Topic
AI Infrastructure
20VC: Will OpenRouter Sell for $10BN to Stripe? | Why Chinese Open Models Are Beating America—and What Happens Next | Why Enterprises Are More Fearful of Anthropic and OpenAI Than China | Is the Routing Layer Becoming a Commodity with Alex Atallah
Alex Atallah argues OpenRouter is building a durable routing layer for a fast-changing, multi-model AI market, not a commodity middleware business. He also says US open models are lagging China, but enterprises fear frontier-model data policies more than Chinese models, and OpenRouter’s value grows as switching, failover, and safety become more important.
Google's AI Brain Drain, SpaceX's Huge Quarter, Airtable's 90% Collapse, US Data Fuels China AI
The episode centers on three big AI/infrastructure stories: Google’s AI leadership shakeup, SpaceX’s blockbuster quarter, and what Airtable’s sale says about SaaS under AI pressure. The panel also debates whether U.S. data-labeling firms are accelerating China’s AI catch-up.
![Artwork for Gavin Baker - AI Market Jitters - [Invest Like the Best, EP.485]](https://megaphone.imgix.net/podcasts/c8fca7de-8f77-11f1-ae96-ab857574605f/image/e34471e6c9b4af0375abbd710ff0fa11.jpg?ixlib=rails-4.3.1&max-w=3000&max-h=3000&fit=crop&auto=format,compress)
Gavin Baker - AI Market Jitters - [Invest Like the Best, EP.485]
Gavin Baker argues the July selloff in AI stocks disconnected public-market prices from improving fundamentals, with GPU availability, rental pricing, token demand, and hyperscaler operating cash flow all moving higher. He says the biggest risk is regulation, while long-term compute demand could still be enormous if AI monetization, open-source dynamics, and new infrastructure financing models keep compounding.
How Retimers Built an $80B Company: The Story of Astera Labs
Astera Labs built a huge business by solving a mundane but critical problem: keeping high-speed copper links alive inside AI servers with retimers. The episode explains the engineering behind PCIe signal conditioning, then follows Astera from Hopper/H100 wins into switches, cables, and CXL.
Jim Chanos: The Math Ain’t Mathing for the AI Data Center Build
Jim Chanos argues the AI/data-center boom is being financed with too much debt and equity against uncertain returns, while the market is rewarding narratives more than economics. He sees extreme stock dispersion, rising speculation, and a growing gap between long-duration assets and short-term spot pricing.
OpenAI’s Compute Chief: We Can’t Build Fast Enough | Sachin Katti
Sachin Katti says OpenAI is racing to build compute faster than the physical world can supply power, chips, cooling, and labor. He frames AI data centers as giant liquid-cooled factories turning electrons into tokens, with custom silicon, new power infrastructure, and networking all becoming strategic bottlenecks.
Andrew Feldman on Building a Chip 58x Larger Than Nvidia's
Andrew Feldman says AI demand is outrunning supply, making chips, memory, data centers, and power infrastructure the new bottlenecks. He argues inference is the immediate battleground, defends Cerebras’ giant wafer-scale approach, and frames AI’s biggest upside as breakthroughs in medicine and personalized education.
Open Source Wins, AGI Is Here, and Scorsese's AI Toolkit with CEOs of Cerebras & Black Forest Labs
All-In’s episode covers the AI infrastructure boom, arguing that demand for inference and reasoning compute is already booked and that the buildout is reaching city-scale power levels. It then shifts to open source, model sovereignty, safety, and Black Forest Labs’ multimodal generative video work, including AI-assisted creative workflows for film and robotics.
Re-engineering the Semiconductor Supply Chain with Intel CEO Lip-Bu Tan
Intel CEO Lip-Bu Tan lays out a turnaround centered on culture, faster decisions, and balance-sheet repair, while arguing that AI is making CPUs, advanced packaging, and full-stack systems more important. He also frames semiconductor investing as bottleneck hunting and says the industry’s capital intensity increasingly requires government, sovereign, and hyperscale backing.
The Bridge Ep. 9 | Software's on Sale. Is the Correction Over?
Steve Tananbaum argues software valuations have fallen sharply, but the correction may still be only halfway done. He connects that view to a broader philosophy of buying transitions with downside protection, while seeing selective opportunities in stressed, structured, and private credit.
Ep. 015 - DG Matrix Explains 800V DC vs Legacy AC Distribution (Datacenter, Energy) | Jordan Nanos, Jeremie Eliahou Ontiveros, Nicolas Bontigui, Haroon Inam
Haroon Inam of DG Matrix argues that 800V DC is becoming necessary as GPU rack power rises beyond what legacy AC distribution can deliver economically. The episode focuses on why voltage, not current, is the key constraint, and how multiport solid-state transformers could make datacenters more flexible, modular, and future-proof.
![Artwork for Alex Sacerdote - How to Invest Through Technology Cycles - [Invest Like the Best, EP.477]](https://megaphone.imgix.net/podcasts/638034f8-63bb-11f1-8c95-6396d39926c0/image/bf350c0e87fc4d280ef1c0572526d26d.jpg?ixlib=rails-4.3.1&max-w=3000&max-h=3000&fit=crop&auto=format,compress)
Alex Sacerdote - How to Invest Through Technology Cycles - [Invest Like the Best, EP.477]
Alex Sacerdote argues that AI is creating a new technology stack, with Anthropic emerging as his highest-conviction private investment because leading models, enterprise distribution, and coding use cases are starting to compound. He also lays out Whale Rock’s broader S-curve framework for investing in tech, then applies it to AI infrastructure, software disruption, and how his firm uses AI in research.
Ep. 014 - Finding Miscompiles For Fun, Not Profit (AI Infrastructure) | Justin Lebar & Jordan Nanos
Justin Lebar and Jordan Nanos discuss how Lebar found compiler miscompiles using both classic fuzzing and LLM-assisted code review. The episode emphasizes severe x86 and AMDGPU bugs, the difficulty of scaling fuzzers, and the surprising effectiveness—but real cost—of using agents to scan compiler code.
(Preview) SpaceX Hype and the Elon Bargain, Nvidia and the Neoclouds, Q&A on Dropbox, Google, Ferrari Luce Backlash
Ben and Andrew open with a framing of SpaceX as a Musk-style capital engine: a risky, audacious company whose public-market appeal comes from belief as much as current financials. They then move through space data centers, terrestrial stranded-energy compute, Nvidia’s AC segment and neocloud demand, plus lighter but pointed commentary on Dropbox, Google, and the Ferrari Luce backlash.
Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Infrastructure, Capstone Case
OpenAI’s compute lead is becoming an industrial-scale infrastructure problem spanning chips, power, cooling, land, and supply-chain coordination. The episode argues that agentic AI is shifting workloads toward inference, latency, and heterogeneous hardware, while long-term value may move from infra toward platforms and apps.
Stanford CS153 Frontier Systems | The Discipline of Delivering Value per Gigawatt
Amin Vahdat argues that frontier AI infrastructure should be judged by value delivered per gigawatt, not by raw capacity or capex alone. He explains how Google is scaling TPUs, networking, and data centers around reliability, system balance, and long-lead power constraints.