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59 件
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1:56:40EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月8日ポッドキャストThe Periodic Table Was Already in the Weightsホスト 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.モデルと学習Model Interpretabilityエージェント工学+3
2:06:41EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月9日ポッドキャストZero the J-Space and a Model's Hidden Goal Lights Up on Token Oneホスト 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.モデルと学習Model Interpretability安全性とガバナンス+3
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月4日ポッドキャスト19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chipホスト 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.モデルと学習Local inferenceScaling Laws+3
2:59:44EN
Cognitive Revolution "How AI Changes Everything"· 2026年6月3日ポッドキャストTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.ホスト 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.モデルと学習Continual learningTransformers & attention+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
1:49:53EN
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
1:34:29EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月18日ポッドキャストThree IMO Golds Missed the Same Problem. Harmonic Wants Math to Compileホスト 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.モデルと学習Reasoning & test-time computeAI research+3
1:04:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月1日ポッドキャスト125 million cells took a decade. The next billion takes monthsホスト 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.モデルと学習AI for scienceData quality & curation+3
2:25:10EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月22日ポッドキャストFine-Tuning Isn't Dead — But It Turned a Helpful Model Evilホスト 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.モデルと学習ファインチューニング安全性とガバナンス+3
1:55:12EN
Cognitive Revolution "How AI Changes Everything"· 2025年11月8日ポッドキャスト28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AIホスト 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.モデルと学習検索拡張生成(RAG)ファインチューニング+3
1:29:30EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月14日ポッドキャスト2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New Antibioticsホスト 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.モデルと学習AI for scienceDrug Discovery+3
1:01:49EN
Cognitive Revolution "How AI Changes Everything"· 2025年10月2日ポッドキャストChatGPT's Co-Creator Left to Put Nature in the Reward Loopホスト 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.モデルと学習AI for scienceReinforcement Learning+3
1:22:07EN
Cognitive Revolution "How AI Changes Everything"· 2025年9月25日ポッドキャストEvery payment is a frame in a movie. Stripe’s foundation model took card-testing detection from 59% to 97%ホスト 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.モデルと学習金融 AIEmbeddings+3
2:02:17EN
Cognitive Revolution "How AI Changes Everything"· 2025年8月27日ポッドキャストSAEs Find the Nouns. Parameter Decomposition Looks for the Verbsホスト 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.モデルと学習Model InterpretabilityAI research+3
38:10EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月16日ポッドキャストPlus Five for Format, Plus Ten if It Compilesホスト 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.モデルと学習ファインチューニングPost-training+3
1:42:06EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月8日ポッドキャストEvery Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It Goesホスト 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.モデルと学習Post-trainingData quality & curation+3
1:37:05EN
Cognitive Revolution "How AI Changes Everything"· 2025年6月19日ポッドキャストAn Algebraic Geometer Quit Tenure Because the Bowl-Shaped Loss Plot Is a Lieホスト 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.モデルと学習Model Interpretability機械学習の基礎+3
1:54:08EN
Cognitive Revolution "How AI Changes Everything"· 2025年5月29日ポッドキャストWhy Anthropic's first check went to a company building microscopes for neural netsホスト 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.モデルと学習Model InterpretabilityAI research+3
2:12:00EN
Cognitive Revolution "How AI Changes Everything"· 2025年5月15日ポッドキャストGradient Descent at Test Time: Titans Pushes LLM Context to 10 Million Tokensホスト Nathan LabenzA Cornell PhD student's neural memory module holds about 70% accuracy where GPT-4's scores fall off a cliff.モデルと学習Agent memoryコンテキストエンジニアリング+3
1:14:11EN
Cognitive Revolution "How AI Changes Everything"· 2025年4月5日ポッドキャストThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGIホスト 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.モデルと学習Reasoning & test-time computeReinforcement Learning+3
1:43:54EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月23日ポッドキャストA Year to Grow a Brain Organoid, an Hour to Simulate Itホスト 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.モデルと学習AI for scienceComputational Biology+3
1:56:38EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月8日ポッドキャストo3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligenceホスト 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.モデルと学習Reinforcement LearningDistributed training & inference+3
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月25日ポッドキャストFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Tableホスト 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.モデルと学習Reinforcement LearningReasoning & test-time compute+3
1:40:22EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月22日ポッドキャストTwenty-atom crystals taught an AI the physics of a heartbeatホスト 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.モデルと学習AI for science機械学習の基礎+3
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