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Cognitive Revolution "How AI Changes Everything"· 4 jul 2026Pódcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipPresenta: 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.
2:59:44ENCognitive Revolution "How AI Changes Everything"· 3 jun 2026PódcastTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.Presenta: 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.
1:21:56EN
Unsupervised Learning: With Jacob Effron· 15 may 2026PódcastYann LeCun Left Meta Because LLMs Will Not Get You to IntelligencePresenta: 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.
2:02:17ENCognitive Revolution "How AI Changes Everything"· 27 ago 2025PódcastSAEs Find the Nouns. Parameter Decomposition Looks for the VerbsPresenta: 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.
1:54:08ENCognitive Revolution "How AI Changes Everything"· 29 may 2025PódcastWhy Anthropic's first check went to a company building microscopes for neural netsPresenta: 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.
1:43:54ENCognitive Revolution "How AI Changes Everything"· 23 mar 2025PódcastA Year to Grow a Brain Organoid, an Hour to Simulate ItPresenta: 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.
1:40:22ENCognitive Revolution "How AI Changes Everything"· 22 ene 2025PódcastTwenty-atom crystals taught an AI the physics of a heartbeatPresenta: 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"· 4 jul 2024Pódcast267 Papers in Seven Months: Albert Gu Explains the State Space Model RevolutionPresenta: 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"· 26 jun 2024PódcastA Tiny Network Grew a Salt Crystal the Training Data Never ShowedPresenta: 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.
1:52:18ENCognitive Revolution "How AI Changes Everything"· 6 may 2024PódcastTwo Weeks, Thirty Compiles: How Adam Majmudar Wrote a GPU From ScratchPresenta: Nathan LabenzA Cognitive Revolution walkthrough of TinyGPU, from SIMD kernels and memory latency to an open-source chip flow that runs on a laptop.
1:19:24ENCognitive Revolution "How AI Changes Everything"· 5 abr 2024PódcastA Gibberish Prompt Unlocks What GPT-J Plans Three Tokens AheadPresenta: 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.
2:30:06ENCognitive Revolution "How AI Changes Everything"· 22 dic 2023PódcastTrained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home TurfPresenta: 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.
1:40:07ENCognitive Revolution "How AI Changes Everything"· 4 jul 2023PódcastThirty thousand voltage updates a second: inside Skydio’s autonomy stackPresenta: 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.
1:52:46ENCognitive Revolution "How AI Changes Everything"· 27 jun 2023PódcastCharge Neural Nets by Connection Length, and the Black Box Splits Into Modules You Can SeePresenta: 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.
1:21:20ENCognitive Revolution "How AI Changes Everything"· 9 mar 2023PódcastFreeze the eyes and the brain. Train only the optic nerve.Presenta: 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.
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Lex Fridman· 17 ene 2019PódcastDeep Learning at the Edge of 2019: BERT, Autopilot, and the Ideas That Broke ThroughPresenta: Lex FridmanA tour of the architectural, applied, and automation breakthroughs that defined deep learning in 2018 and set up 2019.
1:29:03ENLex Fridman· 27 sept 2016PódcastFrom Word Vectors to Memory Networks: The Building Blocks of Deep NLPPresenta: Lex FridmanRichard Socher explains how word embeddings, recurrent models, GRUs, pointer mixtures, and dynamic memory networks turn language tasks into trainable end-to-end systems.
1:00:51ENLex FridmanPódcastDeep Learning From the Ground Up: Hugo Larochelle's One-Hour Tour of Neural Network FoundationsPresenta: Lex FridmanA fast, equation-level walk through feed-forward networks, backpropagation, practical training tricks, dropout and batch normalization, from the 2016 Deep Learning School.
1:07:29ENLex FridmanPódcastDeep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZeroPresenta: Lex FridmanLex Fridman's MIT 6.S091 opening lecture walks from the basic RL framework through DQN, actor-critic methods and AlphaZero to the unsolved problem of moving from simulation to the real world.
9:59ENLex FridmanPódcastIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine LearningPresenta: Lex FridmanIn a short clip from his 2020 conversation with Lex Fridman, Ilya Sutskever explains why vision, language and reinforcement learning share the same few principles, and why asking which problem is harder is the wrong question.
1:25:16ENLex FridmanPódcastFrom Hand-Built Features to ResNets: Andrej Karpathy's Crash Course in Convolutional NetworksPresenta: Lex FridmanA 2016 Deep Learning School talk covering how convnets work, how the ImageNet winners evolved, and how to apply them without being a hero.
1:24:43ENLex FridmanPódcastFrom Sparse Coding to GANs: A Tour of Unsupervised Deep Learning in 2016Presenta: Lex FridmanRuslan Salakhutdinov walks through autoencoders, Boltzmann machines, variational autoencoders and adversarial networks at the Deep Learning School, with candid notes on what did and did not work.
58:46ENLex FridmanPódcastCaging the Neural Network: How Aptiv Thinks About Safe Self-DrivingPresenta: Lex FridmanAptiv Autonomous Mobility's Karl Iagnemma and Oscar Beijbom explain why end-to-end learning is hard to trust in cars, and show how PointPillars and nuScenes push lidar perception forward.
1:15:59ENLex FridmanPódcastSteering Through Time: How Recurrent Networks and LSTMs Learn from SequencesPresenta: Lex FridmanLex Fridman's MIT 6.S094 lecture walks from backpropagation basics to LSTMs and the way they are used to predict steering in self-driving cars.Cargar másMostrando 24 de 51