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71 件
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1:08:02EN
Sequoia Capital· 2026年10月13日ポッドキャスト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.モデルと学習Reinforcement LearningRL environments & simulators+3
1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月9日ポッドキャスト · 2 人10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledgerホスト 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.オープンソースとコミュニティOpen-weight modelsReinforcement Learning+3
56:31EN
Unsupervised Learning: With Jacob Effron· 2026年10月6日ポッドキャストPost-Training Wins Inference: Why Owning the Weights Beats Betting on One Labホスト 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.モデルと学習Post-trainingReinforcement Learning+3
53:44EN
Sequoia Capital· 2026年8月18日ポッドキャスト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.エージェントContinual learningReinforcement Learning+3
49:12EN
Sequoia Capital· 2026年7月29日ポッドキャスト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.モデルと学習AI researchPretraining & midtraining+3
45:33EN
Sequoia Capital· 2026年5月26日ポッドキャスト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.インフラとデプロイDistributed training & inferenceReinforcement Learning+3
59:41EN
Unsupervised Learning: With Jacob Effron· 2026年5月22日ポッドキャストThe GPT moment for video hasn’t arrived, but AGI may already be hereホスト 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.モデルと学習World modelsReinforcement Learning+3
34:56EN
Sequoia Capital· 2026年5月13日ポッドキャスト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.マルチモーダルとメディアGenerative mediaProduct Strategy+3
1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 2026年5月1日ポッドキャストThe reward jumped from 3 to 180. Every Hacker News title was a Google layoff.ホスト 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.モデルと学習Reinforcement LearningPost-training+3
3:36:29EN
Cognitive Revolution "How AI Changes Everything"· 2026年4月23日ポッドキャストClaude Rated Its Own Welfare 4.49 — the First Time Any Version Crossed Neutralホスト Nathan LabenzCameron Berg returns to The Cognitive Revolution to survey six months of introspection, functional-emotion, and model-welfare research, plus a still-unpublished case that learning and feeling may be the same phenomenon.安全性とガバナンスModel InterpretabilityAI research+3
2:31:27EN
Cognitive Revolution "How AI Changes Everything"· 2026年4月15日ポッドキャストAn AI store manager, a 2.6-star rating, and a constitution nobody has to keepホスト Nathan LabenzA live Cognitive Revolution episode puts PCB layout, AI constitutions, and San Francisco’s first AI-run grocery on the same morning clock.エージェント安全性とガバナンスReinforcement Learning+3
58:46EN
Unsupervised Learning: With Jacob Effron· 2026年4月9日ポッドキャストTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028ホスト 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.モデルと学習Continual learningReinforcement Learning+3
54:26EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月22日ポッドキャストTen Billion Active Parameters, and the Unsexy Work of Making Them Agent-Readyホスト 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.コーディングエージェントReinforcement Learningエージェント工学+3
1:03:00EN
Unsupervised Learning: With Jacob Effron· 2026年1月29日ポッドキャストA Model That Solves New Math Problems Every Week Still Isn't AGIホスト 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.モデルと学習Reinforcement LearningAGI Timelines+3
37:00EN
Sequoia Capital· 2026年1月14日ポッドキャスト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.インフラとデプロイReinforcement LearningAI startups & small teams+3
1:01:38EN
Sequoia Capital· 2026年1月6日ポッドキャスト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.モデルと学習RoboticsReinforcement Learning+3
36:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年10月9日ポッドキャスト · 2 人STaR's Author Wants Models With EQ, Not Just More IQホスト 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.モデルと学習Post-trainingReinforcement Learning+3
1:01:49EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月2日ポッドキャストChatGPT's Co-Creator Left to Put Nature in the Reward Loopホスト 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.モデルと学習AI for scienceReinforcement Learning+3
1:02:05EN
Unsupervised Learning: With Jacob Effron· 2025年9月24日ポッドキャスト$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the Mathホスト 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.企業と戦略AI StrategyAI startups & small teams+3
3:14:49EN
Cognitive Revolution "How AI Changes Everything"· 2025年9月6日ポッドキャストNothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI Timelinesホスト 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.セキュリティと安全性AGI Timelines安全性とガバナンス+3
30:11EN
Sequoia Capital· 2025年7月30日ポッドキャスト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.モデルと学習Reasoning & test-time computeBenchmarks+3
1:02:54EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年7月17日ポッドキャスト · 2 人Enterprise Coding Tools Flipped the 80/20. Reflection AI Built the Other Halfホスト 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.コーディングエージェントエージェント工学評価(Evals)+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月16日ポッドキャストPlus Five for Format, Plus Ten if It Compilesホスト 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.モデルと学習ファインチューニングPost-training+3
57:31EN
Unsupervised Learning: With Jacob Effron· 2025年5月22日ポッドキャストThe New Ruler for Models Is How Long They Can Workホスト 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.コーディングエージェントエージェント工学評価(Evals)+3
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