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53:44EN
Sequoia Capital· 18 août 2026PodcastThe Biggest Bug in Today’s Models Is That the Weights Never ChangeTuring Award winner Rich Sutton and Khurram Javed founded Oak Lab to build agents that keep learning after they ship — and they call synthetic data a big mistake.AgentsContinual learningReinforcement Learning+3
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Sequoia Capital· 16 juin 2026PodcastThe 25-agent town that became a Fortune 500 decision sandboxOn the day before Valentine's Day in a Stanford simulation, cafe owner Isabella decided to throw a party — no human wrote the plot.AgentsMulti-agent systemsIngénierie d’agents+3
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Sequoia Capital· 18 nov. 2025PodcastFour Months to Drive Tokyo: How Wayve Bet the Company on One End-to-End NetworkWayve CEO Alex Kendall tells Sequoia’s Training Data why AV 2.0 ditches HD maps and hand-written stacks for a foundation model that can adapt to a new car and a new country in weeks.Modèles et entraînementAutonomous DrivingWorld models+3
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Sequoia Capital· 27 mai 2025PodcastA thousand airplanes will never train an AI engineerFormer Airbus CTO Paul Eremenko explains why physical-world engineering still has no coding-AI moment, and how P-1 AI's agent Archie is supposed to get there anyway.AgentsIngénierie d’agentsSynthetic data+3
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Sequoia Capital· 29 avr. 2025PodcastTo Solve All Diseases, Isomorphic Labs Needs a Half-Dozen AlphaFoldsMax Jaderberg on turning DeepMind's game-playing research into a general AI engine for drug design—and why prediction alone cannot search a 10^60 molecular universe.Entreprise et stratégieAI for scienceSynthetic data+3
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Sequoia Capital· 28 janv. 2025PodcastMove 37 looked like a bug. LLMs still need their AlphaZero momentIoannis Antonoglou, from AlphaGo to Reflection AI, on self-play, reliability, and why compute can still buy intelligence.AgentsReinforcement LearningIngénierie d’agents+3
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Sequoia Capital· 24 sept. 2024PodcastHarmonic’s Bet: Teach AI Math Directly, and the Riemann Hypothesis Falls by 2029Robinhood’s Vlad Tenev and Harmonic co-founder Tudor Achim tell Sequoia why math is reasoning, why Lean is the verifier, and why they refuse to wait for mathematical skill to emerge from scale.Modèles et entraînementSynthetic dataReinforcement Learning+3