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59 篇
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1:56:40EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月8日播客The Periodic Table Was Already in the Weights主持 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.模型与训练Model Interpretability智能体工程+3
2:06:41EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月9日播客Zero the J-Space and a Model's Hidden Goal Lights Up on Token One主持 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.模型与训练Model Interpretability安全与治理+3
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月4日播客19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chip主持 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.模型与训练Local inferenceScaling Laws+3
2:59:44EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月3日播客Two Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.主持 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.模型与训练Continual learningTransformers & attention+3
1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 2026年5月1日播客The reward jumped from 3 to 180. Every Hacker News title was a Google layoff.主持 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.模型与训练Reinforcement LearningPost-training+3
1:49:53EN
Cognitive Revolution "How AI Changes Everything"· 2026年3月5日播客Don't Fight Backprop: Goodfire's Bet on Designing What Models Learn主持 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.模型与训练Model Interpretability安全与治理+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
1:04:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月1日播客125 million cells took a decade. The next billion takes months主持 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.模型与训练AI for scienceData quality & curation+3
2:25:10EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月22日播客Fine-Tuning Isn't Dead — But It Turned a Helpful Model Evil主持 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.模型与训练微调安全与治理+3
1:55:12EN
Cognitive Revolution "How AI Changes Everything"· 2025年11月8日播客28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AI主持 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.模型与训练检索增强生成微调+3
1:29:30EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月14日播客2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New Antibiotics主持 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.模型与训练AI for scienceDrug Discovery+3
1:01:49EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月2日播客ChatGPT's Co-Creator Left to Put Nature in the Reward Loop主持 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.模型与训练AI for scienceReinforcement Learning+3
1:22:07EN
Cognitive Revolution "How AI Changes Everything"· 2025年9月25日播客Every payment is a frame in a movie. Stripe’s foundation model took card-testing detection from 59% to 97%主持 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.模型与训练金融 AIEmbeddings+3
2:02:17EN
Cognitive Revolution "How AI Changes Everything"· 2025年8月27日播客SAEs Find the Nouns. Parameter Decomposition Looks for the Verbs主持 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.模型与训练Model InterpretabilityAI research+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月16日播客Plus Five for Format, Plus Ten if It Compiles主持 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.模型与训练微调Post-training+3
1:42:06EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月8日播客Every Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It Goes主持 Nathan LabenzLabelbox CEO Manu Sharma on the $15 billion Scale deal, RL “gyms,” $250,000 trainers, and why post-training now eats the budget that used to belong to pre-training.模型与训练Post-trainingData quality & curation+3
1:37:05EN
Cognitive Revolution "How AI Changes Everything"· 2025年6月19日播客An Algebraic Geometer Quit Tenure Because the Bowl-Shaped Loss Plot Is a Lie主持 Nathan LabenzJesse Hoogland and Daniel Murfet of Timaeus argue that singularities in the loss landscape — not the smooth valleys in every slide deck — are what actually govern how neural networks learn, generalize, and go wrong.模型与训练Model Interpretability机器学习基础+3
1:54:08EN
Cognitive Revolution "How AI Changes Everything"· 2025年5月29日播客Why Anthropic's first check went to a company building microscopes for neural nets主持 Nathan LabenzGoodfire's Dan Balsam and Tom McGrath argue that mechanistic interpretability now has a proto-paradigm, two stubborn gaps, and three products worth shipping today.模型与训练Model InterpretabilityAI research+3
2:12:00EN
Cognitive Revolution "How AI Changes Everything"· 2025年5月15日播客Gradient Descent at Test Time: Titans Pushes LLM Context to 10 Million Tokens主持 Nathan LabenzA Cornell PhD student's neural memory module holds about 70% accuracy where GPT-4's scores fall off a cliff.模型与训练Agent memory上下文工程+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
1:43:54EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月23日播客A Year to Grow a Brain Organoid, an Hour to Simulate It主持 Nathan LabenzStanford postdoc Siyu He tells Nathan Labenz how Squidiff and CORAL move single-cell and spatial experiments into the computer — and where the models still cannot go.模型与训练AI for scienceComputational Biology+3
1:56:38EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月8日播客o3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligence主持 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.模型与训练Reinforcement LearningDistributed training & inference+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
1:40:22EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月22日播客Twenty-atom crystals taught an AI the physics of a heartbeat主持 Nathan LabenzOrbital Materials' Jonathan Godwin and Tim Duignan tell Nathan Labenz how a neural network trained on tiny crystals simulated a potassium ion channel on a single 2017 GPU.模型与训练AI for science机器学习基础+3
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