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1:47:38EN
Cognitive Revolution "How AI Changes Everything"· Jul 4, 2026Podcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipHost 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.Models & trainingLocal inferenceScaling Laws+3
2:59:44EN
Cognitive Revolution "How AI Changes Everything"· Jun 3, 2026PodcastTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.Host 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.Models & trainingContinual learningTransformers & attention+3
1:21:56EN
Unsupervised Learning: With Jacob Effron· May 15, 2026PodcastYann LeCun Left Meta Because LLMs Will Not Get You to IntelligenceHost Jacob EffronThe Turing Award winner tells Jacob Effron why he spun AMI Labs out of Meta, why JEPA-style world models beat pixel generators, and why he thinks Hinton changed his mind in 2023.Models & trainingWorld modelsAI research+3
41:36EN
Sequoia Capital· Nov 18, 2025PodcastFour Months to Drive Tokyo: How Wayve Bet the Company on One End-to-End NetworkWayve CEO Alex Kendall tells Sequoia’s Training Data why AV 2.0 ditches HD maps and hand-written stacks for a foundation model that can adapt to a new car and a new country in weeks.Models & trainingAutonomous DrivingWorld models+3
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
1:54:08EN
Cognitive Revolution "How AI Changes Everything"· May 29, 2025PodcastWhy Anthropic's first check went to a company building microscopes for neural netsHost 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.Models & trainingModel InterpretabilityAI research+3
1:43:54EN
Cognitive Revolution "How AI Changes Everything"· Mar 23, 2025PodcastA Year to Grow a Brain Organoid, an Hour to Simulate ItHost 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.Models & trainingAI for scienceComputational Biology+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
41:42EN
Sequoia Capital· Oct 22, 2024PodcastNeural Networks Are Still Waiting for Their ThermodynamicsOpenAI researcher Dan Roberts on why physicists keep migrating into AI, and why the field still lacks the equivalent of the ideal gas law.Models & trainingAI researchScaling Laws+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
1:52:18EN
Cognitive Revolution "How AI Changes Everything"· May 6, 2024PodcastTwo Weeks, Thirty Compiles: How Adam Majmudar Wrote a GPU From ScratchHost Nathan LabenzA Cognitive Revolution walkthrough of TinyGPU, from SIMD kernels and memory latency to an open-source chip flow that runs on a laptop.Infrastructure & deploymentGPU programming & kernelsOpen-source ecosystems+2
1:19:24EN
Cognitive Revolution "How AI Changes Everything"· Apr 5, 2024PodcastA Gibberish Prompt Unlocks What GPT-J Plans Three Tokens AheadHost Nathan LabenzNortheastern’s Bau Lab shows that a 40,000-parameter soft prompt can read a model’s future words, and that about ten attention heads carry the task itself.Models & trainingModel InterpretabilityTransformers & attention+3
2:30:06EN
Cognitive Revolution "How AI Changes Everything"· Dec 22, 2023PodcastTrained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home TurfHost Nathan LabenzIn a solo emergency episode, Nathan Labenz argues that Albert Gu and Tri Dao's selective state space model is the first architecture since 2017 that deserves to share the Transformer’s throne.Models & trainingTransformers & attentionAI research+3
35:24EN
No Priors: AI, Machine Learning, Tech, & Startups· Aug 24, 2023Podcast · 2 speakersThe Author of Attention Is All You Need Now Compiles mRNA Like BytecodeHost Sarah Guo, Elad GilJakob Uszkoreit on why Transformers won, why models spend compute on the wrong things, and why drug discovery has to become generation rather than screening.Models & trainingAI for scienceTransformers & attention+2
1:40:07EN
Cognitive Revolution "How AI Changes Everything"· Jul 4, 2023PodcastThirty thousand voltage updates a second: inside Skydio’s autonomy stackHost Nathan LabenzHayk Martiros walks Nathan Labenz through a two-pound drone that sees in every direction, runs more than ten neural nets on board, and will not be weaponized.AgentsRoboticsAutonomous Systems+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
1:21:20EN
Cognitive Revolution "How AI Changes Everything"· Mar 9, 2023PodcastFreeze the eyes and the brain. Train only the optic nerve.Host Nathan LabenzJunnan Li and Dongxu Li tell Nathan Labenz how BLIP cleaned noisy web captions, and how BLIP-2 connected a frozen vision model to a frozen language model in under ten days on one A100.Multimodal & mediaMultimodal AIVision & video+3
3:28:47EN
Lex Fridman· Oct 29, 2022Podcast · 2 speakersKarpathy Calls Trained Neural Nets Complicated Alien ArtifactsGuest Andrej Karpathy · Host Lex FridmanOn Lex Fridman's podcast, Andrej Karpathy refuses the brain analogy, walks the Fermi paradox through Nick Lane's chemistry, and treats the Transformer as a general-purpose differentiable computer.Models & trainingAGIAutonomous Driving+3
2:10:08EN
Lex Fridman· Jul 26, 2022Podcast · 2 speakersGato Is Only the BeginningGuest Oriol Vinyals · Host Lex FridmanDeepMind's Oriol Vinyals talks with Lex Fridman about generalist agents, thrown-away weights, and whether human-level AGI arrives in his lifetime.Models & trainingAGIAI research+3
2:45:10EN
Lex Fridman· Jan 22, 2022Podcast · 2 speakersA Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.Guest Yann Lecun · Host Lex FridmanYann LeCun tells Lex Fridman why self-supervised world models are the missing dark matter of intelligence, and why machines are not even at the level of a house cat.Models & trainingWorld modelsComputer Vision+3
2:31:57EN
Lex Fridman· Sep 20, 2021Podcast · 2 speakersJay McClelland on How Thought Emerges From Neural NetworksGuest Jay McClelland · Host Lex FridmanThe Stanford cognitive scientist talks with Lex Fridman about connectionism, backpropagation, David Rumelhart, and why intuition discovers what logic later proves.Models & trainingML fundamentalsDeep Learning+3
2:18:29EN
Lex Fridman· Aug 8, 2021Podcast · 2 speakersYour Cortex Is 150,000 Brains Voting on a Coffee CupGuest Jeff Hawkins · Host Lex FridmanJeff Hawkins tells Lex Fridman that intelligence is learning a model of the world, the neocortex is tens of thousands of independent maps that vote, and the fastest path to machine intelligence is reverse-engineering that sheet.Models & trainingNeuroscience & AIML fundamentals+3
2:30:30EN
Lex Fridman· Jul 31, 2021Podcast · 2 speakersThe Fallacy of the Successful First StepGuest Ishan Misra · Host Lex FridmanBerkeley's Jitendra Malik explains why computer vision still looks easy, why fully autonomous driving is not near, and what children know that today's networks do not.Models & trainingComputer VisionMultimodal AI+3
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