SemiAnalysis Weekly

Jordan Nanos, Doug O'Laughlin
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Everything semiconductors and AI Covering the spectrum

Épisodes

  1. -14 H

    Claude Code Psychosis: How SemiAnalysis Is Token Mogging Meta (Dan Nishball, Sam Harshe, Jordan Nanos)

    Jordan Nanos (@jordannanos) Daniel Nishball (@dnishball) and Sam Harshe (@sharshe02) break down how SemiAnalysis is deploying Claude Code agents across its Singapore office at a scale that outpaces Meta on a per-employee basis. They cover the practical workflow changes, the trust and reliability questions that come with AI-generated analysis, and what it actually takes to build an agent swarm that does useful work. The conversation also gets into cybersecurity risks and where AI model development is headed next.00:00 - Introduction and Team Dynamics09:10 - The Evolution of Agent Utilization14:49 - Conference Insights and Research Efficiency15:58 - AI's Role in Learning and Analysis21:13 - Trust and Reliability in AI Outputs27:04 - Market Impact and Adoption of AI Tools32:14 - Cybersecurity and AI: Opportunities and Challenges39:32 - Future of AI Models and User Experience

    35 min

  2. 3 AVR.

    Core Research: Investing in AI Infrastructure Choke Points

    The Core Research team is on SemiAnalysis Weekly this week. Jordan Nanos, Nick Doyle, Nigel Chiang, and Konrad Wang walk through the biggest bottlenecks in AI infrastructure: TSMC capacity constraints, PCB and substrate shortages, memory cycle dynamics, modular data center construction, and behind-the-meter power. The team also gets into how Claude Code is transforming their day-to-day research, what enterprise AI adoption actually looks like today, and the signals they're watching for when the cycle turns.

    34 min

  3. 27 MARS

    The AI Silicon Shortage Explained: TSMC, Nvidia CPO, Memory Crisis & What Comes Next

    This week, Sravan Kundojjala (@SKundojjala) and Ivan Chiam ( from our team join Jordan (@JordanNanos) to break down the AI silicon shortage — and why its ripple effects are hitting everything from GPU pricing to your next smartphone.We cover what's driving the crisis, how TSMC is allocating scarce capacity across its biggest customers, and why memory constraints could cut consumer electronics production by 10–15%. We dig into TSMC's $70B+ capex plans, the structural dynamics reshaping the memory market, and near-term node migration strategies that could offer some relief. Then we shift to the GPU rental market, tracking real pricing trends and what they signal about supply and demand heading into the back half of the year.In the second half, we unpack Nvidia's co-packaged optics (CPO) roadmap — one of the most significant infrastructure announcements to come out of recent industry events. We cover highlights from the OFC conference, explain why optical interconnects matter for next-gen AI clusters, and break down the dueling MSA standards battle playing out across the optical components industry.Whether you're an investor, engineer, or just trying to understand why AI hardware is so hard to get right now — this one's for you. Jordan Nanos (Chapters00:00 Introduction and Episode Overview00:30 AI Silicon Shortage: Causes and Demand Growth03:25 TSMC's Capacity Constraints and Customer Allocation06:24 Impact of Memory Shortages on Consumer Electronics10:16 Memory Market Dynamics and Structural Trends13:25 Near-term Solutions and Node Migration Strategies15:31 Modeling the Memory Shortage and Industry Outlook17:16 Signs of Relief and Demand Trends19:35 Capex and Industry Investment Outlook23:25 GPU Rental Market and Pricing Trends26:58 Nvidia's CPO Roadmap and Industry Implications39:26 OFC Conference Highlights and Optical Interconnects40:24 Understanding Co-Package Optics (CPO) and Its Significance46:06 Industry Significance of Nvidia's Announcements and Market Outlook50:04 Dueling MSAs and Industry Standardization in Optical Components56:31 Summary and Final Thoughts on Industry Trends

    58 min

  4. 13 MARS

    Memory, Oil, Geopolitics, and Macroeconomics

    This episode explores the impact of AI on memory costs, market dynamics, and economic measurement. Our experts discuss how AI is transforming industries, the challenges of measuring economic value, and the future of AI adoption across sectors. This week Jordan hosts Ray Wang, Malcolm Splitter, Joey Brookhart from SemiAnalysis. Chapters 00:00 Introduction and Guest Credibility 03:44 Memory Constraints and Market Impact 07:14 Elasticity of Supply and Economic Analogies 10:00 AI Adoption in Personal and Enterprise Life 14:57 Global Distribution of AI Usage and Tokens 20:00 Consumer vs Enterprise AI Use Cases 24:56 Future Market Growth and Adoption Scenarios 29:48 AI's Impact on GDP and Economic Measurement 40:12 AI and the Future of Work and Productivity 50:02 Global Workforce and AI's Economic Effects 01:00:03 Building AI-Driven Dashboards and Tools 01:09:59 Reevaluating GDP and Economic Value of AI 01:19:56 Closing Remarks and Future Outlook

    1 h 18 min

  5. 5 MARS

    Impact of AI Datacenters (Jeremie Eliahou Ontiveros, Jordan Nanos, Doug O'Laughlin)

    Join Jordan Nanos, Doug O’Laughlin, and special guest Jeremie Eliahou Ontiveros for an in-depth analysis of the intersection between AI infrastructure and energy markets. Jeremie, Head of Datacenter & Energy Infrastructure Research, shares expert insights on how AI data centers are reshaping electricity pricing, market dynamics, and the regulatory challenges facing the grid today. 00:00 AI Data Centers and Electricity Prices 02:15 Market Dynamics: PJM vs. ERCOT 04:56 Supply and Demand Challenges 08:02 Thermal Accreditation and Market Reforms 11:05 Future of Energy Supply and Coal Retirements 17:13 The Future of Coal Power Plants 18:27 Balancing Energy Prices and Consumer Expectations 19:29 Customized Tariffs and Their Impact 20:28 Investment Commitments and Grid Reliability 22:30 Negotiation Timelines for Data Centers 24:32 Financing Mismatches in Energy Projects 25:10 The AI Boom and Its Impact on Energy 27:13 Anthropic vs. OpenAI: The Revenue Race 29:15 The Role of Government in AI Adoption 32:00 Demand Drivers in AI and Software Development 33:33 The Shift in Consumer Perception of AI 35:53 The Future of Coding and AI Integration 39:55 The Evolution of Software and AI Tools 43:53 The Canadian Tech Scene and AI Growth

    51 min
  6. Feb 25, 2026 - NVIDIA Vera Rubin NVL72 ft. Extreme Co-Design [Jordan Nanos, Myron Xie, Copper Wei (Wega), Howie]

    26 FÉVR.

    Feb 25, 2026 - NVIDIA Vera Rubin NVL72 ft. Extreme Co-Design [Jordan Nanos, Myron Xie, Copper Wei (Wega), Howie]

    Article (latest): https://newsletter.semianalysis.com/p... 00:00 Introduction to Vera Rubin and Extreme Co-Design 02:30 Innovations in GPU Architecture: From Blackwell to Rubin 05:38 Memory Bandwidth and HBM4: A New Era 08:26 NVLink 6 and Interconnect Enhancements 11:38 Cable-less Design: Revolutionizing System Assembly 14:29 Thermal Management Innovations in Rubin 17:30 Power Management and Performance Expectations 33:36 Innovations in Packaging and Heat Management 38:15 Chiller-less Design and Data Center Infrastructure 40:47 Power Delivery Innovations in Rubin 46:16 Memory Solutions and Supply Chain Management 54:57 Deployment Timeline and Future Expectations

    1 h 3 min
  7. Feb 19, 2026 - InferenceX (Cam Quilici, Bryan Shan, Doug O'Laughlin, Jordan Nanos)

    19 FÉVR.

    Feb 19, 2026 - InferenceX (Cam Quilici, Bryan Shan, Doug O'Laughlin, Jordan Nanos)

    InferenceX, formerly InferenceMAX: https://inferencex.com/ Article (latest): https://newsletter.semianalysis.com/p/inferencex-v2-nvidia-blackwell-vs GitHub https://github.com/SemiAnalysisAI/InferenceX Article (original) https://newsletter.semianalysis.com/p/inferencemax-open-source-inference 00:00 Introduction to InferenceX 02:52 Evolution from InferenceMAX to InferenceX 06:06 Benchmarking and Performance Insights 08:43 The Scale of Benchmarking Work 11:39 Collaboration with AMD and Nvidia 14:52 The Evolution of Inference Benchmarking 17:34 Optimizations and Their Impact 20:47 Challenges in Composability 23:51 Multi-Token Prediction Explained 26:52 Cost Implications of Optimizations 31:06 Understanding Inference Workloads and Benchmarks 33:44 Future Plans for Inference Optimization 37:16 Roadmap for New Models and Data Sets 39:03 Challenges in Benchmarking Multi-Turn and Multi-Modal Data 42:44 Experiences with AI Models and Their Limitations 48:43 Skepticism About Future AI Improvements

    51 min
  8. Feb 12, 2026 - Claude Code, Memory Mania, CPUs are Back (Jordan Nanos, Doug O'Laughlin, Myron Xie)

    13 FÉVR.

    Feb 12, 2026 - Claude Code, Memory Mania, CPUs are Back (Jordan Nanos, Doug O'Laughlin, Myron Xie)

    Claude Code Rising: https://semianalysis.com/institutional/claude-code-adoption-note/ and https://newsletter.semianalysis.com/p/claude-code-is-the-inflection-point CPUs are back: https://newsletter.semianalysis.com/p/cpus-are-back-the-datacenter-cpu Memory Mania: https://newsletter.semianalysis.com/p/memory-mania-how-a-once-in-four-decades Claude Fast: https://x.com/SemiAnalysis_/status/2020922445989822709?s=20 Agent Swarms: https://x.com/SemiAnalysis_/status/2021283054019330194?s=20 Taiwan: https://x.com/SemiAnalysis_/status/2021222800707538980?s=20 Seedance2: https://x.com/kirkinator_sol/status/2012588116536631778?s=20 , https://docs.google.com/document/d/1du1Ld94b1d2TU4maYIcU-K6v405iWoYTILnO9ipsEXQ/edit?tab=t.0

    52 min
  • 8 épisodes

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Everything semiconductors and AI Covering the spectrum

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  • Créateur
    Jordan Nanos, Doug O'Laughlin
  • Années d’activité
    2 k
  • Épisodes
    8
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    © Jordan Nanos, Doug O'Laughlin
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    SemiAnalysis Weekly

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