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1:08:02EN
Sequoia Capital· Oct 13, 2026PodcastAlphaGo 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.
53:44ENSequoia Capital· Aug 18, 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.
49:12ENSequoia Capital· Jul 29, 2026PodcastThe People Writing the Transformer’s Eulogy Want a Lab That Can Take Vacation Without Themo1’s reasoning lead and a Gemini pre-training lead argue the architecture, not more scale, is now the bottleneck — and that replacing it starts with automating kernel generation.
37:00ENSequoia Capital· Jan 14, 2026PodcastThe AlphaChip Team That Laid Out Four TPUs Now Wants Every Company to Be DesignlessAnna Goldie and Azalia Mirhoseini tell Sequoia how an RL floorplanner survived TPU-team anger, learned to draw donut-shaped macros, and became a bet that AI will design chips that then feed AI.
30:11ENSequoia Capital· Jul 30, 2025PodcastFrom 12 Percent on AIME to IMO Gold in Two MonthsAlex Wei, Sheryl Hsu, and Noam Brown tell Sequoia's Sonya Huang how a three-person OpenAI sprint used general-purpose reinforcement learning, not Lean, to reach gold-level on the 2025 International Mathematical Olympiad.
41:13ENSequoia Capital· Jul 11, 2025PodcastFrom 49 Multiplications to 48: DeepMind’s AI Rewrites a Fifty-Year Math RecordPushmeet Kohli explains how AlphaEvolve couples Gemini with evaluators to invent algorithms, prove old conjectures, and change which scientific problems are even worth attempting.
47:07ENSequoia Capital· Jul 8, 2025PodcastGoodfire’s Eric Ho thinks we will decode neural nets by 2028On Sequoia’s Training Data, the interpretability founder argues that sparse autoencoders, model editing, and a third-party lab are how AI stops being grown from data and starts being designed.
52:30ENSequoia Capital· Jan 28, 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.
41:42ENSequoia Capital· Oct 22, 2024PodcastNeural Networks Are Still Waiting for Their ThermodynamicsOpenAI researcher Dan Roberts on why physicists keep migrating into AI, and why the field still lacks the equivalent of the ideal gas law.
45:22ENSequoia Capital· Oct 2, 2024PodcastAlphaGo Thought 30 Seconds a Move. o1 Made “Think Longer” GeneralOpenAI researchers Noam Brown, Ilge Akkaya, and Hunter Lightman on teaching language models to reason, the generator-verifier gap, and a second scaling curve at inference time.
39:45ENSequoia Capital· Sep 24, 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.
55:13ENSequoia Capital· Jul 2, 2024PodcastThe Best AI Scores 39% on This Test. Zapier’s Co-Founder Put $1 Million on Beating ItFrançois Chollet designed ARC to measure skill-acquisition efficiency; five years later humans still crush it and frontier models do not.