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Cognitive Revolution "How AI Changes Everything"· 4. Juli 2026Podcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipModeration: 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. Juni 2026PodcastTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.Moderation: 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.
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Unsupervised Learning: With Jacob Effron· 15. Mai 2026PodcastYann LeCun Left Meta Because LLMs Will Not Get You to IntelligenceModeration: 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.
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Sequoia Capital· 18. Nov. 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.
2:02:17ENCognitive Revolution "How AI Changes Everything"· 27. Aug. 2025PodcastSAEs Find the Nouns. Parameter Decomposition Looks for the VerbsModeration: 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. Mai 2025PodcastWhy Anthropic's first check went to a company building microscopes for neural netsModeration: 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. März 2025PodcastA Year to Grow a Brain Organoid, an Hour to Simulate ItModeration: 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. Jan. 2025PodcastTwenty-atom crystals taught an AI the physics of a heartbeatModeration: 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.
41:42ENSequoia Capital· 22. Okt. 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.
1:42:16ENCognitive Revolution "How AI Changes Everything"· 4. Juli 2024Podcast267 Papers in Seven Months: Albert Gu Explains the State Space Model RevolutionModeration: 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. Juni 2024PodcastA Tiny Network Grew a Salt Crystal the Training Data Never ShowedModeration: 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. Mai 2024PodcastTwo Weeks, Thirty Compiles: How Adam Majmudar Wrote a GPU From ScratchModeration: 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. Apr. 2024PodcastA Gibberish Prompt Unlocks What GPT-J Plans Three Tokens AheadModeration: 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. Dez. 2023PodcastTrained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home TurfModeration: 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.
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No Priors: AI, Machine Learning, Tech, & Startups· 24. Aug. 2023Podcast · 2 StimmenThe Author of Attention Is All You Need Now Compiles mRNA Like BytecodeModeration: 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.
1:40:07ENCognitive Revolution "How AI Changes Everything"· 4. Juli 2023PodcastThirty thousand voltage updates a second: inside Skydio’s autonomy stackModeration: 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. Juni 2023PodcastCharge Neural Nets by Connection Length, and the Black Box Splits Into Modules You Can SeeModeration: 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. März 2023PodcastFreeze the eyes and the brain. Train only the optic nerve.Moderation: 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· 29. Okt. 2022Podcast · 2 StimmenKarpathy Calls Trained Neural Nets Complicated Alien ArtifactsGast: Andrej Karpathy · Moderation: 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.
2:10:08ENLex Fridman· 26. Juli 2022Podcast · 2 StimmenGato Is Only the BeginningGast: Oriol Vinyals · Moderation: Lex FridmanDeepMind's Oriol Vinyals talks with Lex Fridman about generalist agents, thrown-away weights, and whether human-level AGI arrives in his lifetime.
2:45:10ENLex Fridman· 22. Jan. 2022Podcast · 2 StimmenA Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.Gast: Yann Lecun · Moderation: 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.
2:31:57ENLex Fridman· 20. Sept. 2021Podcast · 2 StimmenJay McClelland on How Thought Emerges From Neural NetworksGast: Jay McClelland · Moderation: Lex FridmanThe Stanford cognitive scientist talks with Lex Fridman about connectionism, backpropagation, David Rumelhart, and why intuition discovers what logic later proves.
2:18:29ENLex Fridman· 8. Aug. 2021Podcast · 2 StimmenYour Cortex Is 150,000 Brains Voting on a Coffee CupGast: Jeff Hawkins · Moderation: 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.
2:30:30ENLex Fridman· 31. Juli 2021Podcast · 2 StimmenThe Fallacy of the Successful First StepGast: Ishan Misra · Moderation: 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.Mehr laden24 von 88 angezeigt