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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.
1:37:05ENCognitive 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.
2:12:00ENCognitive 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.
2:33:39ENCognitive Revolution "How AI Changes Everything"· 2025년 2월 27일팟캐스트The Attacker Goes Second: Why Nicholas Carlini Keeps Breaking AI Defenses진행자 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.
1:40:22ENCognitive 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.
1:42:16ENCognitive Revolution "How AI Changes Everything"· 2024년 7월 4일팟캐스트267 Papers in Seven Months: Albert Gu Explains the State Space Model Revolution진행자 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.
1:54:01ENCognitive Revolution "How AI Changes Everything"· 2024년 6월 26일팟캐스트A Tiny Network Grew a Salt Crystal the Training Data Never Showed진행자 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.
1:58:43ENCognitive Revolution "How AI Changes Everything"· 2024년 2월 7일팟캐스트A Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.진행자 Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.
1:19:24ENCognitive Revolution "How AI Changes Everything"· 2023년 11월 17일팟캐스트A Toy Paper Did Not Prove LLMs Cannot Generalize. The Discourse Still Ran With It.진행자 Nathan LabenzNathan Labenz and Erik Torenberg unpack a viral DeepMind result, a weekend reproduction, and a premature war over voluntary AI commitments.
1:33:56ENCognitive Revolution "How AI Changes Everything"· 2023년 7월 6일팟캐스트The AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models Understand진행자 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.
1:32:22ENCognitive Revolution "How AI Changes Everything"· 2023년 6월 29일팟캐스트A Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer Away진행자 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.
1:52:46ENCognitive Revolution "How AI Changes Everything"· 2023년 6월 27일팟캐스트Charge Neural Nets by Connection Length, and the Black Box Splits Into Modules You Can See진행자 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.
1:25:50ENCognitive Revolution "How AI Changes Everything"· 2023년 4월 18일팟캐스트Prompt Engineering Became Programming, and Riley Goodside Is Fine With That진행자 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.
1:03:10ENCognitive Revolution "How AI Changes Everything"팟캐스트Pause Tokens, Analogical Prompts and Ring Attention: A Tour of the Transformer's Next Upgrades진행자 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.