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2:02:17EN
Cognitive Revolution "How AI Changes Everything"· Aug 27, 2025PodcastSAEs Find the Nouns. Parameter Decomposition Looks for the VerbsHost 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.Models & trainingModel InterpretabilityAI research+3
1:37:05EN
Cognitive Revolution "How AI Changes Everything"· Jun 19, 2025PodcastAn Algebraic Geometer Quit Tenure Because the Bowl-Shaped Loss Plot Is a LieHost 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.Models & trainingModel InterpretabilityML fundamentals+3
2:12:00EN
Cognitive Revolution "How AI Changes Everything"· May 15, 2025PodcastGradient Descent at Test Time: Titans Pushes LLM Context to 10 Million TokensHost Nathan LabenzA Cornell PhD student's neural memory module holds about 70% accuracy where GPT-4's scores fall off a cliff.Models & trainingAgent memoryContext engineering+3
2:33:39EN
Cognitive Revolution "How AI Changes Everything"· Feb 27, 2025PodcastThe Attacker Goes Second: Why Nicholas Carlini Keeps Breaking AI DefensesHost Nathan LabenzA Google DeepMind security researcher on simple loss functions, 70% robust accuracy, and why the fix has to live in the system, not the model.Security & safetyAI securitySafety & governance+3
1:40:22EN
Cognitive Revolution "How AI Changes Everything"· Jan 22, 2025PodcastTwenty-atom crystals taught an AI the physics of a heartbeatHost 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.Models & trainingAI for scienceML fundamentals+3
1:42:16EN
Cognitive Revolution "How AI Changes Everything"· Jul 4, 2024Podcast267 Papers in Seven Months: Albert Gu Explains the State Space Model RevolutionHost Nathan LabenzThe Mamba co-author walks through five years of recurrent-model work, why selective compression beats a growing KV cache, and what Mamba 2 trades away to train faster.Models & trainingTransformers & attentionInference+3
1:54:01EN
Cognitive Revolution "How AI Changes Everything"· Jun 26, 2024PodcastA Tiny Network Grew a Salt Crystal the Training Data Never ShowedHost Nathan LabenzTim Duignan trained tens of thousands of parameters on salt water. The model invented a crystal — and a continuum solvent theory he had spent a PhD failing to write by hand.Models & trainingAI for scienceML fundamentals+3
1:58:43EN
Cognitive Revolution "How AI Changes Everything"· Feb 7, 2024PodcastA Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.Host Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.Models & trainingAI HistoryNeuroscience & AI+3
1:19:24EN
Cognitive Revolution "How AI Changes Everything"· Nov 17, 2023PodcastA Toy Paper Did Not Prove LLMs Cannot Generalize. The Discourse Still Ran With It.Host Nathan LabenzNathan Labenz and Erik Torenberg unpack a viral DeepMind result, a weekend reproduction, and a premature war over voluntary AI commitments.Models & trainingAI researchML fundamentals+3
1:33:56EN
Cognitive Revolution "How AI Changes Everything"· Jul 6, 2023PodcastThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models UnderstandHost Nathan LabenzNathan Labenz spends a solo episode walking through what general-purpose models can do, how they are trained, how capabilities unlock, and whether they understand anything at all.Models & trainingML fundamentalsScaling Laws+3
1:32:22EN
Cognitive Revolution "How AI Changes Everything"· Jun 29, 2023PodcastA Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer AwayHost Nathan LabenzLili Yu of Meta AI explains a multiscale transformer that predicts million-byte sequences, skips tokenization, and aims to model any file as raw bytes.Models & trainingMultimodal AITransformers & attention+3
1:52:46EN
Cognitive Revolution "How AI Changes Everything"· Jun 27, 2023PodcastCharge Neural Nets by Connection Length, and the Black Box Splits Into Modules You Can SeeHost Nathan LabenzMIT physicist Ziming Liu walks Nathan Labenz through BIMT, a brain-inspired training trick that sparsifies networks until you can read them by looking.Models & trainingModel InterpretabilityML fundamentals+3
1:25:50EN
Cognitive Revolution "How AI Changes Everything"· Apr 18, 2023PodcastPrompt Engineering Became Programming, and Riley Goodside Is Fine With ThatHost Nathan LabenzScale AI’s first staff prompt engineer on tool use, fine-tuning without amnesia, generate-then-rank, and why the 2023 job-of-the-future story never arrived.Enterprise & strategyPrompting & in-context learningStructured outputs+3
1:03:10EN
Cognitive Revolution "How AI Changes Everything"PodcastPause Tokens, Analogical Prompts and Ring Attention: A Tour of the Transformer's Next UpgradesHost Nathan LabenzNathan Labenz and Trey Kollmer walk through five recent papers on pausing, backspacing, prompting, streaming and long-context training, and sketch how they might combine into a more capable model.Models & trainingTransformers & attentionML fundamentals+3