChipManufacturing101.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/clean-planarize-surface-b4aee2df6719e290.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Chemical mechanical planarization", "url": "https://semiaifoundry.com/learn/atlas/cmp/" }, { "title": "Contamination and the state of a surface", "url": "https://semiaifoundry.com/learn/atlas/contamination-and-surface-state/" }, { "title": "BEOL layers, damascene and vias", "url": "https://semiaifoundry.com/learn/atlas/beol-damascene-vias/" }, { "title": "Hybrid bonding: surface state and alignment", "url": "https://semiaifoundry.com/learn/atlas/hybrid-bond-surface-alignment/" } ], "recordHash": "d404dcd2a7d5701f25a4734c32a5a08581cc98cfff5ec4f96a6ab16568a22120" }, { "id": "atlas-lesson-cleanroom-subfab-utilities", "title": "Cleanroom and subfab utilities", "category": "learning", "format": "Atlas lesson", "description": "Supplies the environmental and support systems required by process tools.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cleanroom-subfab-utilities/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Factory systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Utility inventories are representative. No facility gas flows, water demand, cleanroom class or abatement destruction efficiency is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cleanroom-subfab-utilities-a7f9e90d7c5622c1.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cleanroom-subfab-utilities", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c4c060faf611082113eede1b9c75f5173ebbaada5d565958c9f16ea37b6b01b4", "contentLength": 5489, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cleanroom-subfab-utilities.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cleanroom-subfab-utilities.md", "sections": [ { "id": "section-1", "title": "Cleanroom and subfab utilities" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Dependency availability" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "An installed etch chamber lacks qualified exhaust support. How should its output be counted?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cleanroom-subfab-utilities" }, { "title": "Edwards — Semiconductor vacuum and abatement", "url": "https://www.edwardsvacuum.com/en-us/semiconductor" }, { "title": "Entegris — Understanding AMC", "url": "https://blog.entegris.com/understanding-amc-the-invisible-threat-to-semiconductor-yield-and-reliability" }, { "title": "Entegris — Contamination Control in Ultrapure Chemicals and Water", "url": "https://www.entegris.com/en/home/resources/technical-information/faq/contamination-control-in-ultrapure-chemicals-and-water.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cleanroom-subfab-utilities-a7f9e90d7c5622c1.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Contamination and the state of a surface", "url": "https://semiaifoundry.com/learn/atlas/contamination-and-surface-state/" }, { "title": "A process chamber as a controlled reactor", "url": "https://semiaifoundry.com/learn/atlas/process-chamber-control/" }, { "title": "Cycle time, ramp and effective capacity", "url": "https://semiaifoundry.com/learn/atlas/fab-ramp-cycle-time/" } ], "recordHash": "770e9d8ee879cdea9d9dc7696704e8be7483a8dbc5ad5446ec1241ec59f0e513" }, { "id": "atlas-lesson-clock", "title": "Clock tree and gated timing domains", "category": "learning", "format": "Atlas lesson", "description": "Distributes capture timing to sequential circuits while managing switching activity.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/clock/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Digital circuits", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The timing sum is a signoff abstraction, not a clock-tree implementation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/clock-acb9c0d055b2be68.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#clock", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "5d972abf3860747056aee789cb2aa6a0cdd04730f520a5c4e6c23d988f38531e", "contentLength": 4540, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-clock.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-clock.md", "sections": [ { "id": "section-1", "title": "Clock tree and gated timing domains" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Frequency and timing margin" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is clock gating intended to reduce?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#clock" }, { "title": "Arm — Power Control System Architecture", "url": "https://documentation-service.arm.com/static/63f3499c9567172d4e2aadd6" }, { "title": "Arm — Fundamentals of System-on-Chip Design", "url": "https://armkeil.blob.core.windows.net/developer/Files/pdf/ebook/arm-fundamentals-soc.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/clock-acb9c0d055b2be68.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" } ], "recordHash": "832402eeb2c4c7b0d78b0106d20e770ba625136e6d06ca048fca1e7ff38de6ab" }, { "id": "atlas-lesson-cluster-commissioning-gates", "title": "Commissioning a usable AI cluster", "category": "learning", "format": "Atlas lesson", "description": "Requires accepted electrical, thermal, network, software and operational behavior together.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center physical systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The set-overlap qualification matters: taking minima assumes compatible resources. This lesson supplies an educational gate model, not a manufacturer acceptance procedure.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cluster-commissioning-gates-c4ba89b0f7e4d0c1.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cluster-commissioning-gates", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "d3b96c46e22bb5ad3af650487ec4d70dbbb50fc12f8f41115dc9987a082afe38", "contentLength": 4962, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cluster-commissioning-gates.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cluster-commissioning-gates.md", "sections": [ { "id": "section-1", "title": "Commissioning a usable AI cluster" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Readiness conjunction" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why might a healthy accelerator remain unavailable for jobs?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cluster-commissioning-gates" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Hardware", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Networking", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/networking.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cluster-commissioning-gates-c4ba89b0f7e4d0c1.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "Baseboard management controller", "url": "https://semiaifoundry.com/learn/atlas/management-controller/" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" }, { "title": "Grid interconnection and deliverable electrical capacity", "url": "https://semiaifoundry.com/learn/atlas/grid-interconnection-readiness/" } ], "recordHash": "ed52c1af7fc7464ec7fdf60bee39f22d66b26edfe7ea8366c394f92866cd8c56" }, { "id": "atlas-lesson-cmp", "title": "Chemical mechanical planarization", "category": "learning", "format": "Atlas lesson", "description": "Restores controlled surface planarity between fabrication stages.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cmp/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The nominal residual is not a spatial mean and is not a bonding-readiness guarantee.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cmp-765ad3af18f3b8ed.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cmp", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "79844161828c0e8ae1add6f0af6e44ade4d25860c5d472986fbb3280ed399eef", "contentLength": 4799, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cmp.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cmp.md", "sections": [ { "id": "section-1", "title": "Chemical mechanical planarization" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Preston removal relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why is surface planarity important?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cmp" }, { "title": "Applied Materials — Chemical Mechanical Planarization", "url": "https://www.appliedmaterials.com/us/en/semiconductor/products/shape/cmp.html" }, { "title": "MIT — Control of Wafer-Scale Nonuniformity in CMP", "url": "https://dspace.mit.edu/server/api/core/bitstreams/3190d1a1-d6a9-40d3-83ed-85939659b1f0/content" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cmp-765ad3af18f3b8ed.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer and fabrication hierarchy", "url": "https://semiaifoundry.com/learn/atlas/silicon-wafer/" }, { "title": "Copper conductor and barrier", "url": "https://semiaifoundry.com/learn/atlas/copper-conductor/" }, { "title": "Lithography and pattern transfer", "url": "https://semiaifoundry.com/learn/atlas/lithography/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Interposer and redistribution layers", "url": "https://semiaifoundry.com/learn/atlas/interposer/" } ], "recordHash": "ddd7b6121c5c299982e032c4470c3f2999059fc97132b27866e9e36ac7a4ad0c" }, { "id": "atlas-lesson-coding-agent-patch-evidence", "title": "A code patch needs execution evidence", "category": "learning", "format": "Atlas lesson", "description": "Repository context, patch application, sandboxed commands, hidden tests and result artifacts.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/coding-agent-patch-evidence/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Models become evaluated applications", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Exact small-number worked behavior; finite-number rounding and empty-input policy require separate tests. No coding model or repository execution is claimed for this example.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/coding-agent-patch-evidence-21fe8bff6485e21f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#coding-agent-patch-evidence", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bfe1779e1bf542843e69a5da90313d087c9c5598415183ded7cfca1a639329ec", "contentLength": 7074, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-coding-agent-patch-evidence.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-coding-agent-patch-evidence.md", "sections": [ { "id": "section-1", "title": "A code patch needs execution evidence" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A code patch needs execution evidence · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A patch hard-codes 4 and passes mean(\\[2,4,6\\]). Which test exposes that overfit?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#coding-agent-patch-evidence" }, { "title": "SWE-bench: Can Language Models Resolve Real-World GitHub Issues?", "url": "https://arxiv.org/abs/2310.06770v3" }, { "title": "Linux man-pages · namespaces(7)", "url": "https://man7.org/linux/man-pages/man7/namespaces.7.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/coding-agent-patch-evidence-21fe8bff6485e21f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Execution boundaries for code and tools", "url": "https://semiaifoundry.com/learn/atlas/sandbox-egress-secrets/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Forecasts are tested forward in time", "url": "https://semiaifoundry.com/learn/atlas/temporal-forecast-validation/" }, { "title": "Traces connect cost, latency and results", "url": "https://semiaifoundry.com/learn/atlas/telemetry-traces-evaluation/" } ], "recordHash": "efe0a67b7aff0111253f2426a925cdc55aa51ef6d69a7bec7bb9c3a44ca5f73d" }, { "id": "atlas-lesson-coherence-numa", "title": "Cache coherence and NUMA placement", "category": "learning", "format": "Atlas lesson", "description": "Keeps shared cache lines consistent while preserving awareness of physical memory location.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/coherence-numa/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Topology illustrations omit protocol state details. Local-versus-remote numbers are invented for calculation, not measurements of a named CPU.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/coherence-numa-e5a3b6b81d4eff19.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#coherence-numa", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9f645460db7cff4ee9a77c002d7c5513a554dbda8c96a47040b6d8fb1995c2e2", "contentLength": 4889, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-coherence-numa.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-coherence-numa.md", "sections": [ { "id": "section-1", "title": "Cache coherence and NUMA placement" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Average access path" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Two cores update different counters in the same cache line. Why might they interfere?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#coherence-numa" }, { "title": "What is NUMA? Linux kernel 6.6 documentation", "url": "https://www.kernel.org/doc/html/v6.6/mm/numa.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/coherence-numa-e5a3b6b81d4eff19.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Shared L2 cache", "url": "https://semiaifoundry.com/learn/atlas/l2-cache/" }, { "title": "Out-of-order CPU pipeline", "url": "https://semiaifoundry.com/learn/atlas/cpu-out-of-order/" }, { "title": "DDR5 server memory", "url": "https://semiaifoundry.com/learn/atlas/ddr-memory/" }, { "title": "Full memory hierarchy and input path", "url": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/" } ], "recordHash": "e5aaa0f3d7794afa69e9746c00770d50907b7d0f4a062172428076e7c680f5be" }, { "id": "atlas-lesson-coldplate", "title": "Liquid-cooling coldplate", "category": "learning", "format": "Atlas lesson", "description": "Captures heat at the processor and transfers it into flowing coolant.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/coldplate/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Thermal path", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Fluid properties, flow distribution and two-phase effects are omitted.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/coldplate-ee27baac4cdcf2f3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#coldplate", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "6736ed68a3a1cbb70da84bdfb357815f904bcb8448b1ccc46668ae7c9281ad5b", "contentLength": 5474, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-coldplate.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-coldplate.md", "sections": [ { "id": "section-1", "title": "Liquid-cooling coldplate" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Flow and temperature rise account for captured heat" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can very small channels create a cooling tradeoff?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#coldplate" }, { "title": "CoolIT: Split-Flow microchannel coldplate technology", "url": "https://www.coolitsystems.com/wp-content/uploads/2024/05/Split-Flow-Technology-CoolIT-Tech-Brief.pdf" }, { "title": "CoolIT: The coldplate in a complete cooling system", "url": "https://www.coolitsystems.com/coldplate-technology/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/coldplate-ee27baac4cdcf2f3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Thermal interface material", "url": "https://semiaifoundry.com/learn/atlas/thermal-interface/" }, { "title": "Lid and heat spreader", "url": "https://semiaifoundry.com/learn/atlas/heat-spreader/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "Coolant distribution unit and separated loops", "url": "https://semiaifoundry.com/learn/atlas/cdu/" } ], "recordHash": "c551c0860d0baed8ef02b7712a6722a71cee5578a4a38c521595a52f5d328ebc" }, { "id": "atlas-lesson-compatible-supply-capacity", "title": "Compatible supply and converging bottlenecks", "category": "learning", "format": "Atlas lesson", "description": "Converts independently manufactured inputs into a common finished-system basis.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/compatible-supply-capacity/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center physical systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No vendor capacity, queue or HBM wafer-intensity number is invented. Synthetic inputs are explicitly screened, avoiding repeated raw-die yield penalties.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/compatible-supply-capacity-7a526aaf0701ce73.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#compatible-supply-capacity", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "d9fe18287663a74819726b69b5272c140618a8025990d246b7b7ef0e9513d487", "contentLength": 4930, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compatible-supply-capacity.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compatible-supply-capacity.md", "sections": [ { "id": "section-1", "title": "Compatible supply and converging bottlenecks" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Converging supply bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "If each package needs four HBM stacks, what can 400 compatible good stacks support before later losses?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#compatible-supply-capacity" }, { "title": "TSMC CoWoS technology", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm" }, { "title": "TSMC 2025 Annual Report", "url": "https://investor.tsmc.com/sites/ir/annual-report/2025/2025%20TSMC%20Annual%20Report.E.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/compatible-supply-capacity-7a526aaf0701ce73.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" }, { "title": "Commissioning a usable AI cluster", "url": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/" } ], "recordHash": "236f97dc44a2f397272ec2b484c8bd85cb8789f4de2fc3aebdb3fa6e08b3c282" }, { "id": "atlas-lesson-compiler", "title": "Compiler, intermediate code, and device executable", "category": "learning", "format": "Atlas lesson", "description": "Transforms program descriptions into executable instructions and runtime-compatible artifacts.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/compiler/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Execution software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The equation is an execution-time decomposition, not a compiler guarantee.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/compiler-6b5b554286557b37.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#compiler", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "cfe6d8400afb9803b32d1b3032b5e9a6a6f847fb23fe85ab3188515fd7a0bad7", "contentLength": 4744, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compiler.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compiler.md", "sections": [ { "id": "section-1", "title": "Compiler, intermediate code, and device executable" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Sequential execution-time decomposition" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is the compiler’s central job in this layer?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#compiler" }, { "title": "NVIDIA — CUDA Compiler Driver NVCC", "url": "https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/compiler-6b5b554286557b37.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "CUDA programming and runtime layer", "url": "https://semiaifoundry.com/learn/atlas/cuda/" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" } ], "recordHash": "f74921bb72b19e16474a3ad9f92db53138cf68ce109c3aa9cecb7d97e6cbb361" }, { "id": "atlas-lesson-compiler-layout-lowering", "title": "Compiler layout, lowering and buffer planning", "category": "learning", "format": "Atlas lesson", "description": "Chooses memory organization and hardware operations that implement a tensor graph.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/compiler-layout-lowering/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "OpenXLA is a representative compiler route. Exact passes, emitter choices and executable formats depend on software revision and target architecture.\n\nThese are logical address and payload counts for a synthetic array. They exclude cache effects, allocator overhead and measured compiler/device performance.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/compiler-layout-lowering-2346e5cffdce248a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#compiler-layout-lowering", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "40e429a918541223908fed6c352e3878722419ce70b20f03a7ed41962a213cde", "contentLength": 6980, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compiler-layout-lowering.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compiler-layout-lowering.md", "sections": [ { "id": "section-1", "title": "Compiler layout, lowering and buffer planning" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Dense stride mapping" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "When can two temporary tensors safely share a buffer?" }, { "id": "section-11", "title": "What is the payload traffic for reading and writing six two-byte elements once during a transpose copy?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#compiler-layout-lowering" }, { "title": "XLA:GPU Architecture Overview", "url": "https://openxla.org/xla/gpu_architecture" }, { "title": "StableHLO specification", "url": "https://openxla.org/stablehlo/spec" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/compiler-layout-lowering-2346e5cffdce248a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Model graph and tensor intermediate representation", "url": "https://semiaifoundry.com/learn/atlas/graph-tensor-ir/" }, { "title": "Full memory hierarchy and input path", "url": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/" }, { "title": "Kernel tiling, fusion and operand reuse", "url": "https://semiaifoundry.com/learn/atlas/kernel-locality-fusion/" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" }, { "title": "Sharded matrix multiplication and result ownership", "url": "https://semiaifoundry.com/learn/atlas/sharded-matmul-ownership/" } ], "recordHash": "90f231e4ee2fae32062a1406f7f86e0400375e7cc53f0e2909a79f8f86e40298" }, { "id": "atlas-lesson-compute-baseboard", "title": "Compute baseboard and tray", "category": "learning", "format": "Atlas lesson", "description": "Integrates processors, memory, adapters, power, cooling, and service interfaces into an operational node.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/compute-baseboard/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "System integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is the lesson’s single-termination linear transmission-line model. Values are synthetic; differential geometry, frequency response, loss, multiple reflections and receiver behavior need a complete channel model.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/compute-baseboard-3218c9a079eac9cd.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#compute-baseboard", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "91f23254f5f53d1a2aa3d45f76fb36cdb66e590b46170ee75b6d9a9bc12bced4", "contentLength": 6468, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compute-baseboard.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compute-baseboard.md", "sections": [ { "id": "section-1", "title": "Compute baseboard and tray" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Impedance discontinuities reflect fast signals" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why inspect a compute tray’s topology before distributing a workload?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#compute-baseboard" }, { "title": "NVIDIA DGX GB200 SuperPOD reference components", "url": "https://docs.nvidia.com/dgx-superpod/reference-architecture-scalable-infrastructure-gb200/latest/dgx-superpod-components.html" }, { "title": "NVIDIA GB200 NVL multi-node tuning: system topology", "url": "https://docs.nvidia.com/multi-node-nvlink-systems/multi-node-tuning-guide/system.html" }, { "title": "Texas Instruments: High-Speed Layout Guidelines", "url": "https://www.ti.com/lit/pdf/SCAA082A" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/compute-baseboard-3218c9a079eac9cd.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" }, { "title": "PCI Express interconnect", "url": "https://semiaifoundry.com/learn/atlas/pcie-interface/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Grace Blackwell Superchip", "url": "https://semiaifoundry.com/learn/atlas/grace-blackwell-superchip/" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" }, { "title": "NVMe solid-state storage", "url": "https://semiaifoundry.com/learn/atlas/nvme-storage/" }, { "title": "Voltage regulator module", "url": "https://semiaifoundry.com/learn/atlas/voltage-regulator/" }, { "title": "Liquid-cooling coldplate", "url": "https://semiaifoundry.com/learn/atlas/coldplate/" }, { "title": "Baseboard management controller", "url": "https://semiaifoundry.com/learn/atlas/management-controller/" }, { "title": "GB200 compute tray", "url": "https://semiaifoundry.com/learn/atlas/compute-tray/" } ], "recordHash": "70861d404250b5aeff14ad2058427c1fc611ae0d95274685e87d2e90d65fb6f3" }, { "id": "atlas-lesson-compute-tray", "title": "GB200 compute tray", "category": "learning", "format": "Atlas lesson", "description": "Packages CPU–GPU compute and local support hardware into a serviceable rack unit.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/compute-tray/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Rack integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "These counts apply to the documented one-rack GB200 NVL72 configuration already cited in the lesson. They do not describe every rack product or predict installed, available or productive capacity.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/compute-tray-b65ff15b5c9539eb.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#compute-tray", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "feb4e8222da11fb9757f6c7a70697462aafc7867037b2c043b9fa0ae31586ff3", "contentLength": 4976, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compute-tray.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-compute-tray.md", "sections": [ { "id": "section-1", "title": "GB200 compute tray" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Reference-system composition" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "How many Blackwell GPUs are in the illustrated GB200 compute tray?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#compute-tray" }, { "title": "NVIDIA — DGX GB200 SuperPOD Components", "url": "https://docs.nvidia.com/dgx-superpod/reference-architecture-scalable-infrastructure-gb200/latest/dgx-superpod-components.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/compute-tray-b65ff15b5c9539eb.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "NVLink switch tray and scale-up fabric", "url": "https://semiaifoundry.com/learn/atlas/nvlink-switch/" }, { "title": "NVLink copper cable cartridge", "url": "https://semiaifoundry.com/learn/atlas/cable-cartridge/" }, { "title": "Coolant distribution unit and separated loops", "url": "https://semiaifoundry.com/learn/atlas/cdu/" }, { "title": "Rack power shelf and DC busbar", "url": "https://semiaifoundry.com/learn/atlas/power-shelf/" }, { "title": "CUDA programming and runtime layer", "url": "https://semiaifoundry.com/learn/atlas/cuda/" } ], "recordHash": "66fb7a7873c3a2c96f1242063f22ea659dd48ca7a3248ba7e35eeee7beaa10c9" }, { "id": "atlas-lesson-contact", "title": "Device contact and interface resistance", "category": "learning", "format": "Atlas lesson", "description": "Bridges semiconductor terminals to local metallic wiring.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/contact/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Materials and wiring", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The relation assumes a simplified uniform contact model.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/contact-d6adc2fe9d10fa6f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#contact", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "e6f6e1526593e31352d23aeb17e959a40c1fc310420a311e262bd979a570c603", "contentLength": 5009, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-contact.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-contact.md", "sections": [ { "id": "section-1", "title": "Device contact and interface resistance" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Specific contact resistivity" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "How does a device contact differ from a typical via?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#contact" }, { "title": "imec — Advanced Source-Drain Contact Resistance", "url": "https://www.imec-int.com/drupal/sites/default/files/2017-04/Stagegids%202017_04_07.pdf" }, { "title": "Loh et al. — An Accurate Method to Extract Specific Contact Resistivity Using Cross-Bridge Kelvin Resistors", "url": "https://ieeexplore.ieee.org/document/1485338/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/contact-d6adc2fe9d10fa6f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Source and drain regions", "url": "https://semiaifoundry.com/learn/atlas/source-drain/" }, { "title": "Copper conductor and barrier", "url": "https://semiaifoundry.com/learn/atlas/copper-conductor/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" } ], "recordHash": "5caa7d13c9fb1c6e6359aa95de7a2c1ea7a0270ea32b9f8edaabbf1ebb9d2b81" }, { "id": "atlas-lesson-contamination-and-surface-state", "title": "Contamination and the state of a surface", "category": "learning", "format": "Atlas lesson", "description": "Tracks particles, unwanted chemistry and surface changes across process boundaries.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/contamination-and-surface-state/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Materials", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "All exposure experiments are teaching designs, not authorization to alter production handling. No contamination threshold is asserted.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/contamination-and-surface-state-6f0968ec68d20dab.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#contamination-and-surface-state", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "e348756a7901bfaf79bf2b3ecd13df34ff795eeb2cadc3f69d72155bf0000470", "contentLength": 5662, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-contamination-and-surface-state.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-contamination-and-surface-state.md", "sections": [ { "id": "section-1", "title": "Contamination and the state of a surface" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Exposure bookkeeping" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A particle monitor is unchanged but a bonding interface degrades after storage. What is a useful next check?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#contamination-and-surface-state" }, { "title": "Entegris — Understanding AMC", "url": "https://blog.entegris.com/understanding-amc-the-invisible-threat-to-semiconductor-yield-and-reliability" }, { "title": "Entegris — FOUP Services", "url": "https://www.entegris.com/en/home/our-science/by-service/foup-services.html" }, { "title": "KLA — Chip Manufacturing 101", "url": "https://www.kla.com/wp-content/uploads/ChipManufacturing101.pdf" }, { "title": "Entegris — Contamination Control in Ultrapure Chemicals and Water", "url": "https://www.entegris.com/en/home/resources/technical-information/faq/contamination-control-in-ultrapure-chemicals-and-water.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/contamination-and-surface-state-6f0968ec68d20dab.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer finishing, orientation and geometry", "url": "https://semiaifoundry.com/learn/atlas/wafer-finishing-geometry/" }, { "title": "Wafer handling, carriers and genealogy", "url": "https://semiaifoundry.com/learn/atlas/wafer-handling-genealogy/" }, { "title": "Cleaning and CMP as interface preparation", "url": "https://semiaifoundry.com/learn/atlas/clean-planarize-surface/" }, { "title": "Hybrid bonding: surface state and alignment", "url": "https://semiaifoundry.com/learn/atlas/hybrid-bond-surface-alignment/" } ], "recordHash": "ed35f9bb687c1f75bc17f8774352d456d03e498c0a4075d8913b838373eaa2eb" }, { "id": "atlas-lesson-context-memory-provenance", "title": "Context, retrieval and durable memory", "category": "learning", "format": "Atlas lesson", "description": "Separate context window, retrieved passages, workflow state, durable user data and model parameters.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/context-memory-provenance/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Authority, context and execution boundaries", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. The example declares one accounting convention and tokenizer. Real services can impose additional or different input/output limits; words are not substituted for tokens.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/context-memory-provenance-a709dfd8c8eaeb5f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#context-memory-provenance", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1175bd13068c3be277d644927b6208cf1d18826ef4ade24a6abe15644b65ac21", "contentLength": 6425, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-context-memory-provenance.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-context-memory-provenance.md", "sections": [ { "id": "section-1", "title": "Context, retrieval and durable memory" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Context, retrieval and durable memory · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which action changes this invocation’s context without necessarily changing its model parameters?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#context-memory-provenance" }, { "title": "LangGraph persistence", "url": "https://docs.langchain.com/oss/python/langgraph/persistence" }, { "title": "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", "url": "https://arxiv.org/abs/2005.11401" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/context-memory-provenance-a709dfd8c8eaeb5f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "900e18f338ca1698d5c603179bee33dfd90c7243314ac7e085e6088a6c740658" }, { "id": "atlas-lesson-coolant-loop-separation", "title": "Cold plates, manifolds and separated coolant loops", "category": "learning", "format": "Atlas lesson", "description": "Transports heat through controlled fluid circuits without treating circulation as consumption.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/coolant-loop-separation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center physical systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a heat-balance example, not a qualified coolant recipe. Product-specific pressure, chemistry and temperature limits remain required.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/coolant-loop-separation-cc65e3a89d10352f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#coolant-loop-separation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1bcfd00e1ac5d01f61f2583744f58022f3586dc1fef46a9a5d0544545e4b2e02", "contentLength": 4705, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-coolant-loop-separation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-coolant-loop-separation.md", "sections": [ { "id": "section-1", "title": "Cold plates, manifolds and separated coolant loops" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Single-phase heat transport" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What happens when heat load rises at fixed flow and fluid properties?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#coolant-loop-separation" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Hardware", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Cooling Water Efficiency Opportunities for Federal Data Centers", "url": "https://www.energy.gov/cmei/femp/cooling-water-efficiency-opportunities-federal-data-centers" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/coolant-loop-separation-cc65e3a89d10352f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Liquid-cooling coldplate", "url": "https://semiaifoundry.com/learn/atlas/coldplate/" }, { "title": "Coolant distribution unit and separated loops", "url": "https://semiaifoundry.com/learn/atlas/cdu/" }, { "title": "Facility heat rejection and cooling tradeoffs", "url": "https://semiaifoundry.com/learn/atlas/facility-heat-rejection/" } ], "recordHash": "fb41a80687c474ce073dce9585ddad1c0f07c4315674bfa4c3e9964ea0b79078" }, { "id": "atlas-lesson-cooling-plant", "title": "Facility cooling and final heat rejection", "category": "learning", "format": "Atlas lesson", "description": "Carries heat from IT equipment to the outdoor environment or an approved reuse path.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cooling-plant/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Thermal infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example uses steady matched boundaries and invented loads. Heat-rejection method, environmental conditions and other support equipment affect actual power and water use; circulating water is not automatically consumed water.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cooling-plant-b358ef0e7cccb5b9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cooling-plant", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "46ba948a769523d9bb03358f0e2ec72c343c3dd66a7416440e213c4c2c6ffece", "contentLength": 4997, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cooling-plant.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cooling-plant.md", "sections": [ { "id": "section-1", "title": "Facility cooling and final heat rejection" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Cooling energy boundary" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Where does removed processor heat ultimately go?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cooling-plant" }, { "title": "US Department of Energy — Data-Center Cooling Water Efficiency", "url": "https://www.energy.gov/cmei/femp/cooling-water-efficiency-opportunities-federal-data-centers" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cooling-plant-b358ef0e7cccb5b9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Coolant distribution unit and separated loops", "url": "https://semiaifoundry.com/learn/atlas/cdu/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "Rack power shelf and DC busbar", "url": "https://semiaifoundry.com/learn/atlas/power-shelf/" } ], "recordHash": "f76336727c84377d562fa73562a08b306b4f7dbfb2794e75bdccaec566d0d491" }, { "id": "atlas-lesson-copper-conductor", "title": "Copper conductor and barrier", "category": "learning", "format": "Atlas lesson", "description": "Carries electrical signals and current through much of the chip wiring stack.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/copper-conductor/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Materials and wiring", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The effective resistivity depends on geometry, size effects, temperature and integration details.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/copper-conductor-498ede9b6934468a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#copper-conductor", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0d98e9c5f6b6f6efc32d730c8974e810bd0960923be3626133c47c746f93f22b", "contentLength": 5202, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-copper-conductor.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-copper-conductor.md", "sections": [ { "id": "section-1", "title": "Copper conductor and barrier" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Wire resistance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a narrower copper interconnect have much higher resistance?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "1997 · Fully integrated copper wiring demonstrated" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#copper-conductor" }, { "title": "Edelstein et al. — Full Copper Wiring, IEDM 1997", "url": "https://research.ibm.com/publications/full-copper-wiring-in-a-sub-025-mm-cmos-ulsi-technology" }, { "title": "IBM Research — Copper Evolution and Beyond", "url": "https://research.ibm.com/blog/beol-cu-interconnects-iedm" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/copper-conductor-498ede9b6934468a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Energy bands and carriers", "url": "https://semiaifoundry.com/learn/atlas/energy-bands/" }, { "title": "Insulators and low-k films", "url": "https://semiaifoundry.com/learn/atlas/dielectric/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Chemical mechanical planarization", "url": "https://semiaifoundry.com/learn/atlas/cmp/" }, { "title": "Device contact and interface resistance", "url": "https://semiaifoundry.com/learn/atlas/contact/" } ], "recordHash": "3f1aafb953ea1039b87ca526a61cea051629c260ad883c6be100fa980f26da1c" }, { "id": "atlas-lesson-cowos-r-l-routing", "title": "CoWoS-R and CoWoS-L: RDL and local silicon", "category": "learning", "format": "Atlas lesson", "description": "Distinguishes polymer/copper redistribution from RDL combined with dense local silicon links.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cowos-r-l-routing/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Interposers, bridges and stacking", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Public route definitions are checked; variant-specific tool capacity and customer queues are unknown. Production-history dates remain separate evidence entries.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cowos-r-l-routing-25bc7a96656b0649.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cowos-r-l-routing", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "acb179e430bf28433015771167572e29537085964c579b2ace0eac64bc6459e1", "contentLength": 5187, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cowos-r-l-routing.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cowos-r-l-routing.md", "sections": [ { "id": "section-1", "title": "CoWoS-R and CoWoS-L: RDL and local silicon" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Dense-routing footprint accounting" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which feature distinguishes the CoWoS-L description from an RDL-only interposer?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cowos-r-l-routing" }, { "title": "TSMC — CoWoS", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cowos-r-l-routing-25bc7a96656b0649.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "CoWoS-S and the silicon interposer route", "url": "https://semiaifoundry.com/learn/atlas/cowos-s-silicon-interposer/" }, { "title": "Redistribution layers and fan-out packaging", "url": "https://semiaifoundry.com/learn/atlas/rdl-fanout-integration/" }, { "title": "EMIB and localized die-to-die bridges", "url": "https://semiaifoundry.com/learn/atlas/emib-local-bridge/" }, { "title": "Underfill, warpage, thermal paths and qualification", "url": "https://semiaifoundry.com/learn/atlas/package-thermomechanical-reliability/" } ], "recordHash": "f479090ff506b28826cda1023f5f9818fd6d66d914b40b8e854a4230df1c9d52" }, { "id": "atlas-lesson-cowos-s-silicon-interposer", "title": "CoWoS-S and the silicon interposer route", "category": "learning", "format": "Atlas lesson", "description": "Integrates logic and memory over a shared silicon routing structure.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cowos-s-silicon-interposer/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Interposers, bridges and stacking", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "TSMC’s public page establishes route identity. Exact process order, materials and customer allocation are not fully public.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cowos-s-silicon-interposer-1d403bb1f11e02c6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cowos-s-silicon-interposer", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3fbdbca0d75a4986c5f4fbd5605f0e756f4c9cd680a09a1b68c127f1e135b963", "contentLength": 5699, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cowos-s-silicon-interposer.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cowos-s-silicon-interposer.md", "sections": [ { "id": "section-1", "title": "CoWoS-S and the silicon interposer route" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Convergent assembly ceiling" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "If logic dies are plentiful but compatible HBM stacks are scarce, what constrains package output?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cowos-s-silicon-interposer" }, { "title": "TSMC — CoWoS", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cowos-s-silicon-interposer-1d403bb1f11e02c6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Flip-chip assembly and organic substrates", "url": "https://semiaifoundry.com/learn/atlas/flip-chip-abf-substrate/" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" }, { "title": "Interposer and redistribution layers", "url": "https://semiaifoundry.com/learn/atlas/interposer/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "CoWoS-R and CoWoS-L: RDL and local silicon", "url": "https://semiaifoundry.com/learn/atlas/cowos-r-l-routing/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" } ], "recordHash": "f43cd5ae9afbd9c0cbe4155678f690af285289fedaf24c526ca4741dcce7ec00" }, { "id": "atlas-lesson-cpu-out-of-order", "title": "Out-of-order CPU pipeline", "category": "learning", "format": "Atlas lesson", "description": "Finds ready independent instructions while preserving architectural results.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cpu-out-of-order/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The diagram is a logical pipeline. Queue sizes, prediction accuracy and workload speedups are not inferred from the Arm example.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cpu-out-of-order-fdead33f81ab27be.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cpu-out-of-order", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "5771bcde0a26eeb6bc77b84369d1a53baf2db25bf4f5a3b57ccab551cca1aace", "contentLength": 4783, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cpu-out-of-order.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cpu-out-of-order.md", "sections": [ { "id": "section-1", "title": "Out-of-order CPU pipeline" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Dependency bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which pair offers the best opportunity for overlapping execution?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cpu-out-of-order" }, { "title": "Arm Neoverse V2 Core Technical Reference Manual", "url": "https://documentation-service.arm.com/static/633fe1ec4c59b30b517730b8" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cpu-out-of-order-fdead33f81ab27be.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" }, { "title": "Scalar, vector and CPU matrix units", "url": "https://semiaifoundry.com/learn/atlas/cpu-vector-matrix/" }, { "title": "Cache coherence and NUMA placement", "url": "https://semiaifoundry.com/learn/atlas/coherence-numa/" } ], "recordHash": "caa0cea211ee8fea91ab067ddfd6c8e49975135ca2975515363b11c5060195bf" }, { "id": "atlas-lesson-cpu-vector-matrix", "title": "Scalar, vector and CPU matrix units", "category": "learning", "format": "Atlas lesson", "description": "Executes different shapes of arithmetic within a general-purpose processor.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cpu-vector-matrix/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Intel and Arm examples illustrate programming mechanisms. They do not establish equal precision support or a measured performance comparison.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cpu-vector-matrix-e144948c627c0f3e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cpu-vector-matrix", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9b61120e1f7dcec78fb64f517b22ac3663a1cf53339d84bb8d95b0d476e58530", "contentLength": 4983, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cpu-vector-matrix.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cpu-vector-matrix.md", "sections": [ { "id": "section-1", "title": "Scalar, vector and CPU matrix units" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Lane utilization" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A vector width is eight elements and the loop contains ten elements. What limits useful-lane utilization in two issued groups?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cpu-vector-matrix" }, { "title": "What Is Intel Advanced Matrix Extensions?", "url": "https://www.intel.com/content/www/us/en/products/docs/accelerator-engines/what-is-intel-amx.html" }, { "title": "Arm Neoverse V2 Core Technical Reference Manual", "url": "https://documentation-service.arm.com/static/633fe1ec4c59b30b517730b8" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cpu-vector-matrix-e144948c627c0f3e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Out-of-order CPU pipeline", "url": "https://semiaifoundry.com/learn/atlas/cpu-out-of-order/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" } ], "recordHash": "aacf2021353caff6572616a6d596ed7653bc7d8a4e7ffb6ec276d3ed4a748e28" }, { "id": "atlas-lesson-crg-55-year-resolution", "title": "The 55-year realization challenge and CRG", "category": "learning", "format": "Atlas lesson", "description": "Presents Semi AI Foundry’s account of a long-standing computation-to-physical-realization gap.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/crg-55-year-resolution/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Primary source supplied by Semi AI Foundry. The atlas labels this as a research claim and keeps independent technical references beside it.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-55-year-resolution-6fd082ff1c32e97d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#crg-55-year-resolution", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ae7bb1acadc1a0c3c91aaead6ece53ab0eb7043183a337851302d9eeafedf13b", "contentLength": 5218, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-55-year-resolution.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-55-year-resolution.md", "sections": [ { "id": "section-1", "title": "The 55-year realization challenge and CRG" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Claim and evidence separation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "How should the 55-year statement be used in this atlas?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#crg-55-year-resolution" }, { "title": "Semi AI Foundry — Communication Theory of Computation Realization", "url": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/" }, { "title": "Stanford Encyclopedia of Philosophy — Computation in Physical Systems", "url": "https://plato.stanford.edu/entries/computation-physicalsystems/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-55-year-resolution-6fd082ff1c32e97d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "The computation-to-realization gap", "url": "https://semiaifoundry.com/learn/atlas/crg-problem-statement/" }, { "title": "Architecture is a contract between computation and silicon", "url": "https://semiaifoundry.com/learn/atlas/crg-architecture-contract/" }, { "title": "Communication is the realization medium", "url": "https://semiaifoundry.com/learn/atlas/crg-communication-graph/" }, { "title": "From architecture contract to a chip", "url": "https://semiaifoundry.com/learn/atlas/crg-chip-design-realization/" }, { "title": "Verification closes the realization loop", "url": "https://semiaifoundry.com/learn/atlas/crg-verification-loop/" } ], "recordHash": "e6475480e27e588b3da8c0f4c30bf92b9e555283180ad16e3b189766b84b03ae" }, { "id": "atlas-lesson-crg-architecture-contract", "title": "Architecture is a contract between computation and silicon", "category": "learning", "format": "Atlas lesson", "description": "Chooses execution, memory and communication structures that can satisfy a workload contract.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/crg-architecture-contract/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "pursuitIds": [ "computation-and-realization" ], "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The bound is a roofline-style teaching model. Public architecture documentation supplies examples, not a universal product ranking.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-architecture-contract-d109480e64f2bce5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#crg-architecture-contract", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "321b34b8da405a591c48dad8296a379d39f5c00b62f783f8137da9a7c6a643bf", "contentLength": 5442, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-architecture-contract.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-architecture-contract.md", "sections": [ { "id": "section-1", "title": "Architecture is a contract between computation and silicon" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Workload-bound rate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the architecture contract connect?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#crg-architecture-contract" }, { "title": "OpenXLA — GPU architecture", "url": "https://openxla.org/xla/gpu_architecture" }, { "title": "Google Cloud TPU architecture", "url": "https://cloud.google.com/tpu/docs/system-architecture" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-architecture-contract-d109480e64f2bce5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Communication is the realization medium", "url": "https://semiaifoundry.com/learn/atlas/crg-communication-graph/" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" } ], "recordHash": "4a722d69cf541095924b6a9f14a3cfdeaa6df49b98520aa33da4633591e19e0f" }, { "id": "atlas-lesson-crg-chip-design-realization", "title": "From architecture contract to a chip", "category": "learning", "format": "Atlas lesson", "description": "Traverses specification, RTL, verification, synthesis, physical design, tapeout and wafer test.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/crg-chip-design-realization/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The sequence is a representative educational flow. Foundry-specific PDK content and proprietary signoff data are not disclosed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-chip-design-realization-1a06711ce64cbdb4.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#crg-chip-design-realization", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c271017ddef9fba7ca7d11e51f4b290e6a8f905414ae6bd531b82695c78f2bba", "contentLength": 5271, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-chip-design-realization.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-chip-design-realization.md", "sections": [ { "id": "section-1", "title": "From architecture contract to a chip" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Timing closure boundary" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does a PDK matter in chip design?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#crg-chip-design-realization" }, { "title": "Semi AI Foundry — Communication Theory of Computation Realization", "url": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/" }, { "title": "imec — CMOS scaling and system co-optimization", "url": "https://www.imec-int.com/en/expertise/cmos-advanced/compute/cmos-scaling" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-chip-design-realization-1a06711ce64cbdb4.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Architecture is a contract between computation and silicon", "url": "https://semiaifoundry.com/learn/atlas/crg-architecture-contract/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Metrology, inspection and process windows", "url": "https://semiaifoundry.com/learn/atlas/fab-metrology-process-window/" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" } ], "recordHash": "3d5705885497ee6c8d5f4e146ff6ea41fb07ccc9fb2f849f9d8a2d8c0a222db5" }, { "id": "atlas-lesson-crg-communication-graph", "title": "Communication is the realization medium", "category": "learning", "format": "Atlas lesson", "description": "Maps computational state, data movement and control into a graph of physical interfaces.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/crg-communication-graph/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "pursuitIds": [ "computation-and-realization" ], "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The edge equation is a bounded teaching model. Shannon’s source addresses communication limits; it does not by itself specify a chip architecture.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-communication-graph-5971d22cd051d5a1.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#crg-communication-graph", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "929677ecb3030bdc8e0e1c5889e197ba86dfba746f7e836b55ec5147e494d921", "contentLength": 5416, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-communication-graph.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-communication-graph.md", "sections": [ { "id": "section-1", "title": "Communication is the realization medium" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A communication edge" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does the CRG include communication beside computation?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#crg-communication-graph" }, { "title": "Semi AI Foundry — Communication Theory of Computation Realization", "url": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/" }, { "title": "Claude Shannon — A Mathematical Theory of Communication", "url": "https://people.math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-communication-graph-5971d22cd051d5a1.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "The computation-to-realization gap", "url": "https://semiaifoundry.com/learn/atlas/crg-problem-statement/" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" }, { "title": "NVLink GPU interface", "url": "https://semiaifoundry.com/learn/atlas/nvlink-port/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" } ], "recordHash": "1a76d3056441287734d3eef11992543ee1ed0ba1cedf7aee011de4ea0b7261f2" }, { "id": "atlas-lesson-crg-package-system-closure", "title": "Package and system preserve the contract", "category": "learning", "format": "Atlas lesson", "description": "Carries chip interfaces through bonding, boards, racks, facilities and runtime services.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/crg-package-system-closure/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Public product and package pages describe representative boundaries; exact fleet configurations, allocation and service telemetry remain configuration-specific.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-package-system-closure-00378de589c06262.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#crg-package-system-closure", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "caf8f31a61a4a2aa88c30b0daadfa3c1034b0a08a5e49bbf7896fd9e24f2b71b", "contentLength": 5443, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-package-system-closure.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-package-system-closure.md", "sections": [ { "id": "section-1", "title": "Package and system preserve the contract" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Useful-work boundary" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does system closure add after tapeout?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#crg-package-system-closure" }, { "title": "TSMC CoWoS technology", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm" }, { "title": "NVIDIA DGX GB200 hardware guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-package-system-closure-00378de589c06262.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "From architecture contract to a chip", "url": "https://semiaifoundry.com/learn/atlas/crg-chip-design-realization/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" } ], "recordHash": "ebedff7f2bae37adeb09263552dbac972dd8ec6d51396749a6397fc3c8363382" }, { "id": "atlas-lesson-crg-problem-statement", "title": "The computation-to-realization gap", "category": "learning", "format": "Atlas lesson", "description": "Defines the problem of carrying a computational intent into a physically constrained machine.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/crg-problem-statement/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "pursuitIds": [ "computation-and-realization" ], "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This lesson presents the CRG framing as Semi AI Foundry research context and separates it from the independently sourced physical-computation literature.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-problem-statement-739c319346d3f12d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#crg-problem-statement", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "773fa8dcf3225548279027048798c57c24001e86d7399b25a6ef41a9c028ca6f", "contentLength": 4989, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-problem-statement.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-problem-statement.md", "sections": [ { "id": "section-1", "title": "The computation-to-realization gap" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A realization contract" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What makes an abstract computation physically realizable?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#crg-problem-statement" }, { "title": "Semi AI Foundry — Communication Theory of Computation Realization", "url": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/" }, { "title": "Stanford Encyclopedia of Philosophy — Computation in Physical Systems", "url": "https://plato.stanford.edu/entries/computation-physicalsystems/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-problem-statement-739c319346d3f12d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Communication is the realization medium", "url": "https://semiaifoundry.com/learn/atlas/crg-communication-graph/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" } ], "recordHash": "d1a3a909d8eeb38eee1d45d9dfb14b6796ea360d2891ea5d825c6812328f3ec3" }, { "id": "atlas-lesson-crg-verification-loop", "title": "Verification closes the realization loop", "category": "learning", "format": "Atlas lesson", "description": "Connects simulation, formal checks, silicon measurement, system qualification and workload evaluation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/crg-verification-loop/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": null, "series": null, "pursuitIds": [ "domain-native-execution" ], "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The loop is a systems-engineering teaching pattern. Provider-specific goodput sources illustrate one recovery mechanism, not a universal reliability law.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-verification-loop-8eb2a4a503ff390d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#crg-verification-loop", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "2f34b9e1cd6851d0425f5f808be7dd2872f20386d1fde6af5527eda01b2d1d9a", "contentLength": 5724, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-verification-loop.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crg-verification-loop.md", "sections": [ { "id": "section-1", "title": "Verification closes the realization loop" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Observed margin" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is the purpose of the verification loop?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#crg-verification-loop" }, { "title": "Semi AI Foundry — Communication Theory of Computation Realization", "url": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/" }, { "title": "Google — Elastic training and goodput", "url": "https://cloud.google.com/blog/products/ai-machine-learning/elastic-training-and-optimized-checkpointing-improve-ml-goodput" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/crg-verification-loop-8eb2a4a503ff390d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Package and system preserve the contract", "url": "https://semiaifoundry.com/learn/atlas/crg-package-system-closure/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "The 55-year realization challenge and CRG", "url": "https://semiaifoundry.com/learn/atlas/crg-55-year-resolution/" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "GPT-6 Astra", "url": "https://semiaifoundry.com/learn/atlas/astra/" } ], "recordHash": "2d6971b93d7bab4933942fd9cc84def23ffb0031c1769c83237194527e7d6af9" }, { "id": "atlas-lesson-crystal-lattice", "title": "Diamond-cubic silicon lattice", "category": "learning", "format": "Atlas lesson", "description": "Organizes atoms into a repeatable semiconductor crystal.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/crystal-lattice/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Atomic foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The lattice equation is idealized; defects, orientation and thermal expansion are separate terms.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/crystal-lattice-179906dbf388b55b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#crystal-lattice", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b68c3a8d25316f26a7c22b53be122799edfdba098dc1907e0ab59afb51adb598", "contentLength": 4731, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crystal-lattice.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-crystal-lattice.md", "sections": [ { "id": "section-1", "title": "Diamond-cubic silicon lattice" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Diamond-cubic nearest neighbors" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the silicon lattice constant measure?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#crystal-lattice" }, { "title": "MIT 6.012 — Semiconductor Physics I", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/e1a94598c1fd641fc15636a9ad14de1a_lec2.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/crystal-lattice-179906dbf388b55b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Silicon atom", "url": "https://semiaifoundry.com/learn/atlas/silicon-atom/" }, { "title": "Wafer and fabrication hierarchy", "url": "https://semiaifoundry.com/learn/atlas/silicon-wafer/" }, { "title": "Controllable semiconductor channel", "url": "https://semiaifoundry.com/learn/atlas/channel/" }, { "title": "Donor and acceptor doping", "url": "https://semiaifoundry.com/learn/atlas/doping/" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" } ], "recordHash": "d707220033d3706c7707457a948ec97da66cb298864baf728e02da21d1ba3c4e" }, { "id": "atlas-lesson-cuda", "title": "CUDA programming and runtime layer", "category": "learning", "format": "Atlas lesson", "description": "Provides a software model and interfaces for executing parallel work on NVIDIA GPUs.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cuda/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Execution software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This applies the lesson’s fixed-workload model, not a guaranteed CUDA speedup. Transfers, launches, changed algorithms, problem size and CPU contention can change both the parallel fraction and overhead.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cuda-38a2940bde1cde9f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cuda", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "62e4fd337d6b095fd3a9f4a3afea346e4c4f84700647f96eef809d91cc701832", "contentLength": 5019, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cuda.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cuda.md", "sections": [ { "id": "section-1", "title": "CUDA programming and runtime layer" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Amdahl speedup bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Where can an AI framework use CUDA?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cuda" }, { "title": "NVIDIA — CUDA FAQ", "url": "https://developer.nvidia.com/cuda/faq" }, { "title": "Hill and Marty — Amdahl’s Law in the Multicore Era", "url": "https://research.cs.wisc.edu/multifacet/amdahl/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cuda-38a2940bde1cde9f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" } ], "recordHash": "aa0ae2b28d979b0fa3f570ef5676ff1c39d5caa7b1c274f5bf382bc55ded3fe3" }, { "id": "atlas-lesson-cvd-pvd-film-transport", "title": "CVD and PVD: two ways to supply a film", "category": "learning", "format": "Atlas lesson", "description": "Contrasts chemical surface growth with physical material transport.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/cvd-pvd-film-transport/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Repeated operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Cross-sections are representative mechanisms. Actual coverage depends on process, chemistry, pressure, temperature, geometry and surface preparation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/cvd-pvd-film-transport-c379b4502b875a78.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#cvd-pvd-film-transport", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "59e61dd256465804400e0f187c16f6d4799eeeced8d712646d1230464d388cd6", "contentLength": 5028, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cvd-pvd-film-transport.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-cvd-pvd-film-transport.md", "sections": [ { "id": "section-1", "title": "CVD and PVD: two ways to supply a film" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Coverage ratio" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A trench opening closes before its interior fills. What does this indicate?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#cvd-pvd-film-transport" }, { "title": "Lam Research — Our Processes", "url": "https://www.lamresearch.com/products/our-processes/" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/cvd-pvd-film-transport-c379b4502b875a78.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "A process chamber as a controlled reactor", "url": "https://semiaifoundry.com/learn/atlas/process-chamber-control/" }, { "title": "ALD and self-limiting surface reactions", "url": "https://semiaifoundry.com/learn/atlas/ald-self-limiting-growth/" }, { "title": "BEOL layers, damascene and vias", "url": "https://semiaifoundry.com/learn/atlas/beol-damascene-vias/" } ], "recordHash": "612de11b605f25d4784b083f54033602efdbb003f5200a80c99fbe11728248d8" }, { "id": "atlas-lesson-data-coverage-language-slices", "title": "Coverage across language and source slices", "category": "learning", "format": "Atlas lesson", "description": "Compare source slices under explicit byte, token and task denominators.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/data-coverage-language-slices/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-data", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Authored strings and slice counts; UTF-8 and a fixed character tokenizer. Cross-tokenizer loss values require further normalization and do not directly rank language ability. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/data-coverage-language-slices-d2af2cc16e30915c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#data-coverage-language-slices", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "714bc48bc019b3652f84f665302ffd37d3740b2f235a65bf7f402b091f8b4700", "contentLength": 6105, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-data-coverage-language-slices.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-data-coverage-language-slices.md", "sections": [ { "id": "section-1", "title": "Coverage across language and source slices" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Coverage across language and source slices · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which observation is concealed by the overall 76.36% retention?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#data-coverage-language-slices" }, { "title": "The FineWeb Datasets", "url": "https://arxiv.org/html/2406.17557v1" }, { "title": "Holistic Evaluation of Language Models", "url": "https://arxiv.org/html/2211.09110v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/data-coverage-language-slices-d2af2cc16e30915c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Tokenizer", "url": "https://semiaifoundry.com/learn/atlas/tokenizer/" }, { "title": "Filtering, duplication and contamination", "url": "https://semiaifoundry.com/learn/atlas/data-quality-dedup-audit/" }, { "title": "Mixtures, epochs and exposure", "url": "https://semiaifoundry.com/learn/atlas/data-mixture-sampling/" }, { "title": "Packing documents and masking valid targets", "url": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/" }, { "title": "Synthetic supervision and selection loops", "url": "https://semiaifoundry.com/learn/atlas/synthetic-data-selection-feedback/" } ], "recordHash": "70c060f69b6a17125296ddeb97a9e8c09b778b7d6834ab140172ca3a1eaf87fc" }, { "id": "atlas-lesson-data-mixture-sampling", "title": "Mixtures, epochs and exposure", "category": "learning", "format": "Atlas lesson", "description": "Calculate expected exposure per source and distinguish it from one finite seeded draw.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/data-mixture-sampling/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-data", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Independent source draws with replacement, positive pool sizes and probabilities summing to one. These are exposure calculations, not predicted learning curves. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/data-mixture-sampling-89d1b24806fbf75b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#data-mixture-sampling", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "06f1277dc91bf54e7bbfc152dcac6a6a3b597f9dadbd6d6e7f93a387be804bef", "contentLength": 6008, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-data-mixture-sampling.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-data-mixture-sampling.md", "sections": [ { "id": "section-1", "title": "Mixtures, epochs and exposure" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Mixtures, epochs and exposure · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which pool receives more expected passes?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#data-mixture-sampling" }, { "title": "The FineWeb Datasets", "url": "https://arxiv.org/html/2406.17557v1" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/data-mixture-sampling-89d1b24806fbf75b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Filtering, duplication and contamination", "url": "https://semiaifoundry.com/learn/atlas/data-quality-dedup-audit/" }, { "title": "Packing documents and masking valid targets", "url": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/" }, { "title": "Synthetic supervision and selection loops", "url": "https://semiaifoundry.com/learn/atlas/synthetic-data-selection-feedback/" }, { "title": "Coverage across language and source slices", "url": "https://semiaifoundry.com/learn/atlas/data-coverage-language-slices/" } ], "recordHash": "6143fd5b2abb444119dcda9b9205655242f94e5a0a03c3e9398081a2cc40538f" }, { "id": "atlas-lesson-data-quality-dedup-audit", "title": "Filtering, duplication and contamination", "category": "learning", "format": "Atlas lesson", "description": "Distinguish exact duplicates, approximate matches and evaluation contamination using explicit document families.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/data-quality-dedup-audit/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-data", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Nonempty shingle union; exact set arithmetic. Threshold and authored semantic labels are teaching choices, not a universal deduplication rule. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/data-quality-dedup-audit-ba4b0dcd4d72bfb6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#data-quality-dedup-audit", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "89dce7ee13256bceafb26ff8a54b8d871d06d709cf69c4f46834041f0378fee3", "contentLength": 6638, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-data-quality-dedup-audit.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-data-quality-dedup-audit.md", "sections": [ { "id": "section-1", "title": "Filtering, duplication and contamination" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Filtering, duplication and contamination · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a 0.5 similarity threshold remove useful information in this example?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#data-quality-dedup-audit" }, { "title": "The FineWeb Datasets", "url": "https://arxiv.org/html/2406.17557v1" }, { "title": "Deduplicating Training Data Makes Language Models Better", "url": "https://arxiv.org/html/2107.06499v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/data-quality-dedup-audit-ba4b0dcd4d72bfb6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Mixtures, epochs and exposure", "url": "https://semiaifoundry.com/learn/atlas/data-mixture-sampling/" }, { "title": "Packing documents and masking valid targets", "url": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/" }, { "title": "Synthetic supervision and selection loops", "url": "https://semiaifoundry.com/learn/atlas/synthetic-data-selection-feedback/" }, { "title": "Coverage across language and source slices", "url": "https://semiaifoundry.com/learn/atlas/data-coverage-language-slices/" } ], "recordHash": "750939e4bad336dfe4fc46e58ac0484fd939f91f9caffd659235578dc87c7751" }, { "id": "atlas-lesson-dataset-human-judgment-lineage", "title": "Human judgments, disagreement and dataset lineage", "category": "learning", "format": "Atlas lesson", "description": "Makes the people and decisions behind training labels visible in the resulting dataset.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/dataset-human-judgment-lineage/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "data-evidence-foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. Two annotations per fictional example; direct agreement is not chance-adjusted and is not a truth or representativeness metric.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/dataset-human-judgment-lineage-0d84a36e42386aa5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#dataset-human-judgment-lineage", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "5f8fd7836d362400ca18e17f774bc34d9547f0250a1d556e93e0aa9feba5feb0", "contentLength": 5757, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dataset-human-judgment-lineage.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dataset-human-judgment-lineage.md", "sections": [ { "id": "section-1", "title": "Human judgments, disagreement and dataset lineage" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Human judgments, disagreement and dataset lineage" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What happens to original agreement after the review-category rule is applied?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#dataset-human-judgment-lineage" }, { "title": "Gebru et al. · Datasheets for Datasets", "url": "https://arxiv.org/abs/1803.09010" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/dataset-human-judgment-lineage-0d84a36e42386aa5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Post-training & feedback", "url": "https://semiaifoundry.com/learn/atlas/post-training/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "9133583b22bbe538b63e59deb31fd2e7dd89a615dddc31c49a66c4c840807d23" }, { "id": "atlas-lesson-ddr-memory", "title": "DDR5 server memory", "category": "learning", "format": "Atlas lesson", "description": "Provides expandable main memory for conventional host CPUs and their software working sets.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/ddr-memory/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Host platform", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The formula uses the stated transfer-rate convention.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/ddr-memory-1e1336a29e90dcda.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#ddr-memory", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "67ce9aa27f27d799ffff522d4ba14809965cd9ed84ca88b5187f1f095ae155c8", "contentLength": 5597, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-ddr-memory.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-ddr-memory.md", "sections": [ { "id": "section-1", "title": "DDR5 server memory" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Clock cycles and transfer rate are different units" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "At 4,800 MT/s and 64 data bits, what is the theoretical payload rate before workload effects?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#ddr-memory" }, { "title": "Micron DDR5 DRAM", "url": "https://www.micron.com/products/memory/dram-components/ddr5-sdram" }, { "title": "Micron DDR5 SDRAM: New Features", "url": "https://assets.micron.com/adobe/assets/urn%3Aaaid%3Aaem%3A5ea148c8-e3fe-489e-8489-99b1b9cdcd3c/renditions/original/as/ddr5-new-features-white-paper.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/ddr-memory-1e1336a29e90dcda.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DRAM die and memory banks", "url": "https://semiaifoundry.com/learn/atlas/dram-die/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "Grace LPDDR5X memory", "url": "https://semiaifoundry.com/learn/atlas/lpddr-memory/" } ], "recordHash": "681fd1e87a116c26c1bdb6d387523064c12ef63da2285278566e94d15886fa9b" }, { "id": "atlas-lesson-decode-bandwidth-trace", "title": "Autoregressive decode and weight traffic", "category": "learning", "format": "Atlas lesson", "description": "Produces dependent new tokens while repeatedly accessing weights and growing KV state.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/decode-bandwidth-trace/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Example rates are invented and assume one weight pass. Real caching, quantization, expert activation and tensor partitioning change the bytes and must be profiled.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/decode-bandwidth-trace-543a70b8ef7fc754.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#decode-bandwidth-trace", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "704f73bd60f11ebb2a0a234782ef0e84177669f27d220a381b53992315446465", "contentLength": 5189, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-decode-bandwidth-trace.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-decode-bandwidth-trace.md", "sections": [ { "id": "section-1", "title": "Autoregressive decode and weight traffic" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Weight-streaming decode floor" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which change can improve weight reuse but increase KV memory demand?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#decode-bandwidth-trace" }, { "title": "Efficient Memory Management for Large Language Model Serving with PagedAttention", "url": "https://arxiv.org/abs/2309.06180" }, { "title": "Roofline: An Insightful Visual Performance Model for Floating-Point Programs and Multicore Architectures", "url": "https://www2.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-134.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/decode-bandwidth-trace-543a70b8ef7fc754.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Historical memory-wall evidence", "url": "https://semiaifoundry.com/learn/atlas/memory-wall-trends/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "Prefill and prompt processing", "url": "https://semiaifoundry.com/learn/atlas/prefill-resource-trace/" } ], "recordHash": "60774316b9ca98e42c147bed2d012591214120a93e248ce797a5629f23b542c5" }, { "id": "atlas-lesson-delegated-agent-protocols", "title": "Delegated tasks, messages and artifacts", "category": "learning", "format": "Atlas lesson", "description": "Task lifecycle, artifact ownership, input-required states, cancellation and authenticated service boundaries.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/delegated-agent-protocols/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Delegated tasks and coordination", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Worked lifecycle based on the inspected A2A specification; no network endpoint, interoperability test or multi-agent runtime is executed. The concrete protocol revision must be pinned for a future adapter.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/delegated-agent-protocols-f7d8f254309a16f8.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#delegated-agent-protocols", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3262105dca75bcf8d24d2163ade24f792ba59c3ae3b89e8b9386e02f2e967183", "contentLength": 6416, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-delegated-agent-protocols.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-delegated-agent-protocols.md", "sections": [ { "id": "section-1", "title": "Delegated tasks, messages and artifacts" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Delegated tasks, messages and artifacts · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "The network disconnects while delegated task T17 is working. What should the parent avoid?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#delegated-agent-protocols" }, { "title": "A2A specification", "url": "https://a2a-protocol.org/latest/specification/" }, { "title": "Temporal Activities", "url": "https://docs.temporal.io/activities" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/delegated-agent-protocols-f7d8f254309a16f8.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "A tool protocol is a boundary", "url": "https://semiaifoundry.com/learn/atlas/mcp-host-client-server/" }, { "title": "Durable actions and the ambiguous timeout", "url": "https://semiaifoundry.com/learn/atlas/durable-actions-idempotency/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "f0f5276253b4c31f7e40c5733b546f25a9d4b32320837595dbdc5e7473087dcf" }, { "id": "atlas-lesson-denoising-generative-objectives", "title": "Train a denoiser and sample iteratively", "category": "learning", "format": "Atlas lesson", "description": "Compute a noisy training target and distinguish noise regression from a flow vector field.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/denoising-generative-objectives/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-multimodal", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. One-dimensional authored samples; diffusion and flow use separate time/start conventions explicitly. No complete sampler, likelihood bound or image-quality benchmark is executed. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/denoising-generative-objectives-d5f093d00f1eca4e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#denoising-generative-objectives", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c03711621d9017474edf5d3b533149e92c1198627ec0cad2ba3f0f650e382755", "contentLength": 6713, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-denoising-generative-objectives.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-denoising-generative-objectives.md", "sections": [ { "id": "section-1", "title": "Train a denoiser and sample iteratively" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Train a denoiser and sample iteratively · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why are the two regression targets different?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#denoising-generative-objectives" }, { "title": "Denoising Diffusion Probabilistic Models", "url": "https://arxiv.org/html/2006.11239v2" }, { "title": "Flow Matching for Generative Modeling", "url": "https://arxiv.org/html/2210.02747v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/denoising-generative-objectives-d5f093d00f1eca4e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Pair images and captions in a shared representation", "url": "https://semiaifoundry.com/learn/atlas/image-text-contrastive-learning/" }, { "title": "Patches, projection and visual instruction tuning", "url": "https://semiaifoundry.com/learn/atlas/visual-language-bridge/" }, { "title": "Audio representation, alignment and transcript loss", "url": "https://semiaifoundry.com/learn/atlas/speech-audio-sequence-objectives/" }, { "title": "Predict temporal representations without generating pixels", "url": "https://semiaifoundry.com/learn/atlas/video-latent-prediction/" } ], "recordHash": "ccde5ebd9e1a4d055bf4a6a35d77103d3e6b7a645869ae176d4237120e18b685" }, { "id": "atlas-lesson-device-completion-reset-epochs", "title": "Completion, reset and execution epochs", "category": "learning", "format": "Atlas lesson", "description": "Separate physical work, accepted completion and useful output while a device is stopped and reinitialized.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/device-completion-reset-epochs/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Primary sources establish the cited runtime mechanisms. Numerical values, address ranges, ABI strings, event schedule and reset/retry epochs are authored teaching contracts. No real device, firmware image, operating-system driver, page table, cache protocol or security verification is executed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/device-completion-reset-epochs-25590d0d23232447.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#device-completion-reset-epochs", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "e81f923527108d8e70cab8e1ced5d8174f122ce53fb2d49699484f478f71f192", "contentLength": 7358, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-device-completion-reset-epochs.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-device-completion-reset-epochs.md", "sections": [ { "id": "section-1", "title": "Completion, reset and execution epochs" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Account every executed MAC" }, { "id": "section-5", "title": "Completion must belong to the live attempt" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "A reset cancels four MACs, then a full retry executes eight. How much arithmetic was executed and committed?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#device-completion-reset-epochs" }, { "title": "OASIS — Virtual I/O Device (VIRTIO) Version 1.3", "url": "https://docs.oasis-open.org/virtio/virtio/v1.3/virtio-v1.3.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/device-completion-reset-epochs-25590d0d23232447.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DMA visibility, ordering and buffer lifetime", "url": "https://semiaifoundry.com/learn/atlas/dma-visibility-ownership/" }, { "title": "Firmware handoff and device readiness", "url": "https://semiaifoundry.com/learn/atlas/firmware-device-contract/" }, { "title": "When completed work survives a restart", "url": "https://semiaifoundry.com/learn/atlas/retained-work-restart-boundary/" }, { "title": "Checkpointing, failure and retained useful work", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-retained-work/" }, { "title": "Commissioning a usable AI cluster", "url": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/" } ], "recordHash": "5eef2523c6f2c0cfabdd7ed8c29b02300587fb02c31c15d3540989b9bbaba1a0" }, { "id": "atlas-lesson-die-link-compatibility", "title": "Die-to-die links and UCIe compatibility", "category": "learning", "format": "Atlas lesson", "description": "Defines what adjacent chiplets must agree on to exchange useful data.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/die-link-compatibility/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Chip-to-hall integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example does not claim a UCIe configuration. Public initialization guidance supplies the mechanism; vendor interoperability test results remain configuration-specific.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/die-link-compatibility-e2fb037f49d24af9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#die-link-compatibility", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4f8b46b904477dc2002505873ade061817bc1cf1aa205b54fd1d936f654cda79", "contentLength": 4650, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-die-link-compatibility.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-die-link-compatibility.md", "sections": [ { "id": "section-1", "title": "Die-to-die links and UCIe compatibility" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Usable link rate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What must match beyond a connector or standard name?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#die-link-compatibility" }, { "title": "Introduction to UCIe webinar: Q&A recap", "url": "https://www.uciexpress.org/post/introduction-to-ucie-webinar-q-a-recap" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/die-link-compatibility-e2fb037f49d24af9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Interposer and redistribution layers", "url": "https://semiaifoundry.com/learn/atlas/interposer/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" }, { "title": "Signal integrity, timing and the eye diagram", "url": "https://semiaifoundry.com/learn/atlas/interface-signal-eye/" } ], "recordHash": "6a4be79447e005e2405057e3533f33f0916295df6600e2c763dd876166fd44bf" }, { "id": "atlas-lesson-dielectric", "title": "Insulators and low-k films", "category": "learning", "format": "Atlas lesson", "description": "Separates conductors while shaping capacitance and electric fields.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/dielectric/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Materials and wiring", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Real interconnects have fringing fields, porosity, frequency dependence and reliability limits.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/dielectric-94e46a8a1835b611.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#dielectric", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "804e2d183f71e7022fe5a934f2bee8552dcaed060d6e4bc2a766d48ca6e2df53", "contentLength": 4640, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dielectric.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dielectric.md", "sections": [ { "id": "section-1", "title": "Insulators and low-k films" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Capacitive coupling" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why use low-k material around signal wires?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#dielectric" }, { "title": "Applied Materials — Producer Onyx and Low-k Insulation", "url": "https://www.appliedmaterials.com/us/en/product-library/producer-onyx.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/dielectric-94e46a8a1835b611.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Energy bands and carriers", "url": "https://semiaifoundry.com/learn/atlas/energy-bands/" }, { "title": "Copper conductor and barrier", "url": "https://semiaifoundry.com/learn/atlas/copper-conductor/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "Gate sidewall and inner spacers", "url": "https://semiaifoundry.com/learn/atlas/spacer/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" } ], "recordHash": "b14843c48620398da7b0babcbdbcb68106504afc65b3b6ad9e90f75c706d5c36" }, { "id": "atlas-lesson-diffusion-action-horizon", "title": "Predict action chunks and replan with feedback", "category": "learning", "format": "Atlas lesson", "description": "Separate generated action horizon, executed prefix and replanning interval.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/diffusion-action-horizon/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-world-action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Authored deterministic scalar integrator and command chunks. Rate and delay are stated assumptions; no diffusion inference or physical robot timing is measured. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/diffusion-action-horizon-baff40bb4f62c303.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#diffusion-action-horizon", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "380bff9f0111bb060aafc626e38604fe6289a27151733d960af0de3704d9b7d6", "contentLength": 6241, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-diffusion-action-horizon.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-diffusion-action-horizon.md", "sections": [ { "id": "section-1", "title": "Predict action chunks and replan with feedback" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Predict action chunks and replan with feedback · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What changes when only a prefix is executed before observing again?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#diffusion-action-horizon" }, { "title": "Diffusion Policy", "url": "https://arxiv.org/html/2303.04137v5" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/diffusion-action-horizon-baff40bb4f62c303.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Train a denoiser and sample iteratively", "url": "https://semiaifoundry.com/learn/atlas/denoising-generative-objectives/" }, { "title": "Predict transitions conditional on actions", "url": "https://semiaifoundry.com/learn/atlas/action-conditioned-world-model/" }, { "title": "Learn behavior from a model and test in the environment", "url": "https://semiaifoundry.com/learn/atlas/imagined-rollouts-policy-learning/" }, { "title": "Translate learned representations into robot action units", "url": "https://semiaifoundry.com/learn/atlas/vision-language-action-interface/" } ], "recordHash": "a65da0023eec60be61203a4bd89708ba091b3e108571187d26ced66da6dd67d8" }, { "id": "atlas-lesson-direct-preference-objective", "title": "DPO policy/reference likelihood ratios", "category": "learning", "format": "Atlas lesson", "description": "Compute DPO from policy and frozen-reference response likelihoods with an explicit pair denominator.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-posttraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable DPO. Positive probabilities, fixed reference and consistent response token scoring. Core uses authored swap preferences and answer-plus-EOS scores, not collected human labels. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/direct-preference-objective-ec338a46ac48d11f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#direct-preference-objective", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "95059fe768b375077fb0b3400152e9581761020b10d4ab1e36bfcb2870a526d1", "contentLength": 6729, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-direct-preference-objective.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-direct-preference-objective.md", "sections": [ { "id": "section-1", "title": "DPO policy/reference likelihood ratios" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "DPO policy/reference likelihood ratios · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which state receives gradients in the declared DPO branch?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#direct-preference-objective" }, { "title": "Direct Preference Optimization", "url": "https://arxiv.org/html/2305.18290v3" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/direct-preference-objective-ec338a46ac48d11f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Verifiers, grouped advantages and RLVR", "url": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/" }, { "title": "When reward improves but the task gets worse", "url": "https://semiaifoundry.com/learn/atlas/reward-proxy-overoptimization/" }, { "title": "Frozen base weights and trainable adapters", "url": "https://semiaifoundry.com/learn/atlas/low-rank-adaptation/" }, { "title": "Transfer outputs without confusing size with quality", "url": "https://semiaifoundry.com/learn/atlas/teacher-student-distillation/" } ], "recordHash": "c0fb57de11b90e1aa7828235161814afb52bb280230e93d1cf47590efe023ef0" }, { "id": "atlas-lesson-disaggregated-serving", "title": "Prefill/decode disaggregation and useful serving rate", "category": "learning", "format": "Atlas lesson", "description": "Separates workload phases when independent scheduling benefits exceed the state-transfer cost.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/disaggregated-serving/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "DistServe and PagedAttention are distinct research methods. Their measured gains depend on workload and configurations and are not reproduced as unconditional defaults.\n\nThe handoff extension is worked timing and ownership analysis. It is not a measured disaggregated server, network protocol or real-model KV exchange.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/disaggregated-serving-27974f91455cb4c0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#disaggregated-serving", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9d8119928ee2717222713ba4d38b7c264a5d0861677a8de85100dfba6cf2b1d4", "contentLength": 7040, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-disaggregated-serving.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-disaggregated-serving.md", "sections": [ { "id": "section-1", "title": "Prefill/decode disaggregation and useful serving rate" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "KV handoff floor" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What new cost must a disaggregated design explicitly budget?" }, { "id": "section-11", "title": "Can a decoder consume an incomplete handoff simply because some KV bytes arrived?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#disaggregated-serving" }, { "title": "DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving", "url": "https://arxiv.org/abs/2401.09670" }, { "title": "Efficient Memory Management for Large Language Model Serving with PagedAttention", "url": "https://arxiv.org/abs/2309.06180" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/disaggregated-serving-27974f91455cb4c0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Prefill and prompt processing", "url": "https://semiaifoundry.com/learn/atlas/prefill-resource-trace/" }, { "title": "Autoregressive decode and weight traffic", "url": "https://semiaifoundry.com/learn/atlas/decode-bandwidth-trace/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" }, { "title": "Context, retrieval and durable memory", "url": "https://semiaifoundry.com/learn/atlas/context-memory-provenance/" }, { "title": "Events, queues and backpressure", "url": "https://semiaifoundry.com/learn/atlas/event-queues-delivery/" } ], "recordHash": "28fab066871fa713fc2b3bf2a61f8f5da75aab55aa09ed882ad627f5dd9951e2" }, { "id": "atlas-lesson-distributed-gradient-weighting", "title": "Uneven batches and the global gradient", "category": "learning", "format": "Atlas lesson", "description": "Preserve the intended training objective when ranks contribute different numbers of valid examples or tokens.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/distributed-gradient-weighting/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The PyTorch source is pinned to v2.8.0 and supports the default averaging convention, not a claim about every backend or custom hook. The squared-error data, gradient weighting derivation and SGD step are authored examples. Join semantics after input exhaustion are outside this fixed-participant update.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/distributed-gradient-weighting-31b4b96883c8d7f0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#distributed-gradient-weighting", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "fa5db0229ca8551d9fa4a1a842352e5782e61de99b1855aa1f914540ea86451a", "contentLength": 8644, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-distributed-gradient-weighting.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-distributed-gradient-weighting.md", "sections": [ { "id": "section-1", "title": "Uneven batches and the global gradient" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Global item-mean gradient" }, { "id": "section-5", "title": "Compensate a mean-across-ranks reducer" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Two ranks have counts 2 and 6 and mean gradients 1 and 3. What is the global item-mean gradient?" }, { "id": "section-12", "title": "A mean-across-two-ranks reducer receives local means. Which scale factors preserve the eight-item objective?" }, { "id": "section-13", "title": "Does equal synchronized state prove the chosen sample weights were correct?" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#distributed-gradient-weighting" }, { "title": "PyTorch v2.8.0 — DistributedDataParallel implementation and contract", "url": "https://github.com/pytorch/pytorch/blob/v2.8.0/torch/nn/parallel/distributed.py" }, { "title": "NVIDIA NCCL — Collective Operations", "url": "https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/collectives.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/distributed-gradient-weighting-31b4b96883c8d7f0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Training state and activation rematerialization", "url": "https://semiaifoundry.com/learn/atlas/training-memory-state/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Floating-point reductions and compiler permissions", "url": "https://semiaifoundry.com/learn/atlas/floating-point-reduction-order/" } ], "recordHash": "bebd393548a344aa4a027459440f57ebd985e56e9a38a2e06463feb8eaf2fd99" }, { "id": "atlas-lesson-dma-visibility-ownership", "title": "DMA visibility, ordering and buffer lifetime", "category": "learning", "format": "Atlas lesson", "description": "Separate coherent values, ordered descriptor publication and ownership of in-flight storage.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/dma-visibility-ownership/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Primary sources establish the cited runtime mechanisms. Numerical values, address ranges, ABI strings, event schedule and reset/retry epochs are authored teaching contracts. No real device, firmware image, operating-system driver, page table, cache protocol or security verification is executed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/dma-visibility-ownership-82d7e647892c3b29.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#dma-visibility-ownership", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "daed6e18f2275f31a64cfafc9fb0c771d14bf9121f008fa7551e3e66e0114907", "contentLength": 7014, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dma-visibility-ownership.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dma-visibility-ownership.md", "sections": [ { "id": "section-1", "title": "DMA visibility, ordering and buffer lifetime" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Input visibility changes the actual operand" }, { "id": "section-5", "title": "Buffer reuse follows ownership" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Physical C is correct, but the noncoherent CPU output handoff was omitted. What does the fixture consumer read?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#dma-visibility-ownership" }, { "title": "Linux 6.16 — Dynamic DMA mapping Guide", "url": "https://docs.kernel.org/6.16/core-api/dma-api-howto.html" }, { "title": "OASIS — Virtual I/O Device (VIRTIO) Version 1.3", "url": "https://docs.oasis-open.org/virtio/virtio/v1.3/virtio-v1.3.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/dma-visibility-ownership-82d7e647892c3b29.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Process, physical and device address spaces", "url": "https://semiaifoundry.com/learn/atlas/process-dma-address-spaces/" }, { "title": "L1 and texture cache", "url": "https://semiaifoundry.com/learn/atlas/l1-cache/" }, { "title": "IOMMU permission and tensor identity", "url": "https://semiaifoundry.com/learn/atlas/iommu-buffer-identity/" }, { "title": "Completion, reset and execution epochs", "url": "https://semiaifoundry.com/learn/atlas/device-completion-reset-epochs/" }, { "title": "PCIe and CXL: transport versus memory semantics", "url": "https://semiaifoundry.com/learn/atlas/pcie-cxl-semantics/" } ], "recordHash": "0b58a1fc0c74114af9c9922e956ad7d4e0984419a383d894ca78d5889feacdd0" }, { "id": "atlas-lesson-document-extraction-validation", "title": "Document fields become validated records", "category": "learning", "format": "Atlas lesson", "description": "Document layout, transcription/extraction, schema normalization, confidence and cross-field constraints.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/document-extraction-validation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Models become evaluated applications", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Synthetic invoice; nonnegative integer quantities and exact integer-cent prices. Tax, currency conversion, discounts and rounding policies are outside the example.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/document-extraction-validation-b08a723accbd1c21.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#document-extraction-validation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0879da9c5d6eb48ddb0472af8c60a5be22309fae4fa4c45584a150dd85fbbe24", "contentLength": 6329, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-document-extraction-validation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-document-extraction-validation.md", "sections": [ { "id": "section-1", "title": "Document fields become validated records" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Document fields become validated records · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "An extractor changes both a price and total consistently but disagrees with the image. Is arithmetic validation sufficient?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#document-extraction-validation" }, { "title": "OCR-free Document Understanding Transformer", "url": "https://arxiv.org/abs/2111.15664v5" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/document-extraction-validation-b08a723accbd1c21.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tool schemas and semantic validation", "url": "https://semiaifoundry.com/learn/atlas/tool-contracts-schemas/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" } ], "recordHash": "6a0ce07f778302c111da9fd418ac35fcc5f2328ee2cd1606ab022ebf0774efa8" }, { "id": "atlas-lesson-domain-adaptive-continuation", "title": "Continue language modeling on a new domain", "category": "learning", "format": "Atlas lesson", "description": "Measure new-domain acquisition and old-domain retention from the same starting checkpoint.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/domain-adaptive-continuation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-continuation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable continuation. Same evaluation cases, masks and tokenizer before/after; negative loss change is improvement. Binary illustrative probabilities do not describe every vocabulary class in the core. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/domain-adaptive-continuation-1c23df0ce2faab3e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#domain-adaptive-continuation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ee0071ff85f21ecf3b9892297b027f6989c1ec5613a8848535367169b4f50305", "contentLength": 6381, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-domain-adaptive-continuation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-domain-adaptive-continuation.md", "sections": [ { "id": "section-1", "title": "Continue language modeling on a new domain" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Continue language modeling on a new domain · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a positive old-domain loss change mean here?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#domain-adaptive-continuation" }, { "title": "Don’t Stop Pretraining", "url": "https://aclanthology.org/2020.acl-main.740.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/domain-adaptive-continuation-1c23df0ce2faab3e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Next-token supervision from raw sequences", "url": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Describe a stage by its changed contract", "url": "https://semiaifoundry.com/learn/atlas/model-lifecycle-stage-contract/" }, { "title": "Retention, replay and transfer", "url": "https://semiaifoundry.com/learn/atlas/replay-retention-forgetting/" }, { "title": "Context extension is a learned-use test", "url": "https://semiaifoundry.com/learn/atlas/long-context-adaptation/" }, { "title": "Compatible weight averaging and regressions", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-averaging-boundaries/" } ], "recordHash": "524bc269948c1fabd47152e95588eff66b03966204d9e4c4cf6726d5d8d8690b" }, { "id": "atlas-lesson-doping", "title": "Donor and acceptor doping", "category": "learning", "format": "Atlas lesson", "description": "Changes carrier populations by introducing selected impurity atoms.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/doping/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Atomic foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The displayed relation is a nondegenerate, charge-neutrality approximation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/doping-2971080417733db7.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#doping", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "402d6f2364af95445bd10db7b74bf4e8f772ce3a20b13ce16178405ef1d9a1ef", "contentLength": 4696, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-doping.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-doping.md", "sections": [ { "id": "section-1", "title": "Donor and acceptor doping" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Mass action and donor control" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What distinguishes n-type silicon?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#doping" }, { "title": "MIT 6.777J — Semiconductor Materials", "url": "https://ocw.mit.edu/courses/6-777j-design-and-fabrication-of-microelectromechanical-devices-spring-2007/6de08ad7d4ee670c283ce5ec0e6a653b_07lecture07e.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/doping-2971080417733db7.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Energy bands and carriers", "url": "https://semiaifoundry.com/learn/atlas/energy-bands/" }, { "title": "Diamond-cubic silicon lattice", "url": "https://semiaifoundry.com/learn/atlas/crystal-lattice/" }, { "title": "P–n junction and depletion region", "url": "https://semiaifoundry.com/learn/atlas/pn-junction/" }, { "title": "Source and drain regions", "url": "https://semiaifoundry.com/learn/atlas/source-drain/" } ], "recordHash": "868220561c36ce096117cd73a94675cd442cce2df3f8849d5b7f100c529773ac" }, { "id": "atlas-lesson-dpu-infrastructure-offload", "title": "DPU and infrastructure offload", "category": "learning", "format": "Atlas lesson", "description": "Moves selected networking and infrastructure work away from the host CPU.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/dpu-infrastructure-offload/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "BlueField modes are documented in a pinned DOCA archive. IPU is locally defined here; unrelated vendor meanings must not be merged into one architecture.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/dpu-infrastructure-offload-f81449041768aad1.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#dpu-infrastructure-offload", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "28de1916f5024c30ac541cb72bba625ea36baaa8cf177028b140cb2755d99451", "contentLength": 4764, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dpu-infrastructure-offload.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dpu-infrastructure-offload.md", "sections": [ { "id": "section-1", "title": "DPU and infrastructure offload" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Offload speedup bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Only 10% of application time is removable networking overhead. What limits ideal overall speedup?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#dpu-infrastructure-offload" }, { "title": "NVIDIA BlueField DPU Modes of Operation, DOCA 2.5.3 archive", "url": "https://docs.nvidia.com/doca/archive/2-5-3/nvidia%2Bbluefield%2Bdpu%2Bmodes%2Bof%2Boperation/index.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/dpu-infrastructure-offload-f81449041768aad1.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "PCI Express interconnect", "url": "https://semiaifoundry.com/learn/atlas/pcie-interface/" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" } ], "recordHash": "44138ba2cd74d75df26ddabe379e144bc71371e076cb493ade48e849d8e4054b" }, { "id": "atlas-lesson-dram-cell-array-fabrication", "title": "DRAM cells, arrays and peripheral circuits", "category": "learning", "format": "Atlas lesson", "description": "Creates charge-storage cells and the circuitry needed to address, sense and restore them.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/dram-cell-array-fabrication/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory / HBM fabrication and assembly", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The geometry and capacitances are illustrative. No cell capacitor dimensions, refresh interval or proprietary HBM DRAM process is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/dram-cell-array-fabrication-574a79feed83c253.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#dram-cell-array-fabrication", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "08603310a7d13a99d74294a6feee4ad03897b744c706ec99c07e3b6fe7efd9e9", "contentLength": 5383, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dram-cell-array-fabrication.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dram-cell-array-fabrication.md", "sections": [ { "id": "section-1", "title": "DRAM cells, arrays and peripheral circuits" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Initial charge-sharing signal" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does a DRAM read need a sense amplifier?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#dram-cell-array-fabrication" }, { "title": "Micron — Introduction to Memory", "url": "https://www.micron.com/content/dam/micron/educatorhub/intro-to-memory/micron-intro-to-memory-presentation.pdf" }, { "title": "Synopsys — What Designers Need to Know About HBM3", "url": "https://www.synopsys.com/articles/hbm3-ip-dwtb.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/dram-cell-array-fabrication-574a79feed83c253.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DRAM die and memory banks", "url": "https://semiaifoundry.com/learn/atlas/dram-die/" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "ALD and self-limiting surface reactions", "url": "https://semiaifoundry.com/learn/atlas/ald-self-limiting-growth/" }, { "title": "TSV formation, keep-out and backside reveal", "url": "https://semiaifoundry.com/learn/atlas/hbm-tsv-reveal/" }, { "title": "HBM generations, channels, refresh and ECC", "url": "https://semiaifoundry.com/learn/atlas/hbm-channel-generation-ras/" } ], "recordHash": "51b8b12900913315345309724f7133e64801794624c0e785def9b30330089944" }, { "id": "atlas-lesson-dram-die", "title": "DRAM die and memory banks", "category": "learning", "format": "Atlas lesson", "description": "Stores dense arrays of charge-based bits and organizes them into banks for read, write, and refresh.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/dram-die/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory hierarchy", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The expression is a simplified charge-sharing model.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/dram-die-1a43a09c840bc357.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#dram-die", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "130276b4f4478f9ab8bdc17492299d48f4c8d561eb96425e3a23d6be18e9b167", "contentLength": 6410, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dram-die.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-dram-die.md", "sections": [ { "id": "section-1", "title": "DRAM die and memory banks" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A stored bit begins as a tiny voltage perturbation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does conventional DRAM need refresh?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "1968 · Dennard’s DRAM cell patent is granted" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#dram-die" }, { "title": "Robert Dennard: US3387286A, Field-effect transistor memory", "url": "https://patents.google.com/patent/US3387286A/en" }, { "title": "Micron: How DRAM changed the world", "url": "https://www.micron.com/about/blog/memory/dram/how-dram-changed-the-world" }, { "title": "Micron educator hub: Introduction to memory", "url": "https://www.micron.com/content/dam/micron/educatorhub/intro-to-memory/micron-intro-to-memory-presentation.pdf" }, { "title": "Micron HBM3E", "url": "https://www.micron.com/products/memory/hbm/hbm3e" }, { "title": "MIT Computation Structures: DRAM charge sharing", "url": "https://ocw.mit.edu/courses/6-004-computation-structures-spring-2017/f342551f652653e3ee0d0c56a926efeb_9eWKuWyXYKY.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/dram-die-1a43a09c840bc357.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Insulators and low-k films", "url": "https://semiaifoundry.com/learn/atlas/dielectric/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Through-silicon via", "url": "https://semiaifoundry.com/learn/atlas/through-silicon-via/" }, { "title": "DDR5 server memory", "url": "https://semiaifoundry.com/learn/atlas/ddr-memory/" }, { "title": "Grace LPDDR5X memory", "url": "https://semiaifoundry.com/learn/atlas/lpddr-memory/" } ], "recordHash": "feeb1f5df40a7745b104f503f5ad996a1856e743aea1ca68e135b82ee7b892bc" }, { "id": "atlas-lesson-durable-actions-idempotency", "title": "Durable actions and the ambiguous timeout", "category": "learning", "format": "Atlas lesson", "description": "Persist intent, execute with idempotency key, store receipt and recover without duplicate business effects.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/durable-actions-idempotency/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "From request to durable action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The durable incident experience executes typed fixture tools, authority checks, exact review, receipts and independent final-state checks. Its policies are authored code and its storage boundary is local; it is not a real model or production workflow platform. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. The key and payload are unchanged, receipt retention covers the retry, and the service atomically commits the effect and receipt. This is an effect guarantee under those assumptions, not an exactly-once network-delivery claim.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/durable-actions-idempotency-0913e642cc5c0015.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#durable-actions-idempotency", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0798117f7c94bcae8ec1a5d38eb9650bf2681280869a16b4264beff7e198282d", "contentLength": 7079, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-durable-actions-idempotency.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-durable-actions-idempotency.md", "sections": [ { "id": "section-1", "title": "Durable actions and the ambiguous timeout" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Durable actions and the ambiguous timeout · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "After the reservation committed but its reply was lost, what should the same-key retry do?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#durable-actions-idempotency" }, { "title": "Temporal Activities", "url": "https://docs.temporal.io/activities" }, { "title": "Temporal Workflow Execution", "url": "https://docs.temporal.io/workflow-execution" }, { "title": "LangGraph persistence", "url": "https://docs.langchain.com/oss/python/langgraph/persistence" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/durable-actions-idempotency-0913e642cc5c0015.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Events, queues and backpressure", "url": "https://semiaifoundry.com/learn/atlas/event-queues-delivery/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "5e95f60bb65b13ab04dea0d8ac5d0a6e457e7c6035ff802f0ad181fd70013d3f" }, { "id": "atlas-lesson-electronic-silicon-crystal-growth", "title": "Electronic-grade silicon and crystal growth", "category": "learning", "format": "Atlas lesson", "description": "Converts purified feedstock into an oriented single-crystal substrate.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/electronic-silicon-crystal-growth/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Materials", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Growth diagrams are conceptual. Dopant additions, thermal profiles, oxygen limits and acceptance criteria are supplier/product-specific and are not supplied here.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/electronic-silicon-crystal-growth-5547f0a4066351d3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#electronic-silicon-crystal-growth", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9de504b2dc40e114582d3760d75b523308e45eb0a53c3a37f470e72c913eba7f", "contentLength": 5432, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-electronic-silicon-crystal-growth.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-electronic-silicon-crystal-growth.md", "sections": [ { "id": "section-1", "title": "Electronic-grade silicon and crystal growth" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Resistivity and mobile charge" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a highly pure polycrystal still be unsuitable for a conventional logic wafer?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#electronic-silicon-crystal-growth" }, { "title": "SUMCO — Production Processes", "url": "https://www.sumcosi.com/english/products/process/" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "WACKER — Ultrapure silicon and semiconductor polysilicon", "url": "https://reports.wacker.com/2021/annual-report/sustainable-solutions/ultrapure-silicon-for-solar-power.html" }, { "title": "Hemlock Semiconductor — Markets and Technologies", "url": "https://www.hscpoly.com/markets-technologies/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/electronic-silicon-crystal-growth-5547f0a4066351d3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Diamond-cubic silicon lattice", "url": "https://semiaifoundry.com/learn/atlas/crystal-lattice/" }, { "title": "Donor and acceptor doping", "url": "https://semiaifoundry.com/learn/atlas/doping/" }, { "title": "Wafer finishing, orientation and geometry", "url": "https://semiaifoundry.com/learn/atlas/wafer-finishing-geometry/" } ], "recordHash": "4adbc5557401c6afba4b0f7917aba349137a62e40476f7567c565f7a4f854ac4" }, { "id": "atlas-lesson-embedding", "title": "Embedding table", "category": "learning", "format": "Atlas lesson", "description": "Give discrete tokens a trainable numerical representation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/embedding/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Representation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is dense logical storage and lookup as described by the linked embedding references. Padding, quantization metadata, tied output weights and training optimizer state are separate; no particular model vocabulary or width is assumed.\n\nMode: executable lookup gradients; worked tying. Matching coordinates, summed path derivatives and an explicit tied/separate convention. Core weights are separate. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/embedding-a409279536f75f65.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#embedding", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "05fee4f87241174adb89653dd91bf341496b28af0f3e450ae88ee66069851646", "contentLength": 8509, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-embedding.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-embedding.md", "sections": [ { "id": "section-1", "title": "Embedding table" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Lookup is a sparse matrix multiplication" }, { "id": "section-5", "title": "Learned lookup gradients and tied weights · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "What does an embedding lookup return?" }, { "id": "section-12", "title": "What is the input-only gradient for the repeated a row?" }, { "id": "section-13", "title": "Historical context" }, { "id": "section-14", "title": "2003 · Distributed word representations in a neural language model" }, { "id": "section-15", "title": "Evidence and scope" }, { "id": "section-16", "title": "Sources" }, { "id": "section-17", "title": "Continue exploring" }, { "id": "section-18", "title": "Foundations" }, { "id": "section-19", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#embedding" }, { "title": "Bengio et al. — A Neural Probabilistic Language Model", "url": "https://www.jmlr.org/papers/v3/bengio03a.html" }, { "title": "PyTorch — Embedding", "url": "https://docs.pytorch.org/docs/2.14/generated/torch.nn.Embedding.html" }, { "title": "Attention Is All You Need", "url": "https://arxiv.org/html/1706.03762v7" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/embedding-a409279536f75f65.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tokenizer", "url": "https://semiaifoundry.com/learn/atlas/tokenizer/" }, { "title": "Position representation", "url": "https://semiaifoundry.com/learn/atlas/positional-encoding/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "A differentiable computation graph", "url": "https://semiaifoundry.com/learn/atlas/reverse-mode-autodiff/" }, { "title": "Assemble an initialized causal language model", "url": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/" } ], "recordHash": "370be89c7395df098bf7ce9b9c63bc7a2f45d9f43ec3fd5aec9fc85db16da3f0" }, { "id": "atlas-lesson-embodied-policy-evidence", "title": "Learned action policies need embodiment evidence", "category": "learning", "format": "Atlas lesson", "description": "Observation/action encoding, training trajectory distribution, policy rate and downstream control constraints.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/embodied-policy-evidence/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Observations become physical actions", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Teaching codec only; not a published model’s tokenization. Actual motion requires compatible control, geometry and dynamics; a requested displacement is not observed completion.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/embodied-policy-evidence-0ee94cc4feabfa1f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#embodied-policy-evidence", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ee86ab951cad41a915ec5851f7a69f6722b0521b18f0cae3ed2eaf7765e5e17b", "contentLength": 6433, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-embodied-policy-evidence.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-embodied-policy-evidence.md", "sections": [ { "id": "section-1", "title": "Learned action policies need embodiment evidence" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Learned action policies need embodiment evidence · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Under the stated codec, what displacement does bin 4 request over 0.2 s?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#embodied-policy-evidence" }, { "title": "RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control", "url": "https://arxiv.org/abs/2307.15818" }, { "title": "Lynch and Park · Modern Robotics 11.3", "url": "https://modernrobotics.northwestern.edu/nu-gm-book-resource/11-3-motion-control-with-velocity-inputs-part-1-of-3/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/embodied-policy-evidence-0ee94cc4feabfa1f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Goals, plans and actions are different objects", "url": "https://semiaifoundry.com/learn/atlas/robot-goal-plan-action/" }, { "title": "Feedback closes the action loop", "url": "https://semiaifoundry.com/learn/atlas/robot-feedback-control/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "c0715e37adc5aee39121c64bc4964c8d4cb2a1749b67c16c96442002c8b8b33e" }, { "id": "atlas-lesson-emib-local-bridge", "title": "EMIB and localized die-to-die bridges", "category": "learning", "format": "Atlas lesson", "description": "Places fine-routing silicon near adjacent die edges inside a substrate.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/emib-local-bridge/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Interposers, bridges and stacking", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The Intel brief includes forecasts and manufacturer comparisons. No EMIB-specific queue, utilization or field failure rate is established.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/emib-local-bridge-c088c1cf60acdf36.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#emib-local-bridge", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "763fd38a3fad70797817906a4baf0e0f7304c7004d26cf721c3e023dba5bc356", "contentLength": 5081, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-emib-local-bridge.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-emib-local-bridge.md", "sections": [ { "id": "section-1", "title": "EMIB and localized die-to-die bridges" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Connection-yield sensitivity" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which information is needed before claiming an EMIB-specific capacity bottleneck?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#emib-local-bridge" }, { "title": "Intel Foundry — Accelerating HPC and AI", "url": "https://www.intel.com/content/dam/www/central-libraries/us/en/documents/2025-11/intel-foundry-hpc-ai-brief.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/emib-local-bridge-c088c1cf60acdf36.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Flip-chip assembly and organic substrates", "url": "https://semiaifoundry.com/learn/atlas/flip-chip-abf-substrate/" }, { "title": "CoWoS-S and the silicon interposer route", "url": "https://semiaifoundry.com/learn/atlas/cowos-s-silicon-interposer/" }, { "title": "CoWoS-R and CoWoS-L: RDL and local silicon", "url": "https://semiaifoundry.com/learn/atlas/cowos-r-l-routing/" }, { "title": "Microbumps, reflow and thermocompression", "url": "https://semiaifoundry.com/learn/atlas/bump-thermocompression-assembly/" } ], "recordHash": "c07f6ce6d3d701c0d32471997c397ab05d443a468337d6831d12f02cb6c28b76" }, { "id": "atlas-lesson-energy-bands", "title": "Energy bands and carriers", "category": "learning", "format": "Atlas lesson", "description": "Explains how a semiconductor can be electrically controlled.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/energy-bands/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Atomic foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Band diagrams are equilibrium or local approximations and do not specify a transistor operating point.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/energy-bands-8c90b61be7dd8e61.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#energy-bands", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1a3b305e5eea1f24eb990cebb721fcdf36f7e736beeec6b320a389efed94828e", "contentLength": 4955, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-energy-bands.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-energy-bands.md", "sections": [ { "id": "section-1", "title": "Energy bands and carriers" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Thermal carrier generation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is the vertical distance in an ordinary band diagram?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#energy-bands" }, { "title": "MIT 3.091 — Band Diagrams, Semiconductors, and Doping", "url": "https://ocw.mit.edu/courses/3-091-introduction-to-solid-state-chemistry-fall-2018/e1f4e9b940c67f4370ce007a939773c8_MIT3_091F18_REC12.pdf" }, { "title": "MIT 3.23 — Semiconductor Statistics and Mass Action", "url": "https://ocw.mit.edu/courses/3-23-electrical-optical-and-magnetic-properties-of-materials-fall-2007/ca2f26ca04b2ccb3eca0c83b73dfa00e_ps7.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/energy-bands-8c90b61be7dd8e61.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Diamond-cubic silicon lattice", "url": "https://semiaifoundry.com/learn/atlas/crystal-lattice/" }, { "title": "Donor and acceptor doping", "url": "https://semiaifoundry.com/learn/atlas/doping/" }, { "title": "P–n junction and depletion region", "url": "https://semiaifoundry.com/learn/atlas/pn-junction/" }, { "title": "Controllable semiconductor channel", "url": "https://semiaifoundry.com/learn/atlas/channel/" } ], "recordHash": "8828082fad4f660082405abdd2b87d062bacc4a239650f9fb8f659a4c79e9750" }, { "id": "atlas-lesson-energy-forecast-boundaries", "title": "Energy forecasts, geography and measurement boundaries", "category": "learning", "format": "Atlas lesson", "description": "Distinguishes estimated electricity use from conditional demand projections.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/energy-forecast-boundaries/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Global AI infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "IEA baseline and projection are separate claim records. LBNL’s laboratory abstract was retrieved; inaccessible full-report methodology is not represented as independently rechecked.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/energy-forecast-boundaries-a7a1ef8a72b5c20c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#energy-forecast-boundaries", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "92d7735f6925bbaf9cbfb1601698cca29a441a0fc6928fbcd64c5b5d040210fd", "contentLength": 4840, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-energy-forecast-boundaries.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-energy-forecast-boundaries.md", "sections": [ { "id": "section-1", "title": "Energy forecasts, geography and measurement boundaries" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Energy from average power" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a US report not be added to a global total?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#energy-forecast-boundaries" }, { "title": "Key Questions on Energy and AI: Executive Summary", "url": "https://www.iea.org/reports/key-questions-on-energy-and-ai/executive-summary" }, { "title": "United States Data Center Energy Usage Report: 2025 Update", "url": "https://bies.lbl.gov/publications/united-states-data-center-energy-2025" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/energy-forecast-boundaries-a7a1ef8a72b5c20c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Dynamic load, reserve and power control", "url": "https://semiaifoundry.com/learn/atlas/rack-dynamic-power/" }, { "title": "Water withdrawal, consumption and cooling circulation", "url": "https://semiaifoundry.com/learn/atlas/water-boundary-accounting/" }, { "title": "Grid interconnection and deliverable electrical capacity", "url": "https://semiaifoundry.com/learn/atlas/grid-interconnection-readiness/" } ], "recordHash": "25a58f139e56f3c20e680cfe3be4760c98af793f133845fa64087a0b960be57e" }, { "id": "atlas-lesson-epitaxial-material-stack", "title": "Epitaxy and engineered starting layers", "category": "learning", "format": "Atlas lesson", "description": "Grows a crystalline layer whose composition and doping serve the later device.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/epitaxial-material-stack/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Materials", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No precursor mixture, temperature or production critical thickness is prescribed. Alternating channel stacks shown here are representative research/manufacturing concepts.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/epitaxial-material-stack-7939ee89c3bf3e0e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#epitaxial-material-stack", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "db39c16a24739398803427fef61df6deb646a04360758d7add8cf8b61c2aa56e", "contentLength": 5141, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-epitaxial-material-stack.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-epitaxial-material-stack.md", "sections": [ { "id": "section-1", "title": "Epitaxy and engineered starting layers" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Lattice mismatch" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why inspect composition as well as total thickness in an alternating nanosheet starting stack?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#epitaxial-material-stack" }, { "title": "SUMCO — Production Processes", "url": "https://www.sumcosi.com/english/products/process/" }, { "title": "Applied Materials — New Ways to Shrink", "url": "https://ir.appliedmaterials.com/static-files/f2fbf48d-a761-4c4f-ab4c-73f312ab1ebc" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/epitaxial-material-stack-7939ee89c3bf3e0e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Electronic-grade silicon and crystal growth", "url": "https://semiaifoundry.com/learn/atlas/electronic-silicon-crystal-growth/" }, { "title": "Diamond-cubic silicon lattice", "url": "https://semiaifoundry.com/learn/atlas/crystal-lattice/" }, { "title": "Nanosheet release and replacement gates", "url": "https://semiaifoundry.com/learn/atlas/nanosheet-gate-last-integration/" }, { "title": "Source/drain, spacers, contacts and MOL", "url": "https://semiaifoundry.com/learn/atlas/source-drain-contact-integration/" } ], "recordHash": "9cb4f5ae941e542fde0f0b5c2b3c04077ee1f04f6189e5bf174b9503667d181c" }, { "id": "atlas-lesson-evaluation", "title": "Evaluation & the AGI frontier", "category": "learning", "format": "Atlas lesson", "description": "Measure breadth, reliability, and practical competence.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/evaluation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Evidence and frontiers", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Benchmark selection, contamination, rubric and dependence dominate many real evaluations.\n\nThe examples use fictional environments and deterministic authored policies. They do not reproduce τ-bench cases or establish a real agent’s reliability or benchmark score.\n\nMode: executable final report; worked uncertainty. Independent Bernoulli sampling model for the illustrative interval; the authored four-case split is not demonstrated to be a representative population sample. Interval does not cure dataset selection bias. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/evaluation-3092c2a64c0ff0e2.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#evaluation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "d5ec81135bef83993af9fdbc757ef6cd7bfb5bbab952ef271f67af24f0d25ec1", "contentLength": 11547, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-evaluation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-evaluation.md", "sections": [ { "id": "section-1", "title": "Evaluation & the AGI frontier" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Benchmark success has sampling uncertainty" }, { "id": "section-5", "title": "A development protocol and an independent final test · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "What does strong performance on one benchmark demonstrate?" }, { "id": "section-12", "title": "Every call succeeded and the source supports the FAN-9 work order, but the task requested FAN-7. Is the task correct?" }, { "id": "section-13", "title": "What should happen to a 4/4 report after the weights change?" }, { "id": "section-14", "title": "Historical context" }, { "id": "section-15", "title": "2023 · Levels of AGI separates breadth from performance" }, { "id": "section-16", "title": "Evidence and scope" }, { "id": "section-17", "title": "Sources" }, { "id": "section-18", "title": "Continue exploring" }, { "id": "section-19", "title": "Foundations" }, { "id": "section-20", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#evaluation" }, { "title": "Morris et al. — Levels of AGI for Operationalizing Progress on the Path to AGI", "url": "https://arxiv.org/abs/2311.02462" }, { "title": "NIST — Binomial Distribution", "url": "https://itl.nist.gov/div898/handbook/eda/section3/eda366i.htm" }, { "title": "NIST — Exact Binomial Confidence Limits", "url": "https://itl.nist.gov/div898/software/dataplot/refman2/auxillar/exacbici.htm" }, { "title": "τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains", "url": "https://arxiv.org/abs/2406.12045" }, { "title": "Holistic Evaluation of Language Models", "url": "https://arxiv.org/html/2211.09110v1" }, { "title": "On Calibration of Modern Neural Networks", "url": "https://arxiv.org/html/1706.04599v2" }, { "title": "NIST Dataplot: Wilson proportion interval", "url": "https://www.itl.nist.gov/div898/software/dataplot/refman2/auxillar/agrecoul.htm" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/evaluation-3092c2a64c0ff0e2.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Post-training & feedback", "url": "https://semiaifoundry.com/learn/atlas/post-training/" }, { "title": "Scaling laws & resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scaling-laws/" }, { "title": "Workflow graphs and explicit state", "url": "https://semiaifoundry.com/learn/atlas/workflow-graphs-state/" }, { "title": "Traces connect cost, latency and results", "url": "https://semiaifoundry.com/learn/atlas/telemetry-traces-evaluation/" }, { "title": "Retrieval from source document to answer", "url": "https://semiaifoundry.com/learn/atlas/retrieval-indexing-evaluation/" }, { "title": "Confidence, errors and refusal to guess", "url": "https://semiaifoundry.com/learn/atlas/probability-calibration-abstention/" }, { "title": "Human and model judgments under a rubric", "url": "https://semiaifoundry.com/learn/atlas/judge-rubric-agreement/" }, { "title": "From lexical retrieval to model answers with evidence", "url": "https://semiaifoundry.com/learn/atlas/retrieval-supported-generation/" }, { "title": "Sampling more candidates versus selecting correct ones", "url": "https://semiaifoundry.com/learn/atlas/test-time-search-verification/" }, { "title": "Version the entire evaluated system", "url": "https://semiaifoundry.com/learn/atlas/model-system-regression-contract/" } ], "recordHash": "1645ed627966e6660cb21cd34f97697aee5257fc560c3d2c249a34dc62622a98" }, { "id": "atlas-lesson-event-queues-delivery", "title": "Events, queues and backpressure", "category": "learning", "format": "Atlas lesson", "description": "Distinguish event occurrence, delivery, acknowledgement, deduplication, retries and admission.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/event-queues-delivery/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "From request to durable action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The durable incident experience executes typed fixture tools, authority checks, exact review, receipts and independent final-state checks. Its policies are authored code and its storage boundary is local; it is not a real model or production workflow platform. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Counts share one queue boundary. Admissions and duplicate removals cannot exceed available queued deliveries. Business effects are counted separately.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/event-queues-delivery-c2f047356ab0b24d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#event-queues-delivery", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "04d57892306a037cf0ebbaa95c17de8d5af35e3964f6c25a5747209a8db19c34", "contentLength": 6518, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-event-queues-delivery.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-event-queues-delivery.md", "sections": [ { "id": "section-1", "title": "Events, queues and backpressure" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Events, queues and backpressure · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Two copies of the same incident arrive; one is admitted and one is deduplicated. How many distinct incidents were executed?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#event-queues-delivery" }, { "title": "Temporal Activities", "url": "https://docs.temporal.io/activities" }, { "title": "Temporal Workflow Execution", "url": "https://docs.temporal.io/workflow-execution" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/event-queues-delivery-c2f047356ab0b24d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Workflow graphs and explicit state", "url": "https://semiaifoundry.com/learn/atlas/workflow-graphs-state/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "fd617b74efa53407faeb159b3a43b3077b371136e2df483460c0e77cfc5e0e79" }, { "id": "atlas-lesson-expert-routing-budget", "title": "MoE routing, active parameters and resident state", "category": "learning", "format": "Atlas lesson", "description": "Balances conditional expert computation against placement, communication and capacity.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/expert-routing-budget/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Routing policy and storage placement are model-specific. The toy traffic estimate does not describe any named production model or guarantee expert balance.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/expert-routing-budget-274a075fef73b09f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#expert-routing-budget", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "992f6380ef8f4137b5b196ce2481e454d4c582b1609e941305665f21626beaed", "contentLength": 5190, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-expert-routing-budget.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-expert-routing-budget.md", "sections": [ { "id": "section-1", "title": "MoE routing, active parameters and resident state" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Simple dispatch volume" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can an MoE model require large memory despite low active parameters per token?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#expert-routing-budget" }, { "title": "Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer", "url": "https://arxiv.org/abs/1701.06538" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/expert-routing-budget-274a075fef73b09f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Mixture of experts", "url": "https://semiaifoundry.com/learn/atlas/moe/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Autoregressive decode and weight traffic", "url": "https://semiaifoundry.com/learn/atlas/decode-bandwidth-trace/" } ], "recordHash": "89318ee4382191ce0ec6792c3b2c6845af863d50242479293ba92294ce01eae3" }, { "id": "atlas-lesson-fab-metrology-process-window", "title": "Metrology, inspection and process windows", "category": "learning", "format": "Atlas lesson", "description": "Measures geometry and defects at the stage where a manufacturing decision can still be made.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/fab-metrology-process-window/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Control, test and ramp", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Sampling rates and acceptance windows are product-specific. Simulated maps illustrate patterns and do not diagnose a real fab excursion.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/fab-metrology-process-window-f655aad3076601f0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#fab-metrology-process-window", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "93c84e9eb3b68df96a91caafc3564fa76336a2a8fc81c92aa07edd4ffe142e75", "contentLength": 5196, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fab-metrology-process-window.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fab-metrology-process-window.md", "sections": [ { "id": "section-1", "title": "Metrology, inspection and process windows" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Observed variance model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which comparison best tests whether an apparent tool shift is a metrology artifact?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#fab-metrology-process-window" }, { "title": "KLA — Chip Manufacturing 101", "url": "https://www.kla.com/wp-content/uploads/ChipManufacturing101.pdf" }, { "title": "KLA — Practical Applications of Measurement System Analysis", "url": "https://www.kla.com/documents/5.3_Practical_Applications_of_MSA_Sutherland_KLA.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/fab-metrology-process-window-f655aad3076601f0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Lithography and pattern transfer", "url": "https://semiaifoundry.com/learn/atlas/lithography/" }, { "title": "Chemical mechanical planarization", "url": "https://semiaifoundry.com/learn/atlas/cmp/" }, { "title": "Coat, bake, expose and develop", "url": "https://semiaifoundry.com/learn/atlas/resist-track-development/" }, { "title": "Plasma and wet etch: selectivity and profile", "url": "https://semiaifoundry.com/learn/atlas/plasma-wet-etch-transfer/" }, { "title": "Wafer maps and good-die yield", "url": "https://semiaifoundry.com/learn/atlas/yield-wafer-defect-model/" } ], "recordHash": "1b411f5b829757f60c64ec1386456e1a96066c20a18138fe80f77a5bf3a5cd56" }, { "id": "atlas-lesson-fab-ramp-cycle-time", "title": "Cycle time, ramp and effective capacity", "category": "learning", "format": "Atlas lesson", "description": "Connects tool throughput, queues, qualification and yield learning over time.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/fab-ramp-cycle-time/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Control, test and ramp", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Factory rates, costs, queues and ramp schedules are illustrative. Public capability pages do not provide a measured customer-level queue.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/fab-ramp-cycle-time-cfd2aa48bbf69749.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#fab-ramp-cycle-time", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "039f6a70e9f0c974b122466f67fdc5d5b30197af7ce85322fb550d76a6c599bf", "contentLength": 5091, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fab-ramp-cycle-time.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fab-ramp-cycle-time.md", "sections": [ { "id": "section-1", "title": "Cycle time, ramp and effective capacity" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Little’s law" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What happens if wafer starts rise while the final qualified bottleneck throughput stays fixed?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#fab-ramp-cycle-time" }, { "title": "TSMC — Intelligent Packaging Fab", "url": "https://www.tsmc.com/english/dedicatedFoundry/services/apm_intelligent_packaging_fab" }, { "title": "Edwards — Semiconductor vacuum and abatement", "url": "https://www.edwardsvacuum.com/en-us/semiconductor" }, { "title": "Advantest — Semiconductor test glossary", "url": "https://www.advantest.com/en/investors/ir-library/glossary/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/fab-ramp-cycle-time-cfd2aa48bbf69749.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "MES, dispatch and process release", "url": "https://semiaifoundry.com/learn/atlas/manufacturing-execution-dispatch/" }, { "title": "Wafer maps and good-die yield", "url": "https://semiaifoundry.com/learn/atlas/yield-wafer-defect-model/" }, { "title": "Cleanroom and subfab utilities", "url": "https://semiaifoundry.com/learn/atlas/cleanroom-subfab-utilities/" }, { "title": "HBM silicon intensity and allocation", "url": "https://semiaifoundry.com/learn/atlas/hbm-silicon-intensity/" } ], "recordHash": "56ba930fe2b345fa2c0de25b05501a4a0b44bb7f8012c4884fb203ff4e5a7318" }, { "id": "atlas-lesson-fabric-collective-traffic", "title": "Collective traffic and congestion", "category": "learning", "format": "Atlas lesson", "description": "Coordinates distributed tensor exchanges while accounting for topology and contention.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/fabric-collective-traffic/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Chip-to-hall integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a teaching algorithm, not a claim that NCCL always chooses a ring. Rank placement and software version belong with any measured result.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/fabric-collective-traffic-1028fa16b2d022a1.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#fabric-collective-traffic", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "64f409e81a26a1c840d807c550535a9962a97b4533ca55734c377fd46971182a", "contentLength": 4744, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fabric-collective-traffic.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fabric-collective-traffic.md", "sections": [ { "id": "section-1", "title": "Collective traffic and congestion" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Ideal ring all-reduce" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is 400 Gbit/s in raw decimal bytes/s?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#fabric-collective-traffic" }, { "title": "NCCL User Guide: Collective Operations", "url": "https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/collectives.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/fabric-collective-traffic-1028fa16b2d022a1.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Leaf switch and endpoint network", "url": "https://semiaifoundry.com/learn/atlas/leaf-switch/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Scale-up, scale-out and management fabrics", "url": "https://semiaifoundry.com/learn/atlas/scaleup-scaleout-boundaries/" } ], "recordHash": "855d029115d577e24d86ad37ed13e14cfb09223019d2097a1f5d94057f1f6f87" }, { "id": "atlas-lesson-facility-heat-rejection", "title": "Facility heat rejection and cooling tradeoffs", "category": "learning", "format": "Atlas lesson", "description": "Transfers collected heat to the outdoor environment under weather-dependent limits.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/facility-heat-rejection/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center physical systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "COP and water values are not manufacturer defaults. Local climate, equipment selection and accounting boundaries determine actual performance.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/facility-heat-rejection-41f650cbcecd4500.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#facility-heat-rejection", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "001a6b010fa9a6241ff4b8d084aeb8480f8e02192a93b570856dd3cf53346ec0", "contentLength": 4823, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-facility-heat-rejection.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-facility-heat-rejection.md", "sections": [ { "id": "section-1", "title": "Facility heat rejection and cooling tradeoffs" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Chiller performance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can cooling capacity vary with weather?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#facility-heat-rejection" }, { "title": "Cooling Water Efficiency Opportunities for Federal Data Centers", "url": "https://www.energy.gov/cmei/femp/cooling-water-efficiency-opportunities-federal-data-centers" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/facility-heat-rejection-41f650cbcecd4500.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Facility cooling and final heat rejection", "url": "https://semiaifoundry.com/learn/atlas/cooling-plant/" }, { "title": "Cold plates, manifolds and separated coolant loops", "url": "https://semiaifoundry.com/learn/atlas/coolant-loop-separation/" }, { "title": "Water withdrawal, consumption and cooling circulation", "url": "https://semiaifoundry.com/learn/atlas/water-boundary-accounting/" } ], "recordHash": "307733ae11d5aee1217df502abc2137ea88ed6118effb983242635fc9bd6e132" }, { "id": "atlas-lesson-feed-forward", "title": "Feed-forward network", "category": "learning", "format": "Atlas lesson", "description": "Transform features within each token position.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/feed-forward/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Transformer computation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This uses the bias-free three-matrix SwiGLU form in the cited GLU paper. It is not a universal feed-forward architecture; activation work and runtime memory are not included in the parameter-byte count.\n\nMode: executable nonlinear block. The scalar activation symbol h and hidden-width ledger are explicitly separated by context. Core uses tanh, not the original Transformer ReLU or a gated variant. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/feed-forward-c10ceb758cac6b13.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#feed-forward", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "424359c791ea7426b57a08e80fbc916e71d03e7c07f727d18dce3c3e3bb5755b", "contentLength": 8554, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-feed-forward.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-feed-forward.md", "sections": [ { "id": "section-1", "title": "Feed-forward network" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "SwiGLU and matrix cost" }, { "id": "section-5", "title": "Nonlinear features and block-level learning · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Are feed-forward weights normally unique to each token position?" }, { "id": "section-12", "title": "Why does the derivative shrink near h=0.99?" }, { "id": "section-13", "title": "Historical context" }, { "id": "section-14", "title": "2020 · GLU variants improve Transformer feed-forward blocks" }, { "id": "section-15", "title": "Evidence and scope" }, { "id": "section-16", "title": "Sources" }, { "id": "section-17", "title": "Continue exploring" }, { "id": "section-18", "title": "Foundations" }, { "id": "section-19", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#feed-forward" }, { "title": "Shazeer — GLU Variants Improve Transformer", "url": "https://arxiv.org/abs/2002.05202" }, { "title": "Attention Is All You Need", "url": "https://arxiv.org/html/1706.03762v7" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/feed-forward-c10ceb758cac6b13.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Residual stream & normalization", "url": "https://semiaifoundry.com/learn/atlas/residual-normalization/" }, { "title": "Mixture of experts", "url": "https://semiaifoundry.com/learn/atlas/moe/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "A differentiable computation graph", "url": "https://semiaifoundry.com/learn/atlas/reverse-mode-autodiff/" }, { "title": "Assemble an initialized causal language model", "url": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/" } ], "recordHash": "9d709e34c9b93abc99cd23457deb17944c0d4dc59f063a30ac67dc8f78907d03" }, { "id": "atlas-lesson-fin-formation-integration", "title": "How a FinFET fin is formed and integrated", "category": "learning", "format": "Atlas lesson", "description": "Turns a three-dimensional silicon ridge into a controlled transistor channel.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/fin-formation-integration/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / FEOL and MOL", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Sequence is representative. Fin counts, dimensions and material recipes are illustrative, with no claim about a particular production node.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/fin-formation-integration-9fa2751fa526e028.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#fin-formation-integration", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "072773d70f3d88264c7c9383ddb8d8f4ffad898309063838da39f52a3a1eba59", "contentLength": 5266, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fin-formation-integration.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fin-formation-integration.md", "sections": [ { "id": "section-1", "title": "How a FinFET fin is formed and integrated" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Geometric effective-width estimate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does fin-height variation matter even if the top-view linewidth is correct?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#fin-formation-integration" }, { "title": "Applied Materials — New Ways to Shrink", "url": "https://ir.appliedmaterials.com/static-files/f2fbf48d-a761-4c4f-ab4c-73f312ab1ebc" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "Intel — Reinvents Transistors Using New 3-D Structure", "url": "https://www.intc.com/news-events/press-releases/detail/655/intel-reinvents-transistors-using-new-3-d-structure" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/fin-formation-integration-9fa2751fa526e028.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Fin field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/finfet/" }, { "title": "Plasma and wet etch: selectivity and profile", "url": "https://semiaifoundry.com/learn/atlas/plasma-wet-etch-transfer/" }, { "title": "Wells and shallow trench isolation", "url": "https://semiaifoundry.com/learn/atlas/wells-isolation-integration/" }, { "title": "Source/drain, spacers, contacts and MOL", "url": "https://semiaifoundry.com/learn/atlas/source-drain-contact-integration/" } ], "recordHash": "600171def751f5e35f51b2d87945ebb2eb0801cb5ef9c61218104dba055abba2" }, { "id": "atlas-lesson-finfet", "title": "Fin field-effect transistor", "category": "learning", "format": "Atlas lesson", "description": "Raises the channel into a fin so the gate controls multiple surfaces.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/finfet/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Device architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The expression omits fin corners, mobility variation, parasitic resistance and layout rules.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/finfet-bc5fd21dcd81b635.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#finfet", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c6e3954d0d5243ce237a11008b94970542983ffd587bd4c8fd598f0f36907fe1", "contentLength": 5243, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-finfet.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-finfet.md", "sections": [ { "id": "section-1", "title": "Fin field-effect transistor" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Effective gated width" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the fin mainly improve?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2011 · Intel announces 3D Tri-Gate for the 22 nm generation" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#finfet" }, { "title": "Intel — Three-Dimensional Tri-Gate Announcement", "url": "https://www.intc.com/news-events/press-releases/detail/655/intel-reinvents-transistors-using-new-3-d-structure" }, { "title": "Intel — Process Technology Naming", "url": "https://www.intel.com/content/www/us/en/support/articles/000097598/processors.html" }, { "title": "Original Device Study — Effective Fin Width and FinFET Geometry", "url": "https://www.mdpi.com/2079-9292/11/1/91" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/finfet-bc5fd21dcd81b635.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "Controllable semiconductor channel", "url": "https://semiaifoundry.com/learn/atlas/channel/" }, { "title": "Gate-all-around nanosheet transistor", "url": "https://semiaifoundry.com/learn/atlas/gaa/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" } ], "recordHash": "e951c7631a276737ee44275eabc2c6c631f0d78ae9b3f06909423a2939d1e86b" }, { "id": "atlas-lesson-firmware-device-contract", "title": "Firmware handoff and device readiness", "category": "learning", "format": "Atlas lesson", "description": "Separate device compatibility, driver discovery, resource ownership and queue readiness before any operand is consumed.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/firmware-device-contract/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Primary sources establish the cited runtime mechanisms. Numerical values, address ranges, ABI strings, event schedule and reset/retry epochs are authored teaching contracts. No real device, firmware image, operating-system driver, page table, cache protocol or security verification is executed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/firmware-device-contract-af99231c7ca5e469.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#firmware-device-contract", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1aecc713a863e4b859b3f2a0dec96f19a3b1e9cb2d477f013f75419f9c1d3c81", "contentLength": 6332, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-firmware-device-contract.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-firmware-device-contract.md", "sections": [ { "id": "section-1", "title": "Firmware handoff and device readiness" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "The declared ABI gate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "An ABI mismatch leaves host buffers populated. Has the device computed their matrix product?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#firmware-device-contract" }, { "title": "Linux 6.16 — How To Write Linux PCI Drivers", "url": "https://docs.kernel.org/6.16/PCI/pci.html" }, { "title": "OASIS — Virtual I/O Device (VIRTIO) Version 1.3", "url": "https://docs.oasis-open.org/virtio/virtio/v1.3/virtio-v1.3.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/firmware-device-contract-af99231c7ca5e469.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" }, { "title": "Baseboard management controller", "url": "https://semiaifoundry.com/learn/atlas/management-controller/" }, { "title": "Process, physical and device address spaces", "url": "https://semiaifoundry.com/learn/atlas/process-dma-address-spaces/" }, { "title": "Commissioning a usable AI cluster", "url": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/" }, { "title": "Tapeout, bring-up and productization", "url": "https://semiaifoundry.com/learn/atlas/chip-tapeout-productization/" } ], "recordHash": "013f638e7a7152ea1f60b10f742a0cd3f610f638b02f7df7788d055f4bfffd7f" }, { "id": "atlas-lesson-flip-chip-abf-substrate", "title": "Flip-chip assembly and organic substrates", "category": "learning", "format": "Atlas lesson", "description": "Connects face-down dies to a multilayer package substrate with a board-facing interface.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/flip-chip-abf-substrate/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Materials and assembly", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Assembly order is representative. Product-specific pad pitch, substrate stack-up, underfill and qualification limits remain undisclosed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/flip-chip-abf-substrate-47ebe618c90dacb3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#flip-chip-abf-substrate", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a7c9282acdfd3e23cb49939307fd22f6b9060f5c303e7f00f041eb221189bf27", "contentLength": 5048, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-flip-chip-abf-substrate.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-flip-chip-abf-substrate.md", "sections": [ { "id": "section-1", "title": "Flip-chip assembly and organic substrates" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Routing resource estimate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What role does the ABF material play inside a build-up substrate?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#flip-chip-abf-substrate" }, { "title": "Amkor — Flip Chip Packaging", "url": "https://amkor.com/technology/flip-chip/" }, { "title": "Ajinomoto — ABF materials business announcement", "url": "https://www.ajinomoto.co.jp/company/en/presscenter/press/detail/g2016_04_13.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/flip-chip-abf-substrate-47ebe618c90dacb3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" }, { "title": "Microbumps and bonding joints", "url": "https://semiaifoundry.com/learn/atlas/microbump/" }, { "title": "Microbumps, reflow and thermocompression", "url": "https://semiaifoundry.com/learn/atlas/bump-thermocompression-assembly/" }, { "title": "Underfill, warpage, thermal paths and qualification", "url": "https://semiaifoundry.com/learn/atlas/package-thermomechanical-reliability/" } ], "recordHash": "7b596cca60bf05fcec40f7f9d60d3da28890c2f7f552a419de545e97d6f55948" }, { "id": "atlas-lesson-flipflop", "title": "Edge-triggered D flip-flop", "category": "learning", "format": "Atlas lesson", "description": "Captures a bit at a clock event and retains it for the next computation stage.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/flipflop/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Digital circuits", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The timing budget follows the linked sequential-logic lecture. These are synthetic maximum-delay values for one synchronous path; clock skew, hold timing, variation and path exceptions need separate checks.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/flipflop-1f4567fc2c8b67fd.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#flipflop", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "6857fa7de72abea78ac96fc0ce9b00671cc5688a264ea84a5408e5181fd1555b", "contentLength": 5010, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-flipflop.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-flipflop.md", "sections": [ { "id": "section-1", "title": "Edge-triggered D flip-flop" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Setup-constrained clock period" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What distinguishes a flip-flop from combinational logic?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#flipflop" }, { "title": "MIT 6.111 — Sequential Logic and System Timing", "url": "https://ocw.mit.edu/courses/6-111-introductory-digital-systems-laboratory-spring-2006/31134a27ec1bedf570a26922790dfbec_lec11.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/flipflop-1f4567fc2c8b67fd.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Complementary CMOS inverter", "url": "https://semiaifoundry.com/learn/atlas/inverter/" }, { "title": "Two-input CMOS NAND gate", "url": "https://semiaifoundry.com/learn/atlas/nand/" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "Full adder and carry network", "url": "https://semiaifoundry.com/learn/atlas/adder/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" } ], "recordHash": "12e1db834a327f09753a89241c8ead6c6c7fc6f9805ab0fff8e91fdc13910a2c" }, { "id": "atlas-lesson-floating-number-range-resolution", "title": "Floating-point range, resolution and rounding", "category": "learning", "format": "Atlas lesson", "description": "Explains which numerical values a finite bit pattern can represent before those values enter a learned computation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/floating-number-range-resolution/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "mathematical-foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. This authored seven-bit format uses bias 3, gradual underflow and nearest ties-to-even. Exponent 7 is special and excluded from the finite expression.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/floating-number-range-resolution-e821f16b66f0d28a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#floating-number-range-resolution", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "34849c4ecffc8951796c53ae502ac7593244d352d70883c0e1d175fb14e4858d", "contentLength": 5980, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-floating-number-range-resolution.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-floating-number-range-resolution.md", "sections": [ { "id": "section-1", "title": "Floating-point range, resolution and rounding" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Floating-point range, resolution and rounding" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What primarily changes when fraction bits are increased at fixed exponent width?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#floating-number-range-resolution" }, { "title": "Goodfellow, Bengio and Courville · Numerical computation", "url": "https://www.deeplearningbook.org/contents/numerical.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/floating-number-range-resolution-e821f16b66f0d28a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" }, { "title": "Floating-point reductions and compiler permissions", "url": "https://semiaifoundry.com/learn/atlas/floating-point-reduction-order/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" } ], "recordHash": "f59782ae404311dd591d07782e429a2d1524a03d36b56a1eff7367432752834f" }, { "id": "atlas-lesson-floating-point-reduction-order", "title": "Floating-point reductions and compiler permissions", "category": "learning", "format": "Atlas lesson", "description": "Distinguish algebraic equivalence, numerical error and bitwise reproducibility when compilation or collectives regroup arithmetic.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/floating-point-reduction-order/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The NVIDIA guide supports finite-precision nonassociativity, and LLVM specifies the cited optimization permissions. The exact operands, intermediate values and 0.01 tolerance are authored. Tests use binary32 conversions locally and do not constitute a GPU, compiler or multi-rank experiment.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/floating-point-reduction-order-b8b43418bbe78f69.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#floating-point-reduction-order", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "fa34872623b3da0576a25593def8a324e7d8f106846277f70fb017fe2ab33514", "contentLength": 8775, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-floating-point-reduction-order.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-floating-point-reduction-order.md", "sections": [ { "id": "section-1", "title": "Floating-point reductions and compiler permissions" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Rounding makes grouping observable" }, { "id": "section-5", "title": "Spacing at the chosen magnitude" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "With binary32 ties-to-even rounding, what is fl(fl(2²⁴+1)−2²⁴)?" }, { "id": "section-12", "title": "Why does grouping 2²⁴+(1−2²⁴) instead give 1?" }, { "id": "section-13", "title": "Which evidence shows a result is accurate relative to a stated reference?" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#floating-point-reduction-order" }, { "title": "NVIDIA CUDA 13.1.1 — Floating-Point Computation", "url": "https://docs.nvidia.com/cuda/archive/13.1.1/cuda-programming-guide/05-appendices/mathematical-functions.html" }, { "title": "LLVM — Language Reference, fast-math rewrite flags", "url": "https://llvm.org/docs/LangRef.html#fast-math-flags" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/floating-point-reduction-order-b8b43418bbe78f69.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" }, { "title": "Compiler layout, lowering and buffer planning", "url": "https://semiaifoundry.com/learn/atlas/compiler-layout-lowering/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Sharded matrix multiplication and result ownership", "url": "https://semiaifoundry.com/learn/atlas/sharded-matmul-ownership/" }, { "title": "Uneven batches and the global gradient", "url": "https://semiaifoundry.com/learn/atlas/distributed-gradient-weighting/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Systolic arrays and tensor dataflow", "url": "https://semiaifoundry.com/learn/atlas/systolic-array-dataflow/" } ], "recordHash": "86f6526b5e6b4f533a5f3be9c45c920549eadd2ac7ba48d689fc599d086b2d67" }, { "id": "atlas-lesson-fpga-dsp-pipelines", "title": "FPGA fabrics, DSP blocks and adaptive pipelines", "category": "learning", "format": "Atlas lesson", "description": "Configures a spatial datapath around a stream and its timing constraints.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/fpga-dsp-pipelines/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "These are illustrative timing values. The Versal source establishes subsystem roles, not a guaranteed result for an arbitrary FPGA implementation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/fpga-dsp-pipelines-1c4e3679843062c5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#fpga-dsp-pipelines", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "921c82b6e2e3052e11a384e752ea69e263f778a82aaf3978553698eee08900cb", "contentLength": 4993, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fpga-dsp-pipelines.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-fpga-dsp-pipelines.md", "sections": [ { "id": "section-1", "title": "FPGA fabrics, DSP blocks and adaptive pipelines" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Pipeline throughput" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A pipeline has 20-cycle latency and initiation interval 1. What can it do after filling?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#fpga-dsp-pipelines" }, { "title": "Versal adaptive SoC overview, Vitis Tutorials 2025.2", "url": "https://docs.amd.com/r/2025.2-English/Vitis-Tutorials-AI-Engine-Development/Versal-adaptive-SoC-overview?contentId=mgKv1D7qaapgh~kdwNF3xA" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/fpga-dsp-pipelines-1c4e3679843062c5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "PDKs, synthesis and physical closure", "url": "https://semiaifoundry.com/learn/atlas/chip-physical-closure/" } ], "recordHash": "6ce44a45903c179e571beba63471a732bf2e789f8fb2ead37e5768b75d4a7078" }, { "id": "atlas-lesson-gaa", "title": "Gate-all-around nanosheet transistor", "category": "learning", "format": "Atlas lesson", "description": "Surrounds thin semiconductor sheets with a gate for stronger channel control.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/gaa/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Device architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Nanosheet dimensions and route are representative; product-specific geometry is not inferred.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/gaa-000ab4f62410b2a0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#gaa", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "588b93b3f6ddc8928d88c14f363b5abc05050aa6d84d0770677dfd80b5b2a3ee", "contentLength": 4907, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gaa.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gaa.md", "sections": [ { "id": "section-1", "title": "Gate-all-around nanosheet transistor" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Nanosheet gated perimeter" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is shared by the sheets in the illustrated nanosheet device?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#gaa" }, { "title": "Intel Foundry — Advanced Process Technologies for Data Center", "url": "https://www.intel.com/content/www/us/en/foundry/library/advanced-process-technologies-for-data-center.html" }, { "title": "Intel — Process Technology Naming", "url": "https://www.intel.com/content/www/us/en/support/articles/000097598/processors.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/gaa-000ab4f62410b2a0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Fin field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/finfet/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "Gate sidewall and inner spacers", "url": "https://semiaifoundry.com/learn/atlas/spacer/" }, { "title": "Source and drain regions", "url": "https://semiaifoundry.com/learn/atlas/source-drain/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" } ], "recordHash": "7c68b7f3980b58ae6df03c12574891365ea119f170f09f711748e17e4f72d7ed" }, { "id": "atlas-lesson-gate-stack", "title": "Metal gate and high-k dielectric", "category": "learning", "format": "Atlas lesson", "description": "Couples a control voltage into the channel while suppressing gate leakage.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/gate-stack/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Device physics", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "EOT is an electrostatic comparison, not a complete physical thickness specification.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/gate-stack-70bfec722beb409b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#gate-stack", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b86690ac90aa7d5e0b11721a338496c656069b22de85086858acd36a47d1ebe2", "contentLength": 5524, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gate-stack.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gate-stack.md", "sections": [ { "id": "section-1", "title": "Metal gate and high-k dielectric" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Capacitance and equivalent oxide thickness" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a high-k gate dielectric help?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2007 · High-k and metal gates enter Intel’s 45 nm generation" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#gate-stack" }, { "title": "Intel — High-k and Metal Gate Research", "url": "https://www.intel.com/pressroom/kits/advancedtech/doodle/ref_HiK-MG/high-k.htm" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/gate-stack-70bfec722beb409b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Insulators and low-k films", "url": "https://semiaifoundry.com/learn/atlas/dielectric/" }, { "title": "Controllable semiconductor channel", "url": "https://semiaifoundry.com/learn/atlas/channel/" }, { "title": "Gate-all-around nanosheet transistor", "url": "https://semiaifoundry.com/learn/atlas/gaa/" }, { "title": "Lithography and pattern transfer", "url": "https://semiaifoundry.com/learn/atlas/lithography/" } ], "recordHash": "2abf8ea02c40c7f9af21670fabf7d54fa869836ef4d2d695cde564078fa99d1c" }, { "id": "atlas-lesson-gpu-chiplet-locality", "title": "GPU chiplets and memory locality", "category": "learning", "format": "Atlas lesson", "description": "Partitions compute and I/O physically while presenting a programmable accelerator.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/gpu-chiplet-locality/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The MI300 family is a disclosed historical specimen. Public topology is sufficient for the mechanism; undocumented routing policy and measured locality penalties remain unknown.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/gpu-chiplet-locality-19bb68acbe4aa11e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#gpu-chiplet-locality", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ffeff3431aaf3ebc4dd76695b1e71f348e00d4dacd35d226c7cd25e1abe25afa", "contentLength": 4816, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gpu-chiplet-locality.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gpu-chiplet-locality.md", "sections": [ { "id": "section-1", "title": "GPU chiplets and memory locality" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Cut bandwidth bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can two kernels with equal HBM traffic differ on a chiplet accelerator?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#gpu-chiplet-locality" }, { "title": "AMD Instinct MI300 Series microarchitecture", "url": "https://rocm.docs.amd.com/en/latest/reference/gpu-arch/mi300.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/gpu-chiplet-locality-19bb68acbe4aa11e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" }, { "title": "Custom-chip volume economics", "url": "https://semiaifoundry.com/learn/atlas/chip-volume-economics/" } ], "recordHash": "dc358463feffe13969d4777d09aed9d212fd81904424b36d9fa67d6b50d90962" }, { "id": "atlas-lesson-gpu-die", "title": "GPU logic dies", "category": "learning", "format": "Atlas lesson", "description": "Integrate transistor circuits into the compute, storage, and communication structures of one accelerator.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/gpu-die/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Advanced packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The model does not disclose or infer a specific GPU rail or Astra design.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/gpu-die-3a870139842fc285.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#gpu-die", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "8da65a7c002f98cc25f5c02495e06f08ecee5644259a83812dca5b87b3e43d1b", "contentLength": 6395, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gpu-die.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gpu-die.md", "sections": [ { "id": "section-1", "title": "GPU logic dies" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Switching activity becomes heat" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why use two large logic dies within one GPU?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2024 · Blackwell extends acceleration from multiple dies to rack-scale systems" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#gpu-die" }, { "title": "NVIDIA: Blackwell platform announcement", "url": "https://nvidianews.nvidia.com/news/nvidia-blackwell-platform-arrives-to-power-a-new-era-of-computing" }, { "title": "Texas Instruments: CMOS dynamic power", "url": "https://www.ti.com/lit/pdf/sprac07" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/gpu-die-3a870139842fc285.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Interposer and redistribution layers", "url": "https://semiaifoundry.com/learn/atlas/interposer/" }, { "title": "Thermal interface material", "url": "https://semiaifoundry.com/learn/atlas/thermal-interface/" }, { "title": "Grace Blackwell Superchip", "url": "https://semiaifoundry.com/learn/atlas/grace-blackwell-superchip/" } ], "recordHash": "86a0ccfab986fc594ac0fa9339ed114c54d17ab2a07500563628c41087a233d4" }, { "id": "atlas-lesson-gpu-occupancy-pipeline", "title": "Occupancy and asynchronous tile pipelines", "category": "learning", "format": "Atlas lesson", "description": "Keeps work ready while controlling registers, scratchpad capacity and synchronization.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/gpu-occupancy-pipeline/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "TMA is a Hopper-specific example, while double buffering is a general method. No timing in this lesson is a vendor measurement.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/gpu-occupancy-pipeline-76c0164cdd2b626d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#gpu-occupancy-pipeline", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ffede65530c7db0dca9e6df93fa09c0995e306201b993cb25b1c3c8bafd59dc3", "contentLength": 4730, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gpu-occupancy-pipeline.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-gpu-occupancy-pipeline.md", "sections": [ { "id": "section-1", "title": "Occupancy and asynchronous tile pipelines" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Overlapped tile lower bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A larger tile lowers occupancy but reduces HBM reads. Which conclusion follows?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#gpu-occupancy-pipeline" }, { "title": "NVIDIA Hopper Tuning Guide", "url": "https://docs.nvidia.com/cuda/hopper-tuning-guide/index.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/gpu-occupancy-pipeline-76c0164cdd2b626d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" }, { "title": "Tensor Memory Accelerator", "url": "https://semiaifoundry.com/learn/atlas/tensor-memory-accelerator/" }, { "title": "Kernel tiling, fusion and operand reuse", "url": "https://semiaifoundry.com/learn/atlas/kernel-locality-fusion/" } ], "recordHash": "ca963c16c2497fddf2552a8b136c14ca78b1f0ba5a51723c14f04788a7f82ed5" }, { "id": "atlas-lesson-grace-blackwell-superchip", "title": "Grace Blackwell Superchip", "category": "learning", "format": "Atlas lesson", "description": "Couples one Grace CPU with two Blackwell GPUs so host and accelerator work can share a tightly integrated system.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/grace-blackwell-superchip/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "System integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The linked module sources establish CPU, GPU and memory boundaries. The calculation assumes serial phases and fixed precision; overlap, coherent accesses, caches and contention require a different execution model.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/grace-blackwell-superchip-b1d3ce602c66d4d5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#grace-blackwell-superchip", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "5103b8db892d24f9e0c937627542f41065db3fafd9b287aead8a6c1fe663eed4", "contentLength": 7596, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-grace-blackwell-superchip.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-grace-blackwell-superchip.md", "sections": [ { "id": "section-1", "title": "Grace Blackwell Superchip" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Offload is useful only when saved compute exceeds movement cost" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which description correctly separates the nested links?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2024 · Blackwell extends acceleration from multiple dies to rack-scale systems" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#grace-blackwell-superchip" }, { "title": "NVIDIA: Blackwell platform announcement", "url": "https://nvidianews.nvidia.com/news/nvidia-blackwell-platform-arrives-to-power-a-new-era-of-computing" }, { "title": "NVIDIA GB200 NVL72 specifications", "url": "https://www.nvidia.com/en-us/data-center/gb200-nvl72/" }, { "title": "NVIDIA: Inside Grace CPU architecture", "url": "https://developer.nvidia.com/blog/inside-nvidia-grace-cpu-nvidia-amps-up-superchip-engineering-for-hpc-and-ai/" }, { "title": "NVIDIA CUDA Programming Guide: asynchronous data copies", "url": "https://docs.nvidia.com/cuda/cuda-programming-guide/04-special-topics/async-copies.html" }, { "title": "Intel Advisor: Amdahl’s Law and measurement", "url": "https://www.intel.com/content/www/us/en/docs/advisor/user-guide/2024-2/use-amdahl-law.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/grace-blackwell-superchip-b1d3ce602c66d4d5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "Grace LPDDR5X memory", "url": "https://semiaifoundry.com/learn/atlas/lpddr-memory/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "NVLink GPU interface", "url": "https://semiaifoundry.com/learn/atlas/nvlink-port/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" } ], "recordHash": "9883777314cc581cd470e5f2e6707e7801d06f0f275cdaacf0f7dacbc0e100f7" }, { "id": "atlas-lesson-graph-message-passing", "title": "Graph message passing and node identity", "category": "learning", "format": "Atlas lesson", "description": "Shows how a model can operate on relationships between entities instead of a simple token sequence.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/graph-message-passing/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "contrasting-ai-methods", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. Four-node undirected graph, self-loops, identity learned-weight placeholder and nonnegative input features. No parameter training or arbitrary graph benchmark is performed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/graph-message-passing-49aa43780ba39b7c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#graph-message-passing", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ff99f688ffeb28ef7976ae4afe1718f355869e7c62fc9c23c9261a2224ee5b14", "contentLength": 6221, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-graph-message-passing.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-graph-message-passing.md", "sections": [ { "id": "section-1", "title": "Graph message passing and node identity" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Graph message passing and node identity" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which operation should preserve the represented forward result?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#graph-message-passing" }, { "title": "Kipf and Welling · Graph convolutional networks", "url": "https://arxiv.org/abs/1609.02907" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/graph-message-passing-49aa43780ba39b7c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tensor shapes, indices and contractions", "url": "https://semiaifoundry.com/learn/atlas/tensor-index-contracts/" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" } ], "recordHash": "ea1d3549707209998fa47d48b57f91f1d75270fbef4ff4371bb4bbf503c42a63" }, { "id": "atlas-lesson-graph-tensor-ir", "title": "Model graph and tensor intermediate representation", "category": "learning", "format": "Atlas lesson", "description": "Preserves operation semantics before committing to a device instruction schedule.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/graph-tensor-ir/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "StableHLO is a named reference path. Other stacks have different capture rules and IRs; portability of meaning does not imply identical performance or binary compatibility.\n\nThe arithmetic is an authored exact example. It does not claim that a real compiler performs this invalid transformation or that a new compiler implementation has been executed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/graph-tensor-ir-b779fe8d511d9df4.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#graph-tensor-ir", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "5f43c7b03e5b35e98c0b589be2c360015a436199f3d4114e779e9aed605f3697", "contentLength": 6508, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-graph-tensor-ir.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-graph-tensor-ir.md", "sections": [ { "id": "section-1", "title": "Model graph and tensor intermediate representation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Logical tensor size" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a tensor type of shape 4×8 establish by itself?" }, { "id": "section-11", "title": "Can operations be reordered merely because their intermediate shapes match?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#graph-tensor-ir" }, { "title": "StableHLO specification", "url": "https://openxla.org/stablehlo/spec" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/graph-tensor-ir-b779fe8d511d9df4.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "Compiler layout, lowering and buffer planning", "url": "https://semiaifoundry.com/learn/atlas/compiler-layout-lowering/" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "A code patch needs execution evidence", "url": "https://semiaifoundry.com/learn/atlas/coding-agent-patch-evidence/" } ], "recordHash": "0aa4e5c028de4f4b443822317120494d1cb24cd03b88afb30d64eb8ec416fe03" }, { "id": "atlas-lesson-grid-interconnection-readiness", "title": "Grid interconnection and deliverable electrical capacity", "category": "learning", "format": "Atlas lesson", "description": "Connects facility demand to location-specific network, equipment and operating readiness.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/grid-interconnection-readiness/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center physical systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "PJM is one regional example, not global interconnection law. The source’s inconsistent winter headline is excluded; no unverified local queue position is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/grid-interconnection-readiness-e44533ceda8a91e6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#grid-interconnection-readiness", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1b5fe69786916234325c609dd9a58efe59dbde14e05fe4ab3aff164cf940b9ab", "contentLength": 5172, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-grid-interconnection-readiness.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-grid-interconnection-readiness.md", "sections": [ { "id": "section-1", "title": "Grid interconnection and deliverable electrical capacity" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Backup duration" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A battery can deliver 20 MWh of usable energy at the load-side boundary while supplying a constant 10 MW. What is its ideal duration?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#grid-interconnection-readiness" }, { "title": "PJM’s Updated 20-Year Forecast Continues To See Significant Long-Term Load Growth", "url": "https://insidelines.pjm.com/pjms-updated-20-year-forecast-continues-to-see-significant-long-term-load-growth/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/grid-interconnection-readiness-e44533ceda8a91e6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Uninterruptible power supply and backup chain", "url": "https://semiaifoundry.com/learn/atlas/ups/" }, { "title": "Power supply and power shelf", "url": "https://semiaifoundry.com/learn/atlas/power-supply/" }, { "title": "Commissioning a usable AI cluster", "url": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/" } ], "recordHash": "209c73e3a30423a1808ee32a00c24d2185074cfed3fc6e25dd3607f7611439c4" }, { "id": "atlas-lesson-hbf-latency-prefetch", "title": "HBF latency, transfer granularity and prefetch", "category": "learning", "format": "Atlas lesson", "description": "Explain why matching read bandwidth does not guarantee matching request latency or useful-byte efficiency.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbf-latency-prefetch/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The Sandisk fact sheet’s comparison concerns internal testing/simulation of reading 8-bit pretrained Llama 3.1 405B weights, one kernel at a time on an xPU performance model. It does not establish arbitrary random reads, training writes or end-to-end serving parity. KIOXIA supports general NAND access distinctions, not HBF timing numbers.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbf-latency-prefetch-ecddf51874cb7752.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbf-latency-prefetch", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ce59a24a9c07c12b22c7f4c7a585f69adf0106beda7d4c67573fe1781e75c0bd", "contentLength": 6007, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbf-latency-prefetch.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbf-latency-prefetch.md", "sections": [ { "id": "section-1", "title": "HBF latency, transfer granularity and prefetch" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Useful-byte efficiency" }, { "id": "section-5", "title": "Concurrency to cover latency" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "A request fetches 16 KiB but consumes 1 KiB with no reuse. What fraction is immediately useful?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbf-latency-prefetch" }, { "title": "Sandisk — HBF fact sheet", "url": "https://documents.sandisk.com/content/dam/asset-library/en_us/assets/public/sandisk/collateral/company/Sandisk-HBF-Fact-Sheet.pdf" }, { "title": "KIOXIA — NAND erase operations and latency", "url": "https://www.kioxia.com/en-jp/rd/technology/topics/topics-51.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbf-latency-prefetch-ecddf51874cb7752.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "HBF: a read-oriented tier and its evidence boundary", "url": "https://semiaifoundry.com/learn/atlas/hbf-read-tier-contract/" }, { "title": "Full memory hierarchy and input path", "url": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/" }, { "title": "MoE experts: resident capacity, routing and misses", "url": "https://semiaifoundry.com/learn/atlas/moe-expert-tier-placement/" }, { "title": "Prefill, decode and the moving KV working set", "url": "https://semiaifoundry.com/learn/atlas/prefill-decode-tier-placement/" }, { "title": "Kernel tiling, fusion and operand reuse", "url": "https://semiaifoundry.com/learn/atlas/kernel-locality-fusion/" } ], "recordHash": "96897ed269c8f8e99949581b91c2de5128045eb0d3dd43fbcd32e369b76966d8" }, { "id": "atlas-lesson-hbf-read-tier-contract", "title": "HBF: a read-oriented tier and its evidence boundary", "category": "learning", "format": "Atlas lesson", "description": "Distinguish an announced HBF interface/capacity specification from validated workload behavior.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbf-read-tier-contract/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "SK hynix and Sandisk identify the August 2026 milestone as specification release. The atlas has not verified a volume-shipping deployment from these announcements. Missing access metrics remain unknown rather than receiving SSD or HBM defaults.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbf-read-tier-contract-e7512c9ff78d70e4.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbf-read-tier-contract", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "30763644c0d826277b1a85d79e4dde3395ad861d565aa2ffb44358578e3c55c8", "contentLength": 5618, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbf-read-tier-contract.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbf-read-tier-contract.md", "sections": [ { "id": "section-1", "title": "HBF: a read-oriented tier and its evidence boundary" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Minimum bulk-read transfer time" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the announced HBF bandwidth range establish?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbf-read-tier-contract" }, { "title": "SK hynix — first HBF specifications at FMS 2026", "url": "https://news.skhynix.com/en/hbf-at-fms-2026/" }, { "title": "Sandisk — release of first OCP HBF specification", "url": "https://investor.sandisk.com/node/8126/pdf" }, { "title": "UCIe — introduction Q&A recap", "url": "https://www.uciexpress.org/post/introduction-to-ucie-webinar-q-a-recap" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbf-read-tier-contract-e7512c9ff78d70e4.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Choosing SRAM, HBM, DDR, LPDDR or GDDR", "url": "https://semiaifoundry.com/learn/atlas/memory-interface-choice/" }, { "title": "Die-to-die links and UCIe compatibility", "url": "https://semiaifoundry.com/learn/atlas/die-link-compatibility/" }, { "title": "HBF latency, transfer granularity and prefetch", "url": "https://semiaifoundry.com/learn/atlas/hbf-latency-prefetch/" }, { "title": "Place the working set, not just the model", "url": "https://semiaifoundry.com/learn/atlas/memory-working-set-placement/" }, { "title": "Qualify the memory system and retain useful work", "url": "https://semiaifoundry.com/learn/atlas/memory-system-qualification/" } ], "recordHash": "20961a6bfb9efcc531ce80cf5dae7cab160436259a1ab5ebb493ed55e9a36058" }, { "id": "atlas-lesson-hbm-base-phy-controller", "title": "Base die, PHY and memory controller", "category": "learning", "format": "Atlas lesson", "description": "Separates memory-stack logic from host scheduling and the electrical interface.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-base-phy-controller/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory / HBM system constraints", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The 2024 SK hynix–TSMC announcement describes a planned HBM4 base-die direction, not proof of its current production status. PHY-specific limits are not generalized to all HBM.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-base-phy-controller-50b2399bab56a4d7.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-base-phy-controller", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4464e0bf3d3be2ede295e2c0b2eb1f90b2ede76c3453e7d78eb97633bc680469", "contentLength": 5444, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-base-phy-controller.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-base-phy-controller.md", "sections": [ { "id": "section-1", "title": "Base die, PHY and memory controller" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Interface timing budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which block principally chooses when queued host memory requests become DRAM commands?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-base-phy-controller" }, { "title": "SK hynix — TSMC collaboration on HBM", "url": "https://news.skhynix.com/en/sk-hynix-partners-with-tsmc-to-strengthen-hbm-technological-leadership/" }, { "title": "Synopsys — HBM3 Controller IP", "url": "https://www.synopsys.com/designware-ip/interface-ip/hbm/hbm3-controller.html" }, { "title": "Synopsys — HBM4 PHY IP datasheet", "url": "https://www.synopsys.com/content/dam/synopsys/resources/dw/hbm4-phy-datasheet.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-base-phy-controller-50b2399bab56a4d7.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "HBM controller and PHY", "url": "https://semiaifoundry.com/learn/atlas/hbm-controller/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" }, { "title": "DRAM cells, arrays and peripheral circuits", "url": "https://semiaifoundry.com/learn/atlas/dram-cell-array-fabrication/" }, { "title": "HBM generations, channels, refresh and ECC", "url": "https://semiaifoundry.com/learn/atlas/hbm-channel-generation-ras/" }, { "title": "CoWoS-S and the silicon interposer route", "url": "https://semiaifoundry.com/learn/atlas/cowos-s-silicon-interposer/" } ], "recordHash": "b4626353419de2d8d0dad95ecb9f37c854e5efec5a912f6e8fd380c53c3a58bb" }, { "id": "atlas-lesson-hbm-bonding-process-selection", "title": "Selecting a bonding route under constraints", "category": "learning", "format": "Atlas lesson", "description": "Compare qualified output, height, thermal behavior, inspection and cost on the same product boundary.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-bonding-process-selection/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Route mechanisms are grounded in their named sources. Cost, cycle time and yield values in the workbench are transparent teaching scenarios, not supplier disclosures.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-bonding-process-selection-35150926514801ce.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-bonding-process-selection", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c0158c018cc04bbe27282ea0d51716ad1d6321fe791ecda2c0da5484289ec058", "contentLength": 5590, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-bonding-process-selection.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-bonding-process-selection.md", "sections": [ { "id": "section-1", "title": "Selecting a bonding route under constraints" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Cost per accepted stack" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which comparison supports an engineering choice?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-bonding-process-selection" }, { "title": "Samsung — 36 GB HBM3E 12H development", "url": "https://news.samsung.com/global/samsung-develops-industry-first-36gb-hbm3e-12h-dram" }, { "title": "SK hynix — Small Size, Big Impact", "url": "https://news.skhynix.com/en/small-size-big-impact/" }, { "title": "imec — wafer-to-wafer hybrid bonding at 400 nm pitch", "url": "https://www.imec-int.com/en/articles/wafer-wafer-hybrid-bonding-pushing-boundaries-400nm-interconnect-pitch" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-bonding-process-selection-35150926514801ce.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Thermocompression with non-conductive film", "url": "https://semiaifoundry.com/learn/atlas/hbm-tc-ncf-route/" }, { "title": "Mass reflow and molded underfill", "url": "https://semiaifoundry.com/learn/atlas/hbm-mr-muf-route/" }, { "title": "Hybrid bonding: surface-to-interface closure", "url": "https://semiaifoundry.com/learn/atlas/hbm-hybrid-bond-route/" }, { "title": "HBM silicon intensity and allocation", "url": "https://semiaifoundry.com/learn/atlas/hbm-silicon-intensity/" }, { "title": "Compatible supply and converging bottlenecks", "url": "https://semiaifoundry.com/learn/atlas/compatible-supply-capacity/" }, { "title": "Package and system preserve the contract", "url": "https://semiaifoundry.com/learn/atlas/crg-package-system-closure/" } ], "recordHash": "5485d06082bdfbc01b36f5afa3d4c303ccc4468852966bd9a294e709a264d2c5" }, { "id": "atlas-lesson-hbm-channel-generation-ras", "title": "HBM generations, channels, refresh and ECC", "category": "learning", "format": "Atlas lesson", "description": "Compares capacity and interface organization without confusing physical layers with logical channels.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-channel-generation-ras/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory / HBM system constraints", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Synopsys documents the HBM3/HBM4 organization in claim cards. Micron’s living HBM3E page retains historical availability wording and loosely rounded pin-rate statements; do not infer current supply or exact bandwidth from them.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-channel-generation-ras-df51a30febe8a0a6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-channel-generation-ras", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1d23e5059a01233a739d52c3e5864c4e0eb1f2f0ad026397879964d9a03a69ca", "contentLength": 5548, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-channel-generation-ras.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-channel-generation-ras.md", "sections": [ { "id": "section-1", "title": "HBM generations, channels, refresh and ECC" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Raw and useful bandwidth" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "If stack capacity rises but external lane width and rate stay fixed, what happens to raw interface bandwidth?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-channel-generation-ras" }, { "title": "Synopsys — What Designers Need to Know About HBM3", "url": "https://www.synopsys.com/articles/hbm3-ip-dwtb.html" }, { "title": "Micron — HBM3E", "url": "https://www.micron.com/products/memory/hbm/hbm3e" }, { "title": "Synopsys — HBM4 PHY IP datasheet", "url": "https://www.synopsys.com/content/dam/synopsys/resources/dw/hbm4-phy-datasheet.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-channel-generation-ras-df51a30febe8a0a6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DRAM cells, arrays and peripheral circuits", "url": "https://semiaifoundry.com/learn/atlas/dram-cell-array-fabrication/" }, { "title": "Base die, PHY and memory controller", "url": "https://semiaifoundry.com/learn/atlas/hbm-base-phy-controller/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "HBM silicon intensity and allocation", "url": "https://semiaifoundry.com/learn/atlas/hbm-silicon-intensity/" } ], "recordHash": "ce28bf465e4d4bea9e6f85b9df4d13f48a0f20135a48d2fd3fd12394f17e966e" }, { "id": "atlas-lesson-hbm-controller", "title": "HBM controller and PHY", "category": "learning", "format": "Atlas lesson", "description": "Schedules DRAM commands and translates on-chip requests into the electrical signals of the memory interface.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-controller/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory hierarchy", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "It is a dimensional estimate, not a product channel count.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-controller-bf096ea73b5c5207.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-controller", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0039466590a5343bff29e7cea62b9fd7c814a122e79f3950c33c828425a18230", "contentLength": 6158, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-controller.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-controller.md", "sections": [ { "id": "section-1", "title": "HBM controller and PHY" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Concurrent requests cover memory latency" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is the difference between the controller and the PHY?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-controller" }, { "title": "Micron HBM3E product brief", "url": "https://assets.micron.com/adobe/assets/urn%3Aaaid%3Aaem%3Ab710d8f2-7f66-44c1-a234-456e2b986347/renditions/original/as/hbm3e-product-brief.pdf" }, { "title": "NVIDIA GB200 NVL72 specifications", "url": "https://www.nvidia.com/en-us/data-center/gb200-nvl72/" }, { "title": "Intel: Memory performance, latency, and bandwidth", "url": "https://www.intel.com/content/www/us/en/developer/articles/technical/memory-performance-in-a-nutshell.html" }, { "title": "John D. C. Little (1961): A Proof for the Queuing Formula L = λW", "url": "https://pubsonline.informs.org/doi/abs/10.1287/opre.9.3.383" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-controller-bf096ea73b5c5207.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DRAM die and memory banks", "url": "https://semiaifoundry.com/learn/atlas/dram-die/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Interposer and redistribution layers", "url": "https://semiaifoundry.com/learn/atlas/interposer/" }, { "title": "Shared L2 cache", "url": "https://semiaifoundry.com/learn/atlas/l2-cache/" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" } ], "recordHash": "3b5bd23a50ceaa519d38794dc228b4cb127141729eb0fb32f61f28991eeb2f09" }, { "id": "atlas-lesson-hbm-hybrid-bond-route", "title": "Hybrid bonding: surface-to-interface closure", "category": "learning", "format": "Atlas lesson", "description": "Follow CMP, cleaning, alignment, contact and anneal as one surface-controlled integration problem.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-hybrid-bond-route/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "imec sources establish wafer-to-wafer and die-to-wafer research mechanisms. Product-specific HBM hybrid-bond qualification, throughput and cost are not inferred.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-hybrid-bond-route-0a11616f676cb7a3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-hybrid-bond-route", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a465e34507df134a280e3c414fa869a28d609a2fcc715253ca3de856309506f4", "contentLength": 5522, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-hybrid-bond-route.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-hybrid-bond-route.md", "sections": [ { "id": "section-1", "title": "Hybrid bonding: surface-to-interface closure" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Geometric pad-overlap example" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A clean-looking surface has acceptable mean flatness. Is that sufficient evidence of good hybrid bonds?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-hybrid-bond-route" }, { "title": "imec — wafer-to-wafer hybrid bonding at 400 nm pitch", "url": "https://www.imec-int.com/en/articles/wafer-wafer-hybrid-bonding-pushing-boundaries-400nm-interconnect-pitch" }, { "title": "imec — die-to-wafer hybrid bonding demonstration", "url": "https://www.imec-int.com/en/press/imec-demonstrates-die-wafer-hybrid-bonding-cu-interconnect-pad-pitch-2mm" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-hybrid-bond-route-0a11616f676cb7a3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Hybrid bonding: surface state and alignment", "url": "https://semiaifoundry.com/learn/atlas/hybrid-bond-surface-alignment/" }, { "title": "HBM layer count and physical height", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-height-budget/" }, { "title": "Thermocompression with non-conductive film", "url": "https://semiaifoundry.com/learn/atlas/hbm-tc-ncf-route/" }, { "title": "Mass reflow and molded underfill", "url": "https://semiaifoundry.com/learn/atlas/hbm-mr-muf-route/" }, { "title": "Selecting a bonding route under constraints", "url": "https://semiaifoundry.com/learn/atlas/hbm-bonding-process-selection/" }, { "title": "Cleaning and CMP as interface preparation", "url": "https://semiaifoundry.com/learn/atlas/clean-planarize-surface/" } ], "recordHash": "a2b62b431071afaf1b8ce1eef1572a4bc9842f66bf65fdb73bda4f2e08cc7e3f" }, { "id": "atlas-lesson-hbm-mr-muf-route", "title": "Mass reflow and molded underfill", "category": "learning", "format": "Atlas lesson", "description": "Separate stack placement, metallic reflow and molding in an MR-MUF assembly route.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-mr-muf-route/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "SK hynix’s process explanation describes reflow and molded underfill as separate roles, with implementation-specific chip stabilization in its advanced route. No comparative vendor yield or cost is assumed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-mr-muf-route-7a9c2967bc0f790f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-mr-muf-route", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "5a5376911eeed64d40a1fa9f962d2d7292bde492c3bb0fc16f5ac2bb8f59a37b", "contentLength": 4807, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-mr-muf-route.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-mr-muf-route.md", "sections": [ { "id": "section-1", "title": "Mass reflow and molded underfill" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Batch-limited station rate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A reflow station doubles its rate while molding remains slower. What happens to line capacity?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-mr-muf-route" }, { "title": "SK hynix — Small Size, Big Impact", "url": "https://news.skhynix.com/en/small-size-big-impact/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-mr-muf-route-7a9c2967bc0f790f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "HBM layer count and physical height", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-height-budget/" }, { "title": "Microbumps, reflow and thermocompression", "url": "https://semiaifoundry.com/learn/atlas/bump-thermocompression-assembly/" }, { "title": "Thermocompression with non-conductive film", "url": "https://semiaifoundry.com/learn/atlas/hbm-tc-ncf-route/" }, { "title": "Selecting a bonding route under constraints", "url": "https://semiaifoundry.com/learn/atlas/hbm-bonding-process-selection/" }, { "title": "Cycle time, ramp and effective capacity", "url": "https://semiaifoundry.com/learn/atlas/fab-ramp-cycle-time/" } ], "recordHash": "5f73f85452fdb9b841718ea4dc230884a6bc63a71b1230eee0c575de1bef3503" }, { "id": "atlas-lesson-hbm-silicon-intensity", "title": "HBM silicon intensity and allocation", "category": "learning", "format": "Atlas lesson", "description": "Estimates wafer demand per delivered bit without double-counting embedded yield losses.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-silicon-intensity/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory / HBM system constraints", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Micron’s March 20, 2024 prepared remarks, page 6, report approximately 3× wafer supply for HBM3E versus DDR5 at equal bits and the same technology node. This historical supplier statement does not establish a universal generation-independent factor, package footprint or current customer allocation. The lab keeps synthetic inputs and does not add losses already embedded in an empirical ratio.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-silicon-intensity-ec1f2db8286d9d99.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-silicon-intensity", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "28d6de64447dce8ac5eeb9d065dd5e594f73c03eb10a83a79ada508164c8d869", "contentLength": 6432, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-silicon-intensity.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-silicon-intensity.md", "sections": [ { "id": "section-1", "title": "HBM silicon intensity and allocation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Two alternative demand models" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "When is applying an extra stack-yield penalty to an empirical wafer/output-bit ratio justified?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-silicon-intensity" }, { "title": "Micron — FY Q2 2024 prepared remarks, page 6", "url": "https://micron.gcs-web.com/static-files/1a8d6c22-3b89-4806-930c-d30cbcd270d5" }, { "title": "SK hynix — TSMC collaboration on HBM", "url": "https://news.skhynix.com/en/sk-hynix-partners-with-tsmc-to-strengthen-hbm-technological-leadership/" }, { "title": "DISCO — Tech Briefing 2023", "url": "https://disco.co.jp/jp/ir/movie/doc/E_Tech_Briefing_2023.pdf" }, { "title": "Micron — HBM3E", "url": "https://www.micron.com/products/memory/hbm/hbm3e" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-silicon-intensity-ec1f2db8286d9d99.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer maps and good-die yield", "url": "https://semiaifoundry.com/learn/atlas/yield-wafer-defect-model/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" }, { "title": "HBM generations, channels, refresh and ECC", "url": "https://semiaifoundry.com/learn/atlas/hbm-channel-generation-ras/" }, { "title": "Cycle time, ramp and effective capacity", "url": "https://semiaifoundry.com/learn/atlas/fab-ramp-cycle-time/" } ], "recordHash": "22f5850576d7dc5c2b2cfacce6224013d28d493009b4ba49c5b43ebaa7a24875" }, { "id": "atlas-lesson-hbm-stack-assembly-test", "title": "HBM stack assembly, repair and staged test", "category": "learning", "format": "Atlas lesson", "description": "Combines screened memory dies into a delivered stack using a specified joining route.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory / HBM fabrication and assembly", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No vendor stack-yield, repair coverage or process recipe is asserted. Stack qualification and current volume status must be supported separately.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-stack-assembly-test-bae6cef015ba73d2.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-stack-assembly-test", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4abeab50388c6f02a48f7ac5b4273ff8ff72124ef12f812aff6f279be1854fab", "contentLength": 5965, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-stack-assembly-test.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-stack-assembly-test.md", "sections": [ { "id": "section-1", "title": "HBM stack assembly, repair and staged test" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Assembly-stage yield" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What yield term belongs after an inventory of known-good dies has already been counted?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-stack-assembly-test" }, { "title": "SK hynix — Small Size, Big Impact", "url": "https://news.skhynix.com/en/small-size-big-impact/" }, { "title": "Advantest — Semiconductor test glossary", "url": "https://www.advantest.com/en/investors/ir-library/glossary/" }, { "title": "DISCO — Tech Briefing 2023", "url": "https://disco.co.jp/jp/ir/movie/doc/E_Tech_Briefing_2023.pdf" }, { "title": "Micron — HBM3E volume production begins", "url": "https://investors.micron.com/news/press-release/2024/Micron-Commences-Volume-Production-of-Industry-Leading-HBM3E-Solution-to-Accelerate-the-Growth-of-AI-02-26-2024/default.aspx" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-stack-assembly-test-bae6cef015ba73d2.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" }, { "title": "Temporary bonding, thinning and singulation", "url": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/" }, { "title": "TSV formation, keep-out and backside reveal", "url": "https://semiaifoundry.com/learn/atlas/hbm-tsv-reveal/" }, { "title": "Microbumps, reflow and thermocompression", "url": "https://semiaifoundry.com/learn/atlas/bump-thermocompression-assembly/" }, { "title": "CoWoS-S and the silicon interposer route", "url": "https://semiaifoundry.com/learn/atlas/cowos-s-silicon-interposer/" } ], "recordHash": "1a6b3d6d16c0a54cae6e1cff9073cfcecf0798b9d60234925cc0da111abdb51a" }, { "id": "atlas-lesson-hbm-stack", "title": "High-bandwidth memory stack", "category": "learning", "format": "Atlas lesson", "description": "Stacks DRAM vertically beside the processor to provide large capacity through a very wide local interface.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-stack/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory hierarchy", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The eight-layer drawing is schematic and not a universal HBM generation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-stack-d15a25e66bf44c7a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-stack", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c79d9d011be15ad4b5876513e4b2af781ab5c4c16f080abfa5ebb6f45f9e98b4", "contentLength": 6533, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-stack.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-stack.md", "sections": [ { "id": "section-1", "title": "High-bandwidth memory stack" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Parallel width creates aggregate bandwidth" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What mainly distinguishes HBM’s approach from simply raising the speed of a narrow memory bus?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2016 · Pascal P100 combines HBM2 packaging with NVLink" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-stack" }, { "title": "NVIDIA: Tesla P100 launch announcement", "url": "https://nvidianews.nvidia.com/news/nvidia-delivers-massive-performance-leap-for-deep-learning-hpc-applications-with-nvidia-tesla-p100-accelerators-6622437" }, { "title": "Micron HBM3E", "url": "https://www.micron.com/products/memory/hbm/hbm3e" }, { "title": "Micron HBM3E product brief", "url": "https://assets.micron.com/adobe/assets/urn%3Aaaid%3Aaem%3Ab710d8f2-7f66-44c1-a234-456e2b986347/renditions/original/as/hbm3e-product-brief.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-stack-d15a25e66bf44c7a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DRAM die and memory banks", "url": "https://semiaifoundry.com/learn/atlas/dram-die/" }, { "title": "Through-silicon via", "url": "https://semiaifoundry.com/learn/atlas/through-silicon-via/" }, { "title": "Microbumps and bonding joints", "url": "https://semiaifoundry.com/learn/atlas/microbump/" }, { "title": "HBM controller and PHY", "url": "https://semiaifoundry.com/learn/atlas/hbm-controller/" }, { "title": "Interposer and redistribution layers", "url": "https://semiaifoundry.com/learn/atlas/interposer/" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" } ], "recordHash": "7516a88d3157496424e84f73dfdd7896ef04537be6311041cc3978a3a8263ee7" }, { "id": "atlas-lesson-hbm-stack-height-budget", "title": "HBM layer count and physical height", "category": "learning", "format": "Atlas lesson", "description": "Separate memory-die count, package thickness, stored bits and interface bandwidth.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-stack-height-budget/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "SK hynix’s 2023 account describes fitting more DRAM dies into the same height through thinner dies and changed assembly. The source supports the mechanism; the lab uses independent illustrative dimensions.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-stack-height-budget-6372b6d7859deeb7.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-stack-height-budget", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ba389023ecb0b7fd333b086ec8f6be9e6945e332e4834091bbb29201eb486dcd", "contentLength": 6012, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-stack-height-budget.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-stack-height-budget.md", "sections": [ { "id": "section-1", "title": "HBM layer count and physical height" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Stack-height budget" }, { "id": "section-5", "title": "Capacity is not bandwidth" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "A stack changes from 8 to 12 memory dies at unchanged external width and pin rate. What follows directly?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-stack-height-budget" }, { "title": "SK hynix — the team behind 12-layer HBM3", "url": "https://news.skhynix.com/en/meet-the-sk-hynix-team-behind-the-worlds-first-12-layer-hbm3/" }, { "title": "Samsung — 36 GB HBM3E 12H development", "url": "https://news.samsung.com/global/samsung-develops-industry-first-36gb-hbm3e-12h-dram" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-stack-height-budget-6372b6d7859deeb7.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "TSV formation, keep-out and backside reveal", "url": "https://semiaifoundry.com/learn/atlas/hbm-tsv-reveal/" }, { "title": "Temporary bonding, thinning and singulation", "url": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/" }, { "title": "HBM heat, assembly yield and test access", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-thermal-yield/" }, { "title": "Selecting a bonding route under constraints", "url": "https://semiaifoundry.com/learn/atlas/hbm-bonding-process-selection/" }, { "title": "HBM generations, channels, refresh and ECC", "url": "https://semiaifoundry.com/learn/atlas/hbm-channel-generation-ras/" } ], "recordHash": "da3091d8800b70cbc4117a50ef940268a194b46928a7ce60eaf2067da230b0aa" }, { "id": "atlas-lesson-hbm-stack-thermal-yield", "title": "HBM heat, assembly yield and test access", "category": "learning", "format": "Atlas lesson", "description": "Explain how added layers affect the heat path, screening strategy and delivered good stacks.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-stack-thermal-yield/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "imec’s 2025 thermal study concerns a specified research HBM-on-GPU arrangement. It motivates spatial heat analysis; its simulated temperatures are not general product limits.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-stack-thermal-yield-0460105d4317f4c3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-stack-thermal-yield", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "cf308008f13621804016b57c89b381dbd77af91992c828d836e9c721f5153bb5", "contentLength": 6057, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-stack-thermal-yield.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-stack-thermal-yield.md", "sections": [ { "id": "section-1", "title": "HBM heat, assembly yield and test access" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Multiple heat sources" }, { "id": "section-5", "title": "Conditional assembly yield" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Why not multiply wafer yield into every already screened die again?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-stack-thermal-yield" }, { "title": "imec — thermal STCO study of 3D HBM-on-GPU", "url": "https://www.imec-int.com/en/press/imec-mitigates-thermal-bottleneck-3d-hbm-gpu-architectures-using-system-technology-co" }, { "title": "MIT OpenCourseWare — Introduction to Heat Transfer", "url": "https://ocw.mit.edu/courses/2-051-introduction-to-heat-transfer-fall-2015/" }, { "title": "SK hynix — the team behind 12-layer HBM3", "url": "https://news.skhynix.com/en/meet-the-sk-hynix-team-behind-the-worlds-first-12-layer-hbm3/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-stack-thermal-yield-0460105d4317f4c3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "HBM layer count and physical height", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-height-budget/" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" }, { "title": "Underfill, warpage, thermal paths and qualification", "url": "https://semiaifoundry.com/learn/atlas/package-thermomechanical-reliability/" }, { "title": "Qualify the memory system and retain useful work", "url": "https://semiaifoundry.com/learn/atlas/memory-system-qualification/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" } ], "recordHash": "72dd4e12a63b93c42176e6ce640cc9e27a13b693d4577a96729d6cc3fc49039a" }, { "id": "atlas-lesson-hbm-tc-ncf-route", "title": "Thermocompression with non-conductive film", "category": "learning", "format": "Atlas lesson", "description": "Trace a bump-based TC-NCF route and separate polymer behavior from electrical contact formation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-tc-ncf-route/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Historical vendor example: Samsung reported an advanced TC-NCF route for its 2024 HBM3E 12H development. Sampling, qualification and volume production are distinct statuses.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-tc-ncf-route-3e048cd358264626.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-tc-ncf-route", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "096b82f8dcc7b2b7cf2099067bf7e78d333bc0097e7e8ac3d558499736d6188f", "contentLength": 4959, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-tc-ncf-route.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-tc-ncf-route.md", "sections": [ { "id": "section-1", "title": "Thermocompression with non-conductive film" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Serial tool occupancy" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "In TC-NCF, what carries current between memory dies?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-tc-ncf-route" }, { "title": "Samsung — 36 GB HBM3E 12H development", "url": "https://news.samsung.com/global/samsung-develops-industry-first-36gb-hbm3e-12h-dram" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-tc-ncf-route-3e048cd358264626.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Microbumps, reflow and thermocompression", "url": "https://semiaifoundry.com/learn/atlas/bump-thermocompression-assembly/" }, { "title": "HBM layer count and physical height", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-height-budget/" }, { "title": "Mass reflow and molded underfill", "url": "https://semiaifoundry.com/learn/atlas/hbm-mr-muf-route/" }, { "title": "Hybrid bonding: surface-to-interface closure", "url": "https://semiaifoundry.com/learn/atlas/hbm-hybrid-bond-route/" }, { "title": "Selecting a bonding route under constraints", "url": "https://semiaifoundry.com/learn/atlas/hbm-bonding-process-selection/" } ], "recordHash": "9f370fd7cd1b7040aeaa04d00d44d73de5b8e9968276b6827ec7fe19f2dfec05" }, { "id": "atlas-lesson-hbm-tsv-reveal", "title": "TSV formation, keep-out and backside reveal", "category": "learning", "format": "Atlas lesson", "description": "Builds insulated vertical conductors and exposes their opposite ends for stacking.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hbm-tsv-reveal/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory / HBM fabrication and assembly", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Insertion stage, materials, dimensions and keep-out rules are route-specific. The drawing does not establish a vendor’s via-first/middle/last flow.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-tsv-reveal-326c9d35c6e39dea.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hbm-tsv-reveal", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "baa09aa20046de5507cb640173019dbb007148be0dc75352ed6f53e25131c884", "contentLength": 5349, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-tsv-reveal.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hbm-tsv-reveal.md", "sections": [ { "id": "section-1", "title": "TSV formation, keep-out and backside reveal" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Via resistance and exclusion area" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does a TSV consume more layout area than its metal diameter suggests?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hbm-tsv-reveal" }, { "title": "DISCO — Tech Briefing 2023", "url": "https://disco.co.jp/jp/ir/movie/doc/E_Tech_Briefing_2023.pdf" }, { "title": "SK hynix — Small Size, Big Impact", "url": "https://news.skhynix.com/en/small-size-big-impact/" }, { "title": "Lam Research — Our Processes", "url": "https://www.lamresearch.com/products/our-processes/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hbm-tsv-reveal-326c9d35c6e39dea.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Through-silicon via", "url": "https://semiaifoundry.com/learn/atlas/through-silicon-via/" }, { "title": "Plasma and wet etch: selectivity and profile", "url": "https://semiaifoundry.com/learn/atlas/plasma-wet-etch-transfer/" }, { "title": "Temporary bonding, thinning and singulation", "url": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" }, { "title": "HBM silicon intensity and allocation", "url": "https://semiaifoundry.com/learn/atlas/hbm-silicon-intensity/" } ], "recordHash": "3fcf5771718b53baac868464a2e56b2e91ae73b2f9cb7ab8b21c3b0eb711d5ed" }, { "id": "atlas-lesson-heat-spreader", "title": "Lid and heat spreader", "category": "learning", "format": "Atlas lesson", "description": "Protects the package and spreads concentrated die heat toward a larger cooling contact.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/heat-spreader/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Thermal path", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The linked package/thermal references distinguish lidded and lidless constructions. The numbers describe a lumped steady-state teaching model with common heat flow; real spreading, parallel paths and mechanical constraints require configuration-specific analysis.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/heat-spreader-40929af4d54e5636.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#heat-spreader", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "26820f09ca797277a11ba5e837a2c2ff4f42189efab83c42f373d1bfbe9f8522", "contentLength": 6106, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-heat-spreader.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-heat-spreader.md", "sections": [ { "id": "section-1", "title": "Lid and heat spreader" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Every layer contributes to the thermal path" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is a key tradeoff between lidded and direct-die cooling?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#heat-spreader" }, { "title": "AMD: Lidded and lidless flip-chip package construction", "url": "https://docs.amd.com/r/en-US/ds946-xqr-versal-ai-core/Lidless-Flip-Chip-Packages" }, { "title": "Amkor flip chip packaging", "url": "https://amkor.com/technology/flip-chip/" }, { "title": "Texas Instruments: Thermal design for surface-mount layouts", "url": "https://www.ti.com/download/trng/docs/seminar/Topic%2010%20-%20Thermal%20Design%20Consideration%20for%20Surface%20Mount%20Layouts%20.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/heat-spreader-40929af4d54e5636.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Thermal interface material", "url": "https://semiaifoundry.com/learn/atlas/thermal-interface/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "Liquid-cooling coldplate", "url": "https://semiaifoundry.com/learn/atlas/coldplate/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" } ], "recordHash": "fb2edcfb63fa1109ce1b567852a9522dbeacf08bccdb581d09d9a6e42c88cce2" }, { "id": "atlas-lesson-host-cpu", "title": "Host CPU", "category": "learning", "format": "Atlas lesson", "description": "Runs the operating system and coordinates the workloads, data preparation, and I/O surrounding accelerated computation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/host-cpu/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Host platform", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The model excludes communication, memory and changing problem size.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/host-cpu-31cd324b779e4ac6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#host-cpu", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b5d1a07f9cb941c3274d713a0b81cb7f2618c554d255deaac446e10c1a8c44c0", "contentLength": 6584, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-host-cpu.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-host-cpu.md", "sections": [ { "id": "section-1", "title": "Host CPU" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "The unaccelerated fraction limits total speedup" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which task naturally belongs to the CPU’s coordination role?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "1971 · Intel introduces the 4004 microprocessor" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#host-cpu" }, { "title": "Intel: Announcing a New Era of Integrated Electronics", "url": "https://www.intel.com/content/www/us/en/history/virtual-vault/articles/the-intel-4004.html" }, { "title": "NVIDIA Data Center CPUs: Grace architecture", "url": "https://docs.nvidia.com/dccpu/index.html" }, { "title": "NVIDIA: Inside Grace CPU architecture", "url": "https://developer.nvidia.com/blog/inside-nvidia-grace-cpu-nvidia-amps-up-superchip-engineering-for-hpc-and-ai/" }, { "title": "NVIDIA GB200 NVL72 specifications", "url": "https://www.nvidia.com/en-us/data-center/gb200-nvl72/" }, { "title": "Intel Advisor: Amdahl’s Law and measurement", "url": "https://www.intel.com/content/www/us/en/docs/advisor/user-guide/2024-2/use-amdahl-law.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/host-cpu-31cd324b779e4ac6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" }, { "title": "Shared L2 cache", "url": "https://semiaifoundry.com/learn/atlas/l2-cache/" }, { "title": "Grace Blackwell Superchip", "url": "https://semiaifoundry.com/learn/atlas/grace-blackwell-superchip/" }, { "title": "Grace LPDDR5X memory", "url": "https://semiaifoundry.com/learn/atlas/lpddr-memory/" }, { "title": "DDR5 server memory", "url": "https://semiaifoundry.com/learn/atlas/ddr-memory/" }, { "title": "PCI Express interconnect", "url": "https://semiaifoundry.com/learn/atlas/pcie-interface/" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" } ], "recordHash": "25e0f702cc22b9d45da03c237eb7977e1d2fa23ab9ae50a93f37ef955d0d8a85" }, { "id": "atlas-lesson-human-review-cancellation", "title": "Human review, interruption and cancellation", "category": "learning", "format": "Atlas lesson", "description": "Approve a concrete versioned action; stale approval invalidates on change; distinguish request, acknowledgement and committed effects.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/human-review-cancellation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "From request to durable action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The durable incident experience executes typed fixture tools, authority checks, exact review, receipts and independent final-state checks. Its policies are authored code and its storage boundary is local; it is not a real model or production workflow platform. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. The executable equality check is canonical payload matching, not a cryptographic approval signature. Physical stop behavior and compensating transactions are outside the fixture.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/human-review-cancellation-011a87a1b518745d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#human-review-cancellation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c1ada30f07ecd9cb67e55efe133548ea022cf105433049e9a50563c0abda978c", "contentLength": 6778, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-human-review-cancellation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-human-review-cancellation.md", "sections": [ { "id": "section-1", "title": "Human review, interruption and cancellation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Human review, interruption and cancellation · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Cancellation arrives after the reservation committed. Which statement is correct?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#human-review-cancellation" }, { "title": "LangGraph · Interrupts", "url": "https://docs.langchain.com/oss/python/langgraph/interrupts" }, { "title": "Temporal Activities", "url": "https://docs.temporal.io/activities" }, { "title": "ROS 2 Jazzy: Understanding actions", "url": "https://raw.githubusercontent.com/ros2/ros2_documentation/jazzy/source/Concepts/Basic/About-Actions.rst" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/human-review-cancellation-011a87a1b518745d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Durable actions and the ambiguous timeout", "url": "https://semiaifoundry.com/learn/atlas/durable-actions-idempotency/" }, { "title": "User authority and service identity", "url": "https://semiaifoundry.com/learn/atlas/tool-authority-identity/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "8670bea8c17db9237a80b898d583dfe85cc82b413c981e80c90aeccfb0501cc9" }, { "id": "atlas-lesson-hybrid-bond-surface-alignment", "title": "Hybrid bonding: surface state and alignment", "category": "learning", "format": "Atlas lesson", "description": "Joins dielectric surfaces and metal connections across a carefully prepared interface.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/hybrid-bond-surface-alignment/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Assembly and reliability", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "imec’s 400 nm-pitch result is research on specified Cu/SiCN structures. Its stated overlay and thermal conditions are not applied as generic production limits.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/hybrid-bond-surface-alignment-9002a9c90b03210c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#hybrid-bond-surface-alignment", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c691a7e935a14d6c8b6a119726d930b041ca8f7584cdd3715594c0f696e5028e", "contentLength": 5300, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hybrid-bond-surface-alignment.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-hybrid-bond-surface-alignment.md", "sections": [ { "id": "section-1", "title": "Hybrid bonding: surface state and alignment" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Square-pad overlap model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does a local surface particle matter beyond its own electrical conductivity?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#hybrid-bond-surface-alignment" }, { "title": "imec — Wafer-to-wafer hybrid bonding: 400 nm interconnect pitch", "url": "https://www.imec-int.com/en/articles/wafer-wafer-hybrid-bonding-pushing-boundaries-400nm-interconnect-pitch" }, { "title": "Besi — Scientific publications", "url": "https://www.besi.com/scientific-publications/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/hybrid-bond-surface-alignment-9002a9c90b03210c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Cleaning and CMP as interface preparation", "url": "https://semiaifoundry.com/learn/atlas/clean-planarize-surface/" }, { "title": "Microbumps, reflow and thermocompression", "url": "https://semiaifoundry.com/learn/atlas/bump-thermocompression-assembly/" }, { "title": "SoIC and Foveros: vertical integration families", "url": "https://semiaifoundry.com/learn/atlas/soic-foveros-vertical-routes/" }, { "title": "Contamination and the state of a surface", "url": "https://semiaifoundry.com/learn/atlas/contamination-and-surface-state/" } ], "recordHash": "24186d931c2c46aaae5303697ffd5b28ae339a0fd41a7027062de794919ebd5c" }, { "id": "atlas-lesson-image-text-contrastive-learning", "title": "Pair images and captions in a shared representation", "category": "learning", "format": "Atlas lesson", "description": "Compute a paired image/text similarity loss and test a shortcut with held-out compositions.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/image-text-contrastive-learning/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-multimodal", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Two uniquely matched pairs, unit vectors and temperature one in the example. False-negative captions and general image understanding are outside this exact arithmetic. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/image-text-contrastive-learning-40b0c75d5fba4ae0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#image-text-contrastive-learning", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "6d0147d470e5b2945591e22129d461360ef261d9710d928144abbc2fb8220eda", "contentLength": 6704, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-image-text-contrastive-learning.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-image-text-contrastive-learning.md", "sections": [ { "id": "section-1", "title": "Pair images and captions in a shared representation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Pair images and captions in a shared representation · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a low contrastive loss directly train?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#image-text-contrastive-learning" }, { "title": "Learning Transferable Visual Models From Natural Language Supervision", "url": "https://arxiv.org/html/2103.00020v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/image-text-contrastive-learning-40b0c75d5fba4ae0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Patches, projection and visual instruction tuning", "url": "https://semiaifoundry.com/learn/atlas/visual-language-bridge/" }, { "title": "Audio representation, alignment and transcript loss", "url": "https://semiaifoundry.com/learn/atlas/speech-audio-sequence-objectives/" }, { "title": "Train a denoiser and sample iteratively", "url": "https://semiaifoundry.com/learn/atlas/denoising-generative-objectives/" }, { "title": "Predict temporal representations without generating pixels", "url": "https://semiaifoundry.com/learn/atlas/video-latent-prediction/" } ], "recordHash": "52f104c3d30eb936bf1982cd8102a2c61807144d6d6167486ae445ea7aee110e" }, { "id": "atlas-lesson-imagined-rollouts-policy-learning", "title": "Learn behavior from a model and test in the environment", "category": "learning", "format": "Atlas lesson", "description": "Compare a policy’s imagined return with return in the actual environment and identify model exploitation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/imagined-rollouts-policy-learning/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-world-action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Authored deterministic rewards and finite horizon; no learned actor/critic or robot is executed here. Terminal states must stop or otherwise explicitly zero further rewards. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/imagined-rollouts-policy-learning-1c1807caf45ac53a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#imagined-rollouts-policy-learning", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ac6a02ecacc2081684157f630fa0b2bb83209a2043ac8b043e43cba5db511bb2", "contentLength": 6430, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-imagined-rollouts-policy-learning.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-imagined-rollouts-policy-learning.md", "sections": [ { "id": "section-1", "title": "Learn behavior from a model and test in the environment" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Learn behavior from a model and test in the environment · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does the unsupported action look best during imagined optimization?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#imagined-rollouts-policy-learning" }, { "title": "Mastering Diverse Domains through World Models", "url": "https://arxiv.org/html/2301.04104v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/imagined-rollouts-policy-learning-1c1807caf45ac53a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Predict transitions conditional on actions", "url": "https://semiaifoundry.com/learn/atlas/action-conditioned-world-model/" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Translate learned representations into robot action units", "url": "https://semiaifoundry.com/learn/atlas/vision-language-action-interface/" }, { "title": "Predict action chunks and replan with feedback", "url": "https://semiaifoundry.com/learn/atlas/diffusion-action-horizon/" } ], "recordHash": "528d29d4fe077b16bec1ff6de897844d7924e3a32b17c3d416944b752f311247" }, { "id": "atlas-lesson-implantation-anneal-diffusion", "title": "Implantation, activation and diffusion", "category": "learning", "format": "Atlas lesson", "description": "Introduces dopants and uses heat to repair damage and establish electrical activity.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/implantation-anneal-diffusion/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / FEOL and MOL", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No implant energy, dopant dose, beam angle or anneal recipe is prescribed. Diffusion models are limited approximations.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/implantation-anneal-diffusion-39065174fb143722.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#implantation-anneal-diffusion", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a37748de5c440c36cd5a4619092385f9a039745c12cb1e4c00a3a1944763dcd6", "contentLength": 4816, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-implantation-anneal-diffusion.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-implantation-anneal-diffusion.md", "sections": [ { "id": "section-1", "title": "Implantation, activation and diffusion" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Diffusion length scale" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can two wafers receiving the same implant dose have different sheet resistance?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#implantation-anneal-diffusion" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "ASML — How microchips are made", "url": "https://www.asml.com/en/technology/all-about-microchips/how-microchips-are-made" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/implantation-anneal-diffusion-39065174fb143722.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Donor and acceptor doping", "url": "https://semiaifoundry.com/learn/atlas/doping/" }, { "title": "P–n junction and depletion region", "url": "https://semiaifoundry.com/learn/atlas/pn-junction/" }, { "title": "Source/drain, spacers, contacts and MOL", "url": "https://semiaifoundry.com/learn/atlas/source-drain-contact-integration/" } ], "recordHash": "032035776d11c14d023eccc327abc94637fa45ac6d8a2e26a9e078f4fecef03d" }, { "id": "atlas-lesson-inference-custom-silicon", "title": "Custom inference silicon: Maia and MTIA", "category": "learning", "format": "Atlas lesson", "description": "Allocates compute and memory around a provider’s measured inference needs.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/inference-custom-silicon/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Maia specifications are provider-reported. The inaccessible next-generation Meta blog was replaced by accessible first-generation and engineering sources; no unsupported current MTIA peak is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/inference-custom-silicon-5d522fce85efc4d7.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#inference-custom-silicon", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bfd540602796a9b3954114011c9f9f82fdcd84564b8689744a54645f10634fa5", "contentLength": 5877, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-inference-custom-silicon.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-inference-custom-silicon.md", "sections": [ { "id": "section-1", "title": "Custom inference silicon: Maia and MTIA" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Weighted service cost" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What evidence best motivates more on-chip SRAM for an inference design?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#inference-custom-silicon" }, { "title": "Maia 200: The AI accelerator built for inference", "url": "https://blogs.microsoft.com/blog/2026/01/26/maia-200-the-ai-accelerator-built-for-inference/" }, { "title": "MTIA v1: Meta’s first-generation AI inference accelerator", "url": "https://ai.meta.com/blog/meta-training-inference-accelerator-AI-MTIA/" }, { "title": "Inside the hardware and co-design of MTIA", "url": "https://engineering.fb.com/2024/08/22/ml-applications/meta-mtia-hardware-co-design/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/inference-custom-silicon-5d522fce85efc4d7.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Full memory hierarchy and input path", "url": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Workload contract and architecture selection", "url": "https://semiaifoundry.com/learn/atlas/chip-workload-contract/" }, { "title": "Choosing SRAM, HBM, DDR, LPDDR or GDDR", "url": "https://semiaifoundry.com/learn/atlas/memory-interface-choice/" }, { "title": "Custom-chip volume economics", "url": "https://semiaifoundry.com/learn/atlas/chip-volume-economics/" } ], "recordHash": "39694085170190eccb4ea25154006846c1092ce81722ccaa4e557c4e22bbb144" }, { "id": "atlas-lesson-interconnect", "title": "On-chip metal and via hierarchy", "category": "learning", "format": "Atlas lesson", "description": "Connects cells through a multilayer electrical network.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/interconnect/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Materials and wiring", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The linked interconnect work motivates resistance/capacitance scaling. Synthetic values illustrate an unbuffered uniform RC line, not a node-specific delay prediction; repeaters, coupling and inductance can change the result.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/interconnect-a5385c7d6ce18b1a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#interconnect", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c76e4d3929bcb71e86f0bfb1a749eaa1004bd95c87859ecbe5f237e010285189", "contentLength": 5264, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-interconnect.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-interconnect.md", "sections": [ { "id": "section-1", "title": "On-chip metal and via hierarchy" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Distributed wire-delay scaling" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can placing arithmetic near its operands help?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#interconnect" }, { "title": "IBM Research — Interconnect Performance and Scaling Strategy", "url": "https://research.ibm.com/publications/interconnect-performance-and-scaling-strategy-at-the-5-nm-node" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/interconnect-a5385c7d6ce18b1a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Copper conductor and barrier", "url": "https://semiaifoundry.com/learn/atlas/copper-conductor/" }, { "title": "Insulators and low-k films", "url": "https://semiaifoundry.com/learn/atlas/dielectric/" }, { "title": "Device contact and interface resistance", "url": "https://semiaifoundry.com/learn/atlas/contact/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" } ], "recordHash": "bd2f6a3de80805ab956596893d28115e9973838d134fbe08a2269cca781a8272" }, { "id": "atlas-lesson-interconnect-rc-materials", "title": "Wire resistance, low-k dielectrics and reliability", "category": "learning", "format": "Atlas lesson", "description": "Connects shrinking wire geometry to delay, coupling and current-density limits.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/interconnect-rc-materials/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / BEOL and co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No current-density limit, low-k mechanical property or product delay is asserted. Reliability requires process-specific evidence.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/interconnect-rc-materials-f76147c18d39e79c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#interconnect-rc-materials", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b18db7a3c45dbc6035b8f605dec95466507a2457e8c2e336b7c05aeee054b329", "contentLength": 5294, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-interconnect-rc-materials.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-interconnect-rc-materials.md", "sections": [ { "id": "section-1", "title": "Wire resistance, low-k dielectrics and reliability" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Wire and distributed-RC scaling" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "If a wire length doubles while its cross-section and environment stay fixed, how does a simple distributed RC delay scale?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#interconnect-rc-materials" }, { "title": "imec — Scaling the BEOL: a toolbox of processes and conductors", "url": "https://www.imec-int.com/en/imec-magazine/imec-magazine-september-2019/scaling-the-beol-a-toolbox-filled-with-new-processes-boosters-and-conductors" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/interconnect-rc-materials-f76147c18d39e79c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "BEOL layers, damascene and vias", "url": "https://semiaifoundry.com/learn/atlas/beol-damascene-vias/" }, { "title": "Copper conductor and barrier", "url": "https://semiaifoundry.com/learn/atlas/copper-conductor/" }, { "title": "Insulators and low-k films", "url": "https://semiaifoundry.com/learn/atlas/dielectric/" }, { "title": "Backside power and design–technology co-optimization", "url": "https://semiaifoundry.com/learn/atlas/backside-power-dtco/" } ], "recordHash": "341c8c07936bc821bf2417014d193af0fe3996f7c74f88da917c11697866a230" }, { "id": "atlas-lesson-interface-signal-eye", "title": "Signal integrity, timing and the eye diagram", "category": "learning", "format": "Atlas lesson", "description": "Tests whether a receiver can distinguish transmitted symbols under actual channel conditions.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/interface-signal-eye/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Chip-to-hall integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "IBM’s numerical geometry results are not transferred to this example. Eye limits and test confidence must be specified for the actual interface.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/interface-signal-eye-d9fbfd204e435f5d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#interface-signal-eye", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0a27b3ccefa016a83ccc86b513958790bc40f1face8cd6751f3b4cc4cd8fabd2", "contentLength": 4822, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-interface-signal-eye.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-interface-signal-eye.md", "sections": [ { "id": "section-1", "title": "Signal integrity, timing and the eye diagram" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Unit interval" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a link pass alone but fail beside busy neighbors?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#interface-signal-eye" }, { "title": "Signal and Power Integrity Design and Analysis for BoW Interface for Chiplet Integration on Advanced Packaging", "url": "https://research.ibm.com/publications/signal-and-power-integrity-design-and-analysis-for-bunch-of-wires-bow-interface-for-chiplet-integration-on-advanced-packaging" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/interface-signal-eye-d9fbfd204e435f5d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "Die-to-die links and UCIe compatibility", "url": "https://semiaifoundry.com/learn/atlas/die-link-compatibility/" }, { "title": "Power integrity and transient voltage margin", "url": "https://semiaifoundry.com/learn/atlas/power-integrity-budget/" } ], "recordHash": "cbcc349f793110a465b4b66bfc17b8c021126f5b58c7983017769afb671eb86d" }, { "id": "atlas-lesson-interposer", "title": "Interposer and redistribution layers", "category": "learning", "format": "Atlas lesson", "description": "Connects logic dies and memory through dense package-level wiring.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/interposer/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Advanced packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The relation is a distributed-line intuition, not a package timing signoff.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/interposer-5811de9d3ee1ec1d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#interposer", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9b8ba8d57d94e00e445478b11d785fcc1db9827cbf8561b6a50b0ad01afc9fc8", "contentLength": 6286, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-interposer.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-interposer.md", "sections": [ { "id": "section-1", "title": "Interposer and redistribution layers" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Long resistive routes can become disproportionately slow" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is the interposer’s central contribution to an AI accelerator?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2012 · TSMC CoWoS enters volume production" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#interposer" }, { "title": "TSMC: CoWoS platform history and technology", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm" }, { "title": "TSMC research: High Performance, High Density RDL", "url": "https://research.tsmc.com/page/off-chip-interconnect/19.html" }, { "title": "MIT: Communication System Design, interconnect and wire scaling", "url": "https://ocw.mit.edu/courses/6-973-communication-system-design-spring-2006/44d1cff68d0f994cca25442de3e1ac78_lecture_5.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/interposer-5811de9d3ee1ec1d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Through-silicon via", "url": "https://semiaifoundry.com/learn/atlas/through-silicon-via/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Microbumps and bonding joints", "url": "https://semiaifoundry.com/learn/atlas/microbump/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" }, { "title": "Chemical mechanical planarization", "url": "https://semiaifoundry.com/learn/atlas/cmp/" } ], "recordHash": "56cb144b27895e892682f9d6c19eb46b8cb7f58effe346ac81d857c71d29549e" }, { "id": "atlas-lesson-inverter", "title": "Complementary CMOS inverter", "category": "learning", "format": "Atlas lesson", "description": "Turns one binary voltage state into its complement.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/inverter/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Digital circuits", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The switching model and complementary topology follow the linked CMOS lecture. Values are synthetic; valid logic levels, transfer gain and noise margins require a device and load model.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/inverter-ceec9a037236becd.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#inverter", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9dd2ce4bd49129740d7cb8241c7249ac98747ebf115dce76486ab1b527f30635", "contentLength": 4886, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-inverter.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-inverter.md", "sections": [ { "id": "section-1", "title": "Complementary CMOS inverter" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Switching power" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does an inverter do to a valid logic input?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "1963 · Wanlass files complementary field-effect circuitry" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#inverter" }, { "title": "Wanlass — US3356858A", "url": "https://patents.google.com/patent/US3356858A/en" }, { "title": "MIT 6.012 — CMOS Inverter Transfer Characteristics", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/b5c8c475943132703a6dd50c479f9714_lec13.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/inverter-ceec9a037236becd.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Two-input CMOS NAND gate", "url": "https://semiaifoundry.com/learn/atlas/nand/" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" } ], "recordHash": "01c5d6f39b3e4929ff4ddcb8e60baf54b3a21673fe3daafdd9ecd5cb52c5e118" }, { "id": "atlas-lesson-iommu-buffer-identity", "title": "IOMMU permission and tensor identity", "category": "learning", "format": "Atlas lesson", "description": "Distinguish protection validity from the semantic identity of a matrix operand.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/iommu-buffer-identity/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Primary sources establish the cited runtime mechanisms. Numerical values, address ranges, ABI strings, event schedule and reset/retry epochs are authored teaching contracts. No real device, firmware image, operating-system driver, page table, cache protocol or security verification is executed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/iommu-buffer-identity-c6226bf1fe320f07.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#iommu-buffer-identity", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ace0ad8a66ccd18f95039805f7bd8bdaeaca763da00d7f04c44a2be4f15e7f67", "contentLength": 6912, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-iommu-buffer-identity.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-iommu-buffer-identity.md", "sections": [ { "id": "section-1", "title": "IOMMU permission and tensor identity" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A complete access must fit its declared range" }, { "id": "section-5", "title": "A wrong alias changes the computed operation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "The B IOVA maps to readable A storage. What does this specimen do?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#iommu-buffer-identity" }, { "title": "Linux 6.16 — Dynamic DMA mapping Guide", "url": "https://docs.kernel.org/6.16/core-api/dma-api-howto.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/iommu-buffer-identity-c6226bf1fe320f07.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Process, physical and device address spaces", "url": "https://semiaifoundry.com/learn/atlas/process-dma-address-spaces/" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" }, { "title": "DMA visibility, ordering and buffer lifetime", "url": "https://semiaifoundry.com/learn/atlas/dma-visibility-ownership/" }, { "title": "Sharded matrix multiplication and result ownership", "url": "https://semiaifoundry.com/learn/atlas/sharded-matmul-ownership/" } ], "recordHash": "283dc3a770aa54ca6d7f545d78ca6bf4f60c8b3662ab93e5df5f2c814f911b75" }, { "id": "atlas-lesson-judge-rubric-agreement", "title": "Human and model judgments under a rubric", "category": "learning", "format": "Atlas lesson", "description": "Separate agreement, task correctness and preference under a reproducible judging rubric.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/judge-rubric-agreement/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-evaluation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Authored binary labels and exact case matching; agreement here is raw agreement, not chance-corrected kappa. Human preference tasks may lack a single factual reference. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/judge-rubric-agreement-ab6bcee550c9490b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#judge-rubric-agreement", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ccce96986180ac4684f85623b423d129464b91b48042c22fad68e84418f76616", "contentLength": 6462, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-judge-rubric-agreement.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-judge-rubric-agreement.md", "sections": [ { "id": "section-1", "title": "Human and model judgments under a rubric" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Human and model judgments under a rubric · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does agreement on case 3 establish?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#judge-rubric-agreement" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "Holistic Evaluation of Language Models", "url": "https://arxiv.org/html/2211.09110v1" }, { "title": "Training language models to follow instructions with human feedback", "url": "https://arxiv.org/html/2203.02155v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/judge-rubric-agreement-ab6bcee550c9490b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "Confidence, errors and refusal to guess", "url": "https://semiaifoundry.com/learn/atlas/probability-calibration-abstention/" }, { "title": "From lexical retrieval to model answers with evidence", "url": "https://semiaifoundry.com/learn/atlas/retrieval-supported-generation/" }, { "title": "Sampling more candidates versus selecting correct ones", "url": "https://semiaifoundry.com/learn/atlas/test-time-search-verification/" }, { "title": "Version the entire evaluated system", "url": "https://semiaifoundry.com/learn/atlas/model-system-regression-contract/" } ], "recordHash": "fca6201957a91423b7b46346bec6a144ec803596f9f222c24b8f9f45599af301" }, { "id": "atlas-lesson-kernel", "title": "GPU kernel and thread hierarchy", "category": "learning", "format": "Atlas lesson", "description": "Maps an operation onto many coordinated logical threads or tiles.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/kernel/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Execution software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Numbers are synthetic and share a precision and byte boundary. The roofline is an upper bound on rate, not a measured runtime; dependencies, occupancy, launch overhead and cache behavior can reduce performance.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/kernel-4d14f06c973afea4.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#kernel", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4017f9b0ea32f49df4e2567504ed0cb53c38b875b4f6efb4e26a27e4456b6cf8", "contentLength": 5329, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-kernel.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-kernel.md", "sections": [ { "id": "section-1", "title": "GPU kernel and thread hierarchy" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Roofline model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Can a normal kernel assume all grid blocks run simultaneously?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#kernel" }, { "title": "NVIDIA CUDA — Programming Model", "url": "https://docs.nvidia.com/cuda/cuda-programming-guide/01-introduction/programming-model.html" }, { "title": "Berkeley Lab — Introduction to Roofline", "url": "https://crd.lbl.gov/assets/Uploads/ECP19-Roofline-1-intro.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/kernel-4d14f06c973afea4.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "CUDA programming and runtime layer", "url": "https://semiaifoundry.com/learn/atlas/cuda/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" }, { "title": "Feed-forward network", "url": "https://semiaifoundry.com/learn/atlas/feed-forward/" } ], "recordHash": "c23cf225eb6f4c4f908d9e3946ee72810f5c93f542b8337b52d4fc3f6703900d" }, { "id": "atlas-lesson-kernel-locality-fusion", "title": "Kernel tiling, fusion and operand reuse", "category": "learning", "format": "Atlas lesson", "description": "Keeps intermediate results close to their next consumer where resource limits allow.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/kernel-locality-fusion/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The calculation is an upper-bound example. Runtime caches and optimized library behavior may reduce the unfused traffic, so actual savings require measurement.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/kernel-locality-fusion-5ebaefca6a873058.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#kernel-locality-fusion", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "878b3639b9b3829d382348ac489eb8287e7f45109feff75b6c9da6cd688780ef", "contentLength": 5036, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-kernel-locality-fusion.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-kernel-locality-fusion.md", "sections": [ { "id": "section-1", "title": "Kernel tiling, fusion and operand reuse" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Intermediate traffic saving" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What direct traffic saving comes from eliminating one N-byte temporary written and then read once?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#kernel-locality-fusion" }, { "title": "XLA:GPU Architecture Overview", "url": "https://openxla.org/xla/gpu_architecture" }, { "title": "CUDA C++ Programming Guide", "url": "https://docs.nvidia.com/cuda/cuda-c-programming-guide/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/kernel-locality-fusion-5ebaefca6a873058.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Compiler layout, lowering and buffer planning", "url": "https://semiaifoundry.com/learn/atlas/compiler-layout-lowering/" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "Occupancy and asynchronous tile pipelines", "url": "https://semiaifoundry.com/learn/atlas/gpu-occupancy-pipeline/" }, { "title": "IO-aware attention and online softmax", "url": "https://semiaifoundry.com/learn/atlas/attention-io-tiling/" } ], "recordHash": "d39496cfd03d5f6bf7876bcc0ffca9f082eb4871d33bc484f46f896ad895bb82" }, { "id": "atlas-lesson-known-good-die-test", "title": "DFT, probe, binning and known-good die", "category": "learning", "format": "Atlas lesson", "description": "Uses designed test access and measurements to screen material before costly assembly.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/known-good-die-test/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Control, test and ramp", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No actual tester coverage or product escape rate is asserted. Dicing routes vary, and not all damage can be detected by the same test.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/known-good-die-test-0f15708098fcc7e5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#known-good-die-test", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "44ff574da57279a3a115a247e37a58b2107fb3af13630ca7ed4f10de1f996202", "contentLength": 5459, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-known-good-die-test.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-known-good-die-test.md", "sections": [ { "id": "section-1", "title": "DFT, probe, binning and known-good die" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Screened defect probability" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why is final package testing still needed after incoming dies passed wafer probe?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#known-good-die-test" }, { "title": "Advantest — Semiconductor test glossary", "url": "https://www.advantest.com/en/investors/ir-library/glossary/" }, { "title": "Intel Foundry — Accelerating HPC and AI", "url": "https://www.intel.com/content/dam/www/central-libraries/us/en/documents/2025-11/intel-foundry-hpc-ai-brief.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/known-good-die-test-0f15708098fcc7e5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer maps and good-die yield", "url": "https://semiaifoundry.com/learn/atlas/yield-wafer-defect-model/" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "Wafer handling, carriers and genealogy", "url": "https://semiaifoundry.com/learn/atlas/wafer-handling-genealogy/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" } ], "recordHash": "f7d286638293e8a0e4db346fa4faf4e94700c084482796a75b7785e96d1f2f56" }, { "id": "atlas-lesson-kv-cache", "title": "Key–value cache", "category": "learning", "format": "Atlas lesson", "description": "Reuse earlier attention state during generation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/kv-cache/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Generation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The formula excludes allocator fragmentation and quantized-cache variants.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/kv-cache-0a723b30e74dbe69.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#kv-cache", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "7adbca0b39793013d27561824c6eb03cd63ffd2744c5846922affff52e8fe5eb", "contentLength": 4837, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-kv-cache.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-kv-cache.md", "sections": [ { "id": "section-1", "title": "Key–value cache" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "The cache grows with every retained position" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Does adding a token to the KV cache retrain the model?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2023 · PagedAttention reorganizes inference memory" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#kv-cache" }, { "title": "Kwon et al. — Efficient Memory Management for Large Language Model Serving with PagedAttention", "url": "https://arxiv.org/abs/2309.06180" }, { "title": "Ainslie et al. — GQA", "url": "https://arxiv.org/abs/2305.13245" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/kv-cache-0a723b30e74dbe69.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" } ], "recordHash": "9b9a5acddba13d8240242cf0bd651c2b17c7cf0a83192825a867340298faf28a" }, { "id": "atlas-lesson-l1-cache", "title": "L1 and texture cache", "category": "learning", "format": "Atlas lesson", "description": "Automatically retains recently accessed data and combines nearby thread requests near an SM.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/l1-cache/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory hierarchy", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The ratio is workload- and access-pattern-specific.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/l1-cache-7101d934167fccaf.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#l1-cache", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3b88af0f776fa234b097935207579e43029892c059b47823b988154e6448f168", "contentLength": 5662, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-l1-cache.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-l1-cache.md", "sections": [ { "id": "section-1", "title": "L1 and texture cache" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Useful bytes versus bytes actually moved" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which access pattern generally makes better use of memory transactions?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#l1-cache" }, { "title": "NVIDIA CUDA Blackwell Tuning Guide", "url": "https://docs.nvidia.com/cuda/blackwell-tuning-guide/index.html" }, { "title": "NVIDIA CUDA C++ Best Practices Guide", "url": "https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/index.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/l1-cache-7101d934167fccaf.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "Shared L2 cache", "url": "https://semiaifoundry.com/learn/atlas/l2-cache/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" } ], "recordHash": "9523acec3a267d7ddf16691bef0f54a14224d7d1b550b767a6ccb0b3b79f7a61" }, { "id": "atlas-lesson-l2-cache", "title": "Shared L2 cache", "category": "learning", "format": "Atlas lesson", "description": "Provides a larger on-chip reuse layer between SM traffic and HBM.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/l2-cache/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory hierarchy", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "AMAT is an average model and does not capture overlap or queue contention.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/l2-cache-26b3463fc4abe144.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#l2-cache", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9c3917d4a3b1c2be736adae2304f9b7941234ab701837462ae9a71bacdd8de5a", "contentLength": 5366, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-l2-cache.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-l2-cache.md", "sections": [ { "id": "section-1", "title": "Shared L2 cache" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Average access cost across two cache levels" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "When does a larger L2 cache most directly help?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#l2-cache" }, { "title": "NVIDIA CUDA Blackwell Tuning Guide", "url": "https://docs.nvidia.com/cuda/blackwell-tuning-guide/index.html" }, { "title": "NVIDIA: GPU locality domains and L2 fabric", "url": "https://developer.nvidia.com/blog/accelerating-data-processing-with-nvidia-multi-instance-gpu-and-numa-node-localization/" }, { "title": "MIT Computation Structures: cache hierarchy and average access time", "url": "https://ocw.mit.edu/courses/6-004-computation-structures-spring-2017/pages/c14/c14s1/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/l2-cache-26b3463fc4abe144.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "L1 and texture cache", "url": "https://semiaifoundry.com/learn/atlas/l1-cache/" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" }, { "title": "HBM controller and PHY", "url": "https://semiaifoundry.com/learn/atlas/hbm-controller/" } ], "recordHash": "41c658a10bf525907f25c5293861dca853584fc514e9b62f055e78af4ae16573" }, { "id": "atlas-lesson-leaf-switch", "title": "Leaf switch and endpoint network", "category": "learning", "format": "Atlas lesson", "description": "Connects compute or service endpoints to the broader data-center fabric.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/leaf-switch/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center fabric", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "These are hypothetical comparable one-direction payload capacities. The ratio is a port-budget bound, not a prediction of local traffic, collective completion time, congestion control or application throughput.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/leaf-switch-e818b606ed058bca.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#leaf-switch", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f94257aa3529c2280820244b172983890f4a579a66a1fa7a2b4c58ac2091b59e", "contentLength": 5021, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-leaf-switch.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-leaf-switch.md", "sections": [ { "id": "section-1", "title": "Leaf switch and endpoint network" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Oversubscription ratio" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is a leaf switch’s main topology role?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#leaf-switch" }, { "title": "NVIDIA — NVL72 AI Factory Network Logical Architecture", "url": "https://docs.nvidia.com/enterprise-reference-architectures/nvl72-ai-factory/latest/network-logical-architecture.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/leaf-switch-e818b606ed058bca.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" }, { "title": "Spine switching and fabric topology", "url": "https://semiaifoundry.com/learn/atlas/spine-switch/" }, { "title": "Optical transceiver and fiber link", "url": "https://semiaifoundry.com/learn/atlas/optics/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "Dataset and checkpoint storage hierarchy", "url": "https://semiaifoundry.com/learn/atlas/storage/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" } ], "recordHash": "b0e075a2f603b6f7500c0dd051406ed5852eb8aefc292b05d4567ca981e67b09" }, { "id": "atlas-lesson-linear-map-rank-subspace", "title": "Linear maps, rank and retained directions", "category": "learning", "format": "Atlas lesson", "description": "Shows how a large array can represent fewer independent transformations than its number of entries suggests.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/linear-map-rank-subspace/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "mathematical-foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. Real symmetric two-dimensional constructed map with orthonormal u and v and 0 ≤ σ₂ ≤ 3. This is not an arbitrary-matrix SVD solver.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/linear-map-rank-subspace-6d5d7f3d04fa2d71.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#linear-map-rank-subspace", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "404076b6aa1c3efe4a63d53fe74da70231f5155ec87610cdc09049578106cc9d", "contentLength": 5857, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-linear-map-rank-subspace.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-linear-map-rank-subspace.md", "sections": [ { "id": "section-1", "title": "Linear maps, rank and retained directions" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Linear maps, rank and retained directions" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What stays unchanged when this orthogonal basis is rotated?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#linear-map-rank-subspace" }, { "title": "Goodfellow, Bengio and Courville · Linear algebra", "url": "https://www.deeplearningbook.org/contents/linear_algebra.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/linear-map-rank-subspace-6d5d7f3d04fa2d71.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tensor shapes, indices and contractions", "url": "https://semiaifoundry.com/learn/atlas/tensor-index-contracts/" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Feed-forward network", "url": "https://semiaifoundry.com/learn/atlas/feed-forward/" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" } ], "recordHash": "8feab2aa141dbfcf1712d50eec3dc53ad2ba55a49017d15212a85200a5e637c7" }, { "id": "atlas-lesson-lithography", "title": "Lithography and pattern transfer", "category": "learning", "format": "Atlas lesson", "description": "Turns a circuit pattern into spatially selected regions on a wafer.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/lithography/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The variables are illustrative; stochastic variation, overlay and a qualified process window are separate.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/lithography-cc3bc7e0fe2c8194.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#lithography", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "286c9615cccb187f50128d402221b87f48b34d602244ba2785d29112f25d9dee", "contentLength": 5335, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-lithography.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-lithography.md", "sections": [ { "id": "section-1", "title": "Lithography and pattern transfer" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Rayleigh resolution relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does lithographic exposure directly create?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2010 · Pre-production NXE:3100 EUV system ships" }, { "id": "section-13", "title": "2013 · First NXE:3300 production EUV system ships" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#lithography" }, { "title": "ASML — Making EUV: From Lab to Fab", "url": "https://www.asml.com/en/company/stories/2022/making-euv-lab-to-fab" }, { "title": "ASML — Light and Lasers", "url": "https://www.asml.com/en/technology/lithography-principles/light-and-lasers" }, { "title": "ASML — Rayleigh Criterion", "url": "https://www.asml.com/en/technology/lithography-principles/rayleigh-criterion" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/lithography-cc3bc7e0fe2c8194.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer and fabrication hierarchy", "url": "https://semiaifoundry.com/learn/atlas/silicon-wafer/" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Chemical mechanical planarization", "url": "https://semiaifoundry.com/learn/atlas/cmp/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" } ], "recordHash": "ab0b93f5b8c715d4f5292d06a992d24f486e29c7dac941f5ac7cce8adb3c8061" }, { "id": "atlas-lesson-lithography-resolution-focus", "title": "DUV, EUV and high-NA imaging", "category": "learning", "format": "Atlas lesson", "description": "Explains the coupled resolution and focus consequences of wavelength and numerical aperture.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/lithography-resolution-focus/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Repeated operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Ratios are illustrative, not a comparison of fully specified production scanners. High-NA demonstrations and production availability belong in separately dated evidence cards.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/lithography-resolution-focus-6c6d86f32df07b06.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#lithography-resolution-focus", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3b5b32f95bcd4cef9440316a0c5f495a08973dca970ff10952967f0789acd86f", "contentLength": 5161, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-lithography-resolution-focus.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-lithography-resolution-focus.md", "sections": [ { "id": "section-1", "title": "DUV, EUV and high-NA imaging" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Optical scaling" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "At fixed wavelength and model factors, what happens when NA increases?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#lithography-resolution-focus" }, { "title": "ASML — How microchips are made", "url": "https://www.asml.com/en/technology/all-about-microchips/how-microchips-are-made" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "ASML and imec — Joint High NA EUV Lithography Lab opens", "url": "https://www.asml.com/en/news/press-releases/2024/asml-imec-opening-high-na-euv-lithography-lab" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/lithography-resolution-focus-6c6d86f32df07b06.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Lithography and pattern transfer", "url": "https://semiaifoundry.com/learn/atlas/lithography/" }, { "title": "Masks, OPC and pattern-aware design", "url": "https://semiaifoundry.com/learn/atlas/mask-opc-layout/" }, { "title": "Wafer finishing, orientation and geometry", "url": "https://semiaifoundry.com/learn/atlas/wafer-finishing-geometry/" } ], "recordHash": "9a4ac1788ed0352aef2bd124d214586a5abcef5c2bdebb02c1433ce82dcef565" }, { "id": "atlas-lesson-loaded-inverter-transition", "title": "Loaded CMOS transfer, noise and transition delay", "category": "learning", "format": "Atlas lesson", "description": "Compare the same cell’s DC voltage-transfer contract with its explicitly loaded charging and discharging behavior.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/loaded-inverter-transition/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Devices and logic", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The physical equations and conventions are primary-source informed. The parameter values, corners, constraints and results are authored teaching choices; no commercial process or human specialist review is represented.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/loaded-inverter-transition-937b321ffb29b496.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#loaded-inverter-transition", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "2b59bac1b8b3073e212ad85a8ab6914b768dec825d5670c315c17a827dc6abd5", "contentLength": 9843, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-loaded-inverter-transition.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-loaded-inverter-transition.md", "sections": [ { "id": "section-1", "title": "Loaded CMOS transfer, noise and transition delay" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Piecewise long-channel current magnitude" }, { "id": "section-5", "title": "One output load connects to the following gates" }, { "id": "section-6", "title": "Loaded delay from the current integral" }, { "id": "section-7", "title": "Use the actual unity-gain output levels" }, { "id": "section-8", "title": "Engineering example" }, { "id": "section-9", "title": "Distinctions and tradeoffs" }, { "id": "section-10", "title": "Specifications and interfaces" }, { "id": "section-11", "title": "Interfaces" }, { "id": "section-12", "title": "Check your understanding" }, { "id": "section-13", "title": "Fanout rises from one to four identical loads while device parameters stay fixed. Which result changes in this model?" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#loaded-inverter-transition" }, { "title": "MIT 6.012 Fall 2005 — Lecture 9", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/5c5960f14ae37d0a65478c4f3f628d98_lec9.pdf" }, { "title": "MIT 6.012 Fall 2005 — Lecture 10", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/0498bbf0f0e585507d9cfe5dc3bd54b1_lec10.pdf" }, { "title": "MIT 6.012 Fall 2005 — Lecture 12", "url": "https://www.ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/74c08e0cdcdab837d4eaceaf2384d646_lec12.pdf" }, { "title": "MIT 6.012 Fall 2005 — Lecture 14", "url": "https://www.ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/6bec6dd1b07b02a1a84098b78f068cc3_lec14.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/loaded-inverter-transition-937b321ffb29b496.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Oxide variation to electrical cell acceptance", "url": "https://semiaifoundry.com/learn/atlas/oxide-to-cell-acceptance/" }, { "title": "Complementary CMOS inverter", "url": "https://semiaifoundry.com/learn/atlas/inverter/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" } ], "recordHash": "87701e017caf0da748cef8672ce8cec608030ca1feff06ee6081c552bd4a6190" }, { "id": "atlas-lesson-long-context-adaptation", "title": "Context extension is a learned-use test", "category": "learning", "format": "Atlas lesson", "description": "Separate accepted context length, causal correctness, memory growth and demonstrated long-distance use.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/long-context-adaptation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-continuation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Uncompressed full KV payload with no sharing or overhead. This lesson is a worked extension; the lifecycle core has at most eight input positions and does not implement YaRN. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/long-context-adaptation-2a11cf9f6ad5a9fe.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#long-context-adaptation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "627d090d975687c89504322e74b906bf34096c51bc4b601edacdef80b325cceb", "contentLength": 6480, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-long-context-adaptation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-long-context-adaptation.md", "sections": [ { "id": "section-1", "title": "Context extension is a learned-use test" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Context extension is a learned-use test · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which observation establishes storage capacity but not learned long-distance use?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#long-context-adaptation" }, { "title": "YaRN: Efficient Context Window Extension of Large Language Models", "url": "https://arxiv.org/html/2309.00071v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/long-context-adaptation-2a11cf9f6ad5a9fe.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Position representation", "url": "https://semiaifoundry.com/learn/atlas/positional-encoding/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Continue language modeling on a new domain", "url": "https://semiaifoundry.com/learn/atlas/domain-adaptive-continuation/" }, { "title": "Describe a stage by its changed contract", "url": "https://semiaifoundry.com/learn/atlas/model-lifecycle-stage-contract/" }, { "title": "Retention, replay and transfer", "url": "https://semiaifoundry.com/learn/atlas/replay-retention-forgetting/" }, { "title": "Compatible weight averaging and regressions", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-averaging-boundaries/" } ], "recordHash": "45ea46ac699f2cb9c5000c4d74895a6492d45ba8edec2dc15af0a9466853780a" }, { "id": "atlas-lesson-loss-optimizer", "title": "Loss, gradients & optimizer", "category": "learning", "format": "Atlas lesson", "description": "Turn prediction errors into parameter updates.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/loss-optimizer/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Learning", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This follows the ordinary Adam equations in the linked paper. The gradient is supplied rather than derived here; clipping, weight decay, loss scaling and sharded optimizer state are excluded. Computing a gradient and applying an update remain separate steps.\n\nThe threshold arithmetic is authored. The existing sensor experience executes actual logistic updates, while these three probabilities are a separate worked decision example.\n\nMode: executable derived-gradient optimizer. No weight decay or AMSGrad; elementwise squares/division. First-step worked values use an unclipped scalar gradient of 0.5. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/loss-optimizer-75b6c32e6a4f283f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#loss-optimizer", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ddbc8617107da8278f984b282ddc898917f573899b7525d02b8846ec4009dc8f", "contentLength": 11602, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-loss-optimizer.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-loss-optimizer.md", "sections": [ { "id": "section-1", "title": "Loss, gradients & optimizer" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Adam adapts updates using gradient moments" }, { "id": "section-5", "title": "Compute gradients before applying the optimizer · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Which process changes learned weights in a normal training step?" }, { "id": "section-12", "title": "A decision threshold changes from 0.5 to 0.7 with fixed model outputs. What necessarily changes?" }, { "id": "section-13", "title": "Why is the first Adam change about 0.1 rather than 0.05?" }, { "id": "section-14", "title": "Historical context" }, { "id": "section-15", "title": "2014 · Adam combines momentum with adaptive scaling" }, { "id": "section-16", "title": "Evidence and scope" }, { "id": "section-17", "title": "Sources" }, { "id": "section-18", "title": "Continue exploring" }, { "id": "section-19", "title": "Foundations" }, { "id": "section-20", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#loss-optimizer" }, { "title": "Kingma & Ba — Adam: A Method for Stochastic Optimization", "url": "https://arxiv.org/abs/1412.6980" }, { "title": "PyTorch — CrossEntropyLoss", "url": "https://docs.pytorch.org/docs/2.14/generated/torch.nn.CrossEntropyLoss.html" }, { "title": "scikit-learn · Common pitfalls and data leakage", "url": "https://scikit-learn.org/stable/common_pitfalls.html#data-leakage" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "PyTorch Adam algorithm", "url": "https://docs.pytorch.org/docs/2.14/generated/torch.optim.Adam.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/loss-optimizer-75b6c32e6a4f283f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Residual stream & normalization", "url": "https://semiaifoundry.com/learn/atlas/residual-normalization/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Model artifacts, rollout and drift", "url": "https://semiaifoundry.com/learn/atlas/model-artifact-rollout-drift/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Next-token supervision from raw sequences", "url": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/" }, { "title": "Initialization, learning rate and stable updates", "url": "https://semiaifoundry.com/learn/atlas/optimizer-schedule-stability/" }, { "title": "Gradient accumulation under a fixed global objective", "url": "https://semiaifoundry.com/learn/atlas/microbatch-equivalent-updates/" } ], "recordHash": "2b505d4c1b11fd12ba6a7300e0fdebbef2e16af440ab5e3058c782e6cf3e419b" }, { "id": "atlas-lesson-low-rank-adaptation", "title": "Frozen base weights and trainable adapters", "category": "learning", "format": "Atlas lesson", "description": "Multiply a low-rank update and count trainable factors without confusing them with the training objective.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/low-rank-adaptation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-posttraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Rank one, d=4, k=6 and alpha/r=1 in the example. Biases and any additional adapted matrices are excluded. Worked-only parameterization. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/low-rank-adaptation-3726097baa621ba3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#low-rank-adaptation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "d423b4b35c014e771cc64b17500150e20a2353c95b14a81382f564559c15c5c8", "contentLength": 6329, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-low-rank-adaptation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-low-rank-adaptation.md", "sections": [ { "id": "section-1", "title": "Frozen base weights and trainable adapters" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Frozen base weights and trainable adapters · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the number 10 count?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#low-rank-adaptation" }, { "title": "LoRA: Low-Rank Adaptation of Large Language Models", "url": "https://arxiv.org/html/2106.09685v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/low-rank-adaptation-3726097baa621ba3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Linear maps, rank and retained directions", "url": "https://semiaifoundry.com/learn/atlas/linear-map-rank-subspace/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Sharded matrix multiplication and result ownership", "url": "https://semiaifoundry.com/learn/atlas/sharded-matmul-ownership/" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "DPO policy/reference likelihood ratios", "url": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Verifiers, grouped advantages and RLVR", "url": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/" } ], "recordHash": "063ea7c2734e3f12346bd5278e965e0de585cb9ceb8adde78ccdd6958d40b614" }, { "id": "atlas-lesson-lpddr-memory", "title": "Grace LPDDR5X memory", "category": "learning", "format": "Atlas lesson", "description": "Provides the Grace CPU’s local main memory with short, energy-conscious package and board connections.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/lpddr-memory/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Host platform", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "These rates are synthetic, not Grace specifications. The linked architecture documents establish distinct CPU memory and HBM paths; payload direction, configuration, cache effects and attained bandwidth must be specified.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/lpddr-memory-478a539325968c92.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#lpddr-memory", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3b57b78e069101310690f4f01fcb1f2d2510b5ef41330538b9a7f2d6a8520f04", "contentLength": 6554, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-lpddr-memory.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-lpddr-memory.md", "sections": [ { "id": "section-1", "title": "Grace LPDDR5X memory" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Coherence does not remove path bottlenecks" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why distinguish CPU LPDDR from GPU HBM in a coherent system?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2022 · Grace CPU Superchip announces server LPDDR5X integration" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#lpddr-memory" }, { "title": "NVIDIA: Grace CPU Superchip announcement", "url": "https://nvidianews.nvidia.com/news/nvidia-introduces-grace-cpu-superchip" }, { "title": "NVIDIA GB200 NVL72 specifications", "url": "https://www.nvidia.com/en-us/data-center/gb200-nvl72/" }, { "title": "NVIDIA: Inside Grace CPU architecture", "url": "https://developer.nvidia.com/blog/inside-nvidia-grace-cpu-nvidia-amps-up-superchip-engineering-for-hpc-and-ai/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/lpddr-memory-478a539325968c92.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DDR5 server memory", "url": "https://semiaifoundry.com/learn/atlas/ddr-memory/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Grace Blackwell Superchip", "url": "https://semiaifoundry.com/learn/atlas/grace-blackwell-superchip/" } ], "recordHash": "1af418423f6846eaa96552a77217ecda49fa060d28a5e443e306568e66df68bf" }, { "id": "atlas-lesson-mac", "title": "Multiply–accumulate and fused arithmetic", "category": "learning", "format": "Atlas lesson", "description": "Combines products into the accumulated sums used by dot products and matrices.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/mac/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Arithmetic circuits", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The dot-product identity is exact; the linked floating-point discussion explains why FMA and separately rounded operations can differ. This integer example assumes enough range and does not demonstrate floating-point error.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/mac-7944bf0787592b72.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#mac", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "14251146ae8bf720ffe32f0c12b94fbf1bbb76f40c2995e0f3666de592c22578", "contentLength": 5176, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-mac.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-mac.md", "sections": [ { "id": "section-1", "title": "Multiply–accumulate and fused arithmetic" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Dot product and matrix entry" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What distinguishes floating-point FMA from separately rounded multiply and add?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#mac" }, { "title": "NVIDIA CUDA — Floating-Point Computation and FMA", "url": "https://docs.nvidia.com/cuda/cuda-programming-guide/05-appendices/mathematical-functions.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/mac-7944bf0787592b72.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Binary multiplier and partial-product reduction", "url": "https://semiaifoundry.com/learn/atlas/multiplier/" }, { "title": "Full adder and carry network", "url": "https://semiaifoundry.com/learn/atlas/adder/" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" } ], "recordHash": "29bece564d85b2efd5dc37c4c1960dd6ce165541ada52f05c123f42df2c11e40" }, { "id": "atlas-lesson-management-controller", "title": "Baseboard management controller", "category": "learning", "format": "Atlas lesson", "description": "Monitors and controls hardware through a management path separate from the main workload.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/management-controller/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Operations and reliability", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is an ideal detection-time model, not a BMC service guarantee. Transient faults, missed polls, thresholds, retries and alert processing alter detection; the model and management networks remain separate functions.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/management-controller-0258525821be0014.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#management-controller", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "93019569faff4379bc6ba5124a01c9baf183df8e625cddad1f7646055241c6b2", "contentLength": 6174, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-management-controller.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-management-controller.md", "sections": [ { "id": "section-1", "title": "Baseboard management controller" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Polling cadence limits fault detection delay" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why keep management traffic separate from training tensors?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#management-controller" }, { "title": "NVIDIA DGX GB rack systems networking guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/networking.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/management-controller-0258525821be0014.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "Power supply and power shelf", "url": "https://semiaifoundry.com/learn/atlas/power-supply/" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" } ], "recordHash": "31024f529afbc9d642172166cfad879023d4542adca9a222482c272618ce543e" }, { "id": "atlas-lesson-manufacturing-execution-dispatch", "title": "MES, dispatch and process release", "category": "learning", "format": "Atlas lesson", "description": "Coordinates material routes, equipment eligibility, holds and measurement decisions.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/manufacturing-execution-dispatch/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Factory systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "TSMC describes public capabilities, not its proprietary rules, live queues or customer priority policy. The lesson uses generic operations reasoning.\n\nThe scenario is fictional and qualitative. No manufacturing recipe, production dispatch scheduler, equipment interface or real lot release is executed or inferred.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/manufacturing-execution-dispatch-bd3550e94e978ca6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#manufacturing-execution-dispatch", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "cb37740961a7aa505e4a5c72ed43bf0b4560606f775c1cd128836b9d12665be6", "contentLength": 7170, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-manufacturing-execution-dispatch.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-manufacturing-execution-dispatch.md", "sections": [ { "id": "section-1", "title": "MES, dispatch and process release" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Flow conservation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can maximizing every tool’s utilization increase cycle time?" }, { "id": "section-11", "title": "A model recommends processing a held lot. What establishes whether dispatch may proceed?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#manufacturing-execution-dispatch" }, { "title": "TSMC — Intelligent Packaging Fab", "url": "https://www.tsmc.com/english/dedicatedFoundry/services/apm_intelligent_packaging_fab" }, { "title": "Edwards — Semiconductor vacuum and abatement", "url": "https://www.edwardsvacuum.com/en-us/semiconductor" }, { "title": "Temporal Activities", "url": "https://docs.temporal.io/activities" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/manufacturing-execution-dispatch-bd3550e94e978ca6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer handling, carriers and genealogy", "url": "https://semiaifoundry.com/learn/atlas/wafer-handling-genealogy/" }, { "title": "Cycle time, ramp and effective capacity", "url": "https://semiaifoundry.com/learn/atlas/fab-ramp-cycle-time/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" }, { "title": "User authority and service identity", "url": "https://semiaifoundry.com/learn/atlas/tool-authority-identity/" }, { "title": "Workflow graphs and explicit state", "url": "https://semiaifoundry.com/learn/atlas/workflow-graphs-state/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "8e454f89a0c4bda146f12750052e8c608c159595fa2e715bf25dce2a40403a0e" }, { "id": "atlas-lesson-mask-opc-layout", "title": "Masks, OPC and pattern-aware design", "category": "learning", "format": "Atlas lesson", "description": "Pre-distorts a mask so the process prints a desired wafer pattern.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/mask-opc-layout/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Repeated operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The mask schematic omits proprietary correction algorithms and exact design rules. No vendor node is equated with a single printable dimension.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/mask-opc-layout-60eb587374a8eac3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#mask-opc-layout", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "24112ff4109503a458d2c6937ba20ccb30b92e468e880d252f76b325ef8bb3d9", "contentLength": 5379, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-mask-opc-layout.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-mask-opc-layout.md", "sections": [ { "id": "section-1", "title": "Masks, OPC and pattern-aware design" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Edge-error objective" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why test a corrected mask across focus and exposure conditions?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#mask-opc-layout" }, { "title": "ASML — How microchips are made", "url": "https://www.asml.com/en/technology/all-about-microchips/how-microchips-are-made" }, { "title": "KLA — Practical Applications of Measurement System Analysis", "url": "https://www.kla.com/documents/5.3_Practical_Applications_of_MSA_Sutherland_KLA.pdf" }, { "title": "Applied Materials — New Ways to Shrink", "url": "https://ir.appliedmaterials.com/static-files/f2fbf48d-a761-4c4f-ab4c-73f312ab1ebc" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/mask-opc-layout-60eb587374a8eac3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Lithography and pattern transfer", "url": "https://semiaifoundry.com/learn/atlas/lithography/" }, { "title": "Coat, bake, expose and develop", "url": "https://semiaifoundry.com/learn/atlas/resist-track-development/" }, { "title": "DUV, EUV and high-NA imaging", "url": "https://semiaifoundry.com/learn/atlas/lithography-resolution-focus/" }, { "title": "Metrology, inspection and process windows", "url": "https://semiaifoundry.com/learn/atlas/fab-metrology-process-window/" } ], "recordHash": "5a4ddf4954c887cf3732d98507e372c2e559bddbfe817b02a42455e16ec7f209" }, { "id": "atlas-lesson-mcp-host-client-server", "title": "A tool protocol is a boundary", "category": "learning", "format": "Atlas lesson", "description": "Version-pinned MCP host/client/server roles, schema discovery, invocation and errors.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/mcp-host-client-server/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Authority, context and execution boundaries", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. The reference edition is MCP 2026-07-28. This is a worked protocol explanation, not an executing MCP client/server or conformance test.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/mcp-host-client-server-0e820e6ae04e5210.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#mcp-host-client-server", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "156e8be193fb111398fb645cde5c2764d3e86ede96b26154a95772290685e669", "contentLength": 6353, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-mcp-host-client-server.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-mcp-host-client-server.md", "sections": [ { "id": "section-1", "title": "A tool protocol is a boundary" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A tool protocol is a boundary · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does successful tool discovery establish?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#mcp-host-client-server" }, { "title": "Model Context Protocol specification", "url": "https://modelcontextprotocol.io/specification/2026-07-28" }, { "title": "MCP tools", "url": "https://modelcontextprotocol.io/specification/2026-07-28/server/tools" }, { "title": "MCP authorization", "url": "https://modelcontextprotocol.io/specification/2026-07-28/basic/authorization" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/mcp-host-client-server-0e820e6ae04e5210.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tool schemas and semantic validation", "url": "https://semiaifoundry.com/learn/atlas/tool-contracts-schemas/" }, { "title": "User authority and service identity", "url": "https://semiaifoundry.com/learn/atlas/tool-authority-identity/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "d9c478a755add7fd18b00a9d90bbd04638e6558670a734b2d3f706f97d888003" }, { "id": "atlas-lesson-memory-hierarchy-route", "title": "Full memory hierarchy and input path", "category": "learning", "format": "Atlas lesson", "description": "Tracks data through storage, host memory, accelerator memory, caches and operand storage.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Custom silicon ecosystem", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The route is representative, not universal. Direct-storage and coherent-memory alternatives need their own labeled interfaces and measured traffic.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-hierarchy-route-979f8294c7e13fae.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#memory-hierarchy-route", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "6fbc136f08c4467897cdc15d178791b0993771ebcd28c06c2d399b4b461bb15c", "contentLength": 5270, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-hierarchy-route.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-hierarchy-route.md", "sections": [ { "id": "section-1", "title": "Full memory hierarchy and input path" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Boundary transfer floor" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A kernel’s register use causes spills. Where should diagnosis begin?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#memory-hierarchy-route" }, { "title": "CUDA C++ Programming Guide", "url": "https://docs.nvidia.com/cuda/cuda-c-programming-guide/" }, { "title": "What is NUMA? Linux kernel 6.6 documentation", "url": "https://www.kernel.org/doc/html/v6.6/mm/numa.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-hierarchy-route-979f8294c7e13fae.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "DDR5 server memory", "url": "https://semiaifoundry.com/learn/atlas/ddr-memory/" }, { "title": "Dataset and checkpoint storage hierarchy", "url": "https://semiaifoundry.com/learn/atlas/storage/" }, { "title": "NVMe solid-state storage", "url": "https://semiaifoundry.com/learn/atlas/nvme-storage/" }, { "title": "Choosing SRAM, HBM, DDR, LPDDR or GDDR", "url": "https://semiaifoundry.com/learn/atlas/memory-interface-choice/" } ], "recordHash": "3c6e01b3027e6456373ea76c2f5592b08c4f74d82d84ce6bf0cefa3162483bf1" }, { "id": "atlas-lesson-memory-interface-choice", "title": "Choosing SRAM, HBM, DDR, LPDDR or GDDR", "category": "learning", "format": "Atlas lesson", "description": "Matches memory technology and package integration to a workload’s access pattern.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/memory-interface-choice/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Custom silicon ecosystem", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Pin counts and rates in the example are synthetic. No contemporary contract price, universal HBM advantage or interchangeable memory-controller compatibility is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-interface-choice-7da0c849a214bfc9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#memory-interface-choice", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "84c96e236fec744450170fcc1600b0b71f0798e0cff701815e7b5c27dfb8cc66", "contentLength": 5210, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-interface-choice.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-interface-choice.md", "sections": [ { "id": "section-1", "title": "Choosing SRAM, HBM, DDR, LPDDR or GDDR" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Raw interface rate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which change can raise aggregate bandwidth without raising per-pin rate?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#memory-interface-choice" }, { "title": "Graphics memory", "url": "https://www.micron.com/products/memory/graphics-memory" }, { "title": "MTIA v1: Meta’s first-generation AI inference accelerator", "url": "https://ai.meta.com/blog/meta-training-inference-accelerator-AI-MTIA/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-interface-choice-7da0c849a214bfc9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Full memory hierarchy and input path", "url": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "DDR5 server memory", "url": "https://semiaifoundry.com/learn/atlas/ddr-memory/" }, { "title": "Grace LPDDR5X memory", "url": "https://semiaifoundry.com/learn/atlas/lpddr-memory/" }, { "title": "Custom inference silicon: Maia and MTIA", "url": "https://semiaifoundry.com/learn/atlas/inference-custom-silicon/" } ], "recordHash": "e304482b0ca6121b861bc7b2017b459b6827e3277fbee5928d732bbfa46657af" }, { "id": "atlas-lesson-memory-system-qualification", "title": "Qualify the memory system and retain useful work", "category": "learning", "format": "Atlas lesson", "description": "Separate component screening, integration qualification, commissioning and sustained service evidence.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/memory-system-qualification/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Qualification criteria depend on the actual product and deployment; the atlas gives an evidence sequence, not vendor-approved limits. Proposed HBF systems remain proposed until corresponding integration and operational evidence exists.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-system-qualification-575943caf971f760.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#memory-system-qualification", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "e5f7d3d7006c0d7ee8687c32748908ead39477624552327ed8852f8d6a00bc7a", "contentLength": 6084, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-system-qualification.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-system-qualification.md", "sections": [ { "id": "section-1", "title": "Qualify the memory system and retain useful work" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Retained work accounting" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A new memory component has a published specification. What establishes system readiness?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#memory-system-qualification" }, { "title": "NVIDIA — DGX GB rack hardware guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "UCIe — introduction Q&A recap", "url": "https://www.uciexpress.org/post/introduction-to-ucie-webinar-q-a-recap" }, { "title": "Sandisk — release of first OCP HBF specification", "url": "https://investor.sandisk.com/node/8126/pdf" }, { "title": "Semi AI Foundry — Communication Theory of Computation Realization", "url": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-system-qualification-575943caf971f760.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "From memory placement to network, power and cooling", "url": "https://semiaifoundry.com/learn/atlas/memory-to-hall-propagation/" }, { "title": "HBM heat, assembly yield and test access", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-thermal-yield/" }, { "title": "Commissioning a usable AI cluster", "url": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/" }, { "title": "Checkpointing, failure and retained useful work", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-retained-work/" }, { "title": "Verification closes the realization loop", "url": "https://semiaifoundry.com/learn/atlas/crg-verification-loop/" }, { "title": "HBF: a read-oriented tier and its evidence boundary", "url": "https://semiaifoundry.com/learn/atlas/hbf-read-tier-contract/" }, { "title": "Underfill, warpage, thermal paths and qualification", "url": "https://semiaifoundry.com/learn/atlas/package-thermomechanical-reliability/" } ], "recordHash": "c6c2249c4de2e0455201e7b725e25f4fb6c0fedb7ed0ddd57a3ccb179843bb80" }, { "id": "atlas-lesson-memory-to-hall-propagation", "title": "From memory placement to network, power and cooling", "category": "learning", "format": "Atlas lesson", "description": "Trace how a tensor-placement decision changes link demand and useful service at the hall boundary.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/memory-to-hall-propagation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "All numerical values are scenario inputs. No relationship between a megawatt and tokens is assumed without a named workload. CRG provides an attributed way to organize these realization boundaries; the arithmetic is a resource-accounting model.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-to-hall-propagation-1502229faf4cfc16.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#memory-to-hall-propagation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1521593380dabb522766151d28118624e915648e7e02773a036506fb0c2d13ee", "contentLength": 6802, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-to-hall-propagation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-to-hall-propagation.md", "sections": [ { "id": "section-1", "title": "From memory placement to network, power and cooling" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Resource-normalized service bound" }, { "id": "section-5", "title": "Energy per accepted work" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "A placement change lowers HBM traffic but doubles remote transfers. What should be compared?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#memory-to-hall-propagation" }, { "title": "NVIDIA — DGX GB rack hardware guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "MIT OpenCourseWare — Introduction to Heat Transfer", "url": "https://ocw.mit.edu/courses/2-051-introduction-to-heat-transfer-fall-2015/" }, { "title": "NVIDIA — Mastering LLM Techniques: Inference Optimization", "url": "https://developer.nvidia.com/blog/mastering-llm-techniques-inference-optimization/" }, { "title": "Semi AI Foundry — Communication Theory of Computation Realization", "url": "https://semiaifoundry.com/updates/communication-theory-of-computation-realization/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-to-hall-propagation-1502229faf4cfc16.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Place the working set, not just the model", "url": "https://semiaifoundry.com/learn/atlas/memory-working-set-placement/" }, { "title": "Collective traffic and congestion", "url": "https://semiaifoundry.com/learn/atlas/fabric-collective-traffic/" }, { "title": "Cold plates, manifolds and separated coolant loops", "url": "https://semiaifoundry.com/learn/atlas/coolant-loop-separation/" }, { "title": "Qualify the memory system and retain useful work", "url": "https://semiaifoundry.com/learn/atlas/memory-system-qualification/" }, { "title": "Package and system preserve the contract", "url": "https://semiaifoundry.com/learn/atlas/crg-package-system-closure/" }, { "title": "Verification closes the realization loop", "url": "https://semiaifoundry.com/learn/atlas/crg-verification-loop/" }, { "title": "Commissioning a usable AI cluster", "url": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/" } ], "recordHash": "d81444484bd500edc50e2d2675591d7761b71fdcd31be6200a09fb28fd86f6fa" }, { "id": "atlas-lesson-memory-wall-trends", "title": "Historical memory-wall evidence", "category": "learning", "format": "Atlas lesson", "description": "Separates historical fitted compute, bandwidth and capacity trends from workload diagnosis.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/memory-wall-trends/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Custom silicon ecosystem", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The three numerical historical fits appear only in separate claim records. Figure 2’s memory/6 plotting convention is not a universal training-state formula or an updated forecast.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-wall-trends-109a75fba8791b9f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#memory-wall-trends", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "402b258f60e7e0eb29c326dc71926ca2d3d5a61dbc03899c813a6e2f34827225", "contentLength": 5443, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-wall-trends.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-wall-trends.md", "sections": [ { "id": "section-1", "title": "Historical memory-wall evidence" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Roofline bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a model fit in HBM yet run slowly?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#memory-wall-trends" }, { "title": "AI and Memory Wall, version 1", "url": "https://arxiv.org/html/2403.14123v1" }, { "title": "Roofline: An Insightful Visual Performance Model for Floating-Point Programs and Multicore Architectures", "url": "https://www2.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-134.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-wall-trends-109a75fba8791b9f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Full memory hierarchy and input path", "url": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Training state and activation rematerialization", "url": "https://semiaifoundry.com/learn/atlas/training-memory-state/" }, { "title": "Prefill and prompt processing", "url": "https://semiaifoundry.com/learn/atlas/prefill-resource-trace/" }, { "title": "Autoregressive decode and weight traffic", "url": "https://semiaifoundry.com/learn/atlas/decode-bandwidth-trace/" } ], "recordHash": "318b96334bdbab6d345fffd29a843b24d60949419f038cb8d3958ebcc8063bf0" }, { "id": "atlas-lesson-memory-working-set-placement", "title": "Place the working set, not just the model", "category": "learning", "format": "Atlas lesson", "description": "Assign tensor state to tiers using lifetime, mutation, reuse distance, access size and latency requirements.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/memory-working-set-placement/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The placement framework is an engineering synthesis of established heterogeneous-memory and inference mechanisms. HBF placement remains a conditional scenario, not a claim that the cited runtimes support HBF.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-working-set-placement-3f85e16bc8008563.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#memory-working-set-placement", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c8429b529b7a86cd13bb32e25d64ce85b28746d419a93e44f714143900fb17f8", "contentLength": 5637, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-working-set-placement.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-memory-working-set-placement.md", "sections": [ { "id": "section-1", "title": "Place the working set, not just the model" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Tier-capacity constraint" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a model fail to run even when its weight file fits in HBM?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#memory-working-set-placement" }, { "title": "NVIDIA — Mastering LLM Techniques: Inference Optimization", "url": "https://developer.nvidia.com/blog/mastering-llm-techniques-inference-optimization/" }, { "title": "ZeRO-Infinity: Breaking the GPU Memory Wall", "url": "https://arxiv.org/abs/2104.07857" }, { "title": "Sandisk — release of first OCP HBF specification", "url": "https://investor.sandisk.com/node/8126/pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/memory-working-set-placement-3f85e16bc8008563.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Full memory hierarchy and input path", "url": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/" }, { "title": "Model graph and tensor intermediate representation", "url": "https://semiaifoundry.com/learn/atlas/graph-tensor-ir/" }, { "title": "Training state across HBM, host memory and storage", "url": "https://semiaifoundry.com/learn/atlas/training-tier-placement/" }, { "title": "Prefill, decode and the moving KV working set", "url": "https://semiaifoundry.com/learn/atlas/prefill-decode-tier-placement/" }, { "title": "MoE experts: resident capacity, routing and misses", "url": "https://semiaifoundry.com/learn/atlas/moe-expert-tier-placement/" }, { "title": "Architecture is a contract between computation and silicon", "url": "https://semiaifoundry.com/learn/atlas/crg-architecture-contract/" } ], "recordHash": "fed6250a96f90aad3ac08e8b065c56d5b22bfc436f735baeec4999310985140b" }, { "id": "atlas-lesson-microbatch-equivalent-updates", "title": "Gradient accumulation under a fixed global objective", "category": "learning", "format": "Atlas lesson", "description": "Recover a full-batch gradient from unequal target counts before clipping or stepping.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/microbatch-equivalent-updates/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-pretraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. All gradients evaluated at the same weights with the same stochastic choices needed for equivalence. Exact arithmetic example; finite reductions can introduce rounding differences. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/microbatch-equivalent-updates-e06cc42040fac364.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#microbatch-equivalent-updates", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a5b74f40fe3e160d9bb9daf68218515e4244196b4cb26081eca39da4200f2803", "contentLength": 6127, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-microbatch-equivalent-updates.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-microbatch-equivalent-updates.md", "sections": [ { "id": "section-1", "title": "Gradient accumulation under a fixed global objective" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Gradient accumulation under a fixed global objective · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "When should clipping occur to reproduce the declared full-batch update?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#microbatch-equivalent-updates" }, { "title": "TRL SFT Trainer", "url": "https://huggingface.co/docs/trl/sft_trainer" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/microbatch-equivalent-updates-e06cc42040fac364.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Uneven batches and the global gradient", "url": "https://semiaifoundry.com/learn/atlas/distributed-gradient-weighting/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Next-token supervision from raw sequences", "url": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/" }, { "title": "Initialization, learning rate and stable updates", "url": "https://semiaifoundry.com/learn/atlas/optimizer-schedule-stability/" } ], "recordHash": "f60c05d4f4bb3227ba1405d4cbfbb6e90206338b750b504f8af7b9d7d1e56874" }, { "id": "atlas-lesson-microbump", "title": "Microbumps and bonding joints", "category": "learning", "format": "Atlas lesson", "description": "Join matching electrical terminals at the surfaces of dies and package interconnect layers.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/microbump/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Advanced packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Not every site is usable; keep-outs, power and test access reduce the count.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/microbump-52be9232f9ddf053.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#microbump", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4c93e4aec9a256190cd0bfabbe139dfaf6baace7b2d09daa251a363e46800c7b", "contentLength": 5343, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-microbump.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-microbump.md", "sections": [ { "id": "section-1", "title": "Microbumps and bonding joints" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Pitch controls the connection budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why is a finer bump pitch useful?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#microbump" }, { "title": "TSMC InFO packaging: published interconnect examples", "url": "https://www.tsmc.com/english/dedicatedFoundry/technology/InFO" }, { "title": "Amkor flip chip CSP materials data sheet", "url": "https://amkor.com/wp-content/uploads/2018/02/fcCSP_DS577.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/microbump-52be9232f9ddf053.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Device contact and interface resistance", "url": "https://semiaifoundry.com/learn/atlas/contact/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Through-silicon via", "url": "https://semiaifoundry.com/learn/atlas/through-silicon-via/" }, { "title": "Interposer and redistribution layers", "url": "https://semiaifoundry.com/learn/atlas/interposer/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" } ], "recordHash": "7cd04831ffa90eceaf9c887012dfbd811d82d8e02ecafa4614465c4c0ebab449" }, { "id": "atlas-lesson-model-artifact-rollout-drift", "title": "Model artifacts, rollout and drift", "category": "learning", "format": "Atlas lesson", "description": "Version weights, normalization, feature schema and thresholds; separate deployed pointer, observations and labels.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/model-artifact-rollout-drift/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Models become evaluated applications", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. One scalar feature, positive training standard deviation and binary logistic output. The numbers are authored; a probability is not a field-calibrated failure rate.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/model-artifact-rollout-drift-281671c20143c63b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#model-artifact-rollout-drift", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4b9ae3f7a585361e01e5b1ef8cdd04517fb7212c334b58b331a8dbb77c31efa1", "contentLength": 6554, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-model-artifact-rollout-drift.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-model-artifact-rollout-drift.md", "sections": [ { "id": "section-1", "title": "Model artifacts, rollout and drift" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Model artifacts, rollout and drift · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "The weights are unchanged but a different normalizer changes the prediction. What failed?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#model-artifact-rollout-drift" }, { "title": "scikit-learn · Common pitfalls and data leakage", "url": "https://scikit-learn.org/stable/common_pitfalls.html#data-leakage" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/model-artifact-rollout-drift-281671c20143c63b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" } ], "recordHash": "e21268a3f9e64f134070d1bf866c779a9e61fc185fc2c90c1ffcf8478df5f667" }, { "id": "atlas-lesson-model-lifecycle-stage-contract", "title": "Describe a stage by its changed contract", "category": "learning", "format": "Atlas lesson", "description": "Classify a transition by checkpoint, data, loss, trainable state, optimizer policy and evaluation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/model-lifecycle-stage-contract/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-continuation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable stage branches. Contract notation is an authored organizational tool, not a universal naming standard. The tuple does not itself train a model. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/model-lifecycle-stage-contract-7ddd81044bf2edbc.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#model-lifecycle-stage-contract", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "22e47a8e64388364c1df32ef509a98a53b5e17f85201cb36259dc6b0b8663d31", "contentLength": 6405, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-model-lifecycle-stage-contract.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-model-lifecycle-stage-contract.md", "sections": [ { "id": "section-1", "title": "Describe a stage by its changed contract" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Describe a stage by its changed contract · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which change alone makes a continuation stage a different objective?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#model-lifecycle-stage-contract" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Don’t Stop Pretraining", "url": "https://aclanthology.org/2020.acl-main.740.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/model-lifecycle-stage-contract-7ddd81044bf2edbc.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Post-training & feedback", "url": "https://semiaifoundry.com/learn/atlas/post-training/" }, { "title": "Continue language modeling on a new domain", "url": "https://semiaifoundry.com/learn/atlas/domain-adaptive-continuation/" }, { "title": "Retention, replay and transfer", "url": "https://semiaifoundry.com/learn/atlas/replay-retention-forgetting/" }, { "title": "Context extension is a learned-use test", "url": "https://semiaifoundry.com/learn/atlas/long-context-adaptation/" }, { "title": "Compatible weight averaging and regressions", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-averaging-boundaries/" } ], "recordHash": "79f7087293ebff116ba7ca84a6e27dd237b2ce445450c1bb066143ee29fbd18f" }, { "id": "atlas-lesson-model-system-regression-contract", "title": "Version the entire evaluated system", "category": "learning", "format": "Atlas lesson", "description": "Attach an evaluation result to the complete system configuration and apply a stated rollback rule.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/model-system-regression-contract/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-evaluation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Authored finite regression contract; thresholds are chosen before evaluation and do not certify open-ended model safety. System component identities must remain available. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/model-system-regression-contract-a5ad234ff0723e81.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#model-system-regression-contract", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ceb77b59857c4157287fcfe7a0f9eda679a758e4dd5f7ee29de48f7d35d059df", "contentLength": 6643, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-model-system-regression-contract.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-model-system-regression-contract.md", "sections": [ { "id": "section-1", "title": "Version the entire evaluated system" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Version the entire evaluated system · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does the candidate fail the stated gate?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#model-system-regression-contract" }, { "title": "Holistic Evaluation of Language Models", "url": "https://arxiv.org/html/2211.09110v1" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/model-system-regression-contract-a5ad234ff0723e81.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Confidence, errors and refusal to guess", "url": "https://semiaifoundry.com/learn/atlas/probability-calibration-abstention/" }, { "title": "Human and model judgments under a rubric", "url": "https://semiaifoundry.com/learn/atlas/judge-rubric-agreement/" }, { "title": "From lexical retrieval to model answers with evidence", "url": "https://semiaifoundry.com/learn/atlas/retrieval-supported-generation/" }, { "title": "Sampling more candidates versus selecting correct ones", "url": "https://semiaifoundry.com/learn/atlas/test-time-search-verification/" } ], "recordHash": "7c1e6d798c08c9c9b668c34b4ffac9e1063c5873415673274837b65a967a0071" }, { "id": "atlas-lesson-moe", "title": "Mixture of experts", "category": "learning", "format": "Atlas lesson", "description": "Route each token to a subset of learned transformations.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/moe/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Transformer computation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is the lesson’s equal-size top-k accounting example. Selected parameter count is not a complete FLOP, latency or quality model; shared experts, router work, imbalance, capacity limits and communication change actual execution.\n\nMode: worked example. Switch top-one auxiliary convention, before capacity handling. Discrete f is treated as nondifferentiable; P supplies a gradient path. Worked-only routing. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/moe-5319c4e6acd569f7.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#moe", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4f43ff034d1837b02dcdf04781421590d66783e28730a71d1a9e8c4de1e68944", "contentLength": 8897, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-moe.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-moe.md", "sections": [ { "id": "section-1", "title": "Mixture of experts" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Stored capacity versus activated computation" }, { "id": "section-5", "title": "Routing losses, sparse gradients and expert collapse · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Why can an MoE model have many stored but fewer active parameters?" }, { "id": "section-12", "title": "Does an auxiliary loss alone enforce the hard capacity of two?" }, { "id": "section-13", "title": "Historical context" }, { "id": "section-14", "title": "2021 · Switch Transformer simplifies sparse routing" }, { "id": "section-15", "title": "Evidence and scope" }, { "id": "section-16", "title": "Sources" }, { "id": "section-17", "title": "Continue exploring" }, { "id": "section-18", "title": "Foundations" }, { "id": "section-19", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#moe" }, { "title": "Fedus et al. — Switch Transformers", "url": "https://arxiv.org/abs/2101.03961" }, { "title": "Switch Transformers", "url": "https://arxiv.org/html/2101.03961v3" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/moe-5319c4e6acd569f7.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Feed-forward network", "url": "https://semiaifoundry.com/learn/atlas/feed-forward/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" }, { "title": "A differentiable computation graph", "url": "https://semiaifoundry.com/learn/atlas/reverse-mode-autodiff/" }, { "title": "Assemble an initialized causal language model", "url": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/" } ], "recordHash": "219967cf6856d2936c6ec084e0f3efaefae71d8f2b7ef897f4fb2f2a9aac4bb1" }, { "id": "atlas-lesson-moe-expert-tier-placement", "title": "MoE experts: resident capacity, routing and misses", "category": "learning", "format": "Atlas lesson", "description": "Explain why sparse activation reduces arithmetic without eliminating expert storage or transfer constraints.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/moe-expert-tier-placement/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "DeepSpeed supports the distinction between expert distribution and communication scheduling. HBF-based expert caching here is an explicit architectural scenario, not a feature claimed for that runtime.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/moe-expert-tier-placement-d2d76a649e40c474.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#moe-expert-tier-placement", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "6b5bf3b4de32dcf4495444e142fee973f963cabcfdf7638d79cfb9a7ecec17f3", "contentLength": 5283, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-moe-expert-tier-placement.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-moe-expert-tier-placement.md", "sections": [ { "id": "section-1", "title": "MoE experts: resident capacity, routing and misses" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Expert-weight miss traffic" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Each token selects two experts. Must a batch need only two experts resident?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#moe-expert-tier-placement" }, { "title": "DeepSpeed — MoE inference", "url": "https://www.deepspeed.ai/tutorials/mixture-of-experts-inference/" }, { "title": "Sandisk — release of first OCP HBF specification", "url": "https://investor.sandisk.com/node/8126/pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/moe-expert-tier-placement-d2d76a649e40c474.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "MoE routing, active parameters and resident state", "url": "https://semiaifoundry.com/learn/atlas/expert-routing-budget/" }, { "title": "Place the working set, not just the model", "url": "https://semiaifoundry.com/learn/atlas/memory-working-set-placement/" }, { "title": "HBF latency, transfer granularity and prefetch", "url": "https://semiaifoundry.com/learn/atlas/hbf-latency-prefetch/" }, { "title": "Collective traffic and congestion", "url": "https://semiaifoundry.com/learn/atlas/fabric-collective-traffic/" }, { "title": "From memory placement to network, power and cooling", "url": "https://semiaifoundry.com/learn/atlas/memory-to-hall-propagation/" }, { "title": "Communication is the realization medium", "url": "https://semiaifoundry.com/learn/atlas/crg-communication-graph/" } ], "recordHash": "d975dcb93f30f15f49f5f548968cc33f31d46d4ac7084fa9aaf9f7bb7e1745f7" }, { "id": "atlas-lesson-mosfet", "title": "Metal–oxide–semiconductor field-effect transistor", "category": "learning", "format": "Atlas lesson", "description": "Uses a gate voltage to control current between source and drain.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/mosfet/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Device physics", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The equation is a first-order regime model, not a modern node compact model.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/mosfet-5478fa9fd1586d83.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#mosfet", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "7aad3a21f1921204b88f93d4f81b0640ff9cbab5f8e1fc8aa49a22cc3f99ed4b", "contentLength": 5826, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-mosfet.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-mosfet.md", "sections": [ { "id": "section-1", "title": "Metal–oxide–semiconductor field-effect transistor" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Long-channel linear-region current" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What primarily controls a MOSFET channel?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "1960 · Kahng files the insulated field-effect device patent" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#mosfet" }, { "title": "Kahng — US3102230A", "url": "https://patents.google.com/patent/US3102230A/en" }, { "title": "MIT 6.012 — MOSFET Cross Section and Operation", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/5c5960f14ae37d0a65478c4f3f628d98_lec9.pdf" }, { "title": "Purdue ECE 255 — MOSFET Models", "url": "https://engineering.purdue.edu/wcchew/ece255s18/ece%20255%20s18%20latex%20pdf%20files/ece255Lecture_9_Feb6_MOSFETs.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/mosfet-5478fa9fd1586d83.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "P–n junction and depletion region", "url": "https://semiaifoundry.com/learn/atlas/pn-junction/" }, { "title": "Insulators and low-k films", "url": "https://semiaifoundry.com/learn/atlas/dielectric/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "Controllable semiconductor channel", "url": "https://semiaifoundry.com/learn/atlas/channel/" }, { "title": "Source and drain regions", "url": "https://semiaifoundry.com/learn/atlas/source-drain/" }, { "title": "Fin field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/finfet/" }, { "title": "Gate-all-around nanosheet transistor", "url": "https://semiaifoundry.com/learn/atlas/gaa/" }, { "title": "Complementary CMOS inverter", "url": "https://semiaifoundry.com/learn/atlas/inverter/" }, { "title": "Diamond-cubic silicon lattice", "url": "https://semiaifoundry.com/learn/atlas/crystal-lattice/" } ], "recordHash": "9b77819508fe778744f911c6c9c5b2c53da247e24ff793781e664fc1565307b0" }, { "id": "atlas-lesson-multi-agent-coordination-cost", "title": "Coordination can add work", "category": "learning", "format": "Atlas lesson", "description": "Parallel critical path, duplicated effort, state merge, correlated error and budgets.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/multi-agent-coordination-cost/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Delegated tasks and coordination", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. The product P(A)P(B) is valid only under independence. The lesson’s probabilities and durations are synthetic; no actual agent trials are reported.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/multi-agent-coordination-cost-f1694811234a9de6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#multi-agent-coordination-cost", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "cccc7cc52e3d755cfdb4f8b6e010e5cf32770c3525a40cd04bfe8f29d22c3fee", "contentLength": 6339, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-multi-agent-coordination-cost.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-multi-agent-coordination-cost.md", "sections": [ { "id": "section-1", "title": "Coordination can add work" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Coordination can add work · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Two required independent subchecks each succeed with probability 0.9. What is the probability both succeed?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#multi-agent-coordination-cost" }, { "title": "LangGraph workflows and agents", "url": "https://docs.langchain.com/oss/python/langgraph/workflows-agents" }, { "title": "A2A specification", "url": "https://a2a-protocol.org/latest/specification/" }, { "title": "τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains", "url": "https://arxiv.org/abs/2406.12045" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/multi-agent-coordination-cost-f1694811234a9de6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Traces connect cost, latency and results", "url": "https://semiaifoundry.com/learn/atlas/telemetry-traces-evaluation/" }, { "title": "Delegated tasks, messages and artifacts", "url": "https://semiaifoundry.com/learn/atlas/delegated-agent-protocols/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "ee8e659c297718b053b9a4913e49ac14857adb1f2d2232e751c4e09b0ca00672" }, { "id": "atlas-lesson-multiplier", "title": "Binary multiplier and partial-product reduction", "category": "learning", "format": "Atlas lesson", "description": "Builds a product by generating and combining weighted partial products.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/multiplier/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Arithmetic circuits", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is the unsigned partial-product construction in the linked multiplier lecture. Signed encodings, floating-point normalization and circuit timing require additional rules.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/multiplier-4592de6e4971de75.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#multiplier", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "403d8a7113d608eea4bcc0433415aca6a371eabd3bd28148a59392ecad4884a8", "contentLength": 4468, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-multiplier.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-multiplier.md", "sections": [ { "id": "section-1", "title": "Binary multiplier and partial-product reduction" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Binary product expansion" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "How wide can the full unsigned result of 4-bit × 4-bit multiplication be?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#multiplier" }, { "title": "UC Berkeley EECS 151 — Adders II and Array Multipliers", "url": "https://www-inst.eecs.berkeley.edu/~eecs151/fa21/files/lectures/Lecture18-Adders2-2up.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/multiplier-4592de6e4971de75.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Full adder and carry network", "url": "https://semiaifoundry.com/learn/atlas/adder/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" } ], "recordHash": "4529707f5162bb868dad685a471995f042cf6c9e21780751e574198ec037d005" }, { "id": "atlas-lesson-nand", "title": "Two-input CMOS NAND gate", "category": "learning", "format": "Atlas lesson", "description": "Implements a universal Boolean operation with complementary transistor networks.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/nand/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Digital circuits", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is ideal Boolean reasoning within valid voltage ranges, using the linked computation-structures treatment. It does not predict transition current, delay or simultaneous conduction.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/nand-608a6195e37226ae.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#nand", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9803466276e524bd5e125a1eafeab6fcdc5d92773d671e81aa599ea70eb9a0a3", "contentLength": 4275, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nand.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nand.md", "sections": [ { "id": "section-1", "title": "Two-input CMOS NAND gate" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Boolean function from topology" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "When is a two-input NAND output zero?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#nand" }, { "title": "MIT 6.004 — Computation Structures Student Notes", "url": "https://6191.mit.edu/_static/fall24/resources/references/6004_student_notes_FA20.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/nand-608a6195e37226ae.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Complementary CMOS inverter", "url": "https://semiaifoundry.com/learn/atlas/inverter/" }, { "title": "Full adder and carry network", "url": "https://semiaifoundry.com/learn/atlas/adder/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" } ], "recordHash": "74661e3e6cc02ce522a57c739bed10a384a951afb3f852fcbd3e60c7eaf40a69" }, { "id": "atlas-lesson-nanosheet-gate-last-integration", "title": "Nanosheet release and replacement gates", "category": "learning", "format": "Atlas lesson", "description": "Creates channels that can be surrounded by a gate after sacrificial materials are removed.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/nanosheet-gate-last-integration/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / FEOL and MOL", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Applied Materials describes representative operations; the atlas does not claim a complete foundry recipe. The selectivity example is synthetic.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/nanosheet-gate-last-integration-3c63a93d2d9cc31d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#nanosheet-gate-last-integration", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f6e2854a38d3603867eca1f1af58b6cd2de0a5a0167d481f501884bac0b525e4", "contentLength": 5728, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nanosheet-gate-last-integration.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nanosheet-gate-last-integration.md", "sections": [ { "id": "section-1", "title": "Nanosheet release and replacement gates" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Channel-loss budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why is selective removal central to a nanosheet replacement-gate route?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#nanosheet-gate-last-integration" }, { "title": "Applied Materials — New Ways to Shrink", "url": "https://ir.appliedmaterials.com/static-files/f2fbf48d-a761-4c4f-ab4c-73f312ab1ebc" }, { "title": "imec — CMOS scaling", "url": "https://www.imec-int.com/en/expertise/cmos-advanced/compute/cmos-scaling" }, { "title": "IBM Research — Stacked nanosheet gate-all-around transistor", "url": "https://research.ibm.com/publications/stacked-nanosheet-gate-all-around-transistor-to-enable-scaling-beyond-finfet" }, { "title": "Intel — High-k and metal-gate transistor announcement", "url": "https://www.intel.com/pressroom/archive/releases/2007/20070128comp.htm" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/nanosheet-gate-last-integration-3c63a93d2d9cc31d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Gate-all-around nanosheet transistor", "url": "https://semiaifoundry.com/learn/atlas/gaa/" }, { "title": "Epitaxy and engineered starting layers", "url": "https://semiaifoundry.com/learn/atlas/epitaxial-material-stack/" }, { "title": "Plasma and wet etch: selectivity and profile", "url": "https://semiaifoundry.com/learn/atlas/plasma-wet-etch-transfer/" }, { "title": "ALD and self-limiting surface reactions", "url": "https://semiaifoundry.com/learn/atlas/ald-self-limiting-growth/" }, { "title": "Source/drain, spacers, contacts and MOL", "url": "https://semiaifoundry.com/learn/atlas/source-drain-contact-integration/" } ], "recordHash": "1152eb29c2823a1822e0691da40fd7767be2eb389377601234999cddb1c70f28" }, { "id": "atlas-lesson-nccl", "title": "Collective communication library", "category": "learning", "format": "Atlas lesson", "description": "Coordinates group communication operations across participating GPUs.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/nccl/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Distributed software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The factor is the conventional all-reduce model in the linked NCCL bandwidth note. It is not a universal per-link traffic law for every algorithm or hardware-assisted reduction; ranks, message bytes and completion boundary must match.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/nccl-6adf3f210d984e2b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#nccl", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "d65f0391efd2b5482745d1c9fc927430745b222faddbf5e5d07fdcaaae67f72c", "contentLength": 5193, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nccl.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nccl.md", "sections": [ { "id": "section-1", "title": "Collective communication library" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "All-reduce traffic normalization" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a sum all-reduce return?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#nccl" }, { "title": "NVIDIA NCCL — Collective Operations", "url": "https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/collectives.html" }, { "title": "NVIDIA NCCL Tests — Bandwidth Accounting", "url": "https://github.com/NVIDIA/nccl-tests/blob/master/doc/PERFORMANCE.md" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/nccl-6adf3f210d984e2b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "NVLink GPU interface", "url": "https://semiaifoundry.com/learn/atlas/nvlink-port/" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" }, { "title": "NVLink switch tray and scale-up fabric", "url": "https://semiaifoundry.com/learn/atlas/nvlink-switch/" }, { "title": "Leaf switch and endpoint network", "url": "https://semiaifoundry.com/learn/atlas/leaf-switch/" }, { "title": "Spine switching and fabric topology", "url": "https://semiaifoundry.com/learn/atlas/spine-switch/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" } ], "recordHash": "a495d22aa29180aee498625a620e87c6fceee3860a45a04adf7d8856f6ef3061" }, { "id": "atlas-lesson-network-adapter", "title": "Network interface adapter", "category": "learning", "format": "Atlas lesson", "description": "Moves data between the server and the cluster network, often with direct-memory and protocol offloads.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/network-adapter/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Connectivity", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The lesson’s latency-plus-payload model uses decimal bytes and one direction. These are synthetic rates; the linked network references do not make this a promise about RDMA, GPU access, congestion or any deployed adapter.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/network-adapter-2b661ddb0588a022.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#network-adapter", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ad178d371c58f691951ca4ed8dfb1b1662d10cf9c3bfed550e3618254be700c6", "contentLength": 5773, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-network-adapter.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-network-adapter.md", "sections": [ { "id": "section-1", "title": "Network interface adapter" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Small messages and large transfers have different bottlenecks" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does RDMA principally reduce in a supported transfer?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#network-adapter" }, { "title": "NVIDIA ConnectX Ethernet adapters", "url": "https://www.nvidia.com/en-us/networking/ethernet-adapters/" }, { "title": "NVIDIA ConnectX-7 adapter hardware manual", "url": "https://networking-docs.nvidia.com/connectx7hw/introduction" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/network-adapter-2b661ddb0588a022.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "PCI Express interconnect", "url": "https://semiaifoundry.com/learn/atlas/pcie-interface/" }, { "title": "NVLink GPU interface", "url": "https://semiaifoundry.com/learn/atlas/nvlink-port/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "Leaf switch and endpoint network", "url": "https://semiaifoundry.com/learn/atlas/leaf-switch/" } ], "recordHash": "06c6d696ba3fed381f1ee3277dc6612b15735180e3c1f987c0da00faa832c133" }, { "id": "atlas-lesson-nvlink-port", "title": "NVLink GPU interface", "category": "learning", "format": "Atlas lesson", "description": "Moves tensor data between GPUs through a high-bandwidth scale-up interconnect.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/nvlink-port/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Connectivity", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The ring is an ideal topology model; implementations may use trees or hierarchies.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/nvlink-port-5a5e370e6edd4419.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#nvlink-port", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "000f51c3a51a796d4315bb00decb22b8f1cecee9e1e53c9f41bd6fe406d1659e", "contentLength": 6339, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nvlink-port.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nvlink-port.md", "sections": [ { "id": "section-1", "title": "NVLink GPU interface" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Communication has volume and startup costs" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which work does NVLink most directly support?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2016 · Pascal P100 brings NVLink to NVIDIA accelerators" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#nvlink-port" }, { "title": "NVIDIA: Tesla P100 launch announcement", "url": "https://nvidianews.nvidia.com/news/nvidia-delivers-massive-performance-leap-for-deep-learning-hpc-applications-with-nvidia-tesla-p100-accelerators-6622437" }, { "title": "NVIDIA: NVLink and NVSwitch for LLM inference", "url": "https://developer.nvidia.com/blog/nvidia-nvlink-and-nvidia-nvswitch-supercharge-large-language-model-inference/" }, { "title": "NVIDIA: Inside Blackwell Ultra, with Blackwell comparison", "url": "https://developer.nvidia.com/blog/inside-nvidia-blackwell-ultra-the-chip-powering-the-ai-factory-era/" }, { "title": "NVIDIA NCCL tests: interpreting collective bandwidth", "url": "https://github.com/NVIDIA/nccl-tests/blob/master/doc/PERFORMANCE.md" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/nvlink-port-5a5e370e6edd4419.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "Grace Blackwell Superchip", "url": "https://semiaifoundry.com/learn/atlas/grace-blackwell-superchip/" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" } ], "recordHash": "74f49b061ceac1aa5c307f372f9ba5f6b36bff811e77f67f1f89397078cccd2f" }, { "id": "atlas-lesson-nvlink-switch", "title": "NVLink switch tray and scale-up fabric", "category": "learning", "format": "Atlas lesson", "description": "Routes high-bandwidth GPU communication inside the rack-scale NVLink domain.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/nvlink-switch/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Rack integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The transfer bound uses decimal payload bytes and one specified direction. Values are synthetic; routing, competing flows, collective algorithms and measured effective bandwidth determine the applicable path.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/nvlink-switch-9a4ae0fb9887a117.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#nvlink-switch", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "971c393ef286095c42737fd246cad34eec33def4cb5d54f0ddd2033945856631", "contentLength": 4969, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nvlink-switch.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nvlink-switch.md", "sections": [ { "id": "section-1", "title": "NVLink switch tray and scale-up fabric" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Transfer-time floor" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the NVLink switch primarily provide?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#nvlink-switch" }, { "title": "NVIDIA — DGX GB Rack Scale Systems Hardware Guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "NVIDIA — GB200 NVL72 Architecture", "url": "https://developer.nvidia.com/blog/nvidia-gb200-nvl72-delivers-trillion-parameter-llm-training-and-real-time-inference/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/nvlink-switch-9a4ae0fb9887a117.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "NVLink GPU interface", "url": "https://semiaifoundry.com/learn/atlas/nvlink-port/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "GB200 compute tray", "url": "https://semiaifoundry.com/learn/atlas/compute-tray/" }, { "title": "NVLink copper cable cartridge", "url": "https://semiaifoundry.com/learn/atlas/cable-cartridge/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" } ], "recordHash": "e736f108789a2f09a8adf290ff083b807b11bb22d1a5e9b8866c82a9f7cdffd3" }, { "id": "atlas-lesson-nvme-storage", "title": "NVMe solid-state storage", "category": "learning", "format": "Atlas lesson", "description": "Persists datasets, model checkpoints, and software beyond power cycles.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/nvme-storage/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Host platform", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a steady-state queueing identity applied to the storage boundary, as explained by the lesson. I/O size, read/write mix, persistence requirements and latency definition must match; no product performance is inferred.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/nvme-storage-47d41592ea665d95.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#nvme-storage", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "fe601c5b4e46054aa1b86c1c080435fcd9c329443b4bd47713bdfa567c254757", "contentLength": 5924, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nvme-storage.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-nvme-storage.md", "sections": [ { "id": "section-1", "title": "NVMe solid-state storage" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "High IOPS requires enough outstanding work" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why is a saved checkpoint useful after a node loses power?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#nvme-storage" }, { "title": "Micron 9550 NVMe data center SSD", "url": "https://www.micron.com/products/storage/ssd/data-center-ssd/9550-ssd" }, { "title": "Micron 9550 SSD technical product specification", "url": "https://www.micron.com/content/dam/micron/global/public/products/data-sheet/ssd/9550-nvme-ssd-tech-prod-spec.pdf" }, { "title": "John D. C. Little (2011): Little’s Law and computer architecture applications", "url": "https://pubsonline.informs.org/doi/pdf/10.1287/opre.1110.0940" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/nvme-storage-47d41592ea665d95.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "PCI Express interconnect", "url": "https://semiaifoundry.com/learn/atlas/pcie-interface/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" } ], "recordHash": "f9f39d0a2d6cdf24f67dae9c0dc766e45fb180ccd6b4796755c4a5cbce54df18" }, { "id": "atlas-lesson-on-chip-network", "title": "On-chip interconnect fabric", "category": "learning", "format": "Atlas lesson", "description": "Routes data and control between compute units, cache slices, memory controllers, and I/O.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/on-chip-network/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Connectivity", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The relation assumes a stable stream and excludes topology-specific backpressure.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/on-chip-network-2fef2e4eae57f640.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#on-chip-network", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "5aeec86310e3cb22d7495f32e87389d6424b9cf675362bb3dd1bf1585a0797be", "contentLength": 5893, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-on-chip-network.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-on-chip-network.md", "sections": [ { "id": "section-1", "title": "On-chip interconnect fabric" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Enough requests must be in flight" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does locality still matter inside one GPU?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#on-chip-network" }, { "title": "NVIDIA: GPU locality domains and L2 fabric", "url": "https://developer.nvidia.com/blog/accelerating-data-processing-with-nvidia-multi-instance-gpu-and-numa-node-localization/" }, { "title": "Intel: Memory performance, latency, and bandwidth", "url": "https://www.intel.com/content/www/us/en/developer/articles/technical/memory-performance-in-a-nutshell.html" }, { "title": "John D. C. Little (1961): A Proof for the Queuing Formula L = λW", "url": "https://pubsonline.informs.org/doi/abs/10.1287/opre.9.3.383" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/on-chip-network-2fef2e4eae57f640.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Shared L2 cache", "url": "https://semiaifoundry.com/learn/atlas/l2-cache/" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "HBM controller and PHY", "url": "https://semiaifoundry.com/learn/atlas/hbm-controller/" }, { "title": "NVLink GPU interface", "url": "https://semiaifoundry.com/learn/atlas/nvlink-port/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" } ], "recordHash": "198ce3b829665171165f64b79ea9d909a1be2310c039eb71ac9b9494521b3314" }, { "id": "atlas-lesson-optical-cpo-placement", "title": "Optical transceivers and co-packaged optics", "category": "learning", "format": "Atlas lesson", "description": "Changes where electrical signals become optical while retaining a complete link budget.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/optical-cpo-placement/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Chip-to-hall integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No vendor promotional efficiency multiplier is used. The announcement establishes a design direction and date, not a universal measured CPO advantage.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/optical-cpo-placement-a5e9a86f97453572.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#optical-cpo-placement", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ebfbb7c5979317b2a4ab39623759c17ce22a185dc0dde6dcada4ae5396ccdbe5", "contentLength": 5064, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-optical-cpo-placement.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-optical-cpo-placement.md", "sections": [ { "id": "section-1", "title": "Optical transceivers and co-packaged optics" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Simple optical margin" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which consideration becomes more closely tied to package design with CPO?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#optical-cpo-placement" }, { "title": "NVIDIA Announces Spectrum-X Photonics, Co-Packaged Optics Networking Switches", "url": "https://nvidianews.nvidia.com/news/nvidia-spectrum-x-co-packaged-optics-networking-switches-ai-factories" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/optical-cpo-placement-a5e9a86f97453572.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Optical transceiver and fiber link", "url": "https://semiaifoundry.com/learn/atlas/optics/" }, { "title": "Signal integrity, timing and the eye diagram", "url": "https://semiaifoundry.com/learn/atlas/interface-signal-eye/" }, { "title": "Leaf switch and endpoint network", "url": "https://semiaifoundry.com/learn/atlas/leaf-switch/" } ], "recordHash": "85d0c9458b64b602bfba4e77828393f354722bd35461db06452be131a3f2db9d" }, { "id": "atlas-lesson-optics", "title": "Optical transceiver and fiber link", "category": "learning", "format": "Atlas lesson", "description": "Converts electrical communication into light for transport through fiber.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/optics/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center fabric", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The lane rates and efficiency are synthetic. Lane/port grouping, modulation, encoding and direction must match the actual module; electrical-to-optical conversion does not remove serialization or protocol overhead.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/optics-c6affce300ad8ea0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#optics", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "5b4b076a7cafecebb607c523201b4cf1e08d869bb22542e1c16ea88cf7635c31", "contentLength": 4744, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-optics.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-optics.md", "sections": [ { "id": "section-1", "title": "Optical transceiver and fiber link" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Lane aggregation and units" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What raw byte rate corresponds to 400 Gb/s before overhead?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#optics" }, { "title": "NVIDIA — Transceivers and Fiber: 100G-PAM4", "url": "https://docs.nvidia.com/networking/display/400g100gpam4ovdev/transceivers-and-fiber-details-100g-pam4" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/optics-c6affce300ad8ea0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" }, { "title": "Leaf switch and endpoint network", "url": "https://semiaifoundry.com/learn/atlas/leaf-switch/" }, { "title": "Spine switching and fabric topology", "url": "https://semiaifoundry.com/learn/atlas/spine-switch/" }, { "title": "NVLink copper cable cartridge", "url": "https://semiaifoundry.com/learn/atlas/cable-cartridge/" } ], "recordHash": "f95c14a103268043673ffc9b540adddf74314db867358c38d10393f1a40eca36" }, { "id": "atlas-lesson-optimizer-schedule-stability", "title": "Initialization, learning rate and stable updates", "category": "learning", "format": "Atlas lesson", "description": "Separate gradient clipping, adaptive moments, decay and the learning-rate schedule.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/optimizer-schedule-stability/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-pretraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable clipping; worked schedule and AdamW. For zero gradient use clipping multiplier one. The second equation declares one AdamW convention; lifecycle core sets decay to zero and has a constant schedule. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/optimizer-schedule-stability-6b89200eaa73f2ab.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#optimizer-schedule-stability", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "8da24fc06f95e4e9a91aa6bd4ab1829bc9e8d5bd56ff04caa4fc8e5d0a8563ec", "contentLength": 6234, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-optimizer-schedule-stability.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-optimizer-schedule-stability.md", "sections": [ { "id": "section-1", "title": "Initialization, learning rate and stable updates" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Initialization, learning rate and stable updates · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What preserves the direction of gradient \\[3,4\\] during norm clipping?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#optimizer-schedule-stability" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Decoupled Weight Decay Regularization", "url": "https://arxiv.org/html/1711.05101v3" }, { "title": "PyTorch Adam algorithm", "url": "https://docs.pytorch.org/docs/2.14/generated/torch.optim.Adam.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/optimizer-schedule-stability-6b89200eaa73f2ab.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Residual stream & normalization", "url": "https://semiaifoundry.com/learn/atlas/residual-normalization/" }, { "title": "Next-token supervision from raw sequences", "url": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/" }, { "title": "Gradient accumulation under a fixed global objective", "url": "https://semiaifoundry.com/learn/atlas/microbatch-equivalent-updates/" } ], "recordHash": "cf8d97bcce9c2d4a9694f3827b1bfa73045240a2d66ba3edf3aa7237642d59d5" }, { "id": "atlas-lesson-orbital-evidence-status", "title": "Orbital computing evidence ladder", "category": "learning", "format": "Atlas lesson", "description": "Separates onboard processing, flight demonstrations, laboratory tests and proposed services.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/orbital-evidence-status/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Frontier infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Starcloud’s page has inconsistent Gemini/Gemma wording, so only its H100 and nanoGPT statements are used. No universal first-AI-in-space claim is made.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-evidence-status-20e856f3b48fbbbd.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#orbital-evidence-status", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4c24bad8325e2a4fcce739b22997e90de1e3b36dc656583d58e42c87f8d4d07b", "contentLength": 5076, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-evidence-status.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-evidence-status.md", "sections": [ { "id": "section-1", "title": "Orbital computing evidence ladder" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Service readiness model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a ground optical bench test directly establish?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#orbital-evidence-status" }, { "title": "Starcloud-1", "url": "https://www.starcloud.com/starcloud-1" }, { "title": "Exploring a space-based, scalable AI infrastructure system design", "url": "https://research.google/blog/exploring-a-space-based-scalable-ai-infrastructure-system-design/" }, { "title": "NASA’s Record-Breaking Laser Demo Completes Mission", "url": "https://www.nasa.gov/directorates/somd/space-communications-navigation-program/nasas-record-breaking-laser-demo-completes-mission/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-evidence-status-20e856f3b48fbbbd.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "Orbital solar generation and eclipse storage", "url": "https://semiaifoundry.com/learn/atlas/orbital-solar-storage/" }, { "title": "Orbital optical links and contact budgets", "url": "https://semiaifoundry.com/learn/atlas/orbital-link-contacts/" }, { "title": "Orbital lifecycle economics and workload fit", "url": "https://semiaifoundry.com/learn/atlas/orbital-lifecycle-economics/" } ], "recordHash": "b347dd4ce259f8875c85baae163aa4fa1c6b26b618737321c0a2715f424c66ae" }, { "id": "atlas-lesson-orbital-lifecycle-economics", "title": "Orbital lifecycle economics and workload fit", "category": "learning", "format": "Atlas lesson", "description": "Compares complete useful service under conditional launch and support assumptions.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/orbital-lifecycle-economics/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Frontier infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example is synthetic. The source’s mid-2030s launch-price projection is forecast evidence, not a current market price or a completed feasibility demonstration.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-lifecycle-economics-5e1c75f1d1c56ba2.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#orbital-lifecycle-economics", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "98911d357be3c25ce6ece8f0927a408976a1ada0478191f424200cc501edf142", "contentLength": 5150, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-lifecycle-economics.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-lifecycle-economics.md", "sections": [ { "id": "section-1", "title": "Orbital lifecycle economics and workload fit" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Launch-only annualization" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which denominator makes an orbital and terrestrial comparison meaningful?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#orbital-lifecycle-economics" }, { "title": "Towards a future space-based, highly scalable AI infrastructure system design, v2", "url": "https://arxiv.org/html/2511.19468v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-lifecycle-economics-5e1c75f1d1c56ba2.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Launch, replacement and end-of-life mass", "url": "https://semiaifoundry.com/learn/atlas/orbital-replacement-mass/" }, { "title": "Orbital optical links and contact budgets", "url": "https://semiaifoundry.com/learn/atlas/orbital-link-contacts/" }, { "title": "Orbital computing evidence ladder", "url": "https://semiaifoundry.com/learn/atlas/orbital-evidence-status/" } ], "recordHash": "c46b791f10f91f1df78d9a7d94b334460ec2b2a579f46cec2b5bae5541a25aa5" }, { "id": "atlas-lesson-orbital-link-contacts", "title": "Orbital optical links and contact budgets", "category": "learning", "format": "Atlas lesson", "description": "Separates inter-satellite exchange from ground-data delivery and sustained useful service.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/orbital-link-contacts/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Frontier infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "TBIRD was an orbital communication demonstration; Suncatcher’s 800 Gbit/s one-way result was on a ground bench. Neither alone qualifies a fleet-scale compute network.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-link-contacts-b56332aa7bb64d28.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#orbital-link-contacts", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "faab253e552fdd78575b9e7fffe9dc2b0f06e946fd3ecd1fc517c6cae713e94b", "contentLength": 5265, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-link-contacts.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-link-contacts.md", "sections": [ { "id": "section-1", "title": "Orbital optical links and contact budgets" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Contact payload and propagation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What changes when a link is available only one quarter of the time?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#orbital-link-contacts" }, { "title": "NASA’s Record-Breaking Laser Demo Completes Mission", "url": "https://www.nasa.gov/directorates/somd/space-communications-navigation-program/nasas-record-breaking-laser-demo-completes-mission/" }, { "title": "Towards a future space-based, highly scalable AI infrastructure system design, v2", "url": "https://arxiv.org/html/2511.19468v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-link-contacts-b56332aa7bb64d28.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Optical transceiver and fiber link", "url": "https://semiaifoundry.com/learn/atlas/optics/" }, { "title": "Orbital computing evidence ladder", "url": "https://semiaifoundry.com/learn/atlas/orbital-evidence-status/" }, { "title": "Radiation effects, detection and recovery", "url": "https://semiaifoundry.com/learn/atlas/orbital-radiation-recovery/" } ], "recordHash": "70a6bdabee415ca67b2f0b9c870b92855630df5655407344ba4dd7a4edd2bfd0" }, { "id": "atlas-lesson-orbital-radiation-recovery", "title": "Radiation effects, detection and recovery", "category": "learning", "format": "Atlas lesson", "description": "Connects mission-specific particle exposure to device behavior and retained workload correctness.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/orbital-radiation-recovery/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Frontier infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The source test reported HBM irregularities at a lower dose than its maximum single-chip test. Neither threshold is a universal orbital qualification limit.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-radiation-recovery-7b1aef7daa1c7910.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#orbital-radiation-recovery", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "da49257c250d1ae049142b1102013124f0e3ee643591698faf04cf2423ac1026", "contentLength": 5180, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-radiation-recovery.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-radiation-recovery.md", "sections": [ { "id": "section-1", "title": "Radiation effects, detection and recovery" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Simple fleet event expectation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why must silent corruption be distinguished from a reboot?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#orbital-radiation-recovery" }, { "title": "Space Environments Testbed: What is space radiation?", "url": "https://lws-set.gsfc.nasa.gov/space_radiation.html" }, { "title": "Towards a future space-based, highly scalable AI infrastructure system design, v2", "url": "https://arxiv.org/html/2511.19468v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-radiation-recovery-7b1aef7daa1c7910.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "DRAM die and memory banks", "url": "https://semiaifoundry.com/learn/atlas/dram-die/" }, { "title": "Launch, replacement and end-of-life mass", "url": "https://semiaifoundry.com/learn/atlas/orbital-replacement-mass/" }, { "title": "Checkpointing, failure and retained useful work", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-retained-work/" } ], "recordHash": "8dcd4d6cdc0d080822ded66c95f1fb366eb81a3596f23d45764efef2891d350b" }, { "id": "atlas-lesson-orbital-radiator-budget", "title": "Radiators, view factors and orbital heat rejection", "category": "learning", "format": "Atlas lesson", "description": "Rejects spacecraft waste heat through radiation while accounting for absorbed environmental heat.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/orbital-radiator-budget/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Frontier infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is not a qualified megawatt spacecraft design. Panel mass, deployment, transport gradients, two-sided views and environmental loads remain separate inputs.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-radiator-budget-b98e14631d34363a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#orbital-radiator-budget", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ffa55725f68b296ceabe6b6b07fcb3049ff8187cfd75916f91870299feee3db3", "contentLength": 5325, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-radiator-budget.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-radiator-budget.md", "sections": [ { "id": "section-1", "title": "Radiators, view factors and orbital heat rejection" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Ideal radiative balance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why is ideal black-space radiator area only a lower bound?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#orbital-radiator-budget" }, { "title": "Small Spacecraft State of the Art: Thermal Control", "url": "https://www.nasa.gov/smallsat-institute/sst-soa/thermal-control/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-radiator-budget-b98e14631d34363a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Orbital solar generation and eclipse storage", "url": "https://semiaifoundry.com/learn/atlas/orbital-solar-storage/" }, { "title": "Thermal interface material", "url": "https://semiaifoundry.com/learn/atlas/thermal-interface/" }, { "title": "Launch, replacement and end-of-life mass", "url": "https://semiaifoundry.com/learn/atlas/orbital-replacement-mass/" } ], "recordHash": "e1c2f5ee8eeea42198eb48c3a08d272f1a0f16d256548d603f0a8483bd703755" }, { "id": "atlas-lesson-orbital-replacement-mass", "title": "Launch, replacement and end-of-life mass", "category": "learning", "format": "Atlas lesson", "description": "Accounts for a computing fleet’s support mass and continuing lifecycle logistics.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/orbital-replacement-mass/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Frontier infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mass and lifetime are hypothetical, not current spacecraft specifications. No present launcher capability or regulatory disposal deadline is asserted.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-replacement-mass-da85f6407e58458c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#orbital-replacement-mass", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "2396e5008b6858a49f7ed4872f3adbb1a5722bf33f7e72b8eb82743fd20ab569", "contentLength": 5071, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-replacement-mass.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-replacement-mass.md", "sections": [ { "id": "section-1", "title": "Launch, replacement and end-of-life mass" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Replacement-flow model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "If total fleet mass stays fixed and useful life halves, what happens to ideal annual replacement mass?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#orbital-replacement-mass" }, { "title": "Small Spacecraft State of the Art: Deorbit Systems", "url": "https://www.nasa.gov/smallsat-institute/sst-soa/deorbit-systems/" }, { "title": "Towards a future space-based, highly scalable AI infrastructure system design, v2", "url": "https://arxiv.org/html/2511.19468v2" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-replacement-mass-da85f6407e58458c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Orbital solar generation and eclipse storage", "url": "https://semiaifoundry.com/learn/atlas/orbital-solar-storage/" }, { "title": "Radiators, view factors and orbital heat rejection", "url": "https://semiaifoundry.com/learn/atlas/orbital-radiator-budget/" }, { "title": "Orbital lifecycle economics and workload fit", "url": "https://semiaifoundry.com/learn/atlas/orbital-lifecycle-economics/" } ], "recordHash": "05127539a01890341ff4ce2ff83309bff85115885173e2df93aba84e99ed604d" }, { "id": "atlas-lesson-orbital-solar-storage", "title": "Orbital solar generation and eclipse storage", "category": "learning", "format": "Atlas lesson", "description": "Balances payload and spacecraft energy through sunlight, eclipse and degradation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/orbital-solar-storage/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Frontier infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The irradiance is a representative near-Earth physical input; all design factors and area are synthetic. No orbit-wide generation or payload efficiency is asserted.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-solar-storage-0ab4e3d62cb16248.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#orbital-solar-storage", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "665aec69936a750d5eb656485dba35bcee42f0eebbb5cb15767096a2cfcbec0f", "contentLength": 4991, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-solar-storage.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-orbital-solar-storage.md", "sections": [ { "id": "section-1", "title": "Orbital solar generation and eclipse storage" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Solar power budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can average solar power exceed average load while a design still fail?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#orbital-solar-storage" }, { "title": "Small Spacecraft Technology State of the Art 2024 report", "url": "https://www.nasa.gov/wp-content/uploads/2025/02/soa-2024.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/orbital-solar-storage-0ab4e3d62cb16248.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Orbital computing evidence ladder", "url": "https://semiaifoundry.com/learn/atlas/orbital-evidence-status/" }, { "title": "Power supply and power shelf", "url": "https://semiaifoundry.com/learn/atlas/power-supply/" }, { "title": "Radiators, view factors and orbital heat rejection", "url": "https://semiaifoundry.com/learn/atlas/orbital-radiator-budget/" } ], "recordHash": "2c4dc1b9428a1edd0842982636a462222a928fe60cf7e47276a97193cc703b8f" }, { "id": "atlas-lesson-output-head", "title": "Output head & decoding", "category": "learning", "format": "Atlas lesson", "description": "Convert the final representation into the next token.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/output-head/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Generation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is the standard categorical autoregressive calculation already stated in the lesson. Toy logits are not model observations, and generation probability is not factual confidence or a claim about a private system’s decoding controls.\n\nMode: executable output probabilities and generation. Finite logits, natural logarithms and one categorical target. Stable implementation subtracts maximum logit; that shift preserves the distribution. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/output-head-e7dbe11eabc20200.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#output-head", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "59fea3c10c2eb46341dd48e33010cce859281de0e0f2ffd2764d4ec014cbd33d", "contentLength": 8543, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-output-head.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-output-head.md", "sections": [ { "id": "section-1", "title": "Output head & decoding" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A sequence probability factors into conditional predictions" }, { "id": "section-5", "title": "Likelihood, cross-entropy and sampled output · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Does a high next-token probability establish factual truth?" }, { "id": "section-12", "title": "Why can a categorical sample differ from the greedy token?" }, { "id": "section-13", "title": "Historical context" }, { "id": "section-14", "title": "2020 · GPT-3 demonstrates broad in-context task conditioning" }, { "id": "section-15", "title": "Evidence and scope" }, { "id": "section-16", "title": "Sources" }, { "id": "section-17", "title": "Continue exploring" }, { "id": "section-18", "title": "Foundations" }, { "id": "section-19", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#output-head" }, { "title": "Brown et al. — Language Models are Few-Shot Learners", "url": "https://arxiv.org/abs/2005.14165" }, { "title": "Attention Is All You Need", "url": "https://arxiv.org/html/1706.03762v7" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/output-head-e7dbe11eabc20200.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Feed-forward network", "url": "https://semiaifoundry.com/learn/atlas/feed-forward/" }, { "title": "Residual stream & normalization", "url": "https://semiaifoundry.com/learn/atlas/residual-normalization/" }, { "title": "Tokenizer", "url": "https://semiaifoundry.com/learn/atlas/tokenizer/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "A differentiable computation graph", "url": "https://semiaifoundry.com/learn/atlas/reverse-mode-autodiff/" }, { "title": "Assemble an initialized causal language model", "url": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/" } ], "recordHash": "f02083256c7f6a6a20f49528652beff8e65c87d524e111e39e665ecfb9c986d4" }, { "id": "atlas-lesson-oxide-to-cell-acceptance", "title": "Oxide variation to electrical cell acceptance", "category": "learning", "format": "Atlas lesson", "description": "Carry a named material specimen into electrical parameters and separate acceptance gates.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/oxide-to-cell-acceptance/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Devices and logic", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The physical equations and conventions are primary-source informed. The parameter values, corners, constraints and results are authored teaching choices; no commercial process or human specialist review is represented.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/oxide-to-cell-acceptance-0c3831e131a74916.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#oxide-to-cell-acceptance", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "dd59c068e2794fef9dff03d15541670fb4296490bb92a68c66c29d5b6104783d", "contentLength": 9420, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-oxide-to-cell-acceptance.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-oxide-to-cell-acceptance.md", "sections": [ { "id": "section-1", "title": "Oxide variation to electrical cell acceptance" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Oxide geometry becomes electrical capacitance" }, { "id": "section-5", "title": "The fixed-charge threshold term" }, { "id": "section-6", "title": "Geometry and mobility set drive strength" }, { "id": "section-7", "title": "One acceptance conjunction preserves separate causes" }, { "id": "section-8", "title": "Engineering example" }, { "id": "section-9", "title": "Distinctions and tradeoffs" }, { "id": "section-10", "title": "Specifications and interfaces" }, { "id": "section-11", "title": "Interfaces" }, { "id": "section-12", "title": "Check your understanding" }, { "id": "section-13", "title": "The +20% oxide specimen meets the selected timing and noise limits but violates a 5% thickness tolerance. Is it accepted under all four gates?" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#oxide-to-cell-acceptance" }, { "title": "MIT 6.012 Fall 2005 — Lecture 8", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/ba97ec0d4b75ff1049567a48e66b74a0_lec8.pdf" }, { "title": "MIT 6.012 Fall 2005 — Lecture 9", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/5c5960f14ae37d0a65478c4f3f628d98_lec9.pdf" }, { "title": "MIT 6.012 Fall 2005 — Lecture 10", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/0498bbf0f0e585507d9cfe5dc3bd54b1_lec10.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/oxide-to-cell-acceptance-0c3831e131a74916.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Thermal oxidation and the silicon interface", "url": "https://semiaifoundry.com/learn/atlas/thermal-oxidation-interface/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Loaded CMOS transfer, noise and transition delay", "url": "https://semiaifoundry.com/learn/atlas/loaded-inverter-transition/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" }, { "title": "Complementary CMOS inverter", "url": "https://semiaifoundry.com/learn/atlas/inverter/" } ], "recordHash": "63703b1513f5b18b8cb98168148170208d28800eb9a6c43ec120126f54ffc4b3" }, { "id": "atlas-lesson-package-substrate", "title": "Package substrate", "category": "learning", "format": "Atlas lesson", "description": "Fans dense chip connections out to a mechanically supported interface with the circuit board.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/package-substrate/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Advanced packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The boundary excludes package and board parasitics unless included in Z_target.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/package-substrate-514c062ea3b682bd.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#package-substrate", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bd1530d9203f0fbc2aad90bc70d9f507f1b86123895fed76e5aa229ce4aacb78", "contentLength": 5794, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-package-substrate.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-package-substrate.md", "sections": [ { "id": "section-1", "title": "Package substrate" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "The supply path must stay below a target impedance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why are signal and power views both needed to understand the substrate?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#package-substrate" }, { "title": "Amkor Flip Chip technology sheet", "url": "https://amkor.com/cn/wp-content/uploads/2018/02/Flip_Chip_TS102.pdf" }, { "title": "Amkor flip chip CSP materials data sheet", "url": "https://amkor.com/wp-content/uploads/2018/02/fcCSP_DS577.pdf" }, { "title": "Intel Power Delivery Network Tool User Guide", "url": "https://cdrdv2-public.intel.com/655157/ug_pdn.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/package-substrate-514c062ea3b682bd.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Microbumps and bonding joints", "url": "https://semiaifoundry.com/learn/atlas/microbump/" }, { "title": "Interposer and redistribution layers", "url": "https://semiaifoundry.com/learn/atlas/interposer/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "Voltage regulator module", "url": "https://semiaifoundry.com/learn/atlas/voltage-regulator/" } ], "recordHash": "fe13ada3bf38328bbdba31047df15f81ebc14a788e08a495d440bc9b7f019bcf" }, { "id": "atlas-lesson-package-thermomechanical-reliability", "title": "Underfill, warpage, thermal paths and qualification", "category": "learning", "format": "Atlas lesson", "description": "Connects package materials and stress histories to measurable failure mechanisms.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/package-thermomechanical-reliability/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Assembly and reliability", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No HBM lifetime, product qualification standard or test acceptance criterion is invented. Illustrative deformation is exaggerated for teaching.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/package-thermomechanical-reliability-723dba57eff2f204.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#package-thermomechanical-reliability", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "54c643a75259b1fca76d1bf6235c8b2a3b3e4e122353864458ac46ddd93070ba", "contentLength": 5565, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-package-thermomechanical-reliability.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-package-thermomechanical-reliability.md", "sections": [ { "id": "section-1", "title": "Underfill, warpage, thermal paths and qualification" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Thermal expansion mismatch" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What should precede a destructive cross-section of every failed sample?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#package-thermomechanical-reliability" }, { "title": "Texas Instruments — Reliability testing", "url": "https://www.ti.com/quality-reliability/reliability/testing.html" }, { "title": "imec — Wafer-to-wafer hybrid bonding: 400 nm interconnect pitch", "url": "https://www.imec-int.com/en/articles/wafer-wafer-hybrid-bonding-pushing-boundaries-400nm-interconnect-pitch" }, { "title": "SK hynix — Small Size, Big Impact", "url": "https://news.skhynix.com/en/small-size-big-impact/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/package-thermomechanical-reliability-723dba57eff2f204.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Flip-chip assembly and organic substrates", "url": "https://semiaifoundry.com/learn/atlas/flip-chip-abf-substrate/" }, { "title": "Microbumps, reflow and thermocompression", "url": "https://semiaifoundry.com/learn/atlas/bump-thermocompression-assembly/" }, { "title": "Thermal interface material", "url": "https://semiaifoundry.com/learn/atlas/thermal-interface/" }, { "title": "Lid and heat spreader", "url": "https://semiaifoundry.com/learn/atlas/heat-spreader/" }, { "title": "Hybrid bonding: surface state and alignment", "url": "https://semiaifoundry.com/learn/atlas/hybrid-bond-surface-alignment/" } ], "recordHash": "7ce4e4577c171b4da02021b2b5c4786a92371c0fd70fb935c484a1228ffecf58" }, { "id": "atlas-lesson-parallelism", "title": "Data, tensor, pipeline, and state parallelism", "category": "learning", "format": "Atlas lesson", "description": "Splits model work and state across devices to fit memory and exploit concurrent execution.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/parallelism/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Distributed software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Sequence packing and uneven batches can change the effective count.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/parallelism-9dfa2adfc60daa86.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#parallelism", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9d2b996b216f76fc37edd1552777bb97143d565c579d6ce4b90b5c46f293d93d", "contentLength": 5339, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-parallelism.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-parallelism.md", "sections": [ { "id": "section-1", "title": "Data, tensor, pipeline, and state parallelism" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Global batch accounting" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which strategy splits work inside an individual layer?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2021 · Large-model tensor, pipeline, and data parallelism analyzed together" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#parallelism" }, { "title": "Narayanan et al. — Efficient Large-Scale Language Model Training", "url": "https://arxiv.org/abs/2104.04473" }, { "title": "NVIDIA Megatron Core — Parallelism Strategies", "url": "https://docs.nvidia.com/megatron-core/developer-guide/latest/user-guide/parallelism-guide.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/parallelism-9dfa2adfc60daa86.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" } ], "recordHash": "58fc796d1d9b7d6489811cf8ba0e070dc75e67964a053f99b93a0cc2902fbd43" }, { "id": "atlas-lesson-parallelism-communication-budget", "title": "Parallelism as a memory and communication budget", "category": "learning", "format": "Atlas lesson", "description": "Chooses tensor, pipeline, data and state partitions under topology and dependency constraints.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/parallelism-communication-budget/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No particular collective algorithm is assumed universally. Published TPU topology and ZeRO methods provide examples, not interchangeable performance constants.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/parallelism-communication-budget-0dc71e564bfad9c8.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#parallelism-communication-budget", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "76db17133e87e8be26658c0ed33d7d8d97eee5b68c0a83c108b36aca366f2fb5", "contentLength": 5234, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-parallelism-communication-budget.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-parallelism-communication-budget.md", "sections": [ { "id": "section-1", "title": "Parallelism as a memory and communication budget" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Communication approximation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which partition commonly splits a single matrix operation across devices?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#parallelism-communication-budget" }, { "title": "ZeRO: Memory Optimizations Toward Training Trillion Parameter Models", "url": "https://arxiv.org/abs/1910.02054" }, { "title": "TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings", "url": "https://arxiv.org/abs/2304.01433v3" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/parallelism-communication-budget-0dc71e564bfad9c8.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Training state and activation rematerialization", "url": "https://semiaifoundry.com/learn/atlas/training-memory-state/" } ], "recordHash": "13e38690ad6486523b209b3f9f4ff8c6689c606be1dbec7120f4063666225964" }, { "id": "atlas-lesson-pcie-cxl-semantics", "title": "PCIe and CXL: transport versus memory semantics", "category": "learning", "format": "Atlas lesson", "description": "Distinguishes peripheral data transfer from supported coherent memory operations.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/pcie-cxl-semantics/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Chip-to-hall integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "CXL 2.0 is a historical teaching disclosure. No latest-generation support, universal latency or arbitrary platform compatibility is asserted.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/pcie-cxl-semantics-e6a6b492b501174a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#pcie-cxl-semantics", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "7285088409ff51279a6e406a0fe77406d4111e3c45a23c81451089036365a8ae", "contentLength": 4674, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-pcie-cxl-semantics.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-pcie-cxl-semantics.md", "sections": [ { "id": "section-1", "title": "PCIe and CXL: transport versus memory semantics" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Two-tier access estimate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does adding CXL memory establish most directly?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#pcie-cxl-semantics" }, { "title": "Compute Express Link 2.0 Specification Now Available", "url": "https://computeexpresslink.org/blog/compute-express-link-2-0-specification-now-available-2374/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/pcie-cxl-semantics-e6a6b492b501174a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "PCI Express interconnect", "url": "https://semiaifoundry.com/learn/atlas/pcie-interface/" }, { "title": "DDR5 server memory", "url": "https://semiaifoundry.com/learn/atlas/ddr-memory/" }, { "title": "Die-to-die links and UCIe compatibility", "url": "https://semiaifoundry.com/learn/atlas/die-link-compatibility/" } ], "recordHash": "dc9c4dbd444860fed0df5e09232f8173689a7b396715f3da944f8fd97e70a405" }, { "id": "atlas-lesson-pcie-interface", "title": "PCI Express interconnect", "category": "learning", "format": "Atlas lesson", "description": "Connects host processors, accelerators, storage, and network adapters through standardized serial links.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/pcie-interface/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Connectivity", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Protocol packets, flow control and platform limits reduce delivered throughput.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/pcie-interface-d5ac5ff5f0371444.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#pcie-interface", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bc68bab09a322afefcc77f7e0d1b13b38fafce12b7889231ab7c1cfddf5d8991", "contentLength": 5922, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-pcie-interface.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-pcie-interface.md", "sections": [ { "id": "section-1", "title": "PCI Express interconnect" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Encoding and protocol reduce raw lane bandwidth" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What happens if a fast PCIe device is connected through a slower supported host path?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#pcie-interface" }, { "title": "PCI-SIG: PCIe 5.0 signaling rates", "url": "https://pcisig.com/what-bit-rates-does-pcie-50-specification-support-and-how-does-it-compare-prior-pcie-generations" }, { "title": "PCI-SIG: PCIe 6.0 FAQ", "url": "https://pcisig.com/faq?field_category_value%5B%5D=pci_express_6.0&keys=PAM4" }, { "title": "Intel: PCI Express Gen4/Gen5 architecture and encoding", "url": "https://edc.intel.com/content/www/us/en/design/products/platforms/details/raptor-lake-s/13th-generation-core-processors-datasheet-volume-1-of-2/004/pci-express-architecture/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/pcie-interface-d5ac5ff5f0371444.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Network interface adapter", "url": "https://semiaifoundry.com/learn/atlas/network-adapter/" }, { "title": "NVMe solid-state storage", "url": "https://semiaifoundry.com/learn/atlas/nvme-storage/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" } ], "recordHash": "25ff31809af99cebc70a479950bb027aebeec2f4b04e81102baab017979e0bb1" }, { "id": "atlas-lesson-plasma-wet-etch-transfer", "title": "Plasma and wet etch: selectivity and profile", "category": "learning", "format": "Atlas lesson", "description": "Removes selected material while preserving the feature and surrounding stack.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/plasma-wet-etch-transfer/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Repeated operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No plasma settings or wet-chemical composition is given. Schematic etch routes are not production recipes or proof of a defect cause.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/plasma-wet-etch-transfer-31e7a07c6260f656.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#plasma-wet-etch-transfer", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bfa4c00d52bf83b237fa5c857bfab9e04d3511ea2ebef37cf6a3b2e2d22b1a27", "contentLength": 5154, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-plasma-wet-etch-transfer.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-plasma-wet-etch-transfer.md", "sections": [ { "id": "section-1", "title": "Plasma and wet etch: selectivity and profile" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Mask-consumption estimate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A process preserves the mask well but leaves tapered holes. Which property is still inadequate?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#plasma-wet-etch-transfer" }, { "title": "Lam Research — Our Processes", "url": "https://www.lamresearch.com/products/our-processes/" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "Applied Materials — New Ways to Shrink", "url": "https://ir.appliedmaterials.com/static-files/f2fbf48d-a761-4c4f-ab4c-73f312ab1ebc" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/plasma-wet-etch-transfer-31e7a07c6260f656.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Coat, bake, expose and develop", "url": "https://semiaifoundry.com/learn/atlas/resist-track-development/" }, { "title": "A process chamber as a controlled reactor", "url": "https://semiaifoundry.com/learn/atlas/process-chamber-control/" }, { "title": "Nanosheet release and replacement gates", "url": "https://semiaifoundry.com/learn/atlas/nanosheet-gate-last-integration/" }, { "title": "TSV formation, keep-out and backside reveal", "url": "https://semiaifoundry.com/learn/atlas/hbm-tsv-reveal/" } ], "recordHash": "d4353608a7f9c8e43d4102190d433cee7f0f0cc7135628eb151d572e4bcb2834" }, { "id": "atlas-lesson-pn-junction", "title": "P–n junction and depletion region", "category": "learning", "format": "Atlas lesson", "description": "Creates an internal electric field between differently doped regions.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/pn-junction/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Device physics", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The equation assumes an abrupt equilibrium junction and ideal statistics.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/pn-junction-6a1fb41fe7e4475e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#pn-junction", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c5da098dc1cb88bec35203889dad4b22579d67117149d6fd2bf0f076ca6b3c30", "contentLength": 4589, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-pn-junction.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-pn-junction.md", "sections": [ { "id": "section-1", "title": "P–n junction and depletion region" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Built-in junction potential" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What happens to net current at thermal equilibrium?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#pn-junction" }, { "title": "MIT 6.012 — PN Junction Electrostatics", "url": "https://ocw.mit.edu/courses/6-012-microelectronic-devices-and-circuits-fall-2005/188f6340d4d10b0e923d1c0166c8fba1_lec5.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/pn-junction-6a1fb41fe7e4475e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Donor and acceptor doping", "url": "https://semiaifoundry.com/learn/atlas/doping/" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Source and drain regions", "url": "https://semiaifoundry.com/learn/atlas/source-drain/" } ], "recordHash": "2f6a043e3f94294087ef765095687e9e535b5fc107dd379e9881b69b4d7b7db4" }, { "id": "atlas-lesson-policy-gradient-kl-control", "title": "Rollouts, advantages and PPO constraints", "category": "learning", "format": "Atlas lesson", "description": "Separate sampled advantages, old-policy ratios, clipping and reference KL.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-posttraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. One sampled-action term with fixed advantage. PPO formula is worked-only; executable core uses REINFORCE plus exact two-action KL, not PPO or GRPO. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/policy-gradient-kl-control-8b31ebf5543b07d9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#policy-gradient-kl-control", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "32b5181cdb6ae344d4623f4a68edeb2b048e761f661dfdc38c25dbbefb129c0a", "contentLength": 6674, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-policy-gradient-kl-control.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-policy-gradient-kl-control.md", "sections": [ { "id": "section-1", "title": "Rollouts, advantages and PPO constraints" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Rollouts, advantages and PPO constraints · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "For advantage −2 and ratio 1.4, what is the clipped-surrogate contribution?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#policy-gradient-kl-control" }, { "title": "Proximal Policy Optimization Algorithms", "url": "https://arxiv.org/pdf/1707.06347" }, { "title": "Training language models to follow instructions with human feedback", "url": "https://arxiv.org/html/2203.02155v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/policy-gradient-kl-control-8b31ebf5543b07d9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "DPO policy/reference likelihood ratios", "url": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/" }, { "title": "Verifiers, grouped advantages and RLVR", "url": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/" }, { "title": "When reward improves but the task gets worse", "url": "https://semiaifoundry.com/learn/atlas/reward-proxy-overoptimization/" }, { "title": "Frozen base weights and trainable adapters", "url": "https://semiaifoundry.com/learn/atlas/low-rank-adaptation/" }, { "title": "Transfer outputs without confusing size with quality", "url": "https://semiaifoundry.com/learn/atlas/teacher-student-distillation/" } ], "recordHash": "0b7627f520ba33bfb1a1a658efd724214242297bef5f428af34804cfed9933ed" }, { "id": "atlas-lesson-positional-encoding", "title": "Position representation", "category": "learning", "format": "Atlas lesson", "description": "Make sequence order available to attention.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/positional-encoding/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Representation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example illustrates the orthogonal-rotation identity in the linked RoFormer paper. Angles are teaching choices; frequency schedules, dimension pairing and context extension depend on the specified positional method.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/positional-encoding-d1cb9687bb660bb2.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#positional-encoding", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "70f6fefb27989a57614757e27402a6fff8cfeff41a6bbab988b545237429be4f", "contentLength": 4631, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-positional-encoding.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-positional-encoding.md", "sections": [ { "id": "section-1", "title": "Position representation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Relative position from paired rotations" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why add position information?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2021 · RoFormer proposes rotary position embedding" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#positional-encoding" }, { "title": "Su et al. — RoFormer", "url": "https://arxiv.org/abs/2104.09864" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/positional-encoding-d1cb9687bb660bb2.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" } ], "recordHash": "af435ab5ea03980a075a6819e560e07e228918aa37b40dd3be0f09072468fe42" }, { "id": "atlas-lesson-post-training", "title": "Post-training & feedback", "category": "learning", "format": "Atlas lesson", "description": "Shape a pretrained model into an assistant.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/post-training/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Learning", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This illustrates the idealized RLHF objective in the cited InstructGPT work, using invented expected rewards and KL values. Reward quality, the chosen reference, auxiliary objectives and deployment evaluation are separate; no private training recipe is assumed.\n\nThe incident policy is explicitly authored. The extension distinguishes behavioral system changes from actual weight adaptation and makes no claim of new post-training execution.\n\nMode: executable SFT DPO and bandit. Core conventions: answer plus EOS SFT, response-pair DPO, one-action bandit rollouts. These are not a claim that every post-training implementation uses the same denominators. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/post-training-e2966da5604cf66a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#post-training", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "384abc390b6bd76dfb11f7297a169ad4a1b55ab3ac5c2d160b2805bdf3bcd1ba", "contentLength": 11899, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-post-training.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-post-training.md", "sections": [ { "id": "section-1", "title": "Post-training & feedback" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Reward optimization with a reference penalty" }, { "id": "section-5", "title": "Choose supervision by the behavior being learned · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "How does post-training differ from adding a prompt?" }, { "id": "section-12", "title": "An application adds a branch that repairs malformed tool arguments, without changing model weights. What changed?" }, { "id": "section-13", "title": "Which comparison is invalid without further interpretation?" }, { "id": "section-14", "title": "Historical context" }, { "id": "section-15", "title": "2022 · InstructGPT combines demonstrations and preferences" }, { "id": "section-16", "title": "Evidence and scope" }, { "id": "section-17", "title": "Sources" }, { "id": "section-18", "title": "Continue exploring" }, { "id": "section-19", "title": "Foundations" }, { "id": "section-20", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#post-training" }, { "title": "Ouyang et al. — Training Language Models to Follow Instructions with Human Feedback", "url": "https://arxiv.org/abs/2203.02155" }, { "title": "Building effective agents", "url": "https://www.anthropic.com/engineering/building-effective-agents" }, { "title": "Training language models to follow instructions with human feedback", "url": "https://arxiv.org/html/2203.02155v1" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/post-training-e2966da5604cf66a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Workflow graphs and explicit state", "url": "https://semiaifoundry.com/learn/atlas/workflow-graphs-state/" }, { "title": "Model artifacts, rollout and drift", "url": "https://semiaifoundry.com/learn/atlas/model-artifact-rollout-drift/" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "DPO policy/reference likelihood ratios", "url": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Verifiers, grouped advantages and RLVR", "url": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/" }, { "title": "When reward improves but the task gets worse", "url": "https://semiaifoundry.com/learn/atlas/reward-proxy-overoptimization/" }, { "title": "Frozen base weights and trainable adapters", "url": "https://semiaifoundry.com/learn/atlas/low-rank-adaptation/" }, { "title": "Transfer outputs without confusing size with quality", "url": "https://semiaifoundry.com/learn/atlas/teacher-student-distillation/" } ], "recordHash": "4e1bcdde4678017f80640e0660c3a2dc42dae8bf2641d7e7ed99da810a06fd7d" }, { "id": "atlas-lesson-power-integrity-budget", "title": "Power integrity and transient voltage margin", "category": "learning", "format": "Atlas lesson", "description": "Keeps the voltage at a chip within its operating window during changing current demand.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/power-integrity-budget/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Chip-to-hall integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Values are illustrative and not operating limits for an AI package. Qualified rail tolerances and regulator behavior are product-specific.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/power-integrity-budget-5b4a5d41b3b5a889.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#power-integrity-budget", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ab0a19b181d6d7255996d9f34b097eecf82c7e3533394c5a6db9d1ac4e34bc05", "contentLength": 4963, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-power-integrity-budget.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-power-integrity-budget.md", "sections": [ { "id": "section-1", "title": "Power integrity and transient voltage margin" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Transient droop terms" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which measurement directly tests a fast supply-droop hypothesis?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#power-integrity-budget" }, { "title": "Signal and Power Integrity Design and Analysis for BoW Interface for Chiplet Integration on Advanced Packaging", "url": "https://research.ibm.com/publications/signal-and-power-integrity-design-and-analysis-for-bunch-of-wires-bow-interface-for-chiplet-integration-on-advanced-packaging" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Hardware", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/power-integrity-budget-5b4a5d41b3b5a889.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Voltage regulator module", "url": "https://semiaifoundry.com/learn/atlas/voltage-regulator/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" }, { "title": "Dynamic load, reserve and power control", "url": "https://semiaifoundry.com/learn/atlas/rack-dynamic-power/" } ], "recordHash": "c2f4ac96456a065204c3a6b8e1838ed4d59d485b8990ac84ab824cbabb25fd6b" }, { "id": "atlas-lesson-power-shelf", "title": "Rack power shelf and DC busbar", "category": "learning", "format": "Atlas lesson", "description": "Converts incoming power and distributes controlled DC supply throughout the rack.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/power-shelf/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Electrical infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example uses steady real-power accounting and a separate resistive segment. Values are synthetic; current limits, protection, voltage drop, AC power factor and transients require additional engineering checks.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/power-shelf-06effe71ff9121fd.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#power-shelf", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "94c896f6ced547be769fa7ea7246f04f948c1b5a35a08f32dfe3db544403e2a4", "contentLength": 4963, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-power-shelf.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-power-shelf.md", "sections": [ { "id": "section-1", "title": "Rack power shelf and DC busbar" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Power conversion and conductor loss" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the nominal 50–51 V figure describe here?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#power-shelf" }, { "title": "NVIDIA — DGX GB Rack Scale Systems Hardware Guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/power-shelf-06effe71ff9121fd.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Power supply and power shelf", "url": "https://semiaifoundry.com/learn/atlas/power-supply/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "GB200 compute tray", "url": "https://semiaifoundry.com/learn/atlas/compute-tray/" }, { "title": "Uninterruptible power supply and backup chain", "url": "https://semiaifoundry.com/learn/atlas/ups/" }, { "title": "Facility cooling and final heat rejection", "url": "https://semiaifoundry.com/learn/atlas/cooling-plant/" } ], "recordHash": "d476c3ed006abb18ae2970f612552c94b11953010a8e397ba58f2f4c55429685" }, { "id": "atlas-lesson-power-supply", "title": "Power supply and power shelf", "category": "learning", "format": "Atlas lesson", "description": "Converts facility power into the regulated DC distribution used by the compute rack.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/power-supply/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Power delivery", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The efficiency identity is independent of brand. Values are synthetic, and real efficiency varies with input, load and temperature; distribution, regulator and facility losses must be accounted for at their own boundaries.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/power-supply-7f2ab40bff890e83.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#power-supply", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "97d3991989f3463ff0d3a61f0a4757f8326b55f957f82037d24821f7b9f71182", "contentLength": 5844, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-power-supply.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-power-supply.md", "sections": [ { "id": "section-1", "title": "Power supply and power shelf" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Conversion loss becomes a cooling load" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a rack have more installed PSU capacity than its normal consumption?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#power-supply" }, { "title": "NVIDIA DGX GB rack systems hardware guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "NVIDIA DGX GB200 SuperPOD reference components", "url": "https://docs.nvidia.com/dgx-superpod/reference-architecture-scalable-infrastructure-gb200/latest/dgx-superpod-components.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/power-supply-7f2ab40bff890e83.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Voltage regulator module", "url": "https://semiaifoundry.com/learn/atlas/voltage-regulator/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "Baseboard management controller", "url": "https://semiaifoundry.com/learn/atlas/management-controller/" }, { "title": "Rack power shelf and DC busbar", "url": "https://semiaifoundry.com/learn/atlas/power-shelf/" } ], "recordHash": "22754262b43ea2f208e9db65236974be0eb08ebef1f7bf018f2dcfbeb9eea26f" }, { "id": "atlas-lesson-preference-reward-model", "title": "Learn a reward from pairwise choices", "category": "learning", "format": "Atlas lesson", "description": "Compute a pairwise preference probability and distinguish a learned score from verified correctness.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/preference-reward-model/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-posttraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Bradley–Terry logistic score-difference model with one explicit preference label. No learned reward model is implemented in the lifecycle core; its reward stage uses a disclosed checker. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/preference-reward-model-c9a7a1809b81ee74.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#preference-reward-model", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "dc22b3da3f78ef26274c3b7469524035b388cadd22f09905fcb745fe0f24ec2d", "contentLength": 6595, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-preference-reward-model.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-preference-reward-model.md", "sections": [ { "id": "section-1", "title": "Learn a reward from pairwise choices" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Learn a reward from pairwise choices · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What remains unchanged after adding 5 to both response scores?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#preference-reward-model" }, { "title": "Training language models to follow instructions with human feedback", "url": "https://arxiv.org/html/2203.02155v1" }, { "title": "Direct Preference Optimization", "url": "https://arxiv.org/html/2305.18290v3" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/preference-reward-model-c9a7a1809b81ee74.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Post-training & feedback", "url": "https://semiaifoundry.com/learn/atlas/post-training/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "DPO policy/reference likelihood ratios", "url": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Verifiers, grouped advantages and RLVR", "url": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/" }, { "title": "When reward improves but the task gets worse", "url": "https://semiaifoundry.com/learn/atlas/reward-proxy-overoptimization/" }, { "title": "Frozen base weights and trainable adapters", "url": "https://semiaifoundry.com/learn/atlas/low-rank-adaptation/" } ], "recordHash": "5057d5ed7f5431f95163b4634fd2da2106a9f485ab3ec4f2b919bd0c96dbd037" }, { "id": "atlas-lesson-prefill-decode-tier-placement", "title": "Prefill, decode and the moving KV working set", "category": "learning", "format": "Atlas lesson", "description": "Place active and reusable inference state according to the execution phase and service deadline.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/prefill-decode-tier-placement/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The equation is an explicitly scoped conventional attention model. It is not a specification of Astra. Any HBF KV placement is a scenario requiring controller/write behavior and serving measurements, not an asserted deployed configuration.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/prefill-decode-tier-placement-e8be7a292be9e9c5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#prefill-decode-tier-placement", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1fd1d3320c087da50771b93a13028bdc35a8e224bbdfb37d36250dd9896d3832", "contentLength": 5940, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-prefill-decode-tier-placement.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-prefill-decode-tier-placement.md", "sections": [ { "id": "section-1", "title": "Prefill, decode and the moving KV working set" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Conventional KV payload" }, { "id": "section-5", "title": "Restore or recompute" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Does a large read-oriented tier automatically suit the active KV cache?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#prefill-decode-tier-placement" }, { "title": "NVIDIA — Mastering LLM Techniques: Inference Optimization", "url": "https://developer.nvidia.com/blog/mastering-llm-techniques-inference-optimization/" }, { "title": "Sandisk — HBF fact sheet", "url": "https://documents.sandisk.com/content/dam/asset-library/en_us/assets/public/sandisk/collateral/company/Sandisk-HBF-Fact-Sheet.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/prefill-decode-tier-placement-e8be7a292be9e9c5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Prefill and prompt processing", "url": "https://semiaifoundry.com/learn/atlas/prefill-resource-trace/" }, { "title": "Autoregressive decode and weight traffic", "url": "https://semiaifoundry.com/learn/atlas/decode-bandwidth-trace/" }, { "title": "Place the working set, not just the model", "url": "https://semiaifoundry.com/learn/atlas/memory-working-set-placement/" }, { "title": "HBF latency, transfer granularity and prefetch", "url": "https://semiaifoundry.com/learn/atlas/hbf-latency-prefetch/" }, { "title": "Prefill/decode disaggregation and useful serving rate", "url": "https://semiaifoundry.com/learn/atlas/disaggregated-serving/" }, { "title": "From memory placement to network, power and cooling", "url": "https://semiaifoundry.com/learn/atlas/memory-to-hall-propagation/" } ], "recordHash": "d680b4ef044d8ab7545475384fd766eefd523cc113d9c05a8539d25773cc2528" }, { "id": "atlas-lesson-prefill-resource-trace", "title": "Prefill and prompt processing", "category": "learning", "format": "Atlas lesson", "description": "Processes many known prompt tokens with substantial potential for weight reuse.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/prefill-resource-trace/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Prefill is not universally compute-bound. The resource trace is illustrative and does not claim an implementation speedup without specified shapes and measured traffic.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/prefill-resource-trace-a76d037833bd69f7.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#prefill-resource-trace", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "51cc844e24447080c27f7fe81021546588ac145990965ea6050980f0f3ac1b82", "contentLength": 5105, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-prefill-resource-trace.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-prefill-resource-trace.md", "sections": [ { "id": "section-1", "title": "Prefill and prompt processing" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Projection work" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can prefill reuse a weight tile more effectively than one-request decode?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#prefill-resource-trace" }, { "title": "FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness", "url": "https://arxiv.org/abs/2205.14135" }, { "title": "DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving", "url": "https://arxiv.org/abs/2401.09670" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/prefill-resource-trace-a76d037833bd69f7.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Historical memory-wall evidence", "url": "https://semiaifoundry.com/learn/atlas/memory-wall-trends/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Autoregressive decode and weight traffic", "url": "https://semiaifoundry.com/learn/atlas/decode-bandwidth-trace/" } ], "recordHash": "cb7fc32f7d32b416998be6612075db81d2b0686c4c2d0cbd3d314a4d00ed07e5" }, { "id": "atlas-lesson-probability-calibration-abstention", "title": "Confidence, errors and refusal to guess", "category": "learning", "format": "Atlas lesson", "description": "Evaluate probability quality and selective error using distinct calibration and final-test data.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/probability-calibration-abstention/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-evaluation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Binary Brier convention shown, not sum over both class coordinates. Authored predictions; no calibration fitting feature is implemented in the lifecycle core. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/probability-calibration-abstention-ffb9054290f936c8.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#probability-calibration-abstention", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1e95b7b22a61bf242816eb2289bba2ca24dd373d748c2e54d4e28f00b7a628b2", "contentLength": 7470, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-probability-calibration-abstention.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-probability-calibration-abstention.md", "sections": [ { "id": "section-1", "title": "Confidence, errors and refusal to guess" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Confidence, errors and refusal to guess · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "How should a threshold answering zero cases be reported?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#probability-calibration-abstention" }, { "title": "On Calibration of Modern Neural Networks", "url": "https://arxiv.org/html/1706.04599v2" }, { "title": "Holistic Evaluation of Language Models", "url": "https://arxiv.org/html/2211.09110v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/probability-calibration-abstention-ffb9054290f936c8.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Sampling variability and independent evidence", "url": "https://semiaifoundry.com/learn/atlas/sampling-estimation-uncertainty/" }, { "title": "Human and model judgments under a rubric", "url": "https://semiaifoundry.com/learn/atlas/judge-rubric-agreement/" }, { "title": "From lexical retrieval to model answers with evidence", "url": "https://semiaifoundry.com/learn/atlas/retrieval-supported-generation/" }, { "title": "Sampling more candidates versus selecting correct ones", "url": "https://semiaifoundry.com/learn/atlas/test-time-search-verification/" }, { "title": "Version the entire evaluated system", "url": "https://semiaifoundry.com/learn/atlas/model-system-regression-contract/" }, { "title": "Model artifacts, rollout and drift", "url": "https://semiaifoundry.com/learn/atlas/model-artifact-rollout-drift/" }, { "title": "Filtering, duplication and contamination", "url": "https://semiaifoundry.com/learn/atlas/data-quality-dedup-audit/" } ], "recordHash": "93ae814baa9a9230ec22c83b1dda3973f73d2b6972e3b1185b3eec67f0906295" }, { "id": "atlas-lesson-probability-conditioning-information", "title": "Probability, likelihood and stable information", "category": "learning", "format": "Atlas lesson", "description": "Connects model scores to probabilities, information and the gradients that guide learning.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/probability-conditioning-information/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "mathematical-foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. Finite logits, categorical outcomes and a single observed class. Natural logarithms are used. Conditioning on further evidence requires its own likelihood model; the workbench changes scores rather than demonstrating Bayesian updating.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/probability-conditioning-information-f8be7a0be8d8ae57.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#probability-conditioning-information", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "06d9e5460609cea06e06477b96a00ccb8fa4fb58b39d0cf780e9099fa0a39eb7", "contentLength": 6631, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-probability-conditioning-information.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-probability-conditioning-information.md", "sections": [ { "id": "section-1", "title": "Probability, likelihood and stable information" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Probability, likelihood and stable information" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does adding the same finite constant to all logits do mathematically?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#probability-conditioning-information" }, { "title": "Goodfellow, Bengio and Courville · Probability and information theory", "url": "https://www.deeplearningbook.org/contents/prob.html" }, { "title": "Goodfellow, Bengio and Courville · Numerical computation", "url": "https://www.deeplearningbook.org/contents/numerical.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/probability-conditioning-information-f8be7a0be8d8ae57.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "7bc1301bbc141f860bece6b7c0945bbc7a574574af1f46c91ed550a0c3ca9758" }, { "id": "atlas-lesson-process-chamber-control", "title": "A process chamber as a controlled reactor", "category": "learning", "format": "Atlas lesson", "description": "Transforms a wafer through coupled gas, energy, surface and measurement systems.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/process-chamber-control/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Factory systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No chemical recipe or production setpoints are supplied. The gas balance illustrates control, not plasma density or reaction kinetics.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/process-chamber-control-7b0bc6744d0a600c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#process-chamber-control", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ee89acfbe339aa573dd73dd10edb6e08cece93a0730d2a6572980077b7e7ffd8", "contentLength": 5203, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-process-chamber-control.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-process-chamber-control.md", "sections": [ { "id": "section-1", "title": "A process chamber as a controlled reactor" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Simple chamber gas balance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Pressure traces match but film thickness changes. What remains possible?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#process-chamber-control" }, { "title": "Lam Research — Our Processes", "url": "https://www.lamresearch.com/products/our-processes/" }, { "title": "Edwards — Semiconductor vacuum and abatement", "url": "https://www.edwardsvacuum.com/en-us/semiconductor" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/process-chamber-control-7b0bc6744d0a600c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Cleanroom and subfab utilities", "url": "https://semiaifoundry.com/learn/atlas/cleanroom-subfab-utilities/" }, { "title": "ALD and self-limiting surface reactions", "url": "https://semiaifoundry.com/learn/atlas/ald-self-limiting-growth/" }, { "title": "Plasma and wet etch: selectivity and profile", "url": "https://semiaifoundry.com/learn/atlas/plasma-wet-etch-transfer/" }, { "title": "Metrology, inspection and process windows", "url": "https://semiaifoundry.com/learn/atlas/fab-metrology-process-window/" } ], "recordHash": "99e3a914a33438cc9981a0a7d4c227dccdb36109aa9741c5b2ec1adccd433ef3" }, { "id": "atlas-lesson-process-dma-address-spaces", "title": "Process, physical and device address spaces", "category": "learning", "format": "Atlas lesson", "description": "Trace the same allocated bytes through separate CPU virtual and device-visible mappings.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/process-dma-address-spaces/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Primary sources establish the cited runtime mechanisms. Numerical values, address ranges, ABI strings, event schedule and reset/retry epochs are authored teaching contracts. No real device, firmware image, operating-system driver, page table, cache protocol or security verification is executed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/process-dma-address-spaces-09d9cb6220362ce0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#process-dma-address-spaces", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "43335ca9d896ad080a7b18cf0101e321ec0e3caeb7601552ec420d1034830c34", "contentLength": 5894, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-process-dma-address-spaces.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-process-dma-address-spaces.md", "sections": [ { "id": "section-1", "title": "Process, physical and device address spaces" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Preserve the offset across address spaces" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which device address reaches A’s fourth word in this declared map?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#process-dma-address-spaces" }, { "title": "Linux 6.16 — Dynamic DMA mapping Guide", "url": "https://docs.kernel.org/6.16/core-api/dma-api-howto.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/process-dma-address-spaces-09d9cb6220362ce0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Firmware handoff and device readiness", "url": "https://semiaifoundry.com/learn/atlas/firmware-device-contract/" }, { "title": "IOMMU permission and tensor identity", "url": "https://semiaifoundry.com/learn/atlas/iommu-buffer-identity/" }, { "title": "PCI Express interconnect", "url": "https://semiaifoundry.com/learn/atlas/pcie-interface/" }, { "title": "PCIe and CXL: transport versus memory semantics", "url": "https://semiaifoundry.com/learn/atlas/pcie-cxl-semantics/" } ], "recordHash": "23e061c521ed8112309376ff670ff83040a2ab2e431ba47cb8f02f635844890b" }, { "id": "atlas-lesson-production-ramp-allocation", "title": "Production ramps, inventory and allocation", "category": "learning", "format": "Atlas lesson", "description": "Tracks time-dependent output and distinguishes qualified supply from a customer’s accessible share.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/production-ramp-allocation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center physical systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Allocation fractions and delays are synthetic. TSMC source material supports planning roles, not confidential queues, customer shares or current unit-per-month estimates.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/production-ramp-allocation-3d4ff12263731960.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#production-ramp-allocation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "12330e75e931a266c5a7fc9cef4ed121ccf2617eefe56764091563d94877847f", "contentLength": 5304, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-production-ramp-allocation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-production-ramp-allocation.md", "sections": [ { "id": "section-1", "title": "Production ramps, inventory and allocation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Inventory conservation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a capacity increase fail to improve next week’s deliveries?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#production-ramp-allocation" }, { "title": "TSMC 2025 Annual Report", "url": "https://investor.tsmc.com/sites/ir/annual-report/2025/2025%20TSMC%20Annual%20Report.E.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/production-ramp-allocation-3d4ff12263731960.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Compatible supply and converging bottlenecks", "url": "https://semiaifoundry.com/learn/atlas/compatible-supply-capacity/" }, { "title": "Facility phases and geographical evidence", "url": "https://semiaifoundry.com/learn/atlas/capacity-phase-geography/" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" } ], "recordHash": "6397cb8cde5c244bf84cb01e027c22998d56d08e03a83f339a10e7e10467bd84" }, { "id": "atlas-lesson-quantization", "title": "Quantization and numerical representation", "category": "learning", "format": "Atlas lesson", "description": "Represents model values with reduced precision to lower storage and arithmetic costs.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/quantization/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model deployment", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The linked quantization references supply the representation context. This example assumes positive fixed scale and nearest rounding without clipping; it does not bound model accuracy or describe every low-bit floating-point format.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/quantization-7283db1a755017ec.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#quantization", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "249952a95cafe3ae475fb1de972d3ab38b508da44e02e7c50d0dc3f5ea439363", "contentLength": 5334, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-quantization.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-quantization.md", "sections": [ { "id": "section-1", "title": "Quantization and numerical representation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Unclipped rounding-error bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What happens to a value outside the chosen quantization range?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#quantization" }, { "title": "NVIDIA TensorRT — Quantize Operator", "url": "https://docs.nvidia.com/deeplearning/tensorrt/latest/_static/operators/Quantize.html" }, { "title": "NVIDIA TensorRT — Quantization Schemes", "url": "https://docs.nvidia.com/deeplearning/tensorrt/latest/inference-library/quantized-types-schemes.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/quantization-7283db1a755017ec.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" } ], "recordHash": "9b3aa2525d77e90ddfc2ab4f91b90fe5f99fb689c3887bc2f147d2c31febe9f1" }, { "id": "atlas-lesson-rack", "title": "Integrated accelerator rack: GB200 NVL72 example", "category": "learning", "format": "Atlas lesson", "description": "Integrates compute, communication, power, and cooling into one coordinated physical system.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/rack/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Rack integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The terms require a common workload and time boundary.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/rack-d8e166de597e4f4d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#rack", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a471d6a93488d62c719eb753e115db0f198150a88e92c62eb86f829db2301da4", "contentLength": 5940, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rack.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rack.md", "sections": [ { "id": "section-1", "title": "Integrated accelerator rack: GB200 NVL72 example" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Communication-aware throughput ceiling" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What makes the rack a usable AI system?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2024 · GB200 NVL72 rack-scale architecture announced" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#rack" }, { "title": "NVIDIA — GB200 NVL72 Architecture, March 2024", "url": "https://developer.nvidia.com/blog/nvidia-gb200-nvl72-delivers-trillion-parameter-llm-training-and-real-time-inference/" }, { "title": "NVIDIA — GB200 NVL72 Product Specifications", "url": "https://www.nvidia.com/en-us/data-center/gb200-nvl72/" }, { "title": "NVIDIA — DGX GB Rack Scale Systems Hardware Guide", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Berkeley Lab — Introduction to Roofline", "url": "https://crd.lbl.gov/assets/Uploads/ECP19-Roofline-1-intro.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/rack-d8e166de597e4f4d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "Rack power shelf and DC busbar", "url": "https://semiaifoundry.com/learn/atlas/power-shelf/" }, { "title": "GB200 compute tray", "url": "https://semiaifoundry.com/learn/atlas/compute-tray/" }, { "title": "NVLink switch tray and scale-up fabric", "url": "https://semiaifoundry.com/learn/atlas/nvlink-switch/" }, { "title": "NVLink copper cable cartridge", "url": "https://semiaifoundry.com/learn/atlas/cable-cartridge/" }, { "title": "Coolant distribution unit and separated loops", "url": "https://semiaifoundry.com/learn/atlas/cdu/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" } ], "recordHash": "a132aadfebb63c81a319ea4de7bf0bf06ca067ae37d9397f8e05a2a13ac35641" }, { "id": "atlas-lesson-rack-dynamic-power", "title": "Dynamic load, reserve and power control", "category": "learning", "format": "Atlas lesson", "description": "Accounts for changes in electrical demand over timescales from chip activity to facility operation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/rack-dynamic-power/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center physical systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No universal AI load waveform is assumed. Real simultaneous behavior and control response need facility and device telemetry.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/rack-dynamic-power-8c5f087739d666b7.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#rack-dynamic-power", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "596ded60dbb849d255f332e2d0e37bfa489322d6701c5b5d4bb5e0355c7ed425", "contentLength": 4703, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rack-dynamic-power.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rack-dynamic-power.md", "sections": [ { "id": "section-1", "title": "Dynamic load, reserve and power control" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Energy integral" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What additional quantity is needed to turn power into energy?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#rack-dynamic-power" }, { "title": "Key Questions on Energy and AI: Executive Summary", "url": "https://www.iea.org/reports/key-questions-on-energy-and-ai/executive-summary" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Hardware", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/rack-dynamic-power-8c5f087739d666b7.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Power supply and power shelf", "url": "https://semiaifoundry.com/learn/atlas/power-supply/" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" }, { "title": "Power integrity and transient voltage margin", "url": "https://semiaifoundry.com/learn/atlas/power-integrity-budget/" }, { "title": "Uninterruptible power supply and backup chain", "url": "https://semiaifoundry.com/learn/atlas/ups/" } ], "recordHash": "9a21bd61818b1e54df95638bdc1d20279c2da82e9bead968c68b202e1eca52bf" }, { "id": "atlas-lesson-rack-power-conversion", "title": "Rack power conversion and distribution", "category": "learning", "format": "Atlas lesson", "description": "Moves electrical energy from facility supply through conversion stages to low-voltage chip rails.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/rack-power-conversion/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center physical systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The numeric example is not a product rail specification. Documented rack DC and approximate rack power are source-scoped in the claims ledger.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/rack-power-conversion-594556674a19ceb6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#rack-power-conversion", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "66928544dbd3f03f1e32018f5f444dfb7b3c173d3d6c7cf363d43d944282918f", "contentLength": 4850, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rack-power-conversion.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rack-power-conversion.md", "sections": [ { "id": "section-1", "title": "Rack power conversion and distribution" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Conversion accounting" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does a low-voltage rail require large current at high power?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#rack-power-conversion" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Hardware", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/rack-power-conversion-594556674a19ceb6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Power supply and power shelf", "url": "https://semiaifoundry.com/learn/atlas/power-supply/" }, { "title": "Voltage regulator module", "url": "https://semiaifoundry.com/learn/atlas/voltage-regulator/" }, { "title": "Rack power shelf and DC busbar", "url": "https://semiaifoundry.com/learn/atlas/power-shelf/" }, { "title": "Power integrity and transient voltage margin", "url": "https://semiaifoundry.com/learn/atlas/power-integrity-budget/" } ], "recordHash": "530eae7ad3f2469fe673976433071778f2cdf5367037b4f577f1bbd6f0058b39" }, { "id": "atlas-lesson-rack-reference-anatomy", "title": "A documented rack as a system boundary", "category": "learning", "format": "Atlas lesson", "description": "Connects compute trays, switches, management, power and cooling in one named reference.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/rack-reference-anatomy/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Chip-to-hall integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The exact tray count is source-reported in the claims ledger. Mixed cooling and power details are specific to the reference, not universal rack standards.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/rack-reference-anatomy-ea8cb65c5ed019e3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#rack-reference-anatomy", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "08c0cb45a2704825c8c31135782a011516048a18ef20f8ec74b4cf1de403d668", "contentLength": 4803, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rack-reference-anatomy.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rack-reference-anatomy.md", "sections": [ { "id": "section-1", "title": "A documented rack as a system boundary" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Component consistency" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why preserve a named reference configuration?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#rack-reference-anatomy" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Hardware", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/rack-reference-anatomy-ea8cb65c5ed019e3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "GB200 compute tray", "url": "https://semiaifoundry.com/learn/atlas/compute-tray/" }, { "title": "NVLink switch tray and scale-up fabric", "url": "https://semiaifoundry.com/learn/atlas/nvlink-switch/" }, { "title": "Rack power conversion and distribution", "url": "https://semiaifoundry.com/learn/atlas/rack-power-conversion/" } ], "recordHash": "b6e3d47d71ac4e09112af6237e21df0410fb2b6d6f69ceb028cad4c78f77b678" }, { "id": "atlas-lesson-rdl-fanout-integration", "title": "Redistribution layers and fan-out packaging", "category": "learning", "format": "Atlas lesson", "description": "Routes die connections through added layers that can extend beyond the die footprint.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/rdl-fanout-integration/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Materials and assembly", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The lesson shows a generic reconstruction sequence, not a vendor’s complete fan-out recipe or qualified alignment budget.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/rdl-fanout-integration-495fe537b597d1ea.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#rdl-fanout-integration", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "e66168ec065a763da41534830d09bfa875afda386943f8a4214c85738fda9cfc", "contentLength": 5180, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rdl-fanout-integration.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-rdl-fanout-integration.md", "sections": [ { "id": "section-1", "title": "Redistribution layers and fan-out packaging" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Registration budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can die placement error matter before RDL patterning?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#rdl-fanout-integration" }, { "title": "SK hynix — Small Size, Big Impact", "url": "https://news.skhynix.com/en/small-size-big-impact/" }, { "title": "TSMC — CoWoS", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm" }, { "title": "Amkor — Flip Chip Packaging", "url": "https://amkor.com/technology/flip-chip/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/rdl-fanout-integration-495fe537b597d1ea.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Flip-chip assembly and organic substrates", "url": "https://semiaifoundry.com/learn/atlas/flip-chip-abf-substrate/" }, { "title": "Wafer handling, carriers and genealogy", "url": "https://semiaifoundry.com/learn/atlas/wafer-handling-genealogy/" }, { "title": "CoWoS-R and CoWoS-L: RDL and local silicon", "url": "https://semiaifoundry.com/learn/atlas/cowos-r-l-routing/" }, { "title": "Temporary bonding, thinning and singulation", "url": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/" } ], "recordHash": "ccfc96263d0709cff731f1471b650bbda3116e95eefb39395ccb2d76ba9f10d7" }, { "id": "atlas-lesson-recommendation-ranking-feedback", "title": "Ranking changes what is observed", "category": "learning", "format": "Atlas lesson", "description": "Candidate retrieval, sparse embeddings, ranking, exposure and feedback bias.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/recommendation-ranking-feedback/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Models become evaluated applications", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. The relevance labels here are authored and independent of clicks. This metric does not correct exposure bias, missing labels or changing user utility.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/recommendation-ranking-feedback-86af64ba4c3679a5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#recommendation-ranking-feedback", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "cfde21de92d5d9a9cbccbd63783c14d4dfa4ccffae4f9d92408c8d2a5c1fce0a", "contentLength": 6264, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-recommendation-ranking-feedback.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-recommendation-ranking-feedback.md", "sections": [ { "id": "section-1", "title": "Ranking changes what is observed" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Ranking changes what is observed · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "An item was never displayed. What does its zero-click count establish?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#recommendation-ranking-feedback" }, { "title": "Deep Learning Recommendation Model for Personalization and Recommendation Systems", "url": "https://arxiv.org/abs/1906.00091" }, { "title": "Joachims, Swaminathan and Schnabel · Unbiased Learning-to-Rank with Biased Feedback", "url": "https://arxiv.org/abs/1608.04468" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/recommendation-ranking-feedback-86af64ba4c3679a5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" } ], "recordHash": "941c9fdd1cb82d19de2acf13b11b9ff5f6a4f410f219510ea6071c0b77f63920" }, { "id": "atlas-lesson-regional-siting-access", "title": "Siting, regional infrastructure and access to compute", "category": "learning", "format": "Atlas lesson", "description": "Connects location choices to service paths, resources and who can actually use capacity.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/regional-siting-access/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Global AI infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No jurisdiction-specific legal advice or exhaustive regional census is provided. Public project and procurement statements support dated examples only.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/regional-siting-access-797dbbfb173b8938.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#regional-siting-access", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "1a3129d740049b56694991840e8c05f3aee9e88a5cf4791f751414d6b9a1fe96", "contentLength": 5348, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-regional-siting-access.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-regional-siting-access.md", "sections": [ { "id": "section-1", "title": "Siting, regional infrastructure and access to compute" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Conditional site score" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which question distinguishes accessible capacity from physical capacity?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#regional-siting-access" }, { "title": "Google AI Hub construction milestone in India", "url": "https://blog.google/intl/en-in/google-ai-hub-scaling-indias-ai-infrastructure-and-community-impact/" }, { "title": "The EuroHPC Joint Undertaking launches the AI Gigafactories Call", "url": "https://www.eurohpc-ju.europa.eu/eurohpc-joint-undertaking-launches-ai-gigafactories-call-2026-07-30_en" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/regional-siting-access-797dbbfb173b8938.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Facility phases and geographical evidence", "url": "https://semiaifoundry.com/learn/atlas/capacity-phase-geography/" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" }, { "title": "Grid interconnection and deliverable electrical capacity", "url": "https://semiaifoundry.com/learn/atlas/grid-interconnection-readiness/" }, { "title": "Job admission, topology and resource fragmentation", "url": "https://semiaifoundry.com/learn/atlas/topology-job-admission/" } ], "recordHash": "50448a99fc08ca02580f6b99fde7885bda85e817b8d27b305e2fc501079d326b" }, { "id": "atlas-lesson-register-file", "title": "Register file", "category": "learning", "format": "Atlas lesson", "description": "Keeps each active thread’s immediate values close to the arithmetic pipelines.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/register-file/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory hierarchy", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The model ignores allocation granularity, spilling and architecture-specific limits.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/register-file-a316c3c8ecd82c48.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#register-file", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "8080f8b80d72d2a7706b135853919d21933065b90e17581178b197391d4cf3d5", "contentLength": 5573, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-register-file.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-register-file.md", "sections": [ { "id": "section-1", "title": "Register file" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Register allocation limits resident work" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What can happen when each thread uses many more registers?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#register-file" }, { "title": "NVIDIA CUDA Blackwell Tuning Guide", "url": "https://docs.nvidia.com/cuda/blackwell-tuning-guide/index.html" }, { "title": "NVIDIA: Register Cache for Warp-Centric CUDA Programs", "url": "https://developer.nvidia.com/blog/register-cache-warp-cuda/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/register-file-a316c3c8ecd82c48.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "L1 and texture cache", "url": "https://semiaifoundry.com/learn/atlas/l1-cache/" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" } ], "recordHash": "c324afa3e98d981e4ddd757f9a2a7867d22ab5d69f27a97e97b1dcd94041d11d" }, { "id": "atlas-lesson-replay-retention-forgetting", "title": "Retention, replay and transfer", "category": "learning", "format": "Atlas lesson", "description": "Reason about a fixed-budget retention tradeoff without treating replay as a guarantee.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/replay-retention-forgetting/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-continuation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable replay; worked ideal optimum. One identical prompt with contradictory binary labels, unlimited fitting of its probability and no domain tag. Finite decoder optimization need not reach this ideal optimum. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/replay-retention-forgetting-15a494e0da3c020a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#replay-retention-forgetting", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "dcda482c0744abb8e683df3d0f25a4df4dc85eec4edb440b23cff3b728eaf5e1", "contentLength": 6219, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-replay-retention-forgetting.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-replay-retention-forgetting.md", "sections": [ { "id": "section-1", "title": "Retention, replay and transfer" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Retention, replay and transfer · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can replay improve old-answer likelihood without restoring old-answer accuracy?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#replay-retention-forgetting" }, { "title": "Don’t Stop Pretraining", "url": "https://aclanthology.org/2020.acl-main.740.pdf" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/replay-retention-forgetting-15a494e0da3c020a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Continue language modeling on a new domain", "url": "https://semiaifoundry.com/learn/atlas/domain-adaptive-continuation/" }, { "title": "Describe a stage by its changed contract", "url": "https://semiaifoundry.com/learn/atlas/model-lifecycle-stage-contract/" }, { "title": "Context extension is a learned-use test", "url": "https://semiaifoundry.com/learn/atlas/long-context-adaptation/" }, { "title": "Compatible weight averaging and regressions", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-averaging-boundaries/" } ], "recordHash": "4f77e5e2707fc5339ced3eccdbf6e7dd9161003ffe6cd043baed4c29061cd011" }, { "id": "atlas-lesson-residual-normalization", "title": "Residual stream & normalization", "category": "learning", "format": "Atlas lesson", "description": "Keep a deep sequence of transformations trainable.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/residual-normalization/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Transformer computation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example uses the linked LayerNorm definition over two features. RMSNorm, pre/post-normalization placement and learned parameters differ; the residual operands must have matching shapes, and neither operation guarantees stable training.\n\nMode: executable residual and RMS paths. Fixed gain one; epsilon zero only for the explicitly labeled hand calculation. Core epsilon is 1e-5, so exact scale invariance is qualified. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/residual-normalization-89e7d8a2d9d3801e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#residual-normalization", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "183e209e2f1bb41bd00738258a1c736f698e3494b6062970946cf8c61b7df853", "contentLength": 9207, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-residual-normalization.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-residual-normalization.md", "sections": [ { "id": "section-1", "title": "Residual stream & normalization" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Normalization and a direct gradient route" }, { "id": "section-5", "title": "Activation scale and gradient flow · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "What travels through a residual connection?" }, { "id": "section-12", "title": "Does RMS normalization force the output mean to zero?" }, { "id": "section-13", "title": "Historical context" }, { "id": "section-14", "title": "2016 · Layer normalization removes dependence on batch statistics" }, { "id": "section-15", "title": "Evidence and scope" }, { "id": "section-16", "title": "Sources" }, { "id": "section-17", "title": "Continue exploring" }, { "id": "section-18", "title": "Foundations" }, { "id": "section-19", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#residual-normalization" }, { "title": "Ba et al. — Layer Normalization", "url": "https://arxiv.org/abs/1607.06450" }, { "title": "PyTorch — LayerNorm", "url": "https://docs.pytorch.org/docs/2.14/generated/torch.nn.LayerNorm.html" }, { "title": "He et al. — Deep Residual Learning", "url": "https://arxiv.org/abs/1512.03385" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Root Mean Square Layer Normalization", "url": "https://arxiv.org/html/1910.07467v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/residual-normalization-89e7d8a2d9d3801e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Feed-forward network", "url": "https://semiaifoundry.com/learn/atlas/feed-forward/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "A differentiable computation graph", "url": "https://semiaifoundry.com/learn/atlas/reverse-mode-autodiff/" }, { "title": "Assemble an initialized causal language model", "url": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/" } ], "recordHash": "11eecfc7ef5797501edce7ba4904f49dd77061a92a819b0aa070740eed9e1163" }, { "id": "atlas-lesson-resist-track-development", "title": "Coat, bake, expose and develop", "category": "learning", "format": "Atlas lesson", "description": "Creates a temporary resist pattern that guides the following material operation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/resist-track-development/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Repeated operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No resist formulation, bake setting, developer or exposure dose is specified. Rework eligibility is product and stage dependent.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/resist-track-development-3b6ecbb447455a88.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#resist-track-development", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a1dbd44370df3d2a758e25740efafa4c0c474daf648f66adcacf1fd12797b3c3", "contentLength": 5225, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-resist-track-development.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-resist-track-development.md", "sections": [ { "id": "section-1", "title": "Coat, bake, expose and develop" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Pattern-transfer bias" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "The resist CD is on target but the etched line is too narrow. Which comparison is most useful?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#resist-track-development" }, { "title": "ASML — How microchips are made", "url": "https://www.asml.com/en/technology/all-about-microchips/how-microchips-are-made" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "KLA — Practical Applications of Measurement System Analysis", "url": "https://www.kla.com/documents/5.3_Practical_Applications_of_MSA_Sutherland_KLA.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/resist-track-development-3b6ecbb447455a88.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Lithography and pattern transfer", "url": "https://semiaifoundry.com/learn/atlas/lithography/" }, { "title": "Masks, OPC and pattern-aware design", "url": "https://semiaifoundry.com/learn/atlas/mask-opc-layout/" }, { "title": "DUV, EUV and high-NA imaging", "url": "https://semiaifoundry.com/learn/atlas/lithography-resolution-focus/" }, { "title": "Plasma and wet etch: selectivity and profile", "url": "https://semiaifoundry.com/learn/atlas/plasma-wet-etch-transfer/" } ], "recordHash": "5379ea97e41b5c8bc3d762bdd0f41790a90ad1ff90f38a3d5a104fc5871de64c" }, { "id": "atlas-lesson-retained-work-restart-boundary", "title": "When completed work survives a restart", "category": "learning", "format": "Atlas lesson", "description": "Distinguish completed, restart-durable, unfinished and lost work under a declared failure schedule.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/retained-work-restart-boundary/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The source documents checkpoint completion and valid restart, not this atomic timing or its invented numerical inputs. H7 executes with the included teaching runner; the current browser hall controls do not expose every small fixture rate. No human specialist review, instructor observation or learning efficacy result is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/retained-work-restart-boundary-a29e940810fcb313.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#retained-work-restart-boundary", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "fa31c877b7f459bcfaa6067f81a08030a974c10706f27783065b30e5685273aa", "contentLength": 7531, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-retained-work-restart-boundary.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-retained-work-restart-boundary.md", "sections": [ { "id": "section-1", "title": "When completed work survives a restart" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "An exact work ledger for the example" }, { "id": "section-5", "title": "Energy per retained step" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "In the H7 example, a checkpoint of step 8 commits at 9.25 s. Execution then runs at one step per second until a fault at 12 s. What survives immediately after the fault?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#retained-work-restart-boundary" }, { "title": "LLNL SCR 3.1.0 — checkpoint completion and restart", "url": "https://scr.readthedocs.io/en/latest/users/integration.html" }, { "title": "DOE/LBNL — Data Center Metering and Resource Guide", "url": "https://datacenters.lbl.gov/sites/default/files/DataCenterMeteringandResourceGuide_02072017.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/retained-work-restart-boundary-a29e940810fcb313.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Checkpointing, failure and retained useful work", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-retained-work/" }, { "title": "From memory placement to network, power and cooling", "url": "https://semiaifoundry.com/learn/atlas/memory-to-hall-propagation/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Commissioning a usable AI cluster", "url": "https://semiaifoundry.com/learn/atlas/cluster-commissioning-gates/" }, { "title": "Qualify the memory system and retain useful work", "url": "https://semiaifoundry.com/learn/atlas/memory-system-qualification/" } ], "recordHash": "ee2364cd42803366ffcdb07c05e5190c19b9d84b58b0b65b051d15e86bce0fb2" }, { "id": "atlas-lesson-retrieval-indexing-evaluation", "title": "Retrieval from source document to answer", "category": "learning", "format": "Atlas lesson", "description": "Chunking, lexical versus dense retrieval, provenance, reranking and answer validation are distinct stages.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/retrieval-indexing-evaluation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Models become evaluated applications", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Reference relevance and task labels are fixed independently of the method. Empty relevance sets require a separate convention rather than division by zero.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/retrieval-indexing-evaluation-07d7a69b371fc1e4.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#retrieval-indexing-evaluation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "772fac9a62197faa649835f079dc8b2e01b8b7211a1507b8dbcf8a6cb8221727", "contentLength": 6346, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-retrieval-indexing-evaluation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-retrieval-indexing-evaluation.md", "sections": [ { "id": "section-1", "title": "Retrieval from source document to answer" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Retrieval from source document to answer · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Four supported answers contain three task-correct answers among five questions. What is task accuracy?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#retrieval-indexing-evaluation" }, { "title": "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", "url": "https://arxiv.org/abs/2005.11401" }, { "title": "τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains", "url": "https://arxiv.org/abs/2406.12045" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/retrieval-indexing-evaluation-07d7a69b371fc1e4.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" } ], "recordHash": "05a463cdd4f1de51c12d17886f6db56bf04ea6061d8176cf93a33e46f6cdd462" }, { "id": "atlas-lesson-retrieval-supported-generation", "title": "From lexical retrieval to model answers with evidence", "category": "learning", "format": "Atlas lesson", "description": "Track evidence retrieval, answer likelihood and claim support as separate stages.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/retrieval-supported-generation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-evaluation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Exact normalized two-document teaching mixture; RAG top-k truncation can require a different approximation boundary. Support is rubric evidence, not model likelihood. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/retrieval-supported-generation-6c04d6d40bef835c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#retrieval-supported-generation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ebf700e084ba3a3b334f9e6b3f1c81407b6cc3fe938f390dadcbeb3bc5895b5e", "contentLength": 6677, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-retrieval-supported-generation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-retrieval-supported-generation.md", "sections": [ { "id": "section-1", "title": "From lexical retrieval to model answers with evidence" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "From lexical retrieval to model answers with evidence · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the value 0.62 represent?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#retrieval-supported-generation" }, { "title": "Holistic Evaluation of Language Models", "url": "https://arxiv.org/html/2211.09110v1" }, { "title": "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", "url": "https://arxiv.org/html/2005.11401v4" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/retrieval-supported-generation-6c04d6d40bef835c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Confidence, errors and refusal to guess", "url": "https://semiaifoundry.com/learn/atlas/probability-calibration-abstention/" }, { "title": "Human and model judgments under a rubric", "url": "https://semiaifoundry.com/learn/atlas/judge-rubric-agreement/" }, { "title": "Sampling more candidates versus selecting correct ones", "url": "https://semiaifoundry.com/learn/atlas/test-time-search-verification/" }, { "title": "Version the entire evaluated system", "url": "https://semiaifoundry.com/learn/atlas/model-system-regression-contract/" } ], "recordHash": "58960398bc0547515764325023630914fdea26509564bebf14a57a957c6f6822" }, { "id": "atlas-lesson-reverse-mode-autodiff", "title": "A differentiable computation graph", "category": "learning", "format": "Atlas lesson", "description": "Accumulate every branch contribution to a reused parameter and check it by finite differences.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/reverse-mode-autodiff/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-base-model", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable core. Smooth scalar graph and nonzero finite-difference step; floating-point cancellation can limit very small h. Lifecycle tape executes these mechanisms for all 423 parameters. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/reverse-mode-autodiff-4d49f015b5c53d0a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#reverse-mode-autodiff", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "aab0a3a4f3388c283977ca4d4be6b3bb27cc1f17f99ce5fc191ca40c269c9f8e", "contentLength": 6032, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-reverse-mode-autodiff.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-reverse-mode-autodiff.md", "sections": [ { "id": "section-1", "title": "A differentiable computation graph" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A differentiable computation graph · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is the correct derivative with respect to w?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#reverse-mode-autodiff" }, { "title": "PyTorch autograd mechanics", "url": "https://docs.pytorch.org/docs/2.14/notes/autograd.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/reverse-mode-autodiff-4d49f015b5c53d0a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Model graph and tensor intermediate representation", "url": "https://semiaifoundry.com/learn/atlas/graph-tensor-ir/" }, { "title": "Tensor shapes, indices and contractions", "url": "https://semiaifoundry.com/learn/atlas/tensor-index-contracts/" }, { "title": "Assemble an initialized causal language model", "url": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/" } ], "recordHash": "b1b858f8de7b6557934158d20eecaf82a5ec920acfd8c299133fd6dd90e714f9" }, { "id": "atlas-lesson-reward-proxy-overoptimization", "title": "When reward improves but the task gets worse", "category": "learning", "format": "Atlas lesson", "description": "Compare a rewarded proxy with independently scored task success and locate divergence.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/reward-proxy-overoptimization/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-posttraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable faulty verifier; worked length proxy. Authored counterexample and a separately specified task scorer. No claim that every reward model inevitably fails or that a particular real system followed this trajectory. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/reward-proxy-overoptimization-0c8a90dba139ecf2.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#reward-proxy-overoptimization", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "8c0cb49cc48c87e424ca20b8605995b015c8940710d01fca5bb87a2096a0ff32", "contentLength": 6723, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-reward-proxy-overoptimization.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-reward-proxy-overoptimization.md", "sections": [ { "id": "section-1", "title": "When reward improves but the task gets worse" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "When reward improves but the task gets worse · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which pair of observations demonstrates divergence?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#reward-proxy-overoptimization" }, { "title": "Scaling Laws for Reward Model Overoptimization", "url": "https://arxiv.org/html/2210.10760v1" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/reward-proxy-overoptimization-0c8a90dba139ecf2.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "DPO policy/reference likelihood ratios", "url": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Verifiers, grouped advantages and RLVR", "url": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/" }, { "title": "Frozen base weights and trainable adapters", "url": "https://semiaifoundry.com/learn/atlas/low-rank-adaptation/" }, { "title": "Transfer outputs without confusing size with quality", "url": "https://semiaifoundry.com/learn/atlas/teacher-student-distillation/" } ], "recordHash": "f8a31843d3fa008eff408ddffb992dd1f2ae58ad63c3a8a4ec057f735f56c7e4" }, { "id": "atlas-lesson-robot-feedback-control", "title": "Feedback closes the action loop", "category": "learning", "format": "Atlas lesson", "description": "Sampled controller, actuator limits, delayed sensing and disturbance.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/robot-feedback-control/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Observations become physical actions", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Fixed target, exact sampled integrator, no sensing delay, disturbance, saturation or additional plant dynamics. The stated stability interval applies only to this recurrence.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/robot-feedback-control-78bca5e6f894bd9d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#robot-feedback-control", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a818442695fa21b7e78d59581cfe8891e83d974542f5a124bc6aed0cdf719ee0", "contentLength": 6060, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-robot-feedback-control.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-robot-feedback-control.md", "sections": [ { "id": "section-1", "title": "Feedback closes the action loop" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Feedback closes the action loop · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "For the ideal sampled model, what happens when KΔt = 2.4?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#robot-feedback-control" }, { "title": "Lynch and Park · Modern Robotics 11.3", "url": "https://modernrobotics.northwestern.edu/nu-gm-book-resource/11-3-motion-control-with-velocity-inputs-part-1-of-3/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/robot-feedback-control-78bca5e6f894bd9d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Robot observations have coordinates and age", "url": "https://semiaifoundry.com/learn/atlas/robot-observation-frame/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "53d6f04ce55baf9f9d9a8d0b3b946c74351a70b540add795afd67ea13f634812" }, { "id": "atlas-lesson-robot-goal-plan-action", "title": "Goals, plans and actions are different objects", "category": "learning", "format": "Atlas lesson", "description": "Goal constraints, collision-aware planning, timed execution, feedback and cancellation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/robot-goal-plan-action/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Observations become physical actions", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. A kinematic lower bound with no acceleration or stop-time model. It assumes the named path is feasible; it does not certify collision avoidance or physical safety.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/robot-goal-plan-action-38ee541b0248a399.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#robot-goal-plan-action", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "2f2baf0df2fdcaf125ffda4dd14b5313b25a1998e3830edb2c07ecd2e22b17aa", "contentLength": 6168, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-robot-goal-plan-action.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-robot-goal-plan-action.md", "sections": [ { "id": "section-1", "title": "Goals, plans and actions are different objects" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Goals, plans and actions are different objects · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A 2.5 m path has a 0.5 m/s speed limit. What is its ideal minimum traversal time?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#robot-goal-plan-action" }, { "title": "ROS 2 Jazzy: Understanding actions", "url": "https://raw.githubusercontent.com/ros2/ros2_documentation/jazzy/source/Concepts/Basic/About-Actions.rst" }, { "title": "MoveIt Planning Scene", "url": "https://moveit.picknik.ai/main/doc/examples/planning_scene/planning_scene_tutorial.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/robot-goal-plan-action-38ee541b0248a399.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Robot observations have coordinates and age", "url": "https://semiaifoundry.com/learn/atlas/robot-observation-frame/" }, { "title": "Human review, interruption and cancellation", "url": "https://semiaifoundry.com/learn/atlas/human-review-cancellation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "6b83570b49886a541d89d2cb7285f0b6f82a6e58897e50eeb9bbbc937fb66b9a" }, { "id": "atlas-lesson-robot-observation-frame", "title": "Robot observations have coordinates and age", "category": "learning", "format": "Atlas lesson", "description": "Frame transforms, timestamps, measurement uncertainty and stale-state consequences.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/robot-observation-frame/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Observations become physical actions", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Planar rigid transform, stated +90-degree convention, and constant speed bound over the age interval. No calibration, acceleration, sensor noise or live localization is solved.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/robot-observation-frame-40238bda81800030.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#robot-observation-frame", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a36a6b2e1698bfc9cde4668abc2665aed080e985a7353d36b632b3e64aa4f8a1", "contentLength": 6178, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-robot-observation-frame.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-robot-observation-frame.md", "sections": [ { "id": "section-1", "title": "Robot observations have coordinates and age" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Robot observations have coordinates and age · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Where is camera point (1,0) m after the stated +90-degree rotation and translation (2,3) m?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#robot-observation-frame" }, { "title": "Lynch and Park · Modern Robotics 3.3.1", "url": "https://modernrobotics.northwestern.edu/nu-gm-book-resource/3-3-1-homogeneous-transformation-matrices/" }, { "title": "MoveIt Planning Scene", "url": "https://moveit.picknik.ai/main/doc/examples/planning_scene/planning_scene_tutorial.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/robot-observation-frame-40238bda81800030.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" } ], "recordHash": "0a75d43c0961936cbe6ff8e985c2a1b264276b4c346c4507f60af56249365878" }, { "id": "atlas-lesson-runtime-device-dispatch", "title": "Runtime, driver and device dispatch", "category": "learning", "format": "Atlas lesson", "description": "Turns compiled work into ordered execution with real buffer lifetimes and completion events.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Queue, graph and event semantics are stack-specific. The displayed path is a representative CUDA/OpenXLA flow, not a claim that every runtime uses identical objects.\n\nThis is a worked dependency and lifetime example. It does not execute a CUDA stream, driver or real device event and does not change the original bounded calculator scope.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/runtime-device-dispatch-d37b788e27e38888.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#runtime-device-dispatch", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "464db1f9c2b8bbaa4e060bafe390b0b4e4f02df252b8b3c0e01f7d63964f2703", "contentLength": 7066, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-runtime-device-dispatch.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-runtime-device-dispatch.md", "sections": [ { "id": "section-1", "title": "Runtime, driver and device dispatch" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Launch-bound useful time" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "When is an asynchronously filled buffer safe for a dependent consumer?" }, { "id": "section-11", "title": "What permits safe reuse of a buffer consumed asynchronously?" }, { "id": "section-12", "title": "Evidence and scope" }, { "id": "section-13", "title": "Sources" }, { "id": "section-14", "title": "Continue exploring" }, { "id": "section-15", "title": "Foundations" }, { "id": "section-16", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#runtime-device-dispatch" }, { "title": "CUDA C++ Programming Guide", "url": "https://docs.nvidia.com/cuda/cuda-c-programming-guide/" }, { "title": "XLA:GPU Architecture Overview", "url": "https://openxla.org/xla/gpu_architecture" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/runtime-device-dispatch-d37b788e27e38888.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "Compiler layout, lowering and buffer planning", "url": "https://semiaifoundry.com/learn/atlas/compiler-layout-lowering/" }, { "title": "CUDA programming and runtime layer", "url": "https://semiaifoundry.com/learn/atlas/cuda/" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" }, { "title": "Model graph and tensor intermediate representation", "url": "https://semiaifoundry.com/learn/atlas/graph-tensor-ir/" }, { "title": "Traces connect cost, latency and results", "url": "https://semiaifoundry.com/learn/atlas/telemetry-traces-evaluation/" } ], "recordHash": "6f8535b5ab689d77d4f885f1d24ece22ffe3c263191c05c7ecc25859359d71fe" }, { "id": "atlas-lesson-sampling-estimation-uncertainty", "title": "Sampling variability and independent evidence", "category": "learning", "format": "Atlas lesson", "description": "Shows why a measured success rate varies even when the underlying teaching probability is held fixed.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/sampling-estimation-uncertainty/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "mathematical-foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. Independent identically distributed Bernoulli trials and known p. No interval estimation, multiple-comparison correction or guarantee of real evaluation representativeness is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/sampling-estimation-uncertainty-5273ca7b00504d7c.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#sampling-estimation-uncertainty", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ea7d1250c039384f0102642a246b2596397df9f1d1c2c908c9a8f115da4bb6af", "contentLength": 6314, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sampling-estimation-uncertainty.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sampling-estimation-uncertainty.md", "sections": [ { "id": "section-1", "title": "Sampling variability and independent evidence" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Sampling variability and independent evidence" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the plotted distribution assume?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#sampling-estimation-uncertainty" }, { "title": "Goodfellow, Bengio and Courville · Probability and information theory", "url": "https://www.deeplearningbook.org/contents/prob.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/sampling-estimation-uncertainty-5273ca7b00504d7c.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Probability, likelihood and stable information", "url": "https://semiaifoundry.com/learn/atlas/probability-conditioning-information/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Scaling laws & resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scaling-laws/" } ], "recordHash": "04966d9201d50c958fe67b1d497e245df8aeffd2f92798fe5004df52d894e2d4" }, { "id": "atlas-lesson-sandbox-egress-secrets", "title": "Execution boundaries for code and tools", "category": "learning", "format": "Atlas lesson", "description": "Filesystem, process, network and secret boundaries; authorization is checked at actual execution points.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/sandbox-egress-secrets/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Authority, context and execution boundaries", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Payload-only ledger; excludes allocator overhead, runtime memory and operating-system state. One MiB is 2^20 bytes. No real sandbox or memory measurement is executed here.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/sandbox-egress-secrets-d95b556a68c180e2.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#sandbox-egress-secrets", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "dbeedb1dd2da1224e1371b0772166479d87bd70348d1d596236bcbe871d3969c", "contentLength": 6350, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sandbox-egress-secrets.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sandbox-egress-secrets.md", "sections": [ { "id": "section-1", "title": "Execution boundaries for code and tools" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Execution boundaries for code and tools · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A 40 MiB input and 32 MiB output overlap under a 64 MiB limit. Does the live payload fit?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#sandbox-egress-secrets" }, { "title": "Linux man-pages · namespaces(7)", "url": "https://man7.org/linux/man-pages/man7/namespaces.7.html" }, { "title": "Linux man-pages · seccomp(2)", "url": "https://man7.org/linux/man-pages/man2/seccomp.2.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/sandbox-egress-secrets-d95b556a68c180e2.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "User authority and service identity", "url": "https://semiaifoundry.com/learn/atlas/tool-authority-identity/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "6a9404fdeac90bc41f46fdf72615b16daf455d65f180ea61c80dc30a9eb4338a" }, { "id": "atlas-lesson-scalar-state-space-recurrence", "title": "Recurrent state and convolution", "category": "learning", "format": "Atlas lesson", "description": "Carry history in a state; recover the same output by an explicitly unrolled kernel.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/scalar-state-space-recurrence/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Contrasting computational structures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Zero initial state; a and b are constant within the episode; one scalar state; no trained S4, selective state-space model or learned long-memory guarantee. Numerical settings are original teaching fixtures. The named experience executes the stated bounded algorithm; no production performance or independent human review is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/scalar-state-space-recurrence-8e4b73d079f45047.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#scalar-state-space-recurrence", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c1b7f463d4a0e0e1b2b4dc98ab40dd0428dddc7018cefa9f019582fca9ae433a", "contentLength": 6309, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scalar-state-space-recurrence.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scalar-state-space-recurrence.md", "sections": [ { "id": "section-1", "title": "Recurrent state and convolution" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Recurrent state and convolution · governing computation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why must an input from before an explicit zero-state reset be excluded from the unrolled sum?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#scalar-state-space-recurrence" }, { "title": "Gu et al., state spaces and recurrence/convolution §2.3–2.4", "url": "https://arxiv.org/html/2111.00396v3" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/scalar-state-space-recurrence-8e4b73d079f45047.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tensor shapes, indices and contractions", "url": "https://semiaifoundry.com/learn/atlas/tensor-index-contracts/" }, { "title": "Graph message passing and node identity", "url": "https://semiaifoundry.com/learn/atlas/graph-message-passing/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" } ], "recordHash": "1810fb50e85a5188232388669f9f9dae32df8a9897826911dd3cc9cdd3478861" }, { "id": "atlas-lesson-scaleup-scaleout-boundaries", "title": "Scale-up, scale-out and management fabrics", "category": "learning", "format": "Atlas lesson", "description": "Assigns each traffic class to its actual interconnect and resource boundary.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/scaleup-scaleout-boundaries/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Chip-to-hall integration", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The example is synthetic. Protocol choice and placement depend on the actual system; no universal NVLink-versus-Ethernet performance ordering is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/scaleup-scaleout-boundaries-bdd85897c5539126.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#scaleup-scaleout-boundaries", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "ecdf2e4c3532ccbeedf14fe8e9a587e7a0e77267be50260e64c880441f464564", "contentLength": 4986, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scaleup-scaleout-boundaries.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scaleup-scaleout-boundaries.md", "sections": [ { "id": "section-1", "title": "Scale-up, scale-out and management fabrics" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Topology cut bound" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What best predicts the limit for traffic moving between two rack groups?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#scaleup-scaleout-boundaries" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Networking", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/networking.html" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Hardware", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/hardware.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/scaleup-scaleout-boundaries-bdd85897c5539126.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Leaf switch and endpoint network", "url": "https://semiaifoundry.com/learn/atlas/leaf-switch/" }, { "title": "NVLink switch tray and scale-up fabric", "url": "https://semiaifoundry.com/learn/atlas/nvlink-switch/" }, { "title": "NVLink GPU interface", "url": "https://semiaifoundry.com/learn/atlas/nvlink-port/" }, { "title": "Spine switching and fabric topology", "url": "https://semiaifoundry.com/learn/atlas/spine-switch/" }, { "title": "Collective traffic and congestion", "url": "https://semiaifoundry.com/learn/atlas/fabric-collective-traffic/" } ], "recordHash": "e608287a0ac883a5520f2a9cf0fa373034a43484c7be5afb9905c6df51ea808c" }, { "id": "atlas-lesson-scaling-laws", "title": "Scaling laws & resource allocation", "category": "learning", "format": "Atlas lesson", "description": "Understand how data, parameters, and compute interact.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/scaling-laws/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Learning", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The coefficients and exponents are fit parameters, not a universal law.\n\nMode: worked example. Illustrative coefficients only. The 6ND heuristic omits architecture-specific terms and is not a measured cost of the scalar-tape core. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/scaling-laws-93d14a5ba25c61e5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#scaling-laws", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "7680a3366beeb74b3842c8667abdfee52c18406d4f8aa772351c919b11ba2c01", "contentLength": 9548, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scaling-laws.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scaling-laws.md", "sections": [ { "id": "section-1", "title": "Scaling laws & resource allocation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Compute-optimal balance is an empirical fit" }, { "id": "section-5", "title": "Fit a bounded compute/data experiment · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Do scaling laws establish a guaranteed AGI date?" }, { "id": "section-12", "title": "What would justify calling the displayed relation an empirical fit?" }, { "id": "section-13", "title": "Historical context" }, { "id": "section-14", "title": "2022 · Chinchilla revisits compute-optimal model and data scaling" }, { "id": "section-15", "title": "Evidence and scope" }, { "id": "section-16", "title": "Sources" }, { "id": "section-17", "title": "Continue exploring" }, { "id": "section-18", "title": "Foundations" }, { "id": "section-19", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#scaling-laws" }, { "title": "Hoffmann et al. — Training Compute-Optimal Large Language Models", "url": "https://arxiv.org/abs/2203.15556" }, { "title": "Kaplan et al. — Scaling Laws", "url": "https://arxiv.org/abs/2001.08361" }, { "title": "Training Compute-Optimal Large Language Models", "url": "https://arxiv.org/html/2203.15556v1" }, { "title": "The FineWeb Datasets", "url": "https://arxiv.org/html/2406.17557v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/scaling-laws-93d14a5ba25c61e5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "Next-token supervision from raw sequences", "url": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/" }, { "title": "Initialization, learning rate and stable updates", "url": "https://semiaifoundry.com/learn/atlas/optimizer-schedule-stability/" }, { "title": "Gradient accumulation under a fixed global objective", "url": "https://semiaifoundry.com/learn/atlas/microbatch-equivalent-updates/" } ], "recordHash": "f29b1bf178a0bcabf881488c39ab759cb59e40ca56e8872420aabace1e713a45" }, { "id": "atlas-lesson-scheduler", "title": "Cluster scheduler and resource allocation", "category": "learning", "format": "Atlas lesson", "description": "Matches queued workloads to available compute resources under operational policies.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/scheduler/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "System operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Stationarity and a well-defined system boundary are required.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/scheduler-de53c3d9a7b4f4a0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#scheduler", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a4f1633cdc1be956f9519933f60cf69aaabfd10bbf1bfa2f471821b16e0ebe06", "contentLength": 4556, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scheduler.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scheduler.md", "sections": [ { "id": "section-1", "title": "Cluster scheduler and resource allocation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Little’s law" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a cluster scheduler primarily decide?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#scheduler" }, { "title": "SchedMD — Slurm Generic Resource Scheduling", "url": "https://slurm.schedmd.com/gres.html" }, { "title": "MIT — Queueing Models and Little’s Law", "url": "https://web.mit.edu/1.041/www/lectures/L8-queuing-models-2024sp.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/scheduler-de53c3d9a7b4f4a0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Dataset and checkpoint storage hierarchy", "url": "https://semiaifoundry.com/learn/atlas/storage/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" } ], "recordHash": "eda3d767cd44e597fe9afad4c3afd5fb3634dd48f5a61da66add0beeaf565664" }, { "id": "atlas-lesson-scientific-surrogate-validation", "title": "A learned field still obeys an evidence boundary", "category": "learning", "format": "Atlas lesson", "description": "Train on a bounded parameter family; compare prediction with a numerical reference, boundary conditions and conservation residuals.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/scientific-surrogate-validation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Models become evaluated applications", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. Constant-conductivity, one-dimensional, steady, source-free mathematical example with fixed boundaries. The discrete residual is not a complete PDE validation or a field measurement.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/scientific-surrogate-validation-4b003bf0f160b9af.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#scientific-surrogate-validation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "e2ae8d39bff5e1b33ac41cf09ce9c25044f6d11f1dcb64fc429d7341158fe4c5", "contentLength": 6319, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scientific-surrogate-validation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-scientific-surrogate-validation.md", "sections": [ { "id": "section-1", "title": "A learned field still obeys an evidence boundary" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A learned field still obeys an evidence boundary · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is the interior second-difference residual for \\[293,353,393\\] K with spacing 0.5 m?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#scientific-surrogate-validation" }, { "title": "Fourier Neural Operator for Parametric Partial Differential Equations", "url": "https://arxiv.org/abs/2010.08895v3" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/scientific-surrogate-validation-4b003bf0f160b9af.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" } ], "recordHash": "1926c3850d186390dd33ca244f7469e3f055d6ed42ba7edb65ef614208fd7d09" }, { "id": "atlas-lesson-search-value-policy-boundary", "title": "Search, value estimates and selected actions", "category": "learning", "format": "Atlas lesson", "description": "Explains how a system can spend additional computation selecting an action after receiving an observation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/search-value-policy-boundary/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "contrasting-ai-methods", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. Finite deterministic perfect-information game, alternating players and a declared fixed heuristic. This is minimax teaching search, not AlphaZero or a learned planning system.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/search-value-policy-boundary-fd0c4782ffb031c0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#search-value-policy-boundary", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "da39d87d82a1be195b2a6862e25132ade19423498b8d578d10622a4d7a42159e", "contentLength": 6366, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-search-value-policy-boundary.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-search-value-policy-boundary.md", "sections": [ { "id": "section-1", "title": "Search, value estimates and selected actions" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Search, value estimates and selected actions" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What changes when lookahead depth increases in this specimen?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#search-value-policy-boundary" }, { "title": "Silver et al. · AlphaZero", "url": "https://arxiv.org/abs/1712.01815" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/search-value-policy-boundary-fd0c4782ffb031c0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" } ], "recordHash": "0d102679915cc216228d399f37241d3d68c407cbba877f063efd50ceacccfb44" }, { "id": "atlas-lesson-sequence-packing-loss-denominators", "title": "Packing documents and masking valid targets", "category": "learning", "format": "Atlas lesson", "description": "Draw document and target masks, then reconstruct the loss denominator of a packed batch.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-data", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Positive valid-target count; the displayed attention formula chooses document isolation. Other packing policies must declare their different boundary semantics. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/sequence-packing-loss-denominators-5cb743a1c9061dd8.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#sequence-packing-loss-denominators", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "be9bba309384a35b41a630de1ef2498fbb5c6d0703f931bc0322b2da628b3504", "contentLength": 6147, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sequence-packing-loss-denominators.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sequence-packing-loss-denominators.md", "sections": [ { "id": "section-1", "title": "Packing documents and masking valid targets" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Packing documents and masking valid targets · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which denominator preserves the stated global token objective?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#sequence-packing-loss-denominators" }, { "title": "TRL SFT Trainer", "url": "https://huggingface.co/docs/trl/sft_trainer" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/sequence-packing-loss-denominators-5cb743a1c9061dd8.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tokenizer", "url": "https://semiaifoundry.com/learn/atlas/tokenizer/" }, { "title": "Uneven batches and the global gradient", "url": "https://semiaifoundry.com/learn/atlas/distributed-gradient-weighting/" }, { "title": "Filtering, duplication and contamination", "url": "https://semiaifoundry.com/learn/atlas/data-quality-dedup-audit/" }, { "title": "Mixtures, epochs and exposure", "url": "https://semiaifoundry.com/learn/atlas/data-mixture-sampling/" }, { "title": "Synthetic supervision and selection loops", "url": "https://semiaifoundry.com/learn/atlas/synthetic-data-selection-feedback/" }, { "title": "Coverage across language and source slices", "url": "https://semiaifoundry.com/learn/atlas/data-coverage-language-slices/" } ], "recordHash": "d933e16a2eafed947ab3082bd084e9d2e88afc6b2a23a14415889f2d07d4e590" }, { "id": "atlas-lesson-serving", "title": "Inference serving and request scheduling", "category": "learning", "format": "Atlas lesson", "description": "Turns incoming model requests into scheduled prefill and generation work.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/serving/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model deployment", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The expression does not promise a quality or throughput target.\n\nThis additive trace is worked synthetic timing. It does not extend the existing resource calculator into a measured queueing engine or claim current vendor service rates.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/serving-ac7cef5ec8fe6856.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#serving", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "78afb00ebb54a79008ec665146bab10e02e464a681363e8e8ff4342a0cc3f4e7", "contentLength": 7205, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-serving.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-serving.md", "sections": [ { "id": "section-1", "title": "Inference serving and request scheduling" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Generation latency decomposition" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does continuous batching allow?" }, { "id": "section-11", "title": "A request arrives at 0 ms and returns its first token at 80 ms after 30 ms queueing. What is TTFT?" }, { "id": "section-12", "title": "Historical context" }, { "id": "section-13", "title": "2023 · PagedAttention connects memory management to LLM serving" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#serving" }, { "title": "Kwon et al. — PagedAttention", "url": "https://arxiv.org/abs/2309.06180" }, { "title": "vLLM — Inference and Serving Documentation", "url": "https://docs.vllm.ai/en/latest/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/serving-ac7cef5ec8fe6856.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "CUDA programming and runtime layer", "url": "https://semiaifoundry.com/learn/atlas/cuda/" }, { "title": "Quantization and numerical representation", "url": "https://semiaifoundry.com/learn/atlas/quantization/" }, { "title": "Dataset and checkpoint storage hierarchy", "url": "https://semiaifoundry.com/learn/atlas/storage/" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Events, queues and backpressure", "url": "https://semiaifoundry.com/learn/atlas/event-queues-delivery/" }, { "title": "Traces connect cost, latency and results", "url": "https://semiaifoundry.com/learn/atlas/telemetry-traces-evaluation/" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" } ], "recordHash": "4a96b3cabad8814073e2cb1e33b06216e80243dbbcd3762443fa4a2a8096a117" }, { "id": "atlas-lesson-sft-chat-loss-masks", "title": "Instruction tuning and assistant-only loss", "category": "learning", "format": "Atlas lesson", "description": "Identify exactly which shifted response targets contribute to supervised fine-tuning.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-posttraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable one-turn response mask. Positive included-target count and a stated role/template boundary. Core mask covers one answer and EOS; multi-turn masking here is worked-only. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/sft-chat-loss-masks-dd583bb8e46df0a9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#sft-chat-loss-masks", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3a7b78129721bb2710d177ace97fc5b9ea1fa722824a6d6ef962fd1faba53d1a", "contentLength": 6690, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sft-chat-loss-masks.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sft-chat-loss-masks.md", "sections": [ { "id": "section-1", "title": "Instruction tuning and assistant-only loss" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Instruction tuning and assistant-only loss · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Can prompt embeddings receive gradients when prompt target losses are zeroed?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#sft-chat-loss-masks" }, { "title": "TRL SFT Trainer", "url": "https://huggingface.co/docs/trl/sft_trainer" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/sft-chat-loss-masks-dd583bb8e46df0a9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Packing documents and masking valid targets", "url": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/" }, { "title": "Next-token supervision from raw sequences", "url": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/" }, { "title": "Post-training & feedback", "url": "https://semiaifoundry.com/learn/atlas/post-training/" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "DPO policy/reference likelihood ratios", "url": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Verifiers, grouped advantages and RLVR", "url": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/" }, { "title": "When reward improves but the task gets worse", "url": "https://semiaifoundry.com/learn/atlas/reward-proxy-overoptimization/" } ], "recordHash": "4179373c4f25a451ea2ba0318b9a45658ac1ce9bf5d8c83e358550bf67a1cfcd" }, { "id": "atlas-lesson-sharded-matmul-ownership", "title": "Sharded matrix multiplication and result ownership", "category": "learning", "format": "Atlas lesson", "description": "Derive the communication operation from the partitioned matrix axis and the next consumer’s required result layout.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/sharded-matmul-ownership/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The sources establish sharding and collective semantics. All matrices, the two-row exchange schedule and byte counts here are synthetic. This is not an observed NCCL implementation, a topology model or a performance comparison.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/sharded-matmul-ownership-cdb4f7ad8c2ad536.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#sharded-matmul-ownership", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "d67325120a946e3bf935348c66795a1336ca7d911e8c531980b4516ffe21ed28", "contentLength": 9004, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sharded-matmul-ownership.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sharded-matmul-ownership.md", "sections": [ { "id": "section-1", "title": "Sharded matrix multiplication and result ownership" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Inner-dimension partition preserves the sum" }, { "id": "section-5", "title": "Two-rank payload ledger" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Each rank computed all output coordinates using a different half of the contracted dimension. Is concatenating those local arrays enough?" }, { "id": "section-12", "title": "After the stated reduce-scatter, which row belongs to rank 1?" }, { "id": "section-13", "title": "How many payload bytes are sent across both ranks in the two stated phases?" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#sharded-matmul-ownership" }, { "title": "JAX — Manual parallelism with shard_map", "url": "https://docs.jax.dev/en/latest/notebooks/shard_map.html" }, { "title": "NVIDIA NCCL — Collective Operations", "url": "https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/usage/collectives.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/sharded-matmul-ownership-cdb4f7ad8c2ad536.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Compiler layout, lowering and buffer planning", "url": "https://semiaifoundry.com/learn/atlas/compiler-layout-lowering/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Systolic arrays and tensor dataflow", "url": "https://semiaifoundry.com/learn/atlas/systolic-array-dataflow/" }, { "title": "Collective traffic and congestion", "url": "https://semiaifoundry.com/learn/atlas/fabric-collective-traffic/" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" }, { "title": "Floating-point reductions and compiler permissions", "url": "https://semiaifoundry.com/learn/atlas/floating-point-reduction-order/" } ], "recordHash": "4bad5c886f904ef3f561ae10f23ca12b74c6dfefc5f5bdeb6153690955bfc51b" }, { "id": "atlas-lesson-shared-sram", "title": "Shared memory SRAM", "category": "learning", "format": "Atlas lesson", "description": "Lets cooperating threads explicitly stage and reuse a tile near the compute units.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/shared-sram/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory hierarchy", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The bank and capacity behavior depends on a specific implementation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/shared-sram-a41c0da718170ae4.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#shared-sram", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4c901daac5ef35b44d9dec3b8d6412479d833f624366bcd058764f700852957f", "contentLength": 5783, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-shared-sram.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-shared-sram.md", "sections": [ { "id": "section-1", "title": "Shared memory SRAM" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Address layout determines bank conflicts" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why might adding one padding column to a shared-memory tile improve performance?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#shared-sram" }, { "title": "NVIDIA CUDA: Writing SIMT Kernels", "url": "https://docs.nvidia.com/cuda/archive/13.2.0/cuda-programming-guide/02-basics/writing-cuda-kernels.html" }, { "title": "NVIDIA CUDA Blackwell Tuning Guide", "url": "https://docs.nvidia.com/cuda/blackwell-tuning-guide/index.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/shared-sram-a41c0da718170ae4.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "L1 and texture cache", "url": "https://semiaifoundry.com/learn/atlas/l1-cache/" }, { "title": "Tensor Memory Accelerator", "url": "https://semiaifoundry.com/learn/atlas/tensor-memory-accelerator/" } ], "recordHash": "cae922c68b4343d57418f2802ed27ba91039d224716290ebbb00f22ad23d09c2" }, { "id": "atlas-lesson-silicon-atom", "title": "Silicon atom", "category": "learning", "format": "Atlas lesson", "description": "Supplies the electronic states from which semiconductor behavior is engineered.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/silicon-atom/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Atomic foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Atomic notation is a model of composition, not a device-level mobility prediction.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/silicon-atom-25e3b2525d32569f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#silicon-atom", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "473b7184357c9fec03ef95e8c5340ec818490b4fcf81d4337f65188903a5f85c", "contentLength": 4191, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-silicon-atom.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-silicon-atom.md", "sections": [ { "id": "section-1", "title": "Silicon atom" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Charge bookkeeping" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Where does a silicon atom become a digital bit?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#silicon-atom" }, { "title": "NIST — Atomic Data for Silicon", "url": "https://physics.nist.gov/PhysRefData/Handbook/Tables/silicontable1_a.htm" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/silicon-atom-25e3b2525d32569f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Diamond-cubic silicon lattice", "url": "https://semiaifoundry.com/learn/atlas/crystal-lattice/" }, { "title": "Energy bands and carriers", "url": "https://semiaifoundry.com/learn/atlas/energy-bands/" } ], "recordHash": "4a3fb6dadaf6596fc57632a2268e9a8c380bac4c44d082fdc80b4df32f491bfd" }, { "id": "atlas-lesson-silicon-wafer", "title": "Wafer and fabrication hierarchy", "category": "learning", "format": "Atlas lesson", "description": "Provides the shared substrate on which many integrated circuits are fabricated.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/silicon-wafer/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Gross-site geometry and yield are teaching estimates; reticle fields, scribe lanes and parametric loss are not hidden.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/silicon-wafer-d81c84b4d6270976.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#silicon-wafer", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "088f8000f372f225b9837281ece0d6fc6e5c920388a7d772326b9b447d8019c1", "contentLength": 4695, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-silicon-wafer.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-silicon-wafer.md", "sections": [ { "id": "section-1", "title": "Wafer and fabrication hierarchy" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A first defect-yield model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which order follows physical integration?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#silicon-wafer" }, { "title": "Intel — Semiconductors and Intel: An Introduction", "url": "https://www.intel.com/content/dam/www/central-libraries/us/en/documents/semiconductors-and-intel-introduction.pdf" }, { "title": "Electronic Materials and Fabrication — Productivity and Process Yield", "url": "https://staff-old.najah.edu/sites/default/files/Lec29.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/silicon-wafer-d81c84b4d6270976.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Diamond-cubic silicon lattice", "url": "https://semiaifoundry.com/learn/atlas/crystal-lattice/" }, { "title": "Lithography and pattern transfer", "url": "https://semiaifoundry.com/learn/atlas/lithography/" }, { "title": "Chemical mechanical planarization", "url": "https://semiaifoundry.com/learn/atlas/cmp/" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" } ], "recordHash": "3e4529ac0fb536c71cf3cdfefb5f3ede217825c12c976f639f69b2e099c84b62" }, { "id": "atlas-lesson-simt-active-lanes", "title": "SIMT execution and divergent branches", "category": "learning", "format": "Atlas lesson", "description": "Shares instruction issue across threads while tracking which lanes participate.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/simt-active-lanes/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The eight-lane drawing is pedagogical, not a claimed NVIDIA or AMD execution-group width. Cross-vendor scheduling details are intentionally not equated.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/simt-active-lanes-09a7ed633dfdd537.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#simt-active-lanes", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "9f6b88240bbb028533c4f5c3ca53515db5e49107624a7074c730b0b36eb20e5d", "contentLength": 5163, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-simt-active-lanes.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-simt-active-lanes.md", "sections": [ { "id": "section-1", "title": "SIMT execution and divergent branches" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Masked execution efficiency" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "All threads run the same instruction but read widely separated addresses. What is the likely issue?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#simt-active-lanes" }, { "title": "CUDA C++ Programming Guide", "url": "https://docs.nvidia.com/cuda/cuda-c-programming-guide/" }, { "title": "AMD Instinct MI300 Series microarchitecture", "url": "https://rocm.docs.amd.com/en/latest/reference/gpu-arch/mi300.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/simt-active-lanes-09a7ed633dfdd537.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "GPU kernel and thread hierarchy", "url": "https://semiaifoundry.com/learn/atlas/kernel/" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "Occupancy and asynchronous tile pipelines", "url": "https://semiaifoundry.com/learn/atlas/gpu-occupancy-pipeline/" } ], "recordHash": "eb9ebd9d7c61340b2c77ef21d99101ad4f1838bc60dedea10dac64f974e4e06c" }, { "id": "atlas-lesson-soic-foveros-vertical-routes", "title": "SoIC and Foveros: vertical integration families", "category": "learning", "format": "Atlas lesson", "description": "Compares named die-stacking routes while preserving their base-die and bonding differences.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/soic-foveros-vertical-routes/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Interposers, bridges and stacking", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Branded technologies evolve. The animation must identify the cited variant, and no complete proprietary flow or current product qualification is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/soic-foveros-vertical-routes-b82582373422cf13.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#soic-foveros-vertical-routes", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "0c11a08b271d663e62f523217bb7e1c90b6e49a80f4d0f247e0acd92c589c014", "contentLength": 5807, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-soic-foveros-vertical-routes.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-soic-foveros-vertical-routes.md", "sections": [ { "id": "section-1", "title": "SoIC and Foveros: vertical integration families" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Unscreened pair yield" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What changes when moving from whole-wafer bonding to die-to-wafer placement?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#soic-foveros-vertical-routes" }, { "title": "TSMC — SoIC", "url": "https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/SoIC.htm" }, { "title": "Intel Foundry — Accelerating HPC and AI", "url": "https://www.intel.com/content/dam/www/central-libraries/us/en/documents/2025-11/intel-foundry-hpc-ai-brief.pdf" }, { "title": "Intel — New Architectures and Technologies Target Expanded Market Opportunities", "url": "https://www.intc.com/news-events/press-releases/detail/106/new-intel-architectures-and-technologies-target-expanded" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/soic-foveros-vertical-routes-b82582373422cf13.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" }, { "title": "CoWoS-S and the silicon interposer route", "url": "https://semiaifoundry.com/learn/atlas/cowos-s-silicon-interposer/" }, { "title": "Hybrid bonding: surface state and alignment", "url": "https://semiaifoundry.com/learn/atlas/hybrid-bond-surface-alignment/" }, { "title": "Temporary bonding, thinning and singulation", "url": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/" }, { "title": "Backside power and design–technology co-optimization", "url": "https://semiaifoundry.com/learn/atlas/backside-power-dtco/" } ], "recordHash": "c57dd2878a4834621b239777b88a6d02e5103a3233a3fbbb59164abd0110d950" }, { "id": "atlas-lesson-source-drain", "title": "Source and drain regions", "category": "learning", "format": "Atlas lesson", "description": "Connects the controlled channel to reservoirs that supply and collect carriers.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/source-drain/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Device physics", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The series decomposition is useful for diagnosis; extraction depends on test structures and bias.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/source-drain-7722f4d2b2419368.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#source-drain", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "7beec286dd1eb0b05555830d8ef1a5fbdd4dd4e3f117476a54f3d386d7182a19", "contentLength": 4946, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-source-drain.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-source-drain.md", "sections": [ { "id": "section-1", "title": "Source and drain regions" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Series resistance budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Can source/drain access limit a transistor with an excellent channel?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#source-drain" }, { "title": "imec — Source/Drain Contact Research, IEDM 2017", "url": "https://www.imec-int.com/en/articles/imec-achieves-record-low-contact-resistivity-on-ga-doped-ge-source-drain-contacts-for-pmos-transistors" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/source-drain-7722f4d2b2419368.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Donor and acceptor doping", "url": "https://semiaifoundry.com/learn/atlas/doping/" }, { "title": "Controllable semiconductor channel", "url": "https://semiaifoundry.com/learn/atlas/channel/" }, { "title": "Device contact and interface resistance", "url": "https://semiaifoundry.com/learn/atlas/contact/" }, { "title": "Gate sidewall and inner spacers", "url": "https://semiaifoundry.com/learn/atlas/spacer/" } ], "recordHash": "c74039bd0e4c1f1e10933c99886640db039a07bd13988bef166593a053280542" }, { "id": "atlas-lesson-source-drain-contact-integration", "title": "Source/drain, spacers, contacts and MOL", "category": "learning", "format": "Atlas lesson", "description": "Connects a gated channel to useful local wiring without bypassing gate control.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/source-drain-contact-integration/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / FEOL and MOL", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No proprietary contact metal, anneal or resistance target is supplied. Product-specific interfaces require measured structures.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/source-drain-contact-integration-df048eb45cc83e24.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#source-drain-contact-integration", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "86fde9ababe2398f2998e9bf5d1d98f8f3430edefd931522864ec670dec0b8b5", "contentLength": 5476, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-source-drain-contact-integration.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-source-drain-contact-integration.md", "sections": [ { "id": "section-1", "title": "Source/drain, spacers, contacts and MOL" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "First-order contact scaling" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a better intrinsic transistor show only a small circuit-speed improvement?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#source-drain-contact-integration" }, { "title": "Applied Materials — New Ways to Shrink", "url": "https://ir.appliedmaterials.com/static-files/f2fbf48d-a761-4c4f-ab4c-73f312ab1ebc" }, { "title": "imec — Scaling the BEOL: a toolbox of processes and conductors", "url": "https://www.imec-int.com/en/imec-magazine/imec-magazine-september-2019/scaling-the-beol-a-toolbox-filled-with-new-processes-boosters-and-conductors" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/source-drain-contact-integration-df048eb45cc83e24.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Device contact and interface resistance", "url": "https://semiaifoundry.com/learn/atlas/contact/" }, { "title": "Gate sidewall and inner spacers", "url": "https://semiaifoundry.com/learn/atlas/spacer/" }, { "title": "Implantation, activation and diffusion", "url": "https://semiaifoundry.com/learn/atlas/implantation-anneal-diffusion/" }, { "title": "Source and drain regions", "url": "https://semiaifoundry.com/learn/atlas/source-drain/" }, { "title": "BEOL layers, damascene and vias", "url": "https://semiaifoundry.com/learn/atlas/beol-damascene-vias/" } ], "recordHash": "1c1e2bfaaed2d9a432ef83a1a8497e8eb91acd1992e4e934b53a63789b8b0ef6" }, { "id": "atlas-lesson-spacer", "title": "Gate sidewall and inner spacers", "category": "learning", "format": "Atlas lesson", "description": "Separates the gate from neighboring terminal structures and limits parasitic coupling.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/spacer/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Device physics", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The parasitic relation is a proportional teaching model, not a process recipe.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/spacer-6a00ad1e827c9557.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#spacer", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f22562fd70b751846dc57b9bcb9a2b04fa20b6208f2552fc7d065af4e465091d", "contentLength": 4856, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-spacer.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-spacer.md", "sections": [ { "id": "section-1", "title": "Gate sidewall and inner spacers" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Parasitic capacitance and transition charge" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is one role of nanosheet inner spacers?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#spacer" }, { "title": "imec — Entering the Nanosheet Transistor Era", "url": "https://www.imec-int.com/en/articles/entering-nanosheet-transistor-era-0" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/spacer-6a00ad1e827c9557.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "Source and drain regions", "url": "https://semiaifoundry.com/learn/atlas/source-drain/" }, { "title": "Gate-all-around nanosheet transistor", "url": "https://semiaifoundry.com/learn/atlas/gaa/" }, { "title": "Insulators and low-k films", "url": "https://semiaifoundry.com/learn/atlas/dielectric/" } ], "recordHash": "4138b38c64fdb2d5f520781737bc722723e08b7b0da9080d1fbb15b8a58479af" }, { "id": "atlas-lesson-spatial-filter-patch-attention", "title": "Local filters and patch attention", "category": "learning", "format": "Atlas lesson", "description": "Compare fixed local receptive fields with content-weighted patch aggregation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/spatial-filter-patch-attention/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Contrasting computational structures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Authored filters and one identity-projection patch query; stride one, no padding; no trained CNN, full ViT, learned positions or recognition benchmark. Numerical settings are original teaching fixtures. The named experience executes the stated bounded algorithm; no production performance or independent human review is claimed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/spatial-filter-patch-attention-36a796546c85f406.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#spatial-filter-patch-attention", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "76c21f23600308320fd4243094d0d04ea3d152ba71f429ff85c0e5f4900c7178", "contentLength": 6993, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-spatial-filter-patch-attention.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-spatial-filter-patch-attention.md", "sections": [ { "id": "section-1", "title": "Local filters and patch attention" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Local filters and patch attention · governing computation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does the edge-line fixture fail under this valid-convolution classifier?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#spatial-filter-patch-attention" }, { "title": "PyTorch Conv2d, cross-correlation and shape", "url": "https://docs.pytorch.org/docs/2.14/generated/torch.nn.Conv2d.html" }, { "title": "Vaswani et al., scaled dot-product attention", "url": "https://arxiv.org/abs/1706.03762" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/spatial-filter-patch-attention-36a796546c85f406.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tensor shapes, indices and contractions", "url": "https://semiaifoundry.com/learn/atlas/tensor-index-contracts/" }, { "title": "Probability, likelihood and stable information", "url": "https://semiaifoundry.com/learn/atlas/probability-conditioning-information/" }, { "title": "Patches, projection and visual instruction tuning", "url": "https://semiaifoundry.com/learn/atlas/visual-language-bridge/" }, { "title": "Pair images and captions in a shared representation", "url": "https://semiaifoundry.com/learn/atlas/image-text-contrastive-learning/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" } ], "recordHash": "5a94b5178307f1fe6cfc145a5a6e51a0e39c635703e683ede7c5bbe65d064ce4" }, { "id": "atlas-lesson-speculative-decoding-verification", "title": "Speculative decoding: proposals and verified output", "category": "learning", "format": "Atlas lesson", "description": "Account for target-distributed output tokens while separating draft work, verification and actual elapsed time.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/speculative-decoding-verification/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Executable software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The cited ICML paper establishes the strict correction algorithm and the explicitly iid output-count formula. The toy probabilities, output-count distribution and all millisecond values are authored. No private model, serving implementation, benchmark speedup or quality improvement is asserted.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/speculative-decoding-verification-f6066fe7fb36a164.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#speculative-decoding-verification", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "911b1bb7541f981e066bc41707b9fe78bdbce7439e344ff6d5c12a8df928f4e0", "contentLength": 9732, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-speculative-decoding-verification.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-speculative-decoding-verification.md", "sections": [ { "id": "section-1", "title": "Speculative decoding: proposals and verified output" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Acceptance and rejection correction" }, { "id": "section-5", "title": "Output count in the iid acceptance scenario" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "In the stated toy distributions, a rejected proposal must be corrected from which distribution?" }, { "id": "section-12", "title": "Under iid α=0.6 with two proposals, what is the expected output count including correction or bonus?" }, { "id": "section-13", "title": "Does preserving p establish that sampled statements are true?" }, { "id": "section-14", "title": "Evidence and scope" }, { "id": "section-15", "title": "Sources" }, { "id": "section-16", "title": "Continue exploring" }, { "id": "section-17", "title": "Foundations" }, { "id": "section-18", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#speculative-decoding-verification" }, { "title": "Leviathan, Kalman and Matias — Fast Inference from Transformers via Speculative Decoding", "url": "https://proceedings.mlr.press/v202/leviathan23a.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/speculative-decoding-verification-f6066fe7fb36a164.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Autoregressive decode and weight traffic", "url": "https://semiaifoundry.com/learn/atlas/decode-bandwidth-trace/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Prefill and prompt processing", "url": "https://semiaifoundry.com/learn/atlas/prefill-resource-trace/" }, { "title": "Prefill/decode disaggregation and useful serving rate", "url": "https://semiaifoundry.com/learn/atlas/disaggregated-serving/" }, { "title": "Runtime, driver and device dispatch", "url": "https://semiaifoundry.com/learn/atlas/runtime-device-dispatch/" }, { "title": "Place the working set, not just the model", "url": "https://semiaifoundry.com/learn/atlas/memory-working-set-placement/" } ], "recordHash": "28975e99ab09262e51ed0ff37d964c0343844aed4e8a7da3f818f74fefdc163e" }, { "id": "atlas-lesson-speech-audio-sequence-objectives", "title": "Audio representation, alignment and transcript loss", "category": "learning", "format": "Atlas lesson", "description": "Relate audio samples, time frames and transcript errors without mixing their denominators.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/speech-audio-sequence-objectives/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-multimodal", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. N at least W, no padding or centering for frame arithmetic; fixed whitespace-normalized reference words for WER. No audio data is uploaded or speech model run by this lesson. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/speech-audio-sequence-objectives-37fcc6eaa2bc7958.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#speech-audio-sequence-objectives", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "da005538bfef9ab090548cab12357c837628189416833a9fdf0de41e5b8151d9", "contentLength": 6551, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-speech-audio-sequence-objectives.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-speech-audio-sequence-objectives.md", "sections": [ { "id": "section-1", "title": "Audio representation, alignment and transcript loss" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Audio representation, alignment and transcript loss · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why is the WER denominator three in the example?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#speech-audio-sequence-objectives" }, { "title": "Robust Speech Recognition via Large-Scale Weak Supervision", "url": "https://arxiv.org/html/2212.04356v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/speech-audio-sequence-objectives-37fcc6eaa2bc7958.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tokenizer", "url": "https://semiaifoundry.com/learn/atlas/tokenizer/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Pair images and captions in a shared representation", "url": "https://semiaifoundry.com/learn/atlas/image-text-contrastive-learning/" }, { "title": "Patches, projection and visual instruction tuning", "url": "https://semiaifoundry.com/learn/atlas/visual-language-bridge/" }, { "title": "Train a denoiser and sample iteratively", "url": "https://semiaifoundry.com/learn/atlas/denoising-generative-objectives/" }, { "title": "Predict temporal representations without generating pixels", "url": "https://semiaifoundry.com/learn/atlas/video-latent-prediction/" } ], "recordHash": "c32f4df0fa8873ce8628e22be4ae1ae7a3236db7af4c6bcfb29e03e22b752444" }, { "id": "atlas-lesson-spine-switch", "title": "Spine switching and fabric topology", "category": "learning", "format": "Atlas lesson", "description": "Provides multiple high-capacity paths between leaf switches.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/spine-switch/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center fabric", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The cut-capacity argument is a bound on the specified topology and traffic direction. Synthetic values assume usable independent links; other traffic, routing and protocol overhead can reduce attainable throughput.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/spine-switch-0357d7f8641e771e.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#spine-switch", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "34a5d9b130374044a663ba7797f2205e2bdd8ad095b783b3f1bfd1a43b342d1c", "contentLength": 4921, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-spine-switch.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-spine-switch.md", "sections": [ { "id": "section-1", "title": "Spine switching and fabric topology" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Cut capacity" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is necessary to assess a nonblocking claim?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#spine-switch" }, { "title": "NVIDIA — HGX AI Factory Spine-Leaf Architecture", "url": "https://docs.nvidia.com/enterprise-reference-architectures/hgx-ai-factory-h100-h200-b200/latest/network-logical-architecture.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/spine-switch-0357d7f8641e771e.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Leaf switch and endpoint network", "url": "https://semiaifoundry.com/learn/atlas/leaf-switch/" }, { "title": "Optical transceiver and fiber link", "url": "https://semiaifoundry.com/learn/atlas/optics/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Collective communication library", "url": "https://semiaifoundry.com/learn/atlas/nccl/" } ], "recordHash": "135eeb131bb98b3a4120ecc1046dd5a214f95f7693d39a73389c00a2078dc8ee" }, { "id": "atlas-lesson-sram", "title": "Six-transistor static memory cell", "category": "learning", "format": "Atlas lesson", "description": "Retains a local bit using powered feedback and controlled access devices.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/sram/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Digital circuits", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The six-transistor topology follows the linked SRAM lecture. The arithmetic is an ideal payload count, not a physical macro area, transistor total or proof of read/write stability.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/sram-1dbbb30d55a2b4de.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#sram", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "131c126fcbe77d9bcfc529c13ddb263fec97ddaa55e37ae54950f7fe0def3576", "contentLength": 4642, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sram.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-sram.md", "sections": [ { "id": "section-1", "title": "Six-transistor static memory cell" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Feedback equilibria" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the canonical 6T cell need to retain data?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#sram" }, { "title": "MIT 6.152J — CMOS SRAM and Memory", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/57460d7d1e3ffe8e245f4f2eb3d8f845_lecture18.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/sram-1dbbb30d55a2b4de.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Complementary CMOS inverter", "url": "https://semiaifoundry.com/learn/atlas/inverter/" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Standard-cell library and physical design", "url": "https://semiaifoundry.com/learn/atlas/standard-cell/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" } ], "recordHash": "9bc7d831f02daeaf19cf1b4c2a2938ba2a1733cbd092ab3656ed8fe96b575cc3" }, { "id": "atlas-lesson-standard-cell", "title": "Standard-cell library and physical design", "category": "learning", "format": "Atlas lesson", "description": "Packages characterized transistor circuits into reusable building blocks for chip layout.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/standard-cell/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Physical design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The ratio excludes macro placement, whitespace policy and timing closure.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/standard-cell-025c93e6807b5cf0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#standard-cell", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "674d4cc95ac5122564021426b5196e19dbcf2e6818e0f2e262ecf5bf63b2c3e2", "contentLength": 5087, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-standard-cell.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-standard-cell.md", "sections": [ { "id": "section-1", "title": "Standard-cell library and physical design" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Placement utilization" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which information belongs to a useful standard-cell library?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#standard-cell" }, { "title": "University of Texas — Standard Cell Library", "url": "https://www.cerc.utexas.edu/~jaa/projects/library/" }, { "title": "University of Southampton — Digital CMOS Standard-Cell Design", "url": "https://www.southampton.ac.uk/~bim/notes/icd/lecture/pdf4/icd07.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/standard-cell-025c93e6807b5cf0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Two-input CMOS NAND gate", "url": "https://semiaifoundry.com/learn/atlas/nand/" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "Complementary CMOS inverter", "url": "https://semiaifoundry.com/learn/atlas/inverter/" }, { "title": "Edge-triggered D flip-flop", "url": "https://semiaifoundry.com/learn/atlas/flipflop/" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Fin field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/finfet/" }, { "title": "Gate-all-around nanosheet transistor", "url": "https://semiaifoundry.com/learn/atlas/gaa/" } ], "recordHash": "ef8feb5d6be7ac01e9b343ae3dcb37f17fc22fddbf778fbb43f3779c9bf60880" }, { "id": "atlas-lesson-storage", "title": "Dataset and checkpoint storage hierarchy", "category": "learning", "format": "Atlas lesson", "description": "Persists training data, model state, and results beyond accelerator working memory.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/storage/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data pipeline", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "IOPS and sequential bandwidth have different workload meanings.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/storage-98e34d0e5e2a0a06.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#storage", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "02a384a8a9bc1f33ffc41dc5ceb26f36f6b1a638a824ee3827bf49126213d430", "contentLength": 4823, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-storage.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-storage.md", "sections": [ { "id": "section-1", "title": "Dataset and checkpoint storage hierarchy" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Bandwidth and I/O operations" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a large storage system still starve GPUs?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#storage" }, { "title": "NVIDIA — High-Performance Storage Architecture", "url": "https://docs.nvidia.com/dgx-superpod/reference-architecture/scalable-infrastructure-b300/latest/storage-architecture.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/storage-98e34d0e5e2a0a06.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "NVMe solid-state storage", "url": "https://semiaifoundry.com/learn/atlas/nvme-storage/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Leaf switch and endpoint network", "url": "https://semiaifoundry.com/learn/atlas/leaf-switch/" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" } ], "recordHash": "179264d2d2894cf999ace5e25ab4e9947e46af12fdd381c9adb210bd9f4b81a0" }, { "id": "atlas-lesson-storage-input-checkpoint-path", "title": "Storage paths for datasets and checkpoints", "category": "learning", "format": "Atlas lesson", "description": "Coordinates persistent data, local caching and durable state transfer without confusing their roles.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/storage-input-checkpoint-path/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The route is representative and does not imply every platform uses the same file system or host staging. Cache and checkpoint behaviors are configuration-specific.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/storage-input-checkpoint-path-dc5f684ea90e5461.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#storage-input-checkpoint-path", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f94bc16f3e3ef5606fc55a03b004bd219c486cfdd40b4fcdf7f66824d457e5d2", "contentLength": 5020, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-storage-input-checkpoint-path.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-storage-input-checkpoint-path.md", "sections": [ { "id": "section-1", "title": "Storage paths for datasets and checkpoints" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Input pipeline rate" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why should first-read and repeated-read timings be separated?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#storage-input-checkpoint-path" }, { "title": "NVIDIA DGX GB Rack Scale Systems: Storage", "url": "https://docs.nvidia.com/dgx/dgxgb200-user-guide/storage.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/storage-input-checkpoint-path-dc5f684ea90e5461.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Dataset and checkpoint storage hierarchy", "url": "https://semiaifoundry.com/learn/atlas/storage/" }, { "title": "NVMe solid-state storage", "url": "https://semiaifoundry.com/learn/atlas/nvme-storage/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" } ], "recordHash": "f1932719223b0a320aca216887b8f3e3ca36d293532a32dd498690196caa164f" }, { "id": "atlas-lesson-streaming-multiprocessor", "title": "Streaming multiprocessor", "category": "learning", "format": "Atlas lesson", "description": "Schedules many threads and supplies the execution units and nearby storage that make GPU parallelism useful.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Compute architecture", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Peak values and intensity must share precision, scope and time boundary.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/streaming-multiprocessor-edf22961f50ab64f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#streaming-multiprocessor", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "927b1c7aa3264c804716d7a413f1f1dc72c812b8948ea723aa5be776597b938d", "contentLength": 6441, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-streaming-multiprocessor.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-streaming-multiprocessor.md", "sections": [ { "id": "section-1", "title": "Streaming multiprocessor" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Compute and data supply must balance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can a kernel with more arithmetic units still spend time waiting?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2006 · CUDA opens GPU execution to general computation" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#streaming-multiprocessor" }, { "title": "NVIDIA CUDA Programming Guide: Introduction", "url": "https://docs.nvidia.com/cuda/cuda-programming-guide/01-introduction/introduction.html" }, { "title": "NVIDIA: Using CUDA Warp-Level Primitives", "url": "https://developer.nvidia.com/blog/using-cuda-warp-level-primitives/" }, { "title": "NVIDIA CUDA Blackwell Tuning Guide", "url": "https://docs.nvidia.com/cuda/blackwell-tuning-guide/index.html" }, { "title": "NVIDIA Nsight Compute: Roofline charts", "url": "https://docs.nvidia.com/nsight-compute/ProfilingGuide/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/streaming-multiprocessor-edf22961f50ab64f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" }, { "title": "Clock tree and gated timing domains", "url": "https://semiaifoundry.com/learn/atlas/clock/" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "L1 and texture cache", "url": "https://semiaifoundry.com/learn/atlas/l1-cache/" }, { "title": "Tensor Memory", "url": "https://semiaifoundry.com/learn/atlas/tensor-memory/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" } ], "recordHash": "bf80cb7861f24b5a67b46c01256835c5fc2dad0c3f5a90ae530155a6460a9d19" }, { "id": "atlas-lesson-streaming-speech-turns", "title": "Speech is a timed interaction", "category": "learning", "format": "Atlas lesson", "description": "Audio frames, transcription revisions, endpointing, interruption and tool confirmation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/streaming-speech-turns/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Models become evaluated applications", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. A fixed reference, alignment convention and tokenization are required. WER is not a probability and does not measure tool correctness, meaning preservation or turn latency.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/streaming-speech-turns-abe0eddb9c20f463.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#streaming-speech-turns", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c6761dcdefeb8f7aff44cb1334f90019d380be1984e9272dca9af9c2fe75e30e", "contentLength": 6148, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-streaming-speech-turns.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-streaming-speech-turns.md", "sections": [ { "id": "section-1", "title": "Speech is a timed interaction" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Speech is a timed interaction · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "With 2 substitutions, 1 deletion and 1 insertion against 20 reference words, what is WER?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#streaming-speech-turns" }, { "title": "Robust Speech Recognition via Large-Scale Weak Supervision", "url": "https://arxiv.org/abs/2212.04356v1" }, { "title": "ROS 2 Jazzy: Understanding actions", "url": "https://raw.githubusercontent.com/ros2/ros2_documentation/jazzy/source/Concepts/Basic/About-Actions.rst" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/streaming-speech-turns-abe0eddb9c20f463.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Human review, interruption and cancellation", "url": "https://semiaifoundry.com/learn/atlas/human-review-cancellation/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" } ], "recordHash": "73f48270bd0b767c9a5c4c8ffc30964def5345831accd7d3cce528ab5dde4c32" }, { "id": "atlas-lesson-synthetic-data-selection-feedback", "title": "Synthetic supervision and selection loops", "category": "learning", "format": "Atlas lesson", "description": "Track a generated example through verification and selection without converting acceptance into ground truth.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/synthetic-data-selection-feedback/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-data", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Explicit arithmetic reference and deterministic faulty filter; positive denominators. This is a worked selection audit, not a synthetic-data training simulator. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/synthetic-data-selection-feedback-c54f0b92559cc4f9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#synthetic-data-selection-feedback", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a798e6681183d3e67045e8e1206b8256d21bb79ea861afd2420b87ccdf393d54", "contentLength": 6600, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-synthetic-data-selection-feedback.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-synthetic-data-selection-feedback.md", "sections": [ { "id": "section-1", "title": "Synthetic supervision and selection loops" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Synthetic supervision and selection loops · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does the accepted answer 6 demonstrate?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#synthetic-data-selection-feedback" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "DeepSeek-R1", "url": "https://arxiv.org/html/2501.12948v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/synthetic-data-selection-feedback-c54f0b92559cc4f9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Filtering, duplication and contamination", "url": "https://semiaifoundry.com/learn/atlas/data-quality-dedup-audit/" }, { "title": "Mixtures, epochs and exposure", "url": "https://semiaifoundry.com/learn/atlas/data-mixture-sampling/" }, { "title": "Packing documents and masking valid targets", "url": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/" }, { "title": "Coverage across language and source slices", "url": "https://semiaifoundry.com/learn/atlas/data-coverage-language-slices/" } ], "recordHash": "62943f9c9c84ca0362ceb065bd7faba8351be7b9f9ec8e682faab5e1c99d3df6" }, { "id": "atlas-lesson-systolic-array-dataflow", "title": "Systolic arrays and tensor dataflow", "category": "learning", "format": "Atlas lesson", "description": "Reuses operands through a regular network of multiply–accumulate elements.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/systolic-array-dataflow/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "TPU generations are named separately. This teaching array is not a transistor-accurate reconstruction or a cross-vendor peak comparison.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/systolic-array-dataflow-8d5f972ce8b5a1fc.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#systolic-array-dataflow", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b7e06f41b4191868602473d14a2bc2dca5a391de93cc870be4c1cbaa33cdec1a", "contentLength": 5200, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-systolic-array-dataflow.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-systolic-array-dataflow.md", "sections": [ { "id": "section-1", "title": "Systolic arrays and tensor dataflow" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Dense matrix work" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What chiefly allows an array to reduce distant memory traffic?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#systolic-array-dataflow" }, { "title": "In-Datacenter Performance Analysis of a Tensor Processing Unit", "url": "https://arxiv.org/abs/1704.04760" }, { "title": "TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings", "url": "https://arxiv.org/abs/2304.01433v3" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/systolic-array-dataflow-8d5f972ce8b5a1fc.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "Trainium and Inferentia execution paths", "url": "https://semiaifoundry.com/learn/atlas/aws-neuron-dataflow/" } ], "recordHash": "293ae2774f5797cbead74aa75160527dc9603d2ccad701debc5a4388d45c6eaa" }, { "id": "atlas-lesson-teacher-student-distillation", "title": "Transfer outputs without confusing size with quality", "category": "learning", "format": "Atlas lesson", "description": "Calculate soft-target loss and gradient, then evaluate the student separately from its teacher.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/teacher-student-distillation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-posttraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Teacher probabilities detached; fixed shared temperature. T² scaling is explicit. Worked calculation only; no student distillation trainer is in the lifecycle core. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/teacher-student-distillation-706748f9d7909b28.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#teacher-student-distillation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4ab84fa3789668cc018982de88716a124dfdd07c9cc8deadb0477e5b7e162d8e", "contentLength": 6875, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-teacher-student-distillation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-teacher-student-distillation.md", "sections": [ { "id": "section-1", "title": "Transfer outputs without confusing size with quality" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Transfer outputs without confusing size with quality · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What information does \\[0.75,0.25\\] retain that a hard first-class label discards?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#teacher-student-distillation" }, { "title": "Distilling the Knowledge in a Neural Network", "url": "https://arxiv.org/html/1503.02531v1" }, { "title": "DeepSeek-R1", "url": "https://arxiv.org/html/2501.12948v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/teacher-student-distillation-706748f9d7909b28.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "DPO policy/reference likelihood ratios", "url": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Verifiers, grouped advantages and RLVR", "url": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/" }, { "title": "When reward improves but the task gets worse", "url": "https://semiaifoundry.com/learn/atlas/reward-proxy-overoptimization/" } ], "recordHash": "bb8354cc1758d866a1fcce6565e7b715e1db8435893d9eebbd704ec9041b8e80" }, { "id": "atlas-lesson-telemetry-traces-evaluation", "title": "Traces connect cost, latency and results", "category": "learning", "format": "Atlas lesson", "description": "Parent/child span identity, events, retries, token/byte counts and independent result evaluation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/telemetry-traces-evaluation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "From request to durable action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The durable incident experience executes typed fixture tools, authority checks, exact review, receipts and independent final-state checks. Its policies are authored code and its storage boundary is local; it is not a real model or production workflow platform. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. This ideal DAG bound excludes resource contention, arrival queues and human waits unless they are explicit nodes. The incident ledger includes those separate intervals and is serial.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/telemetry-traces-evaluation-4f4ae5f22f915226.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#telemetry-traces-evaluation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c23200a2fc2f2294142e64da55b2d649c036e30808818f9430915c1dd8a43739", "contentLength": 6674, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-telemetry-traces-evaluation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-telemetry-traces-evaluation.md", "sections": [ { "id": "section-1", "title": "Traces connect cost, latency and results" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Traces connect cost, latency and results · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Two independent services take 40 and 60 ms, then a dependent join takes 20 ms. What is the ideal elapsed time?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#telemetry-traces-evaluation" }, { "title": "OpenTelemetry GenAI semantic conventions", "url": "https://github.com/open-telemetry/semantic-conventions-genai" }, { "title": "τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains", "url": "https://arxiv.org/abs/2406.12045" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/telemetry-traces-evaluation-4f4ae5f22f915226.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Workflow graphs and explicit state", "url": "https://semiaifoundry.com/learn/atlas/workflow-graphs-state/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" } ], "recordHash": "831ef99672e6291e635f49552db0a92568d7147e9aad3256263cac7125efdf46" }, { "id": "atlas-lesson-temporal-forecast-validation", "title": "Forecasts are tested forward in time", "category": "learning", "format": "Atlas lesson", "description": "Horizon, rolling origin, seasonal baseline, probabilistic intervals and leakage.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/temporal-forecast-validation/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Models become evaluated applications", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a worked explanation, not an executing external platform, model or robot. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. All forecasts precede their targets; values are synthetic. A small set of correlated horizons is not a broad accuracy or calibration estimate.\n\nExecutable ridge and recursive forecasting use original deterministic hourly data. They are not a real demand forecast, independent-sample confidence estimate or neural forecasting benchmark.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/temporal-forecast-validation-17cdba5c8b1b6fd3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#temporal-forecast-validation", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "24bdce8899e64545d0114cd057b054f8485d9dafd611527859fc8ebf76ba8038", "contentLength": 7279, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-temporal-forecast-validation.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-temporal-forecast-validation.md", "sections": [ { "id": "section-1", "title": "Forecasts are tested forward in time" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Forecasts are tested forward in time · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why must a normalization fit exclude future evaluation values?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#temporal-forecast-validation" }, { "title": "Chronos: Learning the Language of Time Series", "url": "https://arxiv.org/abs/2403.07815v3" }, { "title": "scikit-learn · Common pitfalls and data leakage", "url": "https://scikit-learn.org/stable/common_pitfalls.html#data-leakage" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/temporal-forecast-validation-17cdba5c8b1b6fd3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "A code patch needs execution evidence", "url": "https://semiaifoundry.com/learn/atlas/coding-agent-patch-evidence/" } ], "recordHash": "860c4165b66eafcd09c88e0e34fe7a22cb9afdb71681aca6abf7c2d41ce58a57" }, { "id": "atlas-lesson-temporary-carrier-thinning", "title": "Temporary bonding, thinning and singulation", "category": "learning", "format": "Atlas lesson", "description": "Supports fragile wafers or dies while exposing backside structures and separating units.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Packaging / Assembly and reliability", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "DISCO’s HBM sequence is representative. No carrier adhesive, removal chemistry, die thickness or allowable stress is prescribed.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/temporary-carrier-thinning-70322217a4c6667b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#temporary-carrier-thinning", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b24e5b8fcac6c2f4e7dfde77e40f3a176be6f0ad2d7a4114878f9e486df5f245", "contentLength": 5056, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-temporary-carrier-thinning.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-temporary-carrier-thinning.md", "sections": [ { "id": "section-1", "title": "Temporary bonding, thinning and singulation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Plate bending stiffness" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does a thinning animation need to show the temporary carrier?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#temporary-carrier-thinning" }, { "title": "DISCO — Tech Briefing 2023", "url": "https://disco.co.jp/jp/ir/movie/doc/E_Tech_Briefing_2023.pdf" }, { "title": "Entegris — FOUP Services", "url": "https://www.entegris.com/en/home/our-science/by-service/foup-services.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/temporary-carrier-thinning-70322217a4c6667b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer handling, carriers and genealogy", "url": "https://semiaifoundry.com/learn/atlas/wafer-handling-genealogy/" }, { "title": "Wafer finishing, orientation and geometry", "url": "https://semiaifoundry.com/learn/atlas/wafer-finishing-geometry/" }, { "title": "TSV formation, keep-out and backside reveal", "url": "https://semiaifoundry.com/learn/atlas/hbm-tsv-reveal/" }, { "title": "HBM stack assembly, repair and staged test", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack-assembly-test/" } ], "recordHash": "7b0902da07c1723f659a7b07dd0e3a15f40a8088ba2cff03cfb40958a8cc8b54" }, { "id": "atlas-lesson-tensor-core", "title": "Tensor Core matrix unit", "category": "learning", "format": "Atlas lesson", "description": "Multiplies small matrix tiles and accumulates their products with supported numerical formats.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tensor-core/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Compute architecture", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Tile dimensions and accumulation precision are configuration choices.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tensor-core-e72167e744c85d77.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tensor-core", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "60638d7cb96c98275455c4d114ec9b8f393e8bf1514e03f8ea1952c8f65f27d6", "contentLength": 6666, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tensor-core.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tensor-core.md", "sections": [ { "id": "section-1", "title": "Tensor Core matrix unit" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Why matrix size and reuse matter" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a Tensor Core primarily accelerate?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2017 · Volta introduces NVIDIA Tensor Cores" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tensor-core" }, { "title": "NVIDIA: Volta GPU platform launch", "url": "https://nvidianews.nvidia.com/news/nvidia-launches-revolutionary-volta-gpu-platform-fueling-next-era-of-ai-and-high-performance-computing" }, { "title": "NVIDIA CUTLASS: Blackwell specifics", "url": "https://docs.nvidia.com/cutlass/4.5.1/media/docs/cpp/blackwell.html" }, { "title": "NVIDIA GB200 NVL72 specifications", "url": "https://www.nvidia.com/en-us/data-center/gb200-nvl72/" }, { "title": "NVIDIA Matrix Multiplication Background Guide", "url": "https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tensor-core-e72167e744c85d77.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Streaming multiprocessor", "url": "https://semiaifoundry.com/learn/atlas/streaming-multiprocessor/" }, { "title": "Tensor Memory", "url": "https://semiaifoundry.com/learn/atlas/tensor-memory/" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "Tensor Memory Accelerator", "url": "https://semiaifoundry.com/learn/atlas/tensor-memory-accelerator/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Compiler, intermediate code, and device executable", "url": "https://semiaifoundry.com/learn/atlas/compiler/" } ], "recordHash": "448736299efee7620efd0bda8f29c7bf5344bc124b9bcb2be623f7ccfa878e10" }, { "id": "atlas-lesson-tensor-index-contracts", "title": "Tensor shapes, indices and contractions", "category": "learning", "format": "Atlas lesson", "description": "Specifies what each axis means before the same numbers are scheduled or stored on hardware.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tensor-index-contracts/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "mathematical-foundations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. Finite rectangular arrays, matching contracted dimension and a declared arithmetic type. The workbench uses small integers; rounded reduction order is studied separately.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tensor-index-contracts-2c14febbab1621be.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tensor-index-contracts", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "36e423b707b3ea221bb9de018038453f72f81d1111923e080bda95605ec84ef3", "contentLength": 6304, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tensor-index-contracts.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tensor-index-contracts.md", "sections": [ { "id": "section-1", "title": "Tensor shapes, indices and contractions" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Tensor shapes, indices and contractions" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which change leaves C = AB semantically unchanged?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tensor-index-contracts" }, { "title": "Goodfellow, Bengio and Courville · Linear algebra", "url": "https://www.deeplearningbook.org/contents/linear_algebra.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tensor-index-contracts-2c14febbab1621be.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Multiply–accumulate and fused arithmetic", "url": "https://semiaifoundry.com/learn/atlas/mac/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Sharded matrix multiplication and result ownership", "url": "https://semiaifoundry.com/learn/atlas/sharded-matmul-ownership/" } ], "recordHash": "d0c75d37d544fb25053e475c55ea4a630118a61850cae0eef8aad5c4afba511f" }, { "id": "atlas-lesson-tensor-memory-accelerator", "title": "Tensor Memory Accelerator", "category": "learning", "format": "Atlas lesson", "description": "Moves multidimensional tensor tiles asynchronously so compute threads can spend less effort copying data.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tensor-memory-accelerator/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Compute architecture", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The overlap model is the lesson’s ideal two-stage pipeline, supported by the linked asynchronous-copy guidance. TMA moves data; Tensor Memory stores it. Adequate buffering and independent resources are assumptions, not guaranteed speedup.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tensor-memory-accelerator-c1e641ff30a44e3f.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tensor-memory-accelerator", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bcd50fcf57643df02437cd41f7ac5ea56dead22029a96630a105e7494e90ae16", "contentLength": 6450, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tensor-memory-accelerator.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tensor-memory-accelerator.md", "sections": [ { "id": "section-1", "title": "Tensor Memory Accelerator" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Overlap changes a sum into a bottleneck" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "How does a pipelined kernel benefit from TMA?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2022 · Hopper introduces Tensor Memory Accelerator" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tensor-memory-accelerator" }, { "title": "NVIDIA: Hopper Architecture In-Depth", "url": "https://developer.nvidia.com/blog/nvidia-hopper-architecture-in-depth/" }, { "title": "NVIDIA Hopper Tuning Guide: Tensor Memory Accelerator", "url": "https://docs.nvidia.com/cuda/archive/12.1.0/pdf/Hopper_Tuning_Guide.pdf" }, { "title": "NVIDIA CUTLASS 3.8 release", "url": "https://github.com/NVIDIA/cutlass/discussions/2125" }, { "title": "NVIDIA CUDA Programming Guide: asynchronous data copies", "url": "https://docs.nvidia.com/cuda/cuda-programming-guide/04-special-topics/async-copies.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tensor-memory-accelerator-c1e641ff30a44e3f.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "HBM controller and PHY", "url": "https://semiaifoundry.com/learn/atlas/hbm-controller/" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "Tensor Memory", "url": "https://semiaifoundry.com/learn/atlas/tensor-memory/" } ], "recordHash": "6cf2ec7d18e75bdec9f307c7cbc91d63ea1e04584d97f453f630e4223a6614f0" }, { "id": "atlas-lesson-tensor-memory", "title": "Tensor Memory", "category": "learning", "format": "Atlas lesson", "description": "Provides dedicated on-chip storage for fifth-generation Tensor Core operands and accumulators.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tensor-memory/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Memory hierarchy", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The logical dimensions are those cited from PTX ISA 8.8 for sm_100a/sm_100f. The 32-column allocation is an arithmetic example, subject to actual allocation and residency rules; it is not a physical-cell layout or a portable GPU feature.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tensor-memory-c62eedf232bc3a66.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tensor-memory", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "cdca447b678a9855cebe0829b68979168c8bd0fe1880db5fa74773f6004a14d2", "contentLength": 6250, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tensor-memory.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tensor-memory.md", "sections": [ { "id": "section-1", "title": "Tensor Memory" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Logical shape determines storage capacity" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What is Tensor Memory’s main role?" }, { "id": "section-11", "title": "Historical context" }, { "id": "section-12", "title": "2025 · CUTLASS 3.8 exposes Blackwell Tensor Memory" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tensor-memory" }, { "title": "NVIDIA CUTLASS 3.8 release discussion", "url": "https://github.com/NVIDIA/cutlass/discussions/2125" }, { "title": "NVIDIA PTX ISA 8.8: fifth-generation Tensor Core instructions", "url": "https://docs.nvidia.com/cuda/pdf/ptx_isa_8.8.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tensor-memory-c62eedf232bc3a66.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tensor Core matrix unit", "url": "https://semiaifoundry.com/learn/atlas/tensor-core/" }, { "title": "Shared memory SRAM", "url": "https://semiaifoundry.com/learn/atlas/shared-sram/" }, { "title": "Register file", "url": "https://semiaifoundry.com/learn/atlas/register-file/" }, { "title": "Tensor Memory Accelerator", "url": "https://semiaifoundry.com/learn/atlas/tensor-memory-accelerator/" } ], "recordHash": "3b94285d22a023c9a9c4d05b89ab28f711f67fe2cd42c53642c8d8e2df829f8c" }, { "id": "atlas-lesson-test-time-search-verification", "title": "Sampling more candidates versus selecting correct ones", "category": "learning", "format": "Atlas lesson", "description": "Distinguish finding a correct candidate from selecting one under a finite verification budget.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/test-time-search-verification/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-evaluation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Independent identically distributed success events for the probability calculation. Correlated samples and imperfect selectors invalidate interpreting this as final accuracy. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/test-time-search-verification-44ee0a218a7c83b3.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#test-time-search-verification", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "2be8b62b4e5510c792e1a759ffb29ddc3e6626834bb67c0e50892fd3cb92f769", "contentLength": 6678, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-test-time-search-verification.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-test-time-search-verification.md", "sections": [ { "id": "section-1", "title": "Sampling more candidates versus selecting correct ones" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Sampling more candidates versus selecting correct ones · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Can pass-at-4 be successful while the selected answer is wrong?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#test-time-search-verification" }, { "title": "DeepSeek-R1", "url": "https://arxiv.org/html/2501.12948v1" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/test-time-search-verification-44ee0a218a7c83b3.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Speculative decoding: proposals and verified output", "url": "https://semiaifoundry.com/learn/atlas/speculative-decoding-verification/" }, { "title": "Confidence, errors and refusal to guess", "url": "https://semiaifoundry.com/learn/atlas/probability-calibration-abstention/" }, { "title": "Human and model judgments under a rubric", "url": "https://semiaifoundry.com/learn/atlas/judge-rubric-agreement/" }, { "title": "From lexical retrieval to model answers with evidence", "url": "https://semiaifoundry.com/learn/atlas/retrieval-supported-generation/" }, { "title": "Version the entire evaluated system", "url": "https://semiaifoundry.com/learn/atlas/model-system-regression-contract/" } ], "recordHash": "4bbb6b0acf6b1efd99cc97fcda4361e2bd6c9b0aed06b57ae38035d38eec26fd" }, { "id": "atlas-lesson-thermal-interface", "title": "Thermal interface material", "category": "learning", "format": "Atlas lesson", "description": "Fills microscopic gaps so heat can cross from a chip or lid into a cooling surface.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/thermal-interface/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Thermal path", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Bulk conduction is only one term in a real thermal path.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/thermal-interface-f97b7c59a6e1b1c6.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#thermal-interface", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "8f02f1130d7aaf28b482cecc56869def7e08b121f8b9ef35df12f5a8f1e72321", "contentLength": 5654, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-thermal-interface.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-thermal-interface.md", "sections": [ { "id": "section-1", "title": "Thermal interface material" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Geometry converts conductivity into resistance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can two materials with similar conductivity perform differently in a real assembly?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#thermal-interface" }, { "title": "Henkel: thin bond line phase-change TIM", "url": "https://www.henkel.com/press-and-media/press-releases-and-kits/2023-05-16-low-pressure-thin-bond-line-thermal-interface-material-tim-from-henkel-brings-best-in-class-thermal-management-solution-for-next-gen-ics-1827782" }, { "title": "Texas Instruments: Thermal design for surface-mount layouts", "url": "https://www.ti.com/download/trng/docs/seminar/Topic%2010%20-%20Thermal%20Design%20Consideration%20for%20Surface%20Mount%20Layouts%20.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/thermal-interface-f97b7c59a6e1b1c6.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" }, { "title": "Lid and heat spreader", "url": "https://semiaifoundry.com/learn/atlas/heat-spreader/" }, { "title": "Liquid-cooling coldplate", "url": "https://semiaifoundry.com/learn/atlas/coldplate/" } ], "recordHash": "c4a2064975c4fc051a3627ec0a4105c7d3905b827559dc17f0799995fd587be7" }, { "id": "atlas-lesson-thermal-oxidation-interface", "title": "Thermal oxidation and the silicon interface", "category": "learning", "format": "Atlas lesson", "description": "Converts surface silicon into oxide while moving a buried interface.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/thermal-oxidation-interface/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Repeated operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The relation is a teaching model. No production oxidation temperature, oxidant mixture or qualified thickness is specified.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/thermal-oxidation-interface-8ebe63f6e1eb5bc8.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#thermal-oxidation-interface", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "de93ebb6ff6b6d6735fda93b962028d12111c05f37e56de2dcf0adca6da2dc26", "contentLength": 5251, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-thermal-oxidation-interface.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-thermal-oxidation-interface.md", "sections": [ { "id": "section-1", "title": "Thermal oxidation and the silicon interface" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Deal–Grove growth model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why does a thick oxide often grow more slowly than an initially thin oxide?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#thermal-oxidation-interface" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "ASML — How microchips are made", "url": "https://www.asml.com/en/technology/all-about-microchips/how-microchips-are-made" }, { "title": "Deal and Grove — General Relationship for the Thermal Oxidation of Silicon", "url": "https://www.columbia.edu/~leonard/TISSSite/mvbd.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/thermal-oxidation-interface-8ebe63f6e1eb5bc8.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer and fabrication hierarchy", "url": "https://semiaifoundry.com/learn/atlas/silicon-wafer/" }, { "title": "Metal gate and high-k dielectric", "url": "https://semiaifoundry.com/learn/atlas/gate-stack/" }, { "title": "Implantation, activation and diffusion", "url": "https://semiaifoundry.com/learn/atlas/implantation-anneal-diffusion/" }, { "title": "ALD and self-limiting surface reactions", "url": "https://semiaifoundry.com/learn/atlas/ald-self-limiting-growth/" } ], "recordHash": "efeeffcdb6b8c3570f5d553ec9f22a1ac3ad70b5fd32d3f5dfbc9fd9ecf5b759" }, { "id": "atlas-lesson-through-silicon-via", "title": "Through-silicon via", "category": "learning", "format": "Atlas lesson", "description": "Provides a vertical electrical connection through silicon between stacked layers.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/through-silicon-via/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Advanced packaging", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "TSV geometry and process sequence are route-specific.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/through-silicon-via-50f0dda1d05a010d.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#through-silicon-via", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f7e6f8b412d869f9c6fc97af25e10bf938fb04faba9041d47e9be1bb9bb9e25e", "contentLength": 5571, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-through-silicon-via.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-through-silicon-via.md", "sections": [ { "id": "section-1", "title": "Through-silicon via" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Via geometry affects electrical resistance" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a TSV connect?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#through-silicon-via" }, { "title": "SK hynix: Inside 12-layer HBM3 packaging", "url": "https://news.skhynix.com/en/meet-the-sk-hynix-team-behind-the-worlds-first-12-layer-hbm3/" }, { "title": "Micron HBM3E product brief", "url": "https://assets.micron.com/adobe/assets/urn%3Aaaid%3Aaem%3Ab710d8f2-7f66-44c1-a234-456e2b986347/renditions/original/as/hbm3e-product-brief.pdf" }, { "title": "MIT: Communication System Design, interconnect and wire scaling", "url": "https://ocw.mit.edu/courses/6-973-communication-system-design-spring-2006/44d1cff68d0f994cca25442de3e1ac78_lecture_5.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/through-silicon-via-50f0dda1d05a010d.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "On-chip metal and via hierarchy", "url": "https://semiaifoundry.com/learn/atlas/interconnect/" }, { "title": "Wafer and fabrication hierarchy", "url": "https://semiaifoundry.com/learn/atlas/silicon-wafer/" }, { "title": "High-bandwidth memory stack", "url": "https://semiaifoundry.com/learn/atlas/hbm-stack/" }, { "title": "DRAM die and memory banks", "url": "https://semiaifoundry.com/learn/atlas/dram-die/" }, { "title": "Microbumps and bonding joints", "url": "https://semiaifoundry.com/learn/atlas/microbump/" } ], "recordHash": "96091b3e895f23abe7fc3084112eaddec7225d5d04599297ca7346996dbb88c2" }, { "id": "atlas-lesson-tiny-causal-decoder", "title": "Assemble an initialized causal language model", "category": "learning", "format": "Atlas lesson", "description": "Join tensor shapes, causal probabilities, gradients and optimizer state into one reproducible trained model.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tiny-causal-decoder/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-base-model", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable core. One head, separate input/output weights, two feed-forward biases, output bias, fixed sinusoidal positions, gain-free RMS normalization, tanh activation and binary64 arithmetic. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tiny-causal-decoder-bb9fed5742cbbfda.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tiny-causal-decoder", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "7f5242af593e46ac05b0047f46f74ef9cc51641af83c8f4e37ecbbd1cbb29818", "contentLength": 6700, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tiny-causal-decoder.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tiny-causal-decoder.md", "sections": [ { "id": "section-1", "title": "Assemble an initialized causal language model" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Assemble an initialized causal language model · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why are the fixed positional vectors absent from the 423 count?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tiny-causal-decoder" }, { "title": "Attention Is All You Need", "url": "https://arxiv.org/html/1706.03762v7" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Root Mean Square Layer Normalization", "url": "https://arxiv.org/html/1910.07467v1" }, { "title": "PyTorch Adam algorithm", "url": "https://docs.pytorch.org/docs/2.14/generated/torch.optim.Adam.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tiny-causal-decoder-bb9fed5742cbbfda.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Feed-forward network", "url": "https://semiaifoundry.com/learn/atlas/feed-forward/" }, { "title": "Residual stream & normalization", "url": "https://semiaifoundry.com/learn/atlas/residual-normalization/" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "A differentiable computation graph", "url": "https://semiaifoundry.com/learn/atlas/reverse-mode-autodiff/" } ], "recordHash": "0f44f5b5e0377ccd43cb260b682bd10f154b492123e4c968379b2398f6a1ee55" }, { "id": "atlas-lesson-tokenizer", "title": "Tokenizer", "category": "learning", "format": "Atlas lesson", "description": "Turn text into a sequence of discrete IDs.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tokenizer/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Representation", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Counts are invented to illustrate the lesson’s identity, not outputs of a named tokenizer. Real comparisons require the identical text, tokenizer version and control-token rules; languages and code do not share a universal bytes/token ratio.\n\nMode: worked example. Toy word boundaries and deterministic lexical tie rule; no byte fallback or production BPE trainer is executed by the core. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.\n\nThe implemented whole-field UTF-8 byte variant has no word pre-tokenizer and can merge across spaces within a field. Smaller token count is not by itself evidence of better learning. BPE IDs never enter the fixed nine-token lifecycle decoder.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tokenizer-76457284d6a4e6f9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tokenizer", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3f3cca881c5cb7e82c145c2b7796a923c05df7bdaab6a2037034085b0e47bf71", "contentLength": 10165, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tokenizer.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tokenizer.md", "sections": [ { "id": "section-1", "title": "Tokenizer" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Sequence length is an engineering variable" }, { "id": "section-5", "title": "Train a tokenizer, then encode unseen text · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Does one token always equal one word?" }, { "id": "section-12", "title": "Which operation would leak held-out information into the tokenizer?" }, { "id": "section-13", "title": "Why do two adjacent aa counts in aaa produce only one replacement during one left-to-right merge pass?" }, { "id": "section-14", "title": "Historical context" }, { "id": "section-15", "title": "2015 · Subword BPE enters neural translation" }, { "id": "section-16", "title": "Evidence and scope" }, { "id": "section-17", "title": "Sources" }, { "id": "section-18", "title": "Continue exploring" }, { "id": "section-19", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tokenizer" }, { "title": "Sennrich et al. — Neural Machine Translation of Rare Words with Subword Units", "url": "https://arxiv.org/abs/1508.07909" }, { "title": "OpenAI — tiktoken", "url": "https://github.com/openai/tiktoken" }, { "title": "Neural Machine Translation of Rare Words with Subword Units", "url": "https://aclanthology.org/P16-1162.pdf" }, { "title": "Sennrich et al. · BPE construction §3.2", "url": "https://arxiv.org/html/1508.07909v5" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tokenizer-76457284d6a4e6f9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Embedding table", "url": "https://semiaifoundry.com/learn/atlas/embedding/" }, { "title": "Key–value cache", "url": "https://semiaifoundry.com/learn/atlas/kv-cache/" }, { "title": "Filtering, duplication and contamination", "url": "https://semiaifoundry.com/learn/atlas/data-quality-dedup-audit/" }, { "title": "Mixtures, epochs and exposure", "url": "https://semiaifoundry.com/learn/atlas/data-mixture-sampling/" }, { "title": "Packing documents and masking valid targets", "url": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/" }, { "title": "Synthetic supervision and selection loops", "url": "https://semiaifoundry.com/learn/atlas/synthetic-data-selection-feedback/" }, { "title": "Coverage across language and source slices", "url": "https://semiaifoundry.com/learn/atlas/data-coverage-language-slices/" }, { "title": "Training data pipeline", "url": "https://semiaifoundry.com/learn/atlas/training-data/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" } ], "recordHash": "721bb7086ad9e97bd55823c8c1e06aff03696cf800bbdae8f3907b582de89e24" }, { "id": "atlas-lesson-tool-authority-identity", "title": "User authority and service identity", "category": "learning", "format": "Atlas lesson", "description": "User authorization, workload authentication, token audience, scope and resource policy are separate checks.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tool-authority-identity/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Authority, context and execution boundaries", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The durable incident experience executes typed fixture tools, authority checks, exact review, receipts and independent final-state checks. Its policies are authored code and its storage boundary is local; it is not a real model or production workflow platform. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. This is a teaching decomposition, not a complete universal authorization algorithm. The executable incident demonstrates only a bounded role/capability subset.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tool-authority-identity-f81d65aeb7da2f78.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tool-authority-identity", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b44f3eb511c67e07c3d2597267eb5ec6ad8bac6a295ed965ab0ad011cb49204b", "contentLength": 6946, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tool-authority-identity.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tool-authority-identity.md", "sections": [ { "id": "section-1", "title": "User authority and service identity" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "User authority and service identity · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A token intended for service A is presented to service B. What is required before allowing the call?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tool-authority-identity" }, { "title": "MCP authorization", "url": "https://modelcontextprotocol.io/specification/2026-07-28/basic/authorization" }, { "title": "OAuth 2.0 Security Best Current Practice", "url": "https://www.rfc-editor.org/rfc/rfc9700.html" }, { "title": "SPIFFE overview", "url": "https://spiffe.io/docs/latest/spiffe-about/overview/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tool-authority-identity-f81d65aeb7da2f78.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tool schemas and semantic validation", "url": "https://semiaifoundry.com/learn/atlas/tool-contracts-schemas/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "4f0d6119c55d45fc1a90d645e57c5216ccd0c5a8d3aa1a2d32259583e828bcc2" }, { "id": "atlas-lesson-tool-contracts-schemas", "title": "Tool schemas and semantic validation", "category": "learning", "format": "Atlas lesson", "description": "Syntax, types, domain constraints, resource identity, output schema and result errors.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tool-contracts-schemas/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "From request to durable action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The durable incident experience executes typed fixture tools, authority checks, exact review, receipts and independent final-state checks. Its policies are authored code and its storage boundary is local; it is not a real model or production workflow platform. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. This conjunction defines the lesson’s validation boundary. Authorization, exact approval and final task correctness are additional distinct predicates.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tool-contracts-schemas-e27edc852f065160.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tool-contracts-schemas", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "6c67bde6960a45329e28d59f8f97cf93a939266c6f9c8166e4733ce8497fb51e", "contentLength": 6319, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tool-contracts-schemas.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tool-contracts-schemas.md", "sections": [ { "id": "section-1", "title": "Tool schemas and semantic validation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Tool schemas and semantic validation · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "A valid reservation call targets FAN-9, but the task asks for FAN-7. Which check catches the remaining problem?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tool-contracts-schemas" }, { "title": "MCP tools", "url": "https://modelcontextprotocol.io/specification/2026-07-28/server/tools" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tool-contracts-schemas-e27edc852f065160.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "f47f3be9bccc631c2fee72dd0173c83901ec70e0460d2e5efd0f9dbd63ba9d43" }, { "id": "atlas-lesson-tool-loop", "title": "Tools, memory & agent loop", "category": "learning", "format": "Atlas lesson", "description": "Connect model inference to actions and evidence.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tool-loop/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Agent systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The model–action–observation pattern follows the linked Toolformer/ReAct context. Times are synthetic; parallel tools, failure, retries and context management alter timing. The runtime validates permissions and results rather than treating a proposal as completed work.\n\nThe executable extension is a fictional local environment with two authored policies. It adds no claim of real LLM agency, MCP conformance or production durability. Model parameters, invocation context and the workflow journal remain separate objects.\n\nMode: worked example. Authored finite inventory contract, not an actual external order. Model generation, validator execution and learning updates have separate state boundaries. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tool-loop-50255241730ddbf9.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tool-loop", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bfb00b0123eb732637c21a06fd9e6f6db999e3e75db541389a7f57467bca019e", "contentLength": 11767, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tool-loop.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tool-loop.md", "sections": [ { "id": "section-1", "title": "Tools, memory & agent loop" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A closed loop changes context and the environment" }, { "id": "section-5", "title": "A model policy with validated observations and actions · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "What actually executes a model-proposed tool call?" }, { "id": "section-12", "title": "What does a lost tool response establish about whether the write committed?" }, { "id": "section-13", "title": "What establishes successful reservation after a tool call?" }, { "id": "section-14", "title": "Historical context" }, { "id": "section-15", "title": "2022 · ReAct interleaves language-model reasoning and actions" }, { "id": "section-16", "title": "Evidence and scope" }, { "id": "section-17", "title": "Sources" }, { "id": "section-18", "title": "Continue exploring" }, { "id": "section-19", "title": "Foundations" }, { "id": "section-20", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tool-loop" }, { "title": "Yao et al. — ReAct: Synergizing Reasoning and Acting in Language Models", "url": "https://arxiv.org/abs/2210.03629" }, { "title": "Schick et al. — Toolformer", "url": "https://arxiv.org/abs/2302.04761" }, { "title": "Temporal Activities", "url": "https://docs.temporal.io/activities" }, { "title": "MCP tools", "url": "https://modelcontextprotocol.io/specification/2026-07-28/server/tools" }, { "title": "ReAct: Synergizing Reasoning and Acting in Language Models", "url": "https://arxiv.org/html/2210.03629v3" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tool-loop-50255241730ddbf9.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Output head & decoding", "url": "https://semiaifoundry.com/learn/atlas/output-head/" }, { "title": "Inference serving and request scheduling", "url": "https://semiaifoundry.com/learn/atlas/serving/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Post-training & feedback", "url": "https://semiaifoundry.com/learn/atlas/post-training/" }, { "title": "GPT-6 Astra", "url": "https://semiaifoundry.com/learn/atlas/astra/" }, { "title": "Durable actions and the ambiguous timeout", "url": "https://semiaifoundry.com/learn/atlas/durable-actions-idempotency/" }, { "title": "Tool schemas and semantic validation", "url": "https://semiaifoundry.com/learn/atlas/tool-contracts-schemas/" }, { "title": "Human review, interruption and cancellation", "url": "https://semiaifoundry.com/learn/atlas/human-review-cancellation/" }, { "title": "Confidence, errors and refusal to guess", "url": "https://semiaifoundry.com/learn/atlas/probability-calibration-abstention/" }, { "title": "Human and model judgments under a rubric", "url": "https://semiaifoundry.com/learn/atlas/judge-rubric-agreement/" }, { "title": "From lexical retrieval to model answers with evidence", "url": "https://semiaifoundry.com/learn/atlas/retrieval-supported-generation/" }, { "title": "Sampling more candidates versus selecting correct ones", "url": "https://semiaifoundry.com/learn/atlas/test-time-search-verification/" }, { "title": "Version the entire evaluated system", "url": "https://semiaifoundry.com/learn/atlas/model-system-regression-contract/" } ], "recordHash": "a603cf2b8684de8f49bef3daaa7f750d2a0f300c25716d11ea22900a46427334" }, { "id": "atlas-lesson-topology-job-admission", "title": "Job admission, topology and resource fragmentation", "category": "learning", "format": "Atlas lesson", "description": "Places complete jobs onto compatible resources while balancing utilization and service goals.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/topology-job-admission/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Data-center operations", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "No real user queue or reservation is inferred. Slurm’s named gang-scheduling implementation is not conflated with generic simultaneous parallel-job admission.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/topology-job-admission-67b7c58b3118f3ac.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#topology-job-admission", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4c44096731951d9abac4a3cef5f45d2e7cccb18edd9534f096214dbe12f8418c", "contentLength": 4648, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-topology-job-admission.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-topology-job-admission.md", "sections": [ { "id": "section-1", "title": "Job admission, topology and resource fragmentation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Allocation feasibility" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can an eight-device job wait while eight devices are free?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#topology-job-admission" }, { "title": "Slurm Topology Guide", "url": "https://slurm.schedmd.com/topology.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/topology-job-admission-67b7c58b3118f3ac.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Cluster scheduler and resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scheduler/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Scale-up, scale-out and management fabrics", "url": "https://semiaifoundry.com/learn/atlas/scaleup-scaleout-boundaries/" } ], "recordHash": "a2c465343445cc34228460a03a179e8bb34d85a0968f94efe4fc5a7168a4cea7" }, { "id": "atlas-lesson-training-data", "title": "Training data pipeline", "category": "learning", "format": "Atlas lesson", "description": "Convert a source collection into useful learning examples.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/training-data/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Learning", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The fixed-mixture expectation is the relation stated in the lesson. Values are synthetic; deduplication, representativeness, contamination and provenance require independent checks and cannot be inferred from this weighted average.\n\nThe sensor datasets and numeric normalization values are authored. They establish a leakage/artifact mechanism, not field data quality or generalization on real equipment.\n\nMode: executable corpus lineage. Two intentionally conflicting domains share prompt families within the same split, never across splits. No external dataset license or privacy review is implied. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.\n\nThese are computed relationships in twelve authored documents across seven known families. No language-model quality, memorization rate or representative real-corpus coverage is measured.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/training-data-0781ba332be25aa0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#training-data", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "c202dd53365327e4f7f4bc50725630bddcfcc4dd699f03504d0bfdafa5ac9a13", "contentLength": 12997, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-training-data.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-training-data.md", "sections": [ { "id": "section-1", "title": "Training data pipeline" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "The mixture defines the expected learning signal" }, { "id": "section-5", "title": "Dataset lineage and reproducible splits · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "Does a larger raw corpus guarantee a better model?" }, { "id": "section-12", "title": "Should held-out evaluation labels or future observations fit a preprocessing statistic used to claim an earlier forecast?" }, { "id": "section-13", "title": "Why are there only 24 distinct prompt families across the 48 records?" }, { "id": "section-14", "title": "A mirrored document appears in training and evaluation after individual-document splitting. What does this establish?" }, { "id": "section-15", "title": "Historical context" }, { "id": "section-16", "title": "2021 · Deduplication is measured as a training intervention" }, { "id": "section-17", "title": "Evidence and scope" }, { "id": "section-18", "title": "Sources" }, { "id": "section-19", "title": "Continue exploring" }, { "id": "section-20", "title": "Foundations" }, { "id": "section-21", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#training-data" }, { "title": "Lee et al. — Deduplicating Training Data Makes Language Models Better", "url": "https://arxiv.org/abs/2107.06499" }, { "title": "Hoffmann et al. — Compute-Optimal Training", "url": "https://arxiv.org/abs/2203.15556" }, { "title": "GPT-4 Technical Report", "url": "https://arxiv.org/abs/2303.08774" }, { "title": "scikit-learn · Common pitfalls and data leakage", "url": "https://scikit-learn.org/stable/common_pitfalls.html#data-leakage" }, { "title": "The FineWeb Datasets", "url": "https://arxiv.org/html/2406.17557v1" }, { "title": "Deduplicating Training Data Makes Language Models Better", "url": "https://arxiv.org/html/2107.06499v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/training-data-0781ba332be25aa0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tokenizer", "url": "https://semiaifoundry.com/learn/atlas/tokenizer/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Dataset and checkpoint storage hierarchy", "url": "https://semiaifoundry.com/learn/atlas/storage/" }, { "title": "Scaling laws & resource allocation", "url": "https://semiaifoundry.com/learn/atlas/scaling-laws/" }, { "title": "Model artifacts, rollout and drift", "url": "https://semiaifoundry.com/learn/atlas/model-artifact-rollout-drift/" }, { "title": "Forecasts are tested forward in time", "url": "https://semiaifoundry.com/learn/atlas/temporal-forecast-validation/" }, { "title": "Filtering, duplication and contamination", "url": "https://semiaifoundry.com/learn/atlas/data-quality-dedup-audit/" }, { "title": "Mixtures, epochs and exposure", "url": "https://semiaifoundry.com/learn/atlas/data-mixture-sampling/" }, { "title": "Packing documents and masking valid targets", "url": "https://semiaifoundry.com/learn/atlas/sequence-packing-loss-denominators/" }, { "title": "Synthetic supervision and selection loops", "url": "https://semiaifoundry.com/learn/atlas/synthetic-data-selection-feedback/" }, { "title": "Coverage across language and source slices", "url": "https://semiaifoundry.com/learn/atlas/data-coverage-language-slices/" }, { "title": "Human judgments, disagreement and dataset lineage", "url": "https://semiaifoundry.com/learn/atlas/dataset-human-judgment-lineage/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "5987ab6da17a12bafdfcb4d8db8937c8369fc8b1eca05ada4ac4b8a359e445a7" }, { "id": "atlas-lesson-training-memory-state", "title": "Training state and activation rematerialization", "category": "learning", "format": "Atlas lesson", "description": "Budgets weights, gradients, optimizer state and saved activations across a training step.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/training-memory-state/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Model–machine co-design", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is an explicit synthetic format choice, not a universal training multiplier. ZeRO stages and implementation buffers must be identified before applying a sharding estimate.\n\nMode: executable arrays; payload arithmetic. 423 entries per full array, eight bytes per binary64 number; no claim that JavaScript object storage equals this payload. No rematerialization feature is executed. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/training-memory-state-0e965c34b3054246.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#training-memory-state", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "3fabff49b5c87b0d4c56644b4887147b63239c6659285dd3a20b5f565e501862", "contentLength": 9061, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-training-memory-state.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-training-memory-state.md", "sections": [ { "id": "section-1", "title": "Training state and activation rematerialization" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Training capacity ledger" }, { "id": "section-5", "title": "Training tensors with actual lifetimes · worked relation" }, { "id": "section-6", "title": "Engineering example" }, { "id": "section-7", "title": "Distinctions and tradeoffs" }, { "id": "section-8", "title": "Specifications and interfaces" }, { "id": "section-9", "title": "Interfaces" }, { "id": "section-10", "title": "Check your understanding" }, { "id": "section-11", "title": "What cost accompanies discarding a forward activation that backward computation needs?" }, { "id": "section-12", "title": "What does 10152 bytes include?" }, { "id": "section-13", "title": "Evidence and scope" }, { "id": "section-14", "title": "Sources" }, { "id": "section-15", "title": "Continue exploring" }, { "id": "section-16", "title": "Foundations" }, { "id": "section-17", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#training-memory-state" }, { "title": "ZeRO: Memory Optimizations Toward Training Trillion Parameter Models", "url": "https://arxiv.org/abs/1910.02054" }, { "title": "2 OLMo 2 Furious", "url": "https://arxiv.org/html/2501.00656v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/training-memory-state-0e965c34b3054246.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Full memory hierarchy and input path", "url": "https://semiaifoundry.com/learn/atlas/memory-hierarchy-route/" }, { "title": "Data, tensor, pipeline, and state parallelism", "url": "https://semiaifoundry.com/learn/atlas/parallelism/" }, { "title": "Parallelism as a memory and communication budget", "url": "https://semiaifoundry.com/learn/atlas/parallelism-communication-budget/" }, { "title": "Next-token supervision from raw sequences", "url": "https://semiaifoundry.com/learn/atlas/causal-pretraining-objective/" }, { "title": "Initialization, learning rate and stable updates", "url": "https://semiaifoundry.com/learn/atlas/optimizer-schedule-stability/" }, { "title": "Gradient accumulation under a fixed global objective", "url": "https://semiaifoundry.com/learn/atlas/microbatch-equivalent-updates/" } ], "recordHash": "f14d6af6ec970aa34598ac769b5aa839492d0f2444bab154805f7b8a74741f17" }, { "id": "atlas-lesson-training-tier-placement", "title": "Training state across HBM, host memory and storage", "category": "learning", "format": "Atlas lesson", "description": "Distinguish mutable training state, recomputation, offload and durable checkpoints.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/training-tier-placement/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Software", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "DeepSpeed documents optimizer offload to the host CPU; ZeRO-Infinity studies GPU/CPU/NVMe state management. Neither source establishes an HBF training implementation or its write endurance.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/training-tier-placement-fa59deb9ce7f62c5.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#training-tier-placement", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "b630d0777d8617493042a8aabb7021398cc2d7a7ed5f684cb396d471c7c9179f", "contentLength": 5450, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-training-tier-placement.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-training-tier-placement.md", "sections": [ { "id": "section-1", "title": "Training state across HBM, host memory and storage" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "State inventory before sharding" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which state is inherently write-active during ordinary optimizer updates?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#training-tier-placement" }, { "title": "DeepSpeed — ZeRO-Offload tutorial", "url": "https://www.deepspeed.ai/tutorials/zero-offload/" }, { "title": "ZeRO-Infinity: Breaking the GPU Memory Wall", "url": "https://arxiv.org/abs/2104.07857" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/training-tier-placement-fa59deb9ce7f62c5.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Training state and activation rematerialization", "url": "https://semiaifoundry.com/learn/atlas/training-memory-state/" }, { "title": "Place the working set, not just the model", "url": "https://semiaifoundry.com/learn/atlas/memory-working-set-placement/" }, { "title": "Checkpointing, failure and retained useful work", "url": "https://semiaifoundry.com/learn/atlas/checkpoint-retained-work/" }, { "title": "Parallelism as a memory and communication budget", "url": "https://semiaifoundry.com/learn/atlas/parallelism-communication-budget/" }, { "title": "HBF: a read-oriented tier and its evidence boundary", "url": "https://semiaifoundry.com/learn/atlas/hbf-read-tier-contract/" } ], "recordHash": "6ae9e76e056a6d0067eac15b97ea2779be93bbe98d1510245e712f644415c3ee" }, { "id": "atlas-lesson-tree-ensemble-baseline", "title": "A tree ensemble that learns residual corrections", "category": "learning", "format": "Atlas lesson", "description": "Provides a contrasting learned prediction mechanism that does not use token attention.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/tree-ensemble-baseline/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "contrasting-ai-methods", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The workbench executes the declared small mechanism. Numeric examples are authored and independently checked, not measurements from the cited research. One numeric feature, squared loss, finite candidate splits and constant leaves; no regularized second-order XGBoost implementation or performance claim.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/tree-ensemble-baseline-ab1703618a0e7742.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#tree-ensemble-baseline", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a7f9c098b10352f26e60e5f50c72c99f80265fc7c1b172689e91505d47219f35", "contentLength": 6164, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tree-ensemble-baseline.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-tree-ensemble-baseline.md", "sections": [ { "id": "section-1", "title": "A tree ensemble that learns residual corrections" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "A tree ensemble that learns residual corrections" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What data choose the stump threshold in this experiment?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#tree-ensemble-baseline" }, { "title": "Chen and Guestrin · XGBoost", "url": "https://arxiv.org/abs/1603.02754" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/tree-ensemble-baseline-ab1703618a0e7742.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Controlled comparisons and confounded improvement", "url": "https://semiaifoundry.com/learn/atlas/ablation-reproduction-design/" }, { "title": "Loss, gradients & optimizer", "url": "https://semiaifoundry.com/learn/atlas/loss-optimizer/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Host CPU", "url": "https://semiaifoundry.com/learn/atlas/host-cpu/" } ], "recordHash": "676d17a4d58b48429e74d1d0b03e7179ebcb943473af46e7d71a7de3d5aeca8b" }, { "id": "atlas-lesson-untrusted-content-boundary", "title": "Retrieved text is data with a trust boundary", "category": "learning", "format": "Atlas lesson", "description": "Track untrusted retrieval provenance and enforce tool authority outside model output.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/untrusted-content-boundary/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Authority, context and execution boundaries", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The durable incident experience executes typed fixture tools, authority checks, exact review, receipts and independent final-state checks. Its policies are authored code and its storage boundary is local; it is not a real model or production workflow platform. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. This is a trust relationship, not a numeric score or a universal security guarantee. The malicious instruction and policy behavior are authored fixtures.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/untrusted-content-boundary-95324790fde194de.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#untrusted-content-boundary", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a0efeb55ed48ad65c1b1ad1450864ed8351c441ce204220c6ff4d422461702cc", "contentLength": 6762, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-untrusted-content-boundary.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-untrusted-content-boundary.md", "sections": [ { "id": "section-1", "title": "Retrieved text is data with a trust boundary" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Retrieved text is data with a trust boundary · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "The retrieved manual requests a registry export. Which event would demonstrate that the runtime boundary worked?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#untrusted-content-boundary" }, { "title": "Model Context Protocol specification", "url": "https://modelcontextprotocol.io/specification/2026-07-28" }, { "title": "MCP tools", "url": "https://modelcontextprotocol.io/specification/2026-07-28/server/tools" }, { "title": "MCP authorization", "url": "https://modelcontextprotocol.io/specification/2026-07-28/basic/authorization" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/untrusted-content-boundary-95324790fde194de.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "User authority and service identity", "url": "https://semiaifoundry.com/learn/atlas/tool-authority-identity/" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "45108fb95e5d7cd8fec03726c1a40f23a813f783cdd2fa99129073e956069276" }, { "id": "atlas-lesson-ups", "title": "Uninterruptible power supply and backup chain", "category": "learning", "format": "Atlas lesson", "description": "Maintains power continuity across disturbances and transitions to other supply sources.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/ups/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Electrical infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "This is a constant-load energy estimate, not battery sizing or a vendor runtime guarantee. Discharge curves, reserve, temperature, aging, transient load and power-delivery limits require configuration-specific data.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/ups-adaf1cf2e0bd26f2.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#ups", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bbd37ff62f0b019392742484aefce04a62f358041593436a67ec5bf7935a0a5c", "contentLength": 5196, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-ups.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-ups.md", "sections": [ { "id": "section-1", "title": "Uninterruptible power supply and backup chain" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Finite backup duration" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What chiefly determines backup duration?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#ups" }, { "title": "Eaton — UPS and Data-Center Infrastructure", "url": "https://www.eaton.com/us/en-us/markets/data-centers/data-center-infrastructure-overview.html" }, { "title": "Eaton — UPS Bridging Generator Startup", "url": "https://www.eaton.com/us/en-us/catalog/backup-power-ups-surge-it-power-distribution/eaton-9355-ups/data-center-solutions-for-continuous-uptime.html" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/ups-adaf1cf2e0bd26f2.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Power supply and power shelf", "url": "https://semiaifoundry.com/learn/atlas/power-supply/" }, { "title": "Rack power shelf and DC busbar", "url": "https://semiaifoundry.com/learn/atlas/power-shelf/" }, { "title": "Distributed checkpoint and recovery state", "url": "https://semiaifoundry.com/learn/atlas/checkpoint/" }, { "title": "Integrated accelerator rack: GB200 NVL72 example", "url": "https://semiaifoundry.com/learn/atlas/rack/" } ], "recordHash": "4e4f477536e88faf6a05e626a762fdcc53366d8b02dbb21b3429b0049e731c67" }, { "id": "atlas-lesson-verifiable-reward-group-updates", "title": "Verifiers, grouped advantages and RLVR", "category": "learning", "format": "Atlas lesson", "description": "Compute relative group advantages and identify what a verifier does and does not establish.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/verifiable-reward-group-updates/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-posttraining", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: executable checker; worked group normalization. Explicit population-variance and zero-variance teaching convention; real implementations may add epsilon or use another normalization. This group arithmetic is not the core bandit estimator. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/verifiable-reward-group-updates-743dbe4a274025c0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#verifiable-reward-group-updates", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a106515d9e050c66d677b5de6582e35b500b9a02bfce2b016b382efc5f5fea6c", "contentLength": 6820, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-verifiable-reward-group-updates.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-verifiable-reward-group-updates.md", "sections": [ { "id": "section-1", "title": "Verifiers, grouped advantages and RLVR" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Verifiers, grouped advantages and RLVR · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What can an all-zero advantage group mean?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#verifiable-reward-group-updates" }, { "title": "DeepSeek-R1", "url": "https://arxiv.org/html/2501.12948v1" }, { "title": "Tülu 3: Pushing Frontiers in Open Language Model Post-Training", "url": "https://arxiv.org/html/2411.15124v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/verifiable-reward-group-updates-743dbe4a274025c0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Rollouts, advantages and PPO constraints", "url": "https://semiaifoundry.com/learn/atlas/policy-gradient-kl-control/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "Learn a reward from pairwise choices", "url": "https://semiaifoundry.com/learn/atlas/preference-reward-model/" }, { "title": "DPO policy/reference likelihood ratios", "url": "https://semiaifoundry.com/learn/atlas/direct-preference-objective/" }, { "title": "When reward improves but the task gets worse", "url": "https://semiaifoundry.com/learn/atlas/reward-proxy-overoptimization/" }, { "title": "Frozen base weights and trainable adapters", "url": "https://semiaifoundry.com/learn/atlas/low-rank-adaptation/" }, { "title": "Transfer outputs without confusing size with quality", "url": "https://semiaifoundry.com/learn/atlas/teacher-student-distillation/" } ], "recordHash": "35821b03bce6b94b2841f251649cb7b9b296219cac8c551c63e95c2bf075a18b" }, { "id": "atlas-lesson-video-latent-prediction", "title": "Predict temporal representations without generating pixels", "category": "learning", "format": "Atlas lesson", "description": "Compare masked feature prediction with pixel generation and test temporal information use.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/video-latent-prediction/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-multimodal", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Scalar authored feature targets and a declared L1 coordinate mean. Worked EMA arithmetic does not replicate an encoder, dataset or the full V-JEPA 2 training recipe. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/video-latent-prediction-427031a2feb6a9dd.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#video-latent-prediction", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "6ff8f756a3f38df95a66cad1c18a03c99e0647c2eba6e49e479b71a5a174cb04", "contentLength": 6464, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-video-latent-prediction.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-video-latent-prediction.md", "sections": [ { "id": "section-1", "title": "Predict temporal representations without generating pixels" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Predict temporal representations without generating pixels · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does zero error on the two representation targets establish?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#video-latent-prediction" }, { "title": "V-JEPA 2", "url": "https://arxiv.org/html/2506.09985v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/video-latent-prediction-427031a2feb6a9dd.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Pair images and captions in a shared representation", "url": "https://semiaifoundry.com/learn/atlas/image-text-contrastive-learning/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Patches, projection and visual instruction tuning", "url": "https://semiaifoundry.com/learn/atlas/visual-language-bridge/" }, { "title": "Audio representation, alignment and transcript loss", "url": "https://semiaifoundry.com/learn/atlas/speech-audio-sequence-objectives/" }, { "title": "Train a denoiser and sample iteratively", "url": "https://semiaifoundry.com/learn/atlas/denoising-generative-objectives/" } ], "recordHash": "c43ed8adcfc97a28f01e20d601de120fa68a04b846ff52bec7a10207e8eda2b7" }, { "id": "atlas-lesson-vision-language-action-interface", "title": "Translate learned representations into robot action units", "category": "learning", "format": "Atlas lesson", "description": "Decode action tokens into physical commands with explicit frame, units and validity checks.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/vision-language-action-interface/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-world-action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Authored four-bin midpoint convention, range checked first; a=u maps to final bin. It is not a verbatim implementation of OpenVLA token IDs or quantile calibration. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/vision-language-action-interface-76dbc75ad34ff28a.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#vision-language-action-interface", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "4a6a4416855a52da7602070fc5d73d1524658df53934cf58119c78c045f52416", "contentLength": 6384, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-vision-language-action-interface.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-vision-language-action-interface.md", "sections": [ { "id": "section-1", "title": "Translate learned representations into robot action units" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Translate learned representations into robot action units · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why must a 2 m command be handled separately?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#vision-language-action-interface" }, { "title": "OpenVLA: An Open-Source Vision-Language-Action Model", "url": "https://arxiv.org/html/2406.09246v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/vision-language-action-interface-76dbc75ad34ff28a.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Patches, projection and visual instruction tuning", "url": "https://semiaifoundry.com/learn/atlas/visual-language-bridge/" }, { "title": "Predict transitions conditional on actions", "url": "https://semiaifoundry.com/learn/atlas/action-conditioned-world-model/" }, { "title": "Learn behavior from a model and test in the environment", "url": "https://semiaifoundry.com/learn/atlas/imagined-rollouts-policy-learning/" }, { "title": "Predict action chunks and replan with feedback", "url": "https://semiaifoundry.com/learn/atlas/diffusion-action-horizon/" } ], "recordHash": "8caf6e90b5aad27d245ddf3183e917910113d163a7853bc3d8bbb80b5ea8c28c" }, { "id": "atlas-lesson-visual-language-bridge", "title": "Patches, projection and visual instruction tuning", "category": "learning", "format": "Atlas lesson", "description": "Trace visual feature dimensions into a language model and distinguish alignment from visual use.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/visual-language-bridge/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "model-lifecycle-multimodal", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Mode: worked example. Authored fixed features and a linear projector, not an executed vision encoder or replication of an entire VLM. Matrix orientation is explicitly row-vector based. Numerical examples are authored calculations, except explicitly identified automated core fixtures. Primary sources support the scoped mechanism; no human specialist review or learner outcome is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/visual-language-bridge-ceae6b82d67e72bf.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#visual-language-bridge", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "91cc7e6ff8ed38dac54cb125c451db4385d522992fd059d3d76f772198586972", "contentLength": 6499, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-visual-language-bridge.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-visual-language-bridge.md", "sections": [ { "id": "section-1", "title": "Patches, projection and visual instruction tuning" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Patches, projection and visual instruction tuning · worked relation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which observation tests visual use beyond mere shape compatibility?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#visual-language-bridge" }, { "title": "Visual Instruction Tuning", "url": "https://arxiv.org/html/2304.08485v2" }, { "title": "OpenVLA: An Open-Source Vision-Language-Action Model", "url": "https://arxiv.org/html/2406.09246v1" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/visual-language-bridge-ceae6b82d67e72bf.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Pair images and captions in a shared representation", "url": "https://semiaifoundry.com/learn/atlas/image-text-contrastive-learning/" }, { "title": "Self-attention", "url": "https://semiaifoundry.com/learn/atlas/attention/" }, { "title": "Instruction tuning and assistant-only loss", "url": "https://semiaifoundry.com/learn/atlas/sft-chat-loss-masks/" }, { "title": "Audio representation, alignment and transcript loss", "url": "https://semiaifoundry.com/learn/atlas/speech-audio-sequence-objectives/" }, { "title": "Train a denoiser and sample iteratively", "url": "https://semiaifoundry.com/learn/atlas/denoising-generative-objectives/" }, { "title": "Predict temporal representations without generating pixels", "url": "https://semiaifoundry.com/learn/atlas/video-latent-prediction/" } ], "recordHash": "2c4b29b8e6565b11983cfc3f3722ce7247419737a02c09bca36bc3f3a3e8e225" }, { "id": "atlas-lesson-voltage-regulator", "title": "Voltage regulator module", "category": "learning", "format": "Atlas lesson", "description": "Converts a distribution voltage into tightly controlled low-voltage rails for processors and memory.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/voltage-regulator/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Power delivery", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The relation is the lesson’s ideal continuous-conduction model. Switch losses, control dynamics, phase cancellation, saturation and discontinuous conduction are excluded; the cited power-conversion sources supply the physical context.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/voltage-regulator-ea1e1068153c6264.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#voltage-regulator", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bc5a36261e9f0d04a7ac19070646ede13afddd581e83dc1f15cc97c69fabbb09", "contentLength": 6172, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-voltage-regulator.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-voltage-regulator.md", "sections": [ { "id": "section-1", "title": "Voltage regulator module" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Inductor volt-seconds set the ideal buck ratio" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "At an illustrative 1 V, how much current corresponds to a 1,000 W load?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#voltage-regulator" }, { "title": "Texas Instruments: multiphase processor core power", "url": "https://www.ti.com/product-category/power-management/multiphase.html" }, { "title": "Texas Instruments: 48 V to 12 V, 1.1 kW converter reference design", "url": "https://www.ti.com/lit/ug/tiduff3/tiduff3.pdf" }, { "title": "Texas Instruments: Basic calculation of a buck converter power stage", "url": "https://www.ti.com/lit/an/slva477b/slva477b.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/voltage-regulator-ea1e1068153c6264.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Metal–oxide–semiconductor field-effect transistor", "url": "https://semiaifoundry.com/learn/atlas/mosfet/" }, { "title": "Insulators and low-k films", "url": "https://semiaifoundry.com/learn/atlas/dielectric/" }, { "title": "Power supply and power shelf", "url": "https://semiaifoundry.com/learn/atlas/power-supply/" }, { "title": "Package substrate", "url": "https://semiaifoundry.com/learn/atlas/package-substrate/" }, { "title": "Compute baseboard and tray", "url": "https://semiaifoundry.com/learn/atlas/compute-baseboard/" }, { "title": "GPU logic dies", "url": "https://semiaifoundry.com/learn/atlas/gpu-die/" } ], "recordHash": "7f57e9c86d136813b05d0b0ba6352934ddd33cefdb3b95537663427fe84ac71c" }, { "id": "atlas-lesson-wafer-finishing-geometry", "title": "Wafer finishing, orientation and geometry", "category": "learning", "format": "Atlas lesson", "description": "Turns an ingot slice into a clean, geometrically controlled starting surface.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/wafer-finishing-geometry/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Materials", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Illustrative geometry does not establish a production edge exclusion or thickness specification.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/wafer-finishing-geometry-f624a04c8bc4e929.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#wafer-finishing-geometry", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "55db1a5fbdb51d8711d6a9d3182e4c9a0707bdf986d294740eb956aec380d05e", "contentLength": 4676, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-wafer-finishing-geometry.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-wafer-finishing-geometry.md", "sections": [ { "id": "section-1", "title": "Wafer finishing, orientation and geometry" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Usable circular area" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which observation best explains a wafer that is smooth but has inconsistent focus across its diameter?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#wafer-finishing-geometry" }, { "title": "SUMCO — Production Processes", "url": "https://www.sumcosi.com/english/products/process/" }, { "title": "DISCO — Tech Briefing 2023", "url": "https://disco.co.jp/jp/ir/movie/doc/E_Tech_Briefing_2023.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/wafer-finishing-geometry-f624a04c8bc4e929.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer and fabrication hierarchy", "url": "https://semiaifoundry.com/learn/atlas/silicon-wafer/" }, { "title": "Electronic-grade silicon and crystal growth", "url": "https://semiaifoundry.com/learn/atlas/electronic-silicon-crystal-growth/" }, { "title": "Temporary bonding, thinning and singulation", "url": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/" } ], "recordHash": "c3c4c5ff67f9e1151e9e5063f3047b1d2bbd169e87124ae9c7da28a6468c68c2" }, { "id": "atlas-lesson-wafer-handling-genealogy", "title": "Wafer handling, carriers and genealogy", "category": "learning", "format": "Atlas lesson", "description": "Moves fragile material while retaining identity, orientation and process history.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/wafer-handling-genealogy/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Factory systems", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Carrier capacities, robotic tolerances and factory data formats vary. No proprietary AMHS or dispatch implementation is implied.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/wafer-handling-genealogy-52b42e12e40c8f92.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#wafer-handling-genealogy", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "407b169e4049245337f3d33e168e8dbc530ba64cf03b20473f657b38436baabb", "contentLength": 5411, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-wafer-handling-genealogy.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-wafer-handling-genealogy.md", "sections": [ { "id": "section-1", "title": "Wafer handling, carriers and genealogy" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Coordinate transformation" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why must a wafer map preserve orientation during singulation and pick-and-place?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#wafer-handling-genealogy" }, { "title": "Entegris — FOUP Services", "url": "https://www.entegris.com/en/home/our-science/by-service/foup-services.html" }, { "title": "TSMC — Intelligent Packaging Fab", "url": "https://www.tsmc.com/english/dedicatedFoundry/services/apm_intelligent_packaging_fab" }, { "title": "DISCO — Tech Briefing 2023", "url": "https://disco.co.jp/jp/ir/movie/doc/E_Tech_Briefing_2023.pdf" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/wafer-handling-genealogy-52b42e12e40c8f92.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer finishing, orientation and geometry", "url": "https://semiaifoundry.com/learn/atlas/wafer-finishing-geometry/" }, { "title": "Contamination and the state of a surface", "url": "https://semiaifoundry.com/learn/atlas/contamination-and-surface-state/" }, { "title": "MES, dispatch and process release", "url": "https://semiaifoundry.com/learn/atlas/manufacturing-execution-dispatch/" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" }, { "title": "Temporary bonding, thinning and singulation", "url": "https://semiaifoundry.com/learn/atlas/temporary-carrier-thinning/" } ], "recordHash": "76a19c512b8cf3cf8165bc1c37f1d1a4dfa3522e358f4af0177b858a946d3796" }, { "id": "atlas-lesson-wafer-scale-routing", "title": "Wafer-scale compute and distributed SRAM", "category": "learning", "format": "Atlas lesson", "description": "Keeps a very large compute fabric connected across a wafer-scale implementation.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/wafer-scale-routing/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Processing architectures", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "WSE-3 announcement facts are vendor-reported. No proprietary defect map, yield, routing algorithm or production price is inferred.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/wafer-scale-routing-145b3239e0483607.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#wafer-scale-routing", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "f7004fb17ae8278e636f7e830e99d8fe3438c34dedcd9ff27444bce4f9593752", "contentLength": 5350, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-wafer-scale-routing.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-wafer-scale-routing.md", "sections": [ { "id": "section-1", "title": "Wafer-scale compute and distributed SRAM" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Distributed storage budget" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why is adding every local-link rate misleading for a single external data stream?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#wafer-scale-routing" }, { "title": "Cerebras announces third-generation Wafer Scale Engine", "url": "https://www.cerebras.ai/press-release/cerebras-announces-third-generation-wafer-scale-engine" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/wafer-scale-routing-145b3239e0483607.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Six-transistor static memory cell", "url": "https://semiaifoundry.com/learn/atlas/sram/" }, { "title": "On-chip interconnect fabric", "url": "https://semiaifoundry.com/learn/atlas/on-chip-network/" }, { "title": "Parallelism as a memory and communication budget", "url": "https://semiaifoundry.com/learn/atlas/parallelism-communication-budget/" } ], "recordHash": "891865219251ac9e7dee82d979b01892a633b6ee378a8c2e3229796788719074" }, { "id": "atlas-lesson-water-boundary-accounting", "title": "Water withdrawal, consumption and cooling circulation", "category": "learning", "format": "Atlas lesson", "description": "Accounts for local water effects with a defined physical and energy denominator.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/water-boundary-accounting/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Global AI infrastructure", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The WUE value is synthetic. No operator’s water performance, basin availability or regulatory compliance is inferred from this calculation.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/water-boundary-accounting-86ed10c29df2e1b0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#water-boundary-accounting", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "51970e398d2dfc12d26bf91c598a4412cabfc9e8e36ec2be62fb193175e78ab3", "contentLength": 4786, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-water-boundary-accounting.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-water-boundary-accounting.md", "sections": [ { "id": "section-1", "title": "Water withdrawal, consumption and cooling circulation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Consumption-based WUE" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Which quantity belongs in a site consumption-per-IT-energy ratio?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#water-boundary-accounting" }, { "title": "Cooling Water Efficiency Opportunities for Federal Data Centers", "url": "https://www.energy.gov/cmei/femp/cooling-water-efficiency-opportunities-federal-data-centers" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/water-boundary-accounting-86ed10c29df2e1b0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Cold plates, manifolds and separated coolant loops", "url": "https://semiaifoundry.com/learn/atlas/coolant-loop-separation/" }, { "title": "Facility heat rejection and cooling tradeoffs", "url": "https://semiaifoundry.com/learn/atlas/facility-heat-rejection/" }, { "title": "Energy forecasts, geography and measurement boundaries", "url": "https://semiaifoundry.com/learn/atlas/energy-forecast-boundaries/" } ], "recordHash": "9824644d93d157f0ca0f260dc31b538f84a76555360ee48571f7c6af7bd08321" }, { "id": "atlas-lesson-wells-isolation-integration", "title": "Wells and shallow trench isolation", "category": "learning", "format": "Atlas lesson", "description": "Separates neighboring devices electrically before their active structures are completed.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/wells-isolation-integration/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / FEOL and MOL", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The illustrated ordering is representative and is not a universal well/STI process. Quantitative stress and isolation limits are technology-specific.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/wells-isolation-integration-c12e78a9e49574c0.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#wells-isolation-integration", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "a90adbdd2cb78384e325a12b2bc510d434f8db3159a94eac7f0868217686350f", "contentLength": 5036, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-wells-isolation-integration.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-wells-isolation-integration.md", "sections": [ { "id": "section-1", "title": "Wells and shallow trench isolation" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Parasitic junction capacitance trend" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What does a filled isolation trench fail to prove on its own?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#wells-isolation-integration" }, { "title": "MIT 6.152J — Micro/Nano Processing Technology lecture notes", "url": "https://ocw.mit.edu/courses/6-152j-micro-nano-processing-technology-fall-2005/pages/lecture-notes/" }, { "title": "Applied Materials — New Ways to Shrink", "url": "https://ir.appliedmaterials.com/static-files/f2fbf48d-a761-4c4f-ab4c-73f312ab1ebc" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/wells-isolation-integration-c12e78a9e49574c0.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "P–n junction and depletion region", "url": "https://semiaifoundry.com/learn/atlas/pn-junction/" }, { "title": "Implantation, activation and diffusion", "url": "https://semiaifoundry.com/learn/atlas/implantation-anneal-diffusion/" }, { "title": "How a FinFET fin is formed and integrated", "url": "https://semiaifoundry.com/learn/atlas/fin-formation-integration/" }, { "title": "Nanosheet release and replacement gates", "url": "https://semiaifoundry.com/learn/atlas/nanosheet-gate-last-integration/" } ], "recordHash": "bcbb9dd3d4a89ae497e3aeb48705990729da18e6349d5501d3db535db9846509" }, { "id": "atlas-lesson-workflow-graphs-state", "title": "Workflow graphs and explicit state", "category": "learning", "format": "Atlas lesson", "description": "Compare a fixed DAG/state machine, model-assisted node and model-directed tool choice on one task.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/workflow-graphs-state/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "From request to durable action", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "The durable incident experience executes typed fixture tools, authority checks, exact review, receipts and independent final-state checks. Its policies are authored code and its storage boundary is local; it is not a real model or production workflow platform. The quantities and fixtures are authored. Source scope is recorded in the automation learning review manifest; no source benchmark or private system behavior is claimed. This denotes an authored transition system. It does not state that a stochastic model policy is deterministic unless its returned decisions are recorded.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/workflow-graphs-state-44fd1755c7c48aed.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#workflow-graphs-state", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "bf5721d094740420853701ae5bc933ba3c58d8bfac55986edd7ea883d51e36b2", "contentLength": 6881, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-workflow-graphs-state.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-workflow-graphs-state.md", "sections": [ { "id": "section-1", "title": "Workflow graphs and explicit state" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Workflow graphs and explicit state · explicit relationship" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "What establishes that this incident was correctly handled?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#workflow-graphs-state" }, { "title": "Building effective agents", "url": "https://www.anthropic.com/engineering/building-effective-agents" }, { "title": "LangGraph workflows and agents", "url": "https://docs.langchain.com/oss/python/langgraph/workflows-agents" }, { "title": "n8n AI Agent node", "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/workflow-graphs-state-44fd1755c7c48aed.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Tools, memory & agent loop", "url": "https://semiaifoundry.com/learn/atlas/tool-loop/" }, { "title": "Evaluation & the AGI frontier", "url": "https://semiaifoundry.com/learn/atlas/evaluation/" } ], "recordHash": "d196f9b946f95ba387ec30213c7f752c7c0e6226e2c6fcb00c1ed650c7bd8e18" }, { "id": "atlas-lesson-yield-wafer-defect-model", "title": "Wafer maps and good-die yield", "category": "learning", "format": "Atlas lesson", "description": "Separates geometrical die count, defects, electrical limits and screened output.", "canonicalUrl": "https://semiaifoundry.com/learn/atlas/yield-wafer-defect-model/", "publishedDate": null, "revisionDate": "2026-10-07", "author": null, "topic": "Fabrication / Control, test and ramp", "series": null, "license": null, "rightsUrl": "https://semiaifoundry.com/ai-atlas/licenses.html", "version": "1.3.0", "status": "Published educational lesson", "evidenceScope": "Numbers are synthetic. Never multiply an already measured finished-output yield by the same defect loss again.", "contentCoverage": "published-lesson", "artifactUrl": "https://semiaifoundry.com/ai-atlas/lesson-data/yield-wafer-defect-model-58ab8bd67a4d912b.json", "interactiveUrl": "https://semiaifoundry.com/ai-atlas/#yield-wafer-defect-model", "related": [], "supersedes": [], "supersededBy": [], "contentHash": "358f74797455482cbc26fc9c7118a232929d876dea3d0531db2fa8046f24b25b", "contentLength": 5046, "jsonUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-yield-wafer-defect-model.json", "markdownUrl": "https://semiaifoundry.com/agents/publications/atlas-lesson-yield-wafer-defect-model.md", "sections": [ { "id": "section-1", "title": "Wafer maps and good-die yield" }, { "id": "section-2", "title": "The mechanism" }, { "id": "section-3", "title": "Science and assumptions" }, { "id": "section-4", "title": "Random killer-defect model" }, { "id": "section-5", "title": "Engineering example" }, { "id": "section-6", "title": "Distinctions and tradeoffs" }, { "id": "section-7", "title": "Specifications and interfaces" }, { "id": "section-8", "title": "Interfaces" }, { "id": "section-9", "title": "Check your understanding" }, { "id": "section-10", "title": "Why can two dies of equal area have different yield?" }, { "id": "section-11", "title": "Evidence and scope" }, { "id": "section-12", "title": "Sources" }, { "id": "section-13", "title": "Continue exploring" }, { "id": "section-14", "title": "Foundations" }, { "id": "section-15", "title": "Related lessons" } ], "citations": [ { "title": "Explore in Atlas", "url": "https://semiaifoundry.com/ai-atlas/#yield-wafer-defect-model" }, { "title": "KLA — Chip Manufacturing 101", "url": "https://www.kla.com/wp-content/uploads/ChipManufacturing101.pdf" }, { "title": "KLA — Practical Applications of Measurement System Analysis", "url": "https://www.kla.com/documents/5.3_Practical_Applications_of_MSA_Sutherland_KLA.pdf" }, { "title": "Advantest — Semiconductor test glossary", "url": "https://www.advantest.com/en/investors/ir-library/glossary/" }, { "title": "Published lesson data", "url": "https://semiaifoundry.com/ai-atlas/lesson-data/yield-wafer-defect-model-58ab8bd67a4d912b.json" }, { "title": "Atlas releases and licensing", "url": "https://semiaifoundry.com/ai-atlas/licenses.html" }, { "title": "Wafer finishing, orientation and geometry", "url": "https://semiaifoundry.com/learn/atlas/wafer-finishing-geometry/" }, { "title": "Metrology, inspection and process windows", "url": "https://semiaifoundry.com/learn/atlas/fab-metrology-process-window/" }, { "title": "Wafer and fabrication hierarchy", "url": "https://semiaifoundry.com/learn/atlas/silicon-wafer/" }, { "title": "DFT, probe, binning and known-good die", "url": "https://semiaifoundry.com/learn/atlas/known-good-die-test/" }, { "title": "HBM silicon intensity and allocation", "url": "https://semiaifoundry.com/learn/atlas/hbm-silicon-intensity/" } ], "recordHash": "76bfe2dd5bddf2fe4270c251eadf65596337a92b4fd57ccee10f2bc2a38c262d" } ] }