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38 件
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2:00:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月10日ポッドキャストResample Every Token and You Can Watch the Model Decideホスト Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.エージェントPrompting & in-context learningReasoning & test-time compute+3
スライド 29 枚51:55EN
3Blue1Brown· 2026年9月18日The last IMO problem AI could not solveGrant Sanderson · 3Blue1BrownGrant Sanderson walks through IMO 2025 Problem 6 — a tiling puzzle that frontier models missed — and the visual patience it takes to prove a construction is optimal.MathematicsAI researchReasoning & test-time compute+2
36:19EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年6月26日ポッドキャスト · 2 人The Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score Modelsホスト Sarah Guo, Elad GilOpenAI researcher Noam Brown argues that static leaderboards hide how long a model is allowed to think — and that safety evals, research taste, and the release cycle have not caught up.評価とオブザーバビリティ評価(Evals)Benchmarks+3
1:34:29EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月18日ポッドキャストThree IMO Golds Missed the Same Problem. Harmonic Wants Math to Compileホスト Nathan LabenzVlad Tenev and Tudor Achim built Aristotle to emit Lean proofs a kernel can check—and they argue that is how mathematical superintelligence stays trustworthy.モデルと学習Reasoning & test-time computeAI research+3
1:16:21EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年1月8日ポッドキャスト · 2 人Jensen Huang’s Year-End Case That Token Costs Can Fall a Billion-Fold Without Killing Jobsホスト Sarah Guo, Elad GilOn No Priors, NVIDIA’s CEO uses radiology, open source, and a $2 trillion R&D budget to argue that 2025’s extremes missed the stack.企業と戦略Reasoning & test-time computeAI cost & performance+3
18:59EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年10月31日ポッドキャスト · 2 人86 Out of 100: The Clips No Priors Could Not Leave on the Cutting-Room Floorホスト Sarah Guo, Elad GilSarah Guo and Elad Gil stitch nine 2025 conversations into one short tour of legal AI, spatial intelligence, jobs, deterrence, and a doctor who made it home for dinner.企業と戦略AI StrategyCompany Building+3
1:39:05EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月29日ポッドキャストThe Summer GPT-5 Disappointed Does Not Mean AI Progress Has Stalledホスト Nathan LabenzNathan Labenz tells Erik Torenberg why the GPT-5 backlash mixed up product mishaps, naming chaos, and a real jump in capabilities.企業と戦略Scaling LawsReasoning & test-time compute+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
スライド 4 枚13:30EN
3Blue1Brown· 2025年8月17日How AlphaGeometry Combines Logical Proof with Creative ConstructionAleph0Aleph0 explains how a symbolic geometry solver gets surprisingly far without AI, and how a language model supplies the auxiliary constructions that take it to Olympiad level.MathematicsReasoning & test-time computeAI research+2
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
48:51EN
Sequoia Capital· 2025年6月17日ポッドキャストThe 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.モデルと学習Reasoning & test-time computePretraining & midtraining+3
38:10EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年5月1日ポッドキャスト · 2 人o3 should wait exactly as long as the answer takesホスト Sarah Guo, Elad GilOpenAI researchers Eric Mitchell and Brandon McKinzie tell No Priors why o3's leap is a chain of tools during reasoning — and why you should send the same prompt a hundred times.モデルと学習Reasoning & test-time computeReinforcement Learning+3
1:14:11EN
Cognitive Revolution "How AI Changes Everything"· 2025年4月5日ポッドキャストThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGIホスト Nathan LabenzDeepMind's thinking-and-inference lead explains why RL-for-reasoning felt sudden, why Gemini shows raw chain of thought, and why a million-token window still is not memory.モデルと学習Reasoning & test-time computeReinforcement Learning+3
1:10:23EN
Unsupervised Learning: With Jacob Effron· 2025年3月17日ポッドキャストA Million Tokens per Dollar: Why Noam Shazeer Thinks Inference Compute Is Still Untappedホスト Jacob EffronThe Transformer co-inventor and Gemini researcher Jack Rae walk through test-time compute, Ilya Sutskever's AGI critique, and a four-year-old who now lectures his teacher about lizards.モデルと学習Reasoning & test-time computeScaling Laws+3
3:18:45EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月20日ポッドキャスト5,000 Samples Topped ARC-AGI. Then Claude Faked Alignment to Keep Its Valuesホスト Nathan LabenzRedwood Research chief scientist Ryan Greenblatt walks through inference scaling, alignment faking, and what it would mean to strike real deals with AIs.セキュリティと安全性安全性とガバナンス評価(Evals)+3
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月25日ポッドキャストFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Tableホスト Nathan LabenzOn Inauguration Day 2025, DeepSeek and Moonshot dropped reasoning-model results that Nathan Labenz reads as proof the reinforcement-learning recipe is simple, public, and still climbing.モデルと学習Reinforcement LearningReasoning & test-time compute+3
1:33:01EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月15日ポッドキャストRare Diseases Are Common: How a Harvard Gene Hunter Uses o1-pro on the Cases Sequencing Already Missedホスト Nathan LabenzDr. Catherine Brownstein of Boston Children's Hospital explains why cheap genomes made her job harder, why data sharing still beats any model, and where ChatGPT Pro actually gives her hours back.AI in healthcareReasoning & test-time computePrompting & in-context learning+3
2:04:45EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月7日ポッドキャストo3 Hit Superhuman on ARC-AGI. It Still Lost at Tic-Tac-Toeホスト Nathan LabenzNathan Labenz walks through OpenAI's o3 scores, deliberative alignment, and why 2024's biggest surprise was beating PhDs while failing to book a calendar invite.モデルと学習Reasoning & test-time computeBenchmarks+3
1:07:32EN
Unsupervised Learning: With Jacob Effron· 2024年12月18日ポッドキャストo1 Is a New Generation — and the Day AGI Arrives Will Feel Boringホスト Jacob EffronOpenAI’s former chief research officer Bob McGrew on why o1 is a 100x leap, why agents stall on reliability, and why AGI may land as office tedium rather than a single dramatic moment.モデルと学習Reasoning & test-time computeエージェント工学+3
48:18EN
Unsupervised Learning: With Jacob Effron· 2024年12月6日ポッドキャストNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of Headroomホスト Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.モデルと学習Reasoning & test-time computeAGI(汎用人工知能)+3
39:22EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年11月14日ポッドキャスト · 2 人A Fields Medalist Stuck for Two Hours. AlphaProof Climbed for Three Days.ホスト Sarah Guo, Elad GilThe DeepMind team behind AlphaProof tells Sarah Guo and Elad Gil how an AlphaZero-style agent, a Lean verifier, and test-time reinforcement learning reached IMO silver — and why the missing skill is still theory building.エージェントReinforcement LearningReasoning & test-time compute+1
29:29EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年10月17日ポッドキャスト · 2 人The Week AI Won Its First Nobels, Two Investors Listed Who Is Most at Riskホスト Sarah Guo, Elad GilSarah Guo and Elad Gil talk NotebookLM, intelligent NPCs, artificial wombs, OpenAI’s o1, and which businesses look AI-durable.企業と戦略AI StrategyProduct Strategy+3
1:06:48EN
Unsupervised Learning: With Jacob Effron· 2024年10月3日ポッドキャストo1 Is Slow and Hard to Use. Percy Liang Still Calls It a Turning Pointホスト Jacob EffronStanford’s Percy Liang splits OpenAI’s o1 into a disappointing product and the most important research signal in years.モデルと学習Reasoning & test-time computeAI research+3
45:22EN
Sequoia Capital· 2024年10月2日ポッドキャストAlphaGo 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.モデルと学習Reasoning & test-time computeReinforcement Learning+3
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