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1:08:02EN
Sequoia Capital· 2026년 10월 13일팟캐스트AlphaGo 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.모델과 학습Reinforcement LearningRL environments & simulators+3
48:51EN
Sequoia Capital· 2025년 6월 17일팟캐스트The 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.모델과 학습Reasoning & test-time computePretraining & midtraining+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
51:15EN
Sequoia Capital· 2024년 9월 10일팟캐스트AGI 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.코딩 에이전트AGI(범용 인공지능)Reasoning & test-time compute+3
1:07:05EN
Sequoia Capital· 2024년 7월 16일팟캐스트AlphaGo 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.에이전트에이전트 엔지니어링Reinforcement Learning+3