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1:08:02EN
Sequoia Capital· 13 oct. 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.Modèles et entraînementReinforcement LearningRL environments & simulators+3
48:51EN
Sequoia Capital· 17 juin 2025PodcastThe Breakthroughs for AGI Are Already Done, Says OpenAI’s Former Research HeadBob McGrew tells Sequoia’s Training Data that 2025 is the year of reasoning, agents will be priced at the cost of compute, and nothing fundamental will be added to the stack by 2035.Modèles et entraînementReasoning & test-time computePretraining & midtraining+3
52:30EN
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
51:15EN
Sequoia Capital· 10 sept. 2024PodcastAGI Has One Problem Left: Spend a Million Times More on a TokenMagic founder Eric Steinberger tells Sequoia’s Training Data why he trains his own models, why a software engineer is the MVP of AGI, and why 96% still is not a colleague.Agents de codeAGIReasoning & test-time compute+3
1:07:05EN
Sequoia Capital· 16 juil. 2024PodcastAlphaGo Combined Learning and Search. Language Models Only Did the First Half.Reflection AI's Misha Laskin tells Sequoia why prompted coding agents stall in the teens, and why the missing piece is still a ground-truth reward.AgentsIngénierie d’agentsReinforcement Learning+3