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0:54ENSam Altman: Seek Major Life Advice From People, Not AISam Altman · OpenAIThe OpenAI CEO distinguishes practical AI assistance from consequential life advice and argues for assistants that can push back.
34:11ENAnatoliy Bilenko and Alberto Carretero: Making Database Protocols Reliable with Formal Methods and AIAnatoliy Bilenko, Alberto Carretero · CanonicalCanonical’s database engineers connect executable specifications, model-based tests, failure exploration, and reconstructed execution histories—and explain why none of these techniques proves a real system correct on its own.
1:03:37ENMatthew Berman’s Team Tests Kimi K3.1 on Animation, Games, and ChartsMatthew Berman, Alex, Brian · Forward FutureA live team AMA turns into an informal test of Kimi K3.1, from personal-agent workflows to motion graphics, a browser game, and a benchmark chart.
1:43:22ENAI Security, Investment and the Debate Over France’s FutureGast: Nikesh Arora · Moderation: Jason Calacanis, Chamath Palihapitiya, David FriedbergThe All-In hosts and Nikesh Arora discuss cybersecurity and AI spending, then debate France’s unrest, public services and US policy.
34:35ENSemiAnalysis on ASML's Hybrid-Bonding Patents, HBM Economics and the Next Tool EcosystemGast: Sherry Zhang, Howie · Moderation: 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 BuildoutGast: Andy Jassy · Moderation: 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?Gast: Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · Moderation: 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.
28:15ENSteve Poole on Open-Source Security and AI’s Maintenance ChallengeOlimpiu Pop, Steve PooleWhy faster vulnerability discovery increases pressure on maintainers, dependency users and upgrade processes.
29:22ENTheo on Security Vulnerabilities, Stolen API Keys and AITheo Browne · Ping LabsA look at the gap between vulnerability disclosure and patching, and a speculative account of why stolen inference keys may be valuable.
59:41EN20VC: Venture Fund Size, AI Valuations and the Changing Software MarketGast: Jason Lemkin, Rory O’Driscoll · Moderation: Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O'Driscoll debate venture concentration, infrastructure risk, code review and the assumptions behind fast-growing AI companies.
1:25:33ENWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, ModalGast: Erik Bernhardsson · Moderation: 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.
57:47ENPeter Thiel on AI Acceleration, Global Power, and the Values of Its BuildersGast: Peter Thiel · Moderation: Walter IsaacsonWalter Isaacson challenges Peter Thiel on AI risk, concentrated power, and the moral responsibilities of visionary founders. Thiel argues that stopping progress carries dangers of its own.
26:41ENAnekha Sokhal on Moshi, a Recommendation Engine for Commodity TradersGast: Anekha Sokhal · Moderation: 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.
0:53ENSam Altman on AI and the Discovery of New KnowledgeSam Altman · OpenAIAltman expects progress in mathematical discovery to extend to biology, materials and energy.
3:13:44ENAI’s Physical Bottlenecks: Compute Markets, Chip Investments and Agent TrustGast: Evan Conrad, Lonis Hamaili · Moderation: Nathan Labenz, Prakash NarayananA full AI:AM discussion of security incidents, GPU financing, semiconductor supply and an agent-to-agent network.
47:43ENDesigning Beyond AI Defaults: Magic Patterns and Website ReviewsAaron Epstein, Alex Danilowicz · Y CombinatorAlex Danilowicz and Aaron Epstein discuss prototypes, context and clearer startup sites.
1:00:34ENMarc Andreessen, Chris Dixon and Ben Horowitz on AI and the Frontier for FoundersGast: Chris Dixon, Marc Andreessen, Ben Horowitz · Moderation: Erik TorenbergThe a16z partners explain their expanded Frontier mandate and why they think AI is widening the possibilities for entrepreneurs, open models and new media.
40:00ENArvind Krishna and Nikesh Arora on Quantum Risk, AI Models and Software ConsolidationGast: Arvind Krishna, Nikesh AroraThe executives discuss post-quantum preparation, the economics of open-weight models and the changing shape of enterprise cybersecurity.
2:40:58ENFrontier AI, Interpretability and the Fight Over Its PaceGast: Zvi Mowshowitz · Moderation: Nathan Labenz, Prakash NarayananZvi Mowshowitz joins AI:AM to discuss neural networks, policy and the institutions facing rapid change.
13:21ENAdrian Twarog: Giving Enterprise Vibe Coding a Governed Path to ProductionAdrian TwarogA Superblocks walkthrough shows how shared integrations, isolated databases, policy agents and audit logs can bring business-built AI apps under IT oversight.
25:55ENAI Access, Software Economics and the Question of PersistenceModeration: Reid Hoffman, Aria FingerReid Hoffman and Aria Finger discuss software replication and a reported study of AI assistance.
17:42ENIs a Faster Model Actually Faster? Measure the Finished Job, Not the TokensMorgan Suo · MiniMaxMiniMax's Morgan Suo takes the engineering changes inside M3.1 Flash one by one and asks the question that matters to users: does the job an analyst needs actually get done sooner, cheaper and correctly?
43:33ENInside Tenex: AI-Native Engineering, Incentives and Enterprise AdoptionGast: Alex Lieberman, CJ Hess · Moderation: swyxAlex Lieberman and CJ Hess describe their engineering model.
0:44ENSam Altman and Matthew Berman on AI, Work and BusynessMatthew Berman, Sam Altman · Forward FutureIn a short conversation, they consider why technology has not necessarily given people more free time.
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