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130 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
1:30:54EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月3日ポッドキャストHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2ホスト Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.エージェントRoboticsMultimodal AI+3
2:13:27EN
Cognitive Revolution "How AI Changes Everything"· 2026年9月29日ポッドキャストHe Wrote a Book to Stop the AI Race — Then Almost Got Addicted to Claudeホスト Nathan LabenzJournalist Garrison Lovely takes the AGI labs at their word, rejects the bubble story, and argues for freezing the frontier until the public actually consents.セキュリティと安全性安全性とガバナンスAI Strategy+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
2:10:42EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月28日ポッドキャストThe Exam Papers Nobody Auditsホスト Nathan LabenzFrontier labs buy reinforcement-learning environments from a cottage industry of small vendors, and almost nobody checks whether those tests match the real work.評価とオブザーバビリティ評価(Evals)Reward hacking+3
2:13:09EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月26日ポッドキャストOne Chain of Thought, 100 Million Tokens: RL Is a Hell of a Drugホスト Nathan LabenzApollo Research's Bronson Schoen on reward-seeking models, invented slang, and why chain-of-thought monitoring will not save us.セキュリティと安全性安全性とガバナンスReward hacking+3
2:16:29EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月2日ポッドキャストFrom Two Papers a Month to Sixty: What Two Weeks in China Revealed About AI Safetyホスト Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.セキュリティと安全性安全性とガバナンスAI security+3
50:57EN
Unsupervised Learning: With Jacob Effron· 2026年7月9日ポッドキャストA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuberホスト Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.モデルと学習AGI(汎用人工知能)AI research+3
1:57:46EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月27日ポッドキャスト30% Consciousness, 47% Bee, 80% Turnover: Putting Numbers on What AI Is Becomingホスト Nathan LabenzA Cognitive Revolution weekly cut that starts inside the model with Cameron Berg, then zooms out through gradual disempowerment, Europe’s bind, and the companies rebuilding around agents.企業と戦略安全性とガバナンスAI research+3
1:44:28EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月13日ポッドキャストFable launch week: a model that refuses, a two-year alignment clock, and a Twitter account handed overホスト Nathan LabenzNathan Labenz’s AI in the AM highlights reel from June 2026 covers Anthropic’s new frontier model, the founding of Sequent, and a week that settled one argument: AI is not slowing down.セキュリティと安全性安全性とガバナンスエージェント工学+3
1:22:36EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月6日ポッドキャストA Thousand Researchers, a Million AIs: Frontier Labs Start Talking About the Brakesホスト Nathan LabenzThe first week of AI in the AM follows OpenAI's timeline for an ML-intern model this year and a human-level AI researcher by early 2028 — and the closed-door meeting where labs admitted they might one day need to slow down together.セキュリティと安全性安全性とガバナンスAI research+3
1:13:33EN
Unsupervised Learning: With Jacob Effron· 2026年6月3日ポッドキャストA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still Missホスト Jacob EffronThe Attention Is All You Need co-author tells Unsupervised Learning that transformers will probably keep winning — and that they still do not learn the way people do.モデルと学習AI researchコーディングエージェント+3
1:41:58EN
Cognitive Revolution "How AI Changes Everything"· 2026年5月26日ポッドキャストA thousand people on guard, a million in the sprintホスト Nathan Labenz80,000 Hours founder Ben Todd on how to spend a career in the years when your impact on AI will actually peak.セキュリティと安全性安全性とガバナンスAI Strategy+3
1:21:56EN
Unsupervised Learning: With Jacob Effron· 2026年5月15日ポッドキャストYann LeCun Left Meta Because LLMs Will Not Get You to Intelligenceホスト Jacob EffronThe Turing Award winner tells Jacob Effron why he spun AMI Labs out of Meta, why JEPA-style world models beat pixel generators, and why he thinks Hinton changed his mind in 2023.モデルと学習World modelsAI research+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
3:10:49EN
Cognitive Revolution "How AI Changes Everything"· 2026年4月11日ポッドキャストCrunch Time: Ajeya Cotra's Playbook for the Months Before Superintelligenceホスト Nathan LabenzA conversation on recursive self-improvement, public warning systems, and using each generation of AI to align and control the next.セキュリティと安全性安全性とガバナンスAGI Timelines+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
1:49:53EN
Cognitive Revolution "How AI Changes Everything"· 2026年3月5日ポッドキャストDon't Fight Backprop: Goodfire's Bet on Designing What Models Learnホスト Nathan LabenzDan Balsam and Tom McGrath return to The Cognitive Revolution with a $150 million Series B, a new research pillar called intentional design, and a rule for anyone who wants to steer training: stop trying to out-muscle gradient descent.モデルと学習Model Interpretability安全性とガバナンス+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
2:25:42EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月14日ポッドキャストThe experts argued through the coffee break — and never agreed whether AI can build AIホスト Nathan LabenzOn a marathon Cognitive Revolution live show, a cancer-AI researcher, a former OpenAI board member, and a national-security analyst each hit a different wall in the boom.セキュリティと安全性安全性とガバナンスAGI(汎用人工知能)+3
1:04:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月1日ポッドキャスト125 million cells took a decade. The next billion takes monthsホスト Nathan LabenzMark Zuckerberg and Priscilla Chan on pairing a frontier biology lab with a frontier AI lab so models train on data that was designed for them.モデルと学習AI for scienceData quality & curation+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
2:25:10EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月22日ポッドキャストFine-Tuning Isn't Dead — But It Turned a Helpful Model Evilホスト Nathan LabenzNathan Labenz on why prompting replaced fine-tuning for most work, what emergent misalignment actually showed, and how he is thinking about jobs, UBI, and AGI.モデルと学習ファインチューニング安全性とガバナンス+3
1:55:02EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月4日ポッドキャストAn Index Fund on AGI: How MATS Filters the Next 120 AI Safety Researchersホスト Nathan LabenzRyan Kidd, co-executive director of MATS, tells Nathan Labenz why he will not shout a timeline, why every safety technique is also a capabilities technique, and who actually gets hired.セキュリティと安全性安全性とガバナンスAI research+3
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