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1:56:40EN
Cognitive Revolution "How AI Changes Everything"· 2026년 8월 8일팟캐스트The Periodic Table Was Already in the Weights진행자 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.모델과 학습Model Interpretability에이전트 엔지니어링+3
2:06:41EN
Cognitive Revolution "How AI Changes Everything"· 2026년 7월 9일팟캐스트Zero the J-Space and a Model's Hidden Goal Lights Up on Token One진행자 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.모델과 학습Model Interpretability안전과 거버넌스+3
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026년 7월 4일팟캐스트19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chip진행자 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.모델과 학습Local inferenceScaling Laws+3
2:59:44EN
Cognitive Revolution "How AI Changes Everything"· 2026년 6월 3일팟캐스트Two Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.진행자 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.모델과 학습Continual learningTransformers & attention+3
1:48:43EN
Cognitive Revolution "How AI Changes Everything"· 2026년 5월 1일팟캐스트The reward jumped from 3 to 180. Every Hacker News title was a Google layoff.진행자 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.모델과 학습Reinforcement LearningPost-training+3
1:49:53EN
Cognitive Revolution "How AI Changes Everything"· 2026년 3월 5일팟캐스트Don't Fight Backprop: Goodfire's Bet on Designing What Models Learn진행자 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.모델과 학습Model Interpretability안전과 거버넌스+3
1:34:29EN
Cognitive Revolution "How AI Changes Everything"· 2026년 2월 18일팟캐스트Three IMO Golds Missed the Same Problem. Harmonic Wants Math to Compile진행자 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.모델과 학습Reasoning & test-time computeAI research+3
1:04:51EN
Cognitive Revolution "How AI Changes Everything"· 2026년 2월 1일팟캐스트125 million cells took a decade. The next billion takes months진행자 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.모델과 학습AI for scienceData quality & curation+3
2:25:10EN
Cognitive Revolution "How AI Changes Everything"· 2026년 1월 22일팟캐스트Fine-Tuning Isn't Dead — But It Turned a Helpful Model Evil진행자 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.모델과 학습파인튜닝안전과 거버넌스+3
1:55:12EN
Cognitive Revolution "How AI Changes Everything"· 2025년 11월 8일팟캐스트28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AI진행자 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.모델과 학습검색 증강 생성(RAG)파인튜닝+3
1:29:30EN
Cognitive Revolution "How AI Changes Everything"· 2025년 10월 14일팟캐스트2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New Antibiotics진행자 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.모델과 학습AI for scienceDrug Discovery+3
1:01:49EN
Cognitive Revolution "How AI Changes Everything"· 2025년 10월 2일팟캐스트ChatGPT's Co-Creator Left to Put Nature in the Reward Loop진행자 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.모델과 학습AI for scienceReinforcement Learning+3
1:22:07EN
Cognitive Revolution "How AI Changes Everything"· 2025년 9월 25일팟캐스트Every payment is a frame in a movie. Stripe’s foundation model took card-testing detection from 59% to 97%진행자 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.모델과 학습금융 AIEmbeddings+3
2:02:17EN
Cognitive Revolution "How AI Changes Everything"· 2025년 8월 27일팟캐스트SAEs Find the Nouns. Parameter Decomposition Looks for the Verbs진행자 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.모델과 학습Model InterpretabilityAI research+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 2025년 7월 16일팟캐스트Plus Five for Format, Plus Ten if It Compiles진행자 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.모델과 학습파인튜닝Post-training+3
1:42:06EN
Cognitive Revolution "How AI Changes Everything"· 2025년 7월 8일팟캐스트Every Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It Goes진행자 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.모델과 학습Post-trainingData quality & curation+3
1:37:05EN
Cognitive Revolution "How AI Changes Everything"· 2025년 6월 19일팟캐스트An Algebraic Geometer Quit Tenure Because the Bowl-Shaped Loss Plot Is a Lie진행자 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.모델과 학습Model Interpretability머신러닝 기초+3
1:54:08EN
Cognitive Revolution "How AI Changes Everything"· 2025년 5월 29일팟캐스트Why Anthropic's first check went to a company building microscopes for neural nets진행자 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.모델과 학습Model InterpretabilityAI research+3
2:12:00EN
Cognitive Revolution "How AI Changes Everything"· 2025년 5월 15일팟캐스트Gradient Descent at Test Time: Titans Pushes LLM Context to 10 Million Tokens진행자 Nathan LabenzA Cornell PhD student's neural memory module holds about 70% accuracy where GPT-4's scores fall off a cliff.모델과 학습Agent memory컨텍스트 엔지니어링+3
1:14:11EN
Cognitive Revolution "How AI Changes Everything"· 2025년 4월 5일팟캐스트The Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGI진행자 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.모델과 학습Reasoning & test-time computeReinforcement Learning+3
1:43:54EN
Cognitive Revolution "How AI Changes Everything"· 2025년 3월 23일팟캐스트A Year to Grow a Brain Organoid, an Hour to Simulate It진행자 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.모델과 학습AI for scienceComputational Biology+3
1:56:38EN
Cognitive Revolution "How AI Changes Everything"· 2025년 3월 8일팟캐스트o3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligence진행자 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.모델과 학습Reinforcement LearningDistributed training & inference+3
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· 2025년 1월 25일팟캐스트From 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Table진행자 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.모델과 학습Reinforcement LearningReasoning & test-time compute+3
1:40:22EN
Cognitive Revolution "How AI Changes Everything"· 2025년 1월 22일팟캐스트Twenty-atom crystals taught an AI the physics of a heartbeat진행자 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.모델과 학습AI for science머신러닝 기초+3
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