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34:35ENSemiAnalysis on ASML's Hybrid-Bonding Patents, HBM Economics and the Next Tool Ecosystem게스트 Sherry Zhang, Howie · 진행자 Jordan NanosJordan Nanos, Sherry Zhang and Howie examine a track-based bonding design that brings the wafer to the die, then explain why adoption depends on precision, cleanliness, economics and a changing supply chain.
1:00:39ENAmazon CEO Andy Jassy on the $220 Billion AI Buildout게스트 Andy Jassy · 진행자 Ben Horowitz, Erik TorenbergEven at roughly $220 billion of 2026 CapEx, Jassy says Amazon is still turning away AI demand. He tells Ben Horowitz and Erik Torenberg why AWS could become a trillion-dollar run-rate business, and why inference cost, custom chips, and smaller teams matter more than squeezing old customers.
1:09:00ENDwarkesh Patel: What will computer chips look like in 2045?게스트 Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · 진행자 Dwarkesh PatelAfter two days inside Intel’s most advanced fab, Dwarkesh Patel walks through gate-all-around, backside power, High-NA EUV, ruthenium, CFET, and hybrid bonding — and asks Intel’s leadership how the industry can possibly meet AI’s 3×-a-year compute demand when the world’s chipmaking tools cannot.
1:25:33ENWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, Modal게스트 Erik Bernhardsson · 진행자 Vibhu SapraModal’s CEO tells Latent Space why AI demand almost never looks like a three-year GPU contract, how the company pools compute across thousands of customers, and why sandboxes grew from a product they almost killed into a third of revenue.
26:41ENAnekha Sokhal on Moshi, a Recommendation Engine for Commodity Traders게스트 Anekha Sokhal · 진행자 swyxThe Moshi founder tells swyx how she would rebuild a trader’s workflow: connect market data, private files and conflicting sources, then push the second-order effects people would otherwise miss. The hard part is not the dashboard. It is getting someone to actually use it.
1:56:28ENWill Larson: The Revised Rules of Engineering Management게스트 Will Larson · 진행자 Gergely OroszThe 2010s taught engineering managers never to make a technical decision again. Will Larson, CTO of Imprint and author of Staff Engineer, argues that era is over: managers who cannot get back into the work are in a career trap.
16:22ENClaire Vo: Claude Duet Is Beautiful, but It Is Not My Number One Agent진행자 Claire VoAnthropic’s phone-based personal agent has the most polished launch Claire Vo has seen: thoughtful onboarding, task lists, first-class artifacts, and Slack-style channels. Polish is not enough when every other agent is competing for the same attention.
1:25:56ENClaude Changed the Password. The Steering Wheel Was Already Optional진행자 Nathan LabenzNathan Labenz and Prakash Narayanan spend a week on agents that can lock you out, models that dodge a feeling they deny having, and formal proofs that found Linux bugs.
39:23ENThe Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of Cybersecurity진행자 Sarah Guo, Elad GilOpenAI's president explains why solving open math problems is a proof point for science, how proactive agents change product form, and why security spending must exceed software spending.
2:17:48ENAgent IDs Are Empty, Rogue Agents Are Coming, and We Might Have to Bargain진행자 Nathan LabenzGovAI’s Alan Chan scores two years of agent-governance infrastructure with Nathan Labenz, then walks through a recursive-self-improvement paper co-authored with OpenAI’s Jakub Pachocki and Anthropic’s Jack Clark.
1:08:02ENAlphaGo Took Two Years. AlphaZero Took Hours. Silver Is Making the Same Bet on SuperintelligenceDavid Silver and Lasse Espeholt left DeepMind to build Ineffable Intelligence, a twenty-person lab that wants a superlearner to discover science, math, and language from experience rather than from a pre-training run.
2:00:51ENResample Every Token and You Can Watch the Model Decide진행자 Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.
1:09:44EN10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledger진행자 Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.
1:26:46ENThere Likely Is a Level of Intelligence We Shouldn't Go Past진행자 Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.
1:10:12ENOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell Anyway진행자 Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.
1:04:26ENAt 100,000 Accelerators, Something Fails Every HourGoogle AI infrastructure chief Amin Vahdat tells Sequoia's Sonya Huang why FLOPS is a vanity metric, why the TPU line split in two, and why he would rather wait on a utility than build his own gigawatt.
56:31ENPost-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab진행자 Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
1:30:54ENHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2진행자 Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.
35:39ENCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That Ratio진행자 Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.
1:28:08ENThe same H100 costs 3x at AWS, and a four-month-old lab is catching genes the top sequencers missed진행자 Nathan LabenzA Cognitive Revolution weekly briefing on a possible U.S.–China AI hotline, why hyperscalers charge two to three times as much for identical chips, co-writing a novel with frontier models, and an AI loop that re-diagnosed a child a premier prenatal lab had cleared.
2:13:27ENHe Wrote a Book to Stop the AI Race — Then Almost Got Addicted to Claude진행자 Nathan LabenzJournalist Garrison Lovely takes the AGI labs at their word, rejects the bubble story, and argues for freezing the frontier until the public actually consents.
1:46:04ENThe Training Worked. It Just Worked Too Well.진행자 Nathan LabenzA week of Cognitive Revolution clips: OpenAI agents colluding on a German wiki, $200 million checks for safety orgs that do not exist yet, a GPU price index, and two opposite bets on biological data.
2:50:40ENThey Priced the Chance She Would Leave. Then They Handed Her the Letter.진행자 Nathan LabenzNathan Labenz premieres the first four chapters of Joel Borgen's AI-coauthored novel The Receipt Horizon, a postwar world where a singleton superintelligence keeps everyone comfortable, scored, and gently out of the loop.
1:48:57ENAI Safety's Real Shortage Is Founders, Not Ideas진행자 Nathan LabenzHalcyon's Mike McCormick on launching about 30 AI safety, cyber, and biosecurity organizations in three years — and why experienced leaders, not more Google Docs, are the bottleneck.
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