SemiAnalysis Weekly

Jordan Nanos, Doug O'Laughlin

Everything semiconductors and AI Covering the spectrum

  1. -9 h

    Ep. 25 - DYLAN IS HERE, LIVE! | Dylan Patel & Jordan Nanos

    Dylan joins the pod today, recorded live from our SF office. Jordan and Dylan discuss SemiAnalysis's AI spend, the model that escaped during training, AI rollups eating private equity, new accelerators vs NVIDIA, and whether the pod gives away too much information for free.0:00 Cold Open5:25 SA AI Spend9:29 AI Performance Reviews10:40 AI Rollups13:47 The Agent Moment15:28 The Escaped Model18:11 Model Exponential22:52 Compute and Chips30:18 Open Models32:00 ADHD and AI

  2. 9/08

    Ep. 024 - SpaceX's 10GW Plan Drives $300B ARR by 2027 (Datacenter, Energy) | Reyk Knuhtsen, Jeremie Eliahou Ontiveros, Jordan Nanos

    OpenAI and Anthropic are adding close to $30 billion of ARR per month, and the driver is gross margin expansion, not new compute. Jeremie Eliahou Ontiveros (@JeremieEO) and Reyk Knuhtsen (@robotknower) join Jordan Nanos (@JordanNanos) to trace the $100 million per megawatt per year figure from real inference workloads on GB200 and GB300 up through SemiAnalysis simulation. The Google deal prices GB300 capacity near $14 an hour against a $3 average, a premium justified by a 90 day cancellation clause and the ability to turn on megawatts immediately. From there the conversation moves to SpaceX's 10 gigawatt ambition, the sites and supply chain needed to hit it, the permitting playbook, and why Microsoft becomes the largest offtaker. The bull and bear cases both get airtime, followed by a Hugging Face security scare to close. Subscribe for weekly coverage of tokenomics, datacenter energy, and AI compute economics. CHAPTERS: 0:00 – Intro0:47 – The $100M Thesis3:59 – Pricing & Google's Deal10:38 – Training vs Inference13:21 – Sites & Supply Chain20:55 – Permitting Playbook25:40 – Microsoft's Role33:31 – Paying For It41:01 – Bull vs Bear43:29 – Hugging Face Security Scare & Wrap-Up Referenced:SpaceX 10GW in 2027 – Why It's Real, Will Drive $300B ARR for SpaceX, and Why Microsoft Will Be the Largest Offtaker: https://newsletter.semianalysis.com/p/spacex-10gw-in-2027-why-its-real

  3. 7/08

    Ep. 023 - Everyone Leaves Google, Elon Forecasts 1T ARR, Reflecting On GPT-5, Building Personalized Software (Roundtable) | Jon Y, Doug O'Laughlin, Jordan Nanos

    Jeff Dean and the Gemini leads are leaving Google. Jon Y (@asianometry) makes his FIRST appearance to unpack the exodus with Doug O'Laughlin (@fabknowledge) and Jordan Nanos (@JordanNanos). The crew debates the Demis CEO question, whether Google acquired its innovation or invented it, and how the Bell Labs comparison reads once disruption arrives. First engineers who spent thirty-five years in one job now leaving for passion projects.The episode opens by revisiting the 2024 Dwarkesh clip where Jon questioned whether GPT-5 would be any good. Two years later the verdict is mixed: GPT-5 was a dud, 5.2 was ass, but 5.6 is strong and GPT-6, codenamed Doug, is rumored to write well. Then the Chinese transceiver ban, where the West depends on a supply chain China already owns. 00:00 Intro 01:02 Was GPT-5 Good? 05:00 The Transceiver Ban 08:57 Everyone Leaves Google 12:56 Google's L Culture 19:20 Do Legends Matter? 23:44 The Protestant Church 28:44 Elon's $1T Pull-In 30:55 Roll Your Own Software 38:17 Start With Memory

  4. 29/07

    Ep. 022 - Market Drawdown, Historic Bubbles, Funding The Buildout, AI Politics (Doug is Back)

    Doug is back this week!Timestamps:00:00 Market Update07:02 Comparing to Past Bubbles in Taiwan and Korea10:08 Memory Prices, LTAs, and Market Cycles18:11 Future Demand for AI and Model Usage37:40 Scaling Laws and Supply Constraints44:45 Financial and Capital Constraints in Tech Expansion50:57 Geopolitical Risks, Policy Impact, Long Term Outlook

  5. 23/07

    Ep. 021 - The AI Project Trinity: Capital, Offtake, Data Center (Datacenter, Energy) | Dan Nishball, Jordan Nanos, Zane Fong, Kang Wen Cheang

    AI and datacenter CapEx hits $11 trillion cumulatively from 2024 to 2029, and $7.1 trillion of that needs funding, roughly 75% debt financed. Dan Nishball (@dnishball), Zane Fong (linkedin.com/in/zanefongzq), and Kang Wen Cheang (linkedin.com/in/cheangkangwen) sit with Jordan Nanos (@JordanNanos) to break down the AI project Trinity: capital, offtake, and data centers. Today only one deal reliably clears the lending bar, a five-year offtake from an investment-grade hyperscaler. Everything else struggles to finance.The crew explains how NVIDIA backstops are structured, how lenders price GPU loans against them, and what NVIDIA actually does with GPUs it takes back. AI debt financing is on track to become the second-largest US asset-backed market behind the $13 trillion mortgage market. Subscribe for weekly analysis on semiconductors and AI infrastructure. References: https://newsletter.semianalysis.com/p/nvidia-gpu-debt-backstop-unleashes CHAPTERS: 00:00 Intro| 01:23 The $11T Funding Problem 09:12 Startups Can't Get GPUs 11:32 How the Backstop Works 20:26 The Central Bank of AI 21:35 The Bullseye 26:23 CoreWeave Credit Spreads 36:58 APAC Examples 42:41 ClusterMax 48:58 Training vs Inference

  6. 18/07

    Ep. 020 - Anthropic vs OpenAI Usage, Margins, Meta Compute, Future of MSL (Tokenomics) | Crystual Huang, Max Kan, Joey Brookhart, Jordan Nanos

    Coding drives over 70% of lab API revenue, and token austerity policies mostly miss the point. Crystal (@crystalthegg), Max Kan (@maxkan), and Joey Brookhart (@SaasquatchC) break down why blocking teams from Opus saves nothing, while power users at the 99th percentile burn $100k per employee per year. Jordan (@Jordannanos) and the team run break-even math on the Max plans and Anthropic's margins. 00:00 Intro00:53 Token Budgeting: Maxing vs Austerity03:05 Coding Eats the Token Market04:49 The ROI Question06:42 Subscriptions vs API Pricing09:08 Break-Even Math on the Max Plans10:42 Anthropic's Profit Margins12:07 Consumer vs Enterprise Mix16:04 The Two-Horse Race18:45 Codex App vs CLI20:41 Who Comes in Third?23:14 Clawbacks and the SpaceX Playbook26:59 Meta's NeoCloud Backstop29:58 Token-as-a-Service Market Forecast32:03 Hyperscalers vs Inference Startups38:50 MSL and the RL Scaling Law41:58 How to Build a Five-Figure RL Task47:10 Vibe Checks48:13 The $400B Anthropic BetReferenced:TokenBudgeting: Our Conversations with Enterprises on Token Spend: https://newsletter.semianalysis.com/p/tokenbudgeting-our-conversationsMeta Compute: Everyone Wants To Be A Neocloud: https://newsletter.semianalysis.com/p/meta-compute-everyone-wants-to-beAnthropic 3Q26 Profit Over $1B: The Anthropic IPO Financials Sneak Peak: https://newsletter.semianalysis.com/p/anthropic-3q26-profit-over-1b-theThe Future of Meta Superintelligence: A 1 Year Progress Update: https://newsletter.semianalysis.com/p/the-future-of-meta-superintelligenceComplete Launch Kit

  7. 18/07 ·  Bónus

    [Emergency Episode] Moonshot’s Kimi K3 has Arrived! China has a Frontier Model

    A year ago, the big three was OpenAI, Anthropic, and Google. Things have changed.Moonshot's Kimi K3 sits above Gemini on every composite benchmark, and it's open source in 10 days.New episode: what K3 reveals about frontier margins, model sizes, and who's actually still in the game. 00:00 Intro 00:11 Is Kimi K3 the Third Best Model? 04:04 Why Delay the Weights? 05:30 2.8T Parameters and Serving Constraints 06:48 Frontier Margins and the 3x Price Hike 11:10 New Architecture, What Comes Next 14:09 Will Open Source Catch Closed? 19:51 Built for Chinese Accelerators 22:57 The Harness Is the Product 28:49 We're Still Early

  8. 16/07

    Ep. 019 - Inside the STEEL Lab: From Package to Transistor (Teardown Lab) | Afzal Ahmad, Andrew Wagner, Jordan Nanos

    SMIC's N+3 node shrank the M0 layer over 15% and cut SRAM area 10 to 20%, all without EUV. SemiAnalysis built a lab just for that; Andrew Wagner and Afzal Ahmad walk Jordan Nanos (@JordanNanos) through the STEEL teardown of Huawei's Kirin 9030, from package to transistor. They explain die shots, FIB and TEM cross sections, NPU discovery, cell height, and standard cell libraries. Then backside power, GAA, and where SMIC goes next. 00:00 Intro: The STEEL Teardown Lab01:02 What Is a Teardown?02:17 Who Uses Teardown Data03:22 SMIC N+3 and the Kirin 903005:02 Inside the Lab: Sourcing to Silicon09:10 Die Shots Explained12:35 The NPU Discovery15:42 Scaling Without EUV17:57 FIB, SEM, and TEM Cross Sections20:59 Cell Height and Transistor Shrink23:56 Standard Cell Libraries26:22 Export Bans and Huawei's Response27:40 What's Next: Backside Power and GAA32:43 Data Center GPUs and Logic Folding34:28 Closing Thoughts Read More: https://newsletter.semianalysis.com/p/steel-smic-n3-teardown

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Sobre

Everything semiconductors and AI Covering the spectrum

Informação

  • Autoria
    Jordan Nanos, Doug O'Laughlin
  • Anos em atividade
    2026
  • Episódios
    26
  • Classificação
    Explícito
  • Copyright
    © Jordan Nanos, Doug O'Laughlin
  • Site do programa
    SemiAnalysis Weekly

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