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1:08:02EN
Sequoia Capital· 2026年10月13日播客AlphaGo 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.模型与训练Reinforcement LearningRL environments & simulators+3
1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月9日播客 · 2 人对谈10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledger主持 Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.开源与社区Open-weight modelsReinforcement Learning+3
56:31EN
Unsupervised Learning: With Jacob Effron· 2026年10月6日播客Post-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab主持 Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.模型与训练Post-trainingReinforcement Learning+3
53:44EN
Sequoia Capital· 2026年8月18日播客The 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.智能体Continual learningReinforcement Learning+3
49:12EN
Sequoia Capital· 2026年7月29日播客The 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.模型与训练AI researchPretraining & midtraining+3
45:33EN
Sequoia Capital· 2026年5月26日播客Cursor Ships 1TB of Composer Weights Across Oceans in Under a MinuteFederico Cassano and Fireworks' Dima walk through the globally split RL stack that trained Composer 2 on a sparse trillion-parameter MoE.基础设施与部署Distributed training & inferenceReinforcement Learning+3
59:41EN
Unsupervised Learning: With Jacob Effron· 2026年5月22日播客The GPT moment for video hasn’t arrived, but AGI may already be here主持 Jacob EffronA day after Google I/O 2026, Gemini co-lead Oriol Vinyals argues that world models, file-system memory, and infinite-complexity RL environments will define the next era of frontier models.模型与训练World modelsReinforcement Learning+3
34:56EN
Sequoia Capital· 2026年5月13日播客On Suno, 90% of Daily Users Make a SongCEO Mikey Shulman on modeling raw sound instead of music theory, why music is not an LLM-style scale problem, and treating creation itself as the entertainment.多模态与媒体Generative mediaProduct Strategy+3
1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 2026年5月1日播客The reward jumped from 3 to 180. Every Hacker News title was a Google layoff.主持 Nathan LabenzCoreWeave's Kyle Corbitt walks Nathan Labenz through GRPO, rubrics, RL environments, and why most reward hacks are easy to catch once you know to look.模型与训练Reinforcement LearningPost-training+3
3:36:29EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2026年4月23日播客Claude 给自己的福利打了 4.49 分:首个越过中性线的版本主持 Nathan LabenzCameron Berg 再次做客《The Cognitive Revolution》,梳理六个月来在内省、功能性情绪和模型福利(model welfare)方面的研究,并介绍一项尚未发表的案例:学习与感受也许是同一种现象。安全与治理Model InterpretabilityAI research+3
2:31:27EN
Cognitive Revolution "How AI Changes Everything"· 2026年4月15日播客An AI store manager, a 2.6-star rating, and a constitution nobody has to keep主持 Nathan LabenzA live Cognitive Revolution episode puts PCB layout, AI constitutions, and San Francisco’s first AI-run grocery on the same morning clock.智能体安全与治理Reinforcement Learning+3
58:46EN
Unsupervised Learning: With Jacob Effron· 2026年4月9日播客Two Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028主持 Jacob EffronJakub Pachocki tells Jacob Effron why those timelines still hold, why continual learning is not a detour, and why showing chain of thought in the product would train the monitor away.模型与训练Continual learningReinforcement Learning+3
54:26EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月22日播客Ten Billion Active Parameters, and the Unsexy Work of Making Them Agent-Ready主持 Nathan LabenzMiniMax researcher Olive Song explains how M2 was trained with expert developers as reward models, interleaved thinking, and a perturbation pipeline that treats every scaffold change as the real generalization test.编程智能体Reinforcement Learning智能体工程+3
1:03:00EN
Unsupervised Learning: With Jacob Effron· 2026年1月29日播客A Model That Solves New Math Problems Every Week Still Isn't AGI主持 Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.模型与训练Reinforcement LearningAGI Timelines+3
37:00EN
Sequoia Capital· 2026年1月14日播客The 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.基础设施与部署Reinforcement LearningAI startups & small teams+3
1:01:38EN
Sequoia Capital· 2026年1月6日播客13-Hour Coffee and 2x Throughput: Physical Intelligence Crosses the Deployment LineKarol Hausman and Tobi Springenberg tell Sequoia’s Training Data how a general robot brain, plus real-world RL, turned coffee, laundry, and chocolate boxes into jobs that actually run.模型与训练RoboticsReinforcement Learning+3
36:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年10月9日播客 · 2 人对谈STaR's Author Wants Models With EQ, Not Just More IQ主持 Sarah Guo, Elad GilEric Zelikman, the Stanford and xAI researcher behind STaR and Quiet-STaR, launches humans& on the bet that three years of IQ scaling left models emotionally unintelligent.模型与训练Post-trainingReinforcement Learning+3
1:01:49EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月2日播客ChatGPT's Co-Creator Left to Put Nature in the Reward Loop主持 Nathan LabenzLiam Fedus and Ekin Dogus Cubuk on why language models still fail at physics, why literature data is too noisy to train on, and why Periodic Labs is aiming at a 200K superconductor.模型与训练AI for scienceReinforcement Learning+3
1:02:05EN
Unsupervised Learning: With Jacob Effron· 2025年9月24日播客$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the Math主持 Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.企业与战略AI StrategyAI startups & small teams+3
3:14:49EN
Cognitive Revolution "How AI Changes Everything"· 2025年9月6日播客Nothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI Timelines主持 Nathan LabenzOn his tenth visit to The Cognitive Revolution, Zvi Mowshowitz argues that GPT-5 and IMO gold stayed on trend, while chip policy, energy, and reinforcement learning nudged his p(doom) slightly up.安全AGI Timelines安全与治理+3
30:11EN
Sequoia Capital· 2025年7月30日播客From 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.模型与训练Reasoning & test-time computeBenchmarks+3
1:02:54EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年7月17日播客 · 2 人对谈Enterprise Coding Tools Flipped the 80/20. Reflection AI Built the Other Half主持 Sarah Guo, Elad GilFormer Gemini reward-model lead Misha Laskin on Asimov, why comprehension beats generation, and why there is no such thing as generalization—only pulling the test distribution into train.编程智能体智能体工程评估+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月16日播客Plus Five for Format, Plus Ten if It Compiles主持 Nathan LabenzPredibase CEO Dev Rishi explains how reinforcement fine-tuning, production feedback, and narrow specialist models turn one-off training into systems that keep learning.模型与训练微调Post-training+3
57:31EN
Unsupervised Learning: With Jacob Effron· 2025年5月22日播客The New Ruler for Models Is How Long They Can Work主持 Jacob EffronOn Claude 4's launch day, Anthropic researcher Sholto Douglas argued that the next phase of AI is less about harder puzzles and more about hours of unsupervised work.编程智能体智能体工程评估+3
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