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5 diapositives10:36EN
MBMatthew Berman· 13 oct. 2026Meta Muse Wonder Tested: Strong Benchmarks, Mixed Demos and Quota FrictionMatthew Berman · Forward FutureMatthew Berman tests Meta’s models on browser demos and reviews their published benchmark scores, availability and cost.Modèles et entraînementBenchmarksAI cost & performance+1
56:31EN
Unsupervised Learning: With Jacob Effron· 6 oct. 2026PodcastPost-Training Wins Inference: Why Owning the Weights Beats Betting on One LabAnime : Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.Modèles et entraînementPost-trainingReinforcement Learning+3
1:56:40EN
Cognitive Revolution "How AI Changes Everything"· 8 août 2026PodcastThe Periodic Table Was Already in the WeightsAnime : Nathan LabenzGoodfire CTO Dan Balsam tells Nathan Labenz how concept manifolds, predictive data debugging, and a $1,000-a-month research agent are turning interpretability into a product.Modèles et entraînementModel InterpretabilityIngénierie d’agents+3
2:06:41EN
Cognitive Revolution "How AI Changes Everything"· 9 juil. 2026PodcastZero the J-Space and a Model's Hidden Goal Lights Up on Token OneAnime : Nathan LabenzA weekly Cognitive Revolution cut of Anthropic's global-workspace paper, AI superforecasters, open video world models, and a chip that treats inference as data movement.Modèles et entraînementModel InterpretabilitySécurité et gouvernance+3
50:57EN
Unsupervised Learning: With Jacob Effron· 9 juil. 2026PodcastA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen SchmidhuberAnime : 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.Modèles et entraînementAGIAI research+3
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 4 juil. 2026Podcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipAnime : Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.Modèles et entraînementLocal inferenceScaling Laws+3
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Cognitive Revolution "How AI Changes Everything"· 3 juin 2026PodcastTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.Anime : Nathan LabenzGoogle researcher Ali Behrouz tells Nathan Labenz how stacking update frequencies — not just layers — and an offline sleep phase could give language models genuine continual learning.Modèles et entraînementContinual learningTransformers & attention+3
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Unsupervised Learning: With Jacob Effron· 3 juin 2026PodcastA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still MissAnime : 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.Modèles et entraînementAI researchAgents de code+3
59:41EN
Unsupervised Learning: With Jacob Effron· 22 mai 2026PodcastThe GPT moment for video hasn’t arrived, but AGI may already be hereAnime : Jacob EffronA day after Google I/O 2026, Gemini co-lead Oriol Vinyals argues that world models, file-system memory, and infinite-complexity RL environments will define the next era of frontier models.Modèles et entraînementWorld modelsReinforcement Learning+3
1:21:56EN
Unsupervised Learning: With Jacob Effron· 15 mai 2026PodcastYann LeCun Left Meta Because LLMs Will Not Get You to IntelligenceAnime : 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.Modèles et entraînementWorld modelsAI research+3
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
58:46EN
Unsupervised Learning: With Jacob Effron· 9 avr. 2026PodcastTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028Anime : 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.Modèles et entraînementContinual learningReinforcement Learning+3
1:49:53EN
Cognitive Revolution "How AI Changes Everything"· 5 mars 2026PodcastDon't Fight Backprop: Goodfire's Bet on Designing What Models LearnAnime : 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.Modèles et entraînementModel InterpretabilitySécurité et gouvernance+3
1:34:29EN
Cognitive Revolution "How AI Changes Everything"· 18 févr. 2026PodcastThree IMO Golds Missed the Same Problem. Harmonic Wants Math to CompileAnime : 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.Modèles et entraînementReasoning & test-time computeAI research+3
1:04:51EN
Cognitive Revolution "How AI Changes Everything"· 1 févr. 2026Podcast125 million cells took a decade. The next billion takes monthsAnime : 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.Modèles et entraînementAI for scienceData quality & curation+3
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Lex Fridman· 31 janv. 2026PodcastThe Architecture Barely Changed. Data, Cost, and Open Weights Did.Anime : Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.Modèles et entraînementScaling LawsOpen-weight models+3
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Unsupervised Learning: With Jacob Effron· 29 janv. 2026PodcastA Model That Solves New Math Problems Every Week Still Isn't AGIAnime : 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.Modèles et entraînementReinforcement LearningAGI Timelines+3
2:25:10EN
Cognitive Revolution "How AI Changes Everything"· 22 janv. 2026PodcastFine-Tuning Isn't Dead — But It Turned a Helpful Model EvilAnime : 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.Modèles et entraînementFine-tuningSécurité et gouvernance+3
1:55:12EN
Cognitive Revolution "How AI Changes Everything"· 8 nov. 2025Podcast28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AIAnime : Nathan LabenzLongbeard CEO Matthew Harvey Sanders tells The Cognitive Revolution how a mission-driven team is aligning models to the Catholic magisterium — and why fine-tuning was not enough.Modèles et entraînementGénération augmentée par récupérationFine-tuning+3
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Cognitive Revolution "How AI Changes Everything"· 14 oct. 2025Podcast2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New AntibioticsAnime : Nathan LabenzMIT's Jim Collins tells Nathan Labenz how a bootlegged 2018 project, a binary growth-inhibition label, and Chemprop graph networks pulled novel antibiotics out of chemical space that labs could never screen by hand.Modèles et entraînementAI for scienceDrug Discovery+3
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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
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Cognitive Revolution "How AI Changes Everything"· 25 sept. 2025PodcastEvery payment is a frame in a movie. Stripe’s foundation model took card-testing detection from 59% to 97%Anime : Nathan LabenzEmily Sands, Stripe’s head of data and AI, explains how a domain-specific payments model, shared embeddings, and mixed rules turn a $1.4 trillion network into compounding advantage.Modèles et entraînementIA en financeEmbeddings+3
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Cognitive Revolution "How AI Changes Everything"· 27 août 2025PodcastSAEs Find the Nouns. Parameter Decomposition Looks for the VerbsAnime : Nathan LabenzGoodfire's Lee Sharkey argues that sparse autoencoders recover a network's variables, not the algorithms those variables run, and shows how stochastic parameter decomposition tries to recover the computations themselves.Modèles et entraînementModel InterpretabilityAI research+3
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Unsupervised Learning: With Jacob Effron· 13 août 2025PodcastThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.Anime : Jacob EffronJoshua Meier on three waves of AI drug discovery, why Chai-2 behaves like Photoshop for molecules, and why a 1% hit rate was supposed to be enough to change the industry.Modèles et entraînementAI for scienceComputational Biology+3
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