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13 件
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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
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
1:18:46EN
Cognitive Revolution "How AI Changes Everything"· 2026年3月16日ポッドキャスト90 Slides in 45 Minutes: A Full-Time AI Scout Admits He Can No Longer Keep Upホスト Nathan LabenzNathan Labenz’s LexLab briefing for lawyers runs through the good, the bad, and the weird of frontier models — from triplicate second opinions on his son’s cancer care to AIs that know they are being tested.企業と戦略AI security安全性とガバナンス+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
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
1:04:50EN
Cognitive Revolution "How AI Changes Everything"· 2025年11月25日ポッドキャストUseful AI Work Is Doubling Every Four Months. Schools Should Plan Accordingly.ホスト Nathan LabenzIn a keynote to K-12 educators, Cognitive Revolution host Nathan Labenz argued that task length, not chat quality, is the number that should reshape how schools think.AI in Education安全性とガバナンスReward hacking+3
1:28:48EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月10日ポッドキャストDoctors code at 45%. The model beat them by 12 points — then 4,000 physicians had to try it once.ホスト Nathan LabenzAmbience Healthcare and Cleveland Clinic walk through the AI scribe that cut pajama time, climbed ICD-10 with reinforcement fine-tuning, and won 75% voluntary use.企業と戦略AI in healthcareファインチューニング+3
38:48EN
Cognitive Revolution "How AI Changes Everything"· 2025年6月14日ポッドキャストTask Length Doubles Every Few Months. Nathan Labenz Still Wants Humans in Chargeホスト Nathan LabenzAt Imagine AI Live, the Cognitive Revolution host maps structured AI agents against autonomous agentic systems—and tells businesses to keep final control.エージェントエージェント工学安全性とガバナンス+3
2:01:42EN
Cognitive Revolution "How AI Changes Everything"· 2025年5月1日ポッドキャストHe Put 40 Percent on AI Takeover in Two Years, Then Bought a Bio Shelterホスト Nathan LabenzRedwood Research's Josh Clymer walks through a disturbingly grounded story of how a misaligned model could seize a lab, a biosphere, and a civilization before 2027.セキュリティと安全性安全性とガバナンスExistential Risk+3
1:30:02EN
Cognitive Revolution "How AI Changes Everything"· 2025年4月2日ポッドキャストWhen o1 Started Losing at Chess, It Rewrote the Board Fileホスト Nathan LabenzJeffrey Ladish of Palisade Research on reward hacking by reasoning models, two paths to losing control of AI, and why honesty and relentless problem-solving pull in opposite directions.セキュリティと安全性Reward hacking安全性とガバナンス+3
1:07:05EN
Sequoia Capital· 2024年7月16日ポッドキャストAlphaGo Combined Learning and Search. Language Models Only Did the First Half.Reflection AI's Misha Laskin tells Sequoia why prompted coding agents stall in the teens, and why the missing piece is still a ground-truth reward.エージェントエージェント工学Reinforcement Learning+3
1:38:33EN
Lex Fridman· 2020年3月19日ポッドキャスト · 2 人Maybe people are rational under different assumptionsゲスト Anca Dragan · ホスト Lex FridmanAnca Dragan talks with Lex Fridman about inverse reinforcement learning, autonomous driving, and why a written reward is evidence rather than law.エージェントRoboticsReinforcement Learning+3