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53:44EN
Sequoia Capital· 2026년 8월 18일팟캐스트The 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.에이전트Continual learningReinforcement Learning+3
38:45EN
Sequoia Capital· 2026년 6월 16일팟캐스트The 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.에이전트Multi-agent systems에이전트 엔지니어링+3
41:36EN
Sequoia Capital· 2025년 11월 18일팟캐스트Four 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.모델과 학습Autonomous DrivingWorld models+3
38:25EN
Sequoia Capital· 2025년 5월 27일팟캐스트A 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.에이전트에이전트 엔지니어링Synthetic data+3
55:40EN
Sequoia Capital· 2025년 4월 29일팟캐스트To 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.기업과 전략AI for scienceSynthetic data+3
52:30EN
Sequoia Capital· 2025년 1월 28일팟캐스트Move 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.에이전트Reinforcement Learning에이전트 엔지니어링+3
39:45EN
Sequoia Capital· 2024년 9월 24일팟캐스트Harmonic’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.모델과 학습Synthetic dataReinforcement Learning+3