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1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 1 mai 2026PodcastThe reward jumped from 3 to 180. Every Hacker News title was a Google layoff.Anime : 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.Modèles et entraînementReinforcement LearningPost-training+3
3:36:29EN
Cognitive Revolution "How AI Changes Everything"· 23 avr. 2026PodcastClaude Rated Its Own Welfare 4.49 — the First Time Any Version Crossed NeutralAnime : 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Revolution to survey six months of introspection, functional-emotion, and model-welfare research, plus a still-unpublished case that learning and feeling may be the same phenomenon.Sécurité et gouvernanceModel InterpretabilityAI research+3
2:31:27EN
Cognitive Revolution "How AI Changes Everything"· 15 avr. 2026PodcastAn AI store manager, a 2.6-star rating, and a constitution nobody has to keepAnime : Nathan LabenzA live Cognitive Revolution episode puts PCB layout, AI constitutions, and San Francisco’s first AI-run grocery on the same morning clock.AgentsSécurité et gouvernanceReinforcement Learning+3
54:26EN
Cognitive Revolution "How AI Changes Everything"· 22 févr. 2026PodcastTen Billion Active Parameters, and the Unsexy Work of Making Them Agent-ReadyAnime : 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.Agents de codeReinforcement LearningIngénierie d’agents+3
1:01:49EN
Cognitive Revolution "How AI Changes Everything"· 2 oct. 2025PodcastChatGPT's Co-Creator Left to Put Nature in the Reward LoopAnime : 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.Modèles et entraînementAI for scienceReinforcement Learning+3
3:14:49EN
Cognitive Revolution "How AI Changes Everything"· 6 sept. 2025PodcastNothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI TimelinesAnime : 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.SécuritéAGI TimelinesSécurité et gouvernance+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 16 juil. 2025PodcastPlus Five for Format, Plus Ten if It CompilesAnime : 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.Modèles et entraînementFine-tuningPost-training+3
1:14:11EN
Cognitive Revolution "How AI Changes Everything"· 5 avr. 2025PodcastThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGIAnime : 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.Modèles et entraînementReasoning & test-time computeReinforcement Learning+3
1:56:38EN
Cognitive Revolution "How AI Changes Everything"· 8 mars 2025Podcasto3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligenceAnime : Nathan LabenzOn Consistently Candid, the Cognitive Revolution host argues that math and coding will be superhuman by 2026, and that a reasoning core plus specialist “intuitive physics” may already be enough.Modèles et entraînementReinforcement LearningDistributed training & inference+3
2:16:17EN
Cognitive Revolution "How AI Changes Everything"· 5 févr. 2025PodcastA 10B Model Trained Across Three Continents — and an H200 for $1.49 an HourAnime : Nathan LabenzPrime Intellect's founders lay out a four-step plan to turn spare global GPUs into collectively owned intelligence, and argue that reinforcement learning just made their job easier.Infrastructure et déploiementDistributed training & inferenceAI cost & performance+3
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· 25 janv. 2025PodcastFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the TableAnime : 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.Modèles et entraînementReinforcement LearningReasoning & test-time compute+3
1:27:33EN
Cognitive Revolution "How AI Changes Everything"· 3 déc. 2024PodcastA 70B Model Booked Dinner 20% of the Time. MultiOn Took It to 95% in a DayAnime : Nathan LabenzMultiOn CEO Div Garg returns to The Cognitive Revolution to recap 18 months of agent hype, the AgentQ stack, and why 2025 might still be the year of vertical agents.AgentsIngénierie d’agentsComputer use+3
52:45EN
Cognitive Revolution "How AI Changes Everything"· 13 juin 2024PodcastA $150 million model, $5 million six months later: Benchmark’s AI investment mathAnime : Nathan LabenzEric Vishria and Quilter’s Sergiy Nesterenko explain why PCB layout is not a Copilot problem, why human board data would be the wrong training set, and which AI companies look like sugar highs.Entreprise et stratégieAI StrategyAI startups & small teams+3
56:56EN
Cognitive Revolution "How AI Changes Everything"· 25 avr. 2024PodcastA Week of PCB Layout in an Hour: Quilter Trains Agents, Not ImitatorsAnime : Nathan LabenzSpaceX alum Sergiy Nesterenko tells Will Summerlin how Quilter uses reinforcement learning to compile schematics into manufacturable boards, and why cloning human layouts would cap the system at human skill.Entreprise et stratégieReinforcement LearningRL environments & simulators+3
1:58:43EN
Cognitive Revolution "How AI Changes Everything"· 7 févr. 2024PodcastA Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.Anime : Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.Modèles et entraînementAI HistoryNeuroscience & AI+3