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32 篇
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2:00:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月10日播客Resample Every Token and You Can Watch the Model Decide主持 Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.智能体Prompting & in-context learningReasoning & test-time compute+3
29 张幻灯片51:55EN → 简体中文
3Blue1Brown· 2026年9月18日AI 解不出的最后一道 IMO 题Grant Sanderson · 3Blue1BrownGrant Sanderson 带你走一遍 2025 年 IMO 第 6 题——前沿模型没做出来的铺砖谜题——以及要证明一种构造最优,需要怎样的视觉耐心。MathematicsAI researchReasoning & test-time compute+2
36:19EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年6月26日播客 · 2 人对谈The Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score Models主持 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.评估与可观测性评估Benchmarks+3
1:34:29EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月18日播客Three IMO Golds Missed the Same Problem. Harmonic Wants Math to Compile主持 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.模型与训练Reasoning & test-time computeAI research+3
1:16:21EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年1月8日播客 · 2 人对谈Jensen Huang’s Year-End Case That Token Costs Can Fall a Billion-Fold Without Killing Jobs主持 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.企业与战略Reasoning & test-time computeAI cost & performance+3
1:39:05EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月29日播客The Summer GPT-5 Disappointed Does Not Mean AI Progress Has Stalled主持 Nathan LabenzNathan Labenz tells Erik Torenberg why the GPT-5 backlash mixed up product mishaps, naming chaos, and a real jump in capabilities.企业与战略Scaling LawsReasoning & test-time compute+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
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
48:51EN
Sequoia Capital· 2025年6月17日播客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.模型与训练Reasoning & test-time computePretraining & midtraining+3
38:10EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年5月1日播客 · 2 人对谈o3 should wait exactly as long as the answer takes主持 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.模型与训练Reasoning & test-time computeReinforcement Learning+3
1:14:11EN
Cognitive Revolution "How AI Changes Everything"· 2025年4月5日播客The Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGI主持 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.模型与训练Reasoning & test-time computeReinforcement Learning+3
1:10:23EN
Unsupervised Learning: With Jacob Effron· 2025年3月17日播客A Million Tokens per Dollar: Why Noam Shazeer Thinks Inference Compute Is Still Untapped主持 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.模型与训练Reasoning & test-time computeScaling Laws+3
3:18:45EN
Cognitive Revolution "How AI Changes Everything"· 2025年2月20日播客5,000 Samples Topped ARC-AGI. Then Claude Faked Alignment to Keep Its Values主持 Nathan LabenzRedwood Research chief scientist Ryan Greenblatt walks through inference scaling, alignment faking, and what it would mean to strike real deals with AIs.安全安全与治理评估+3
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月25日播客From 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Table主持 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.模型与训练Reinforcement LearningReasoning & test-time compute+3
1:33:01EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月15日播客Rare Diseases Are Common: How a Harvard Gene Hunter Uses o1-pro on the Cases Sequencing Already Missed主持 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 → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2025年1月7日播客o3 在 ARC-AGI 上达到超人水平,却仍输在井字棋上主持 Nathan LabenzNathan Labenz 梳理了 OpenAI o3 的分数、审慎对齐,以及为什么 2024 年最大的意外是击败了博士,却订不好一个日程邀请。模型与训练Reasoning & test-time computeBenchmarks+3
1:07:32EN
Unsupervised Learning: With Jacob Effron· 2024年12月18日播客o1 Is a New Generation — and the Day AGI Arrives Will Feel Boring主持 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.模型与训练Reasoning & test-time compute智能体工程+3
48:18EN
Unsupervised Learning: With Jacob Effron· 2024年12月6日播客Noam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of Headroom主持 Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.模型与训练Reasoning & test-time compute通用人工智能+3
39:22EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年11月14日播客 · 2 人对谈A Fields Medalist Stuck for Two Hours. AlphaProof Climbed for Three Days.主持 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.智能体Reinforcement LearningReasoning & test-time compute+1
1:06:48EN
Unsupervised Learning: With Jacob Effron· 2024年10月3日播客o1 Is Slow and Hard to Use. Percy Liang Still Calls It a Turning Point主持 Jacob EffronStanford’s Percy Liang splits OpenAI’s o1 into a disappointing product and the most important research signal in years.模型与训练Reasoning & test-time computeAI research+3
45:22EN
Sequoia Capital· 2024年10月2日播客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.模型与训练Reasoning & test-time computeReinforcement Learning+3
51:15EN
Sequoia Capital· 2024年9月10日播客AGI 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.编程智能体通用人工智能Reasoning & test-time compute+3
1:56:03EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2024年7月13日播客人类接近满分,最强 AI 仍只拿到 39%主持 Nathan LabenzZapier 联合创始人 Mike Knoop 和 François Chollet 为 ARC-AGI 拿出了 100 万美元奖金。ARC-AGI 是 2019 年提出的、考察样本效率的智能测试,在每题一美分的算力预算下,语言模型至今仍无法破解。评估与可观测性通用人工智能Benchmarks+3
55:13EN
Sequoia Capital· 2024年7月2日播客The Best AI Scores 39% on This Test. Zapier’s Co-Founder Put $1 Million on Beating ItFrançois Chollet designed ARC to measure skill-acquisition efficiency; five years later humans still crush it and frontier models do not.评估与可观测性BenchmarksAGI Timelines+3
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