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1:47:38EN
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.Modelos y entrenamientoLocal inferenceScaling Laws+3
1:13:33EN
Unsupervised Learning: With Jacob Effron· 3 jun 2026PódcastA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still MissPresenta: Jacob EffronThe Attention Is All You Need co-author tells Unsupervised Learning that transformers will probably keep winning — and that they still do not learn the way people do.Modelos y entrenamientoAI researchAgentes de programación+3
4:25:13EN
Lex Fridman· 31 ene 2026PódcastThe Architecture Barely Changed. Data, Cost, and Open Weights Did.Presenta: Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.Modelos y entrenamientoScaling LawsOpen-weight models+3
1:03:00EN
Unsupervised Learning: With Jacob Effron· 29 ene 2026PódcastA Model That Solves New Math Problems Every Week Still Isn't AGIPresenta: Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.Modelos y entrenamientoReinforcement LearningAGI Timelines+3
1:18:05EN
Unsupervised Learning: With Jacob Effron· 18 dic 2025PódcastThe Real Bottleneck in AI Research Is Compute, Not IdeasPresenta: Jacob EffronAfter NeurIPS, Ari Morcos and Rob Toews sit down with Jacob Effron to argue about plateauing models, SSI’s secrecy, OpenAI’s cash burn, and a set of spicy 2026 bets.Empresa y estrategiaAI StrategyScaling Laws+3
1:39:05EN
Cognitive Revolution "How AI Changes Everything"· 29 oct 2025PódcastThe Summer GPT-5 Disappointed Does Not Mean AI Progress Has StalledPresenta: Nathan LabenzNathan Labenz tells Erik Torenberg why the GPT-5 backlash mixed up product mishaps, naming chaos, and a real jump in capabilities.Empresa y estrategiaScaling LawsReasoning & test-time compute+3
1:02:05EN
Unsupervised Learning: With Jacob Effron· 24 sept 2025Pódcast$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the MathPresenta: Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.Empresa y estrategiaAI StrategyAI startups & small teams+3
51:08EN
Unsupervised Learning: With Jacob Effron· 15 abr 2025PódcastThe Transformer Co-Author Who Says Scaling Hit a WallPresenta: Jacob EffronCohere CEO Aidan Gomez tells Redpoint that a $100 million model is still an amnesiac genius, and that enterprise AI money is concentrating in support, research, and the back office.Empresa y estrategiaIA empresarialAI Strategy+3
1:10:23EN
Unsupervised Learning: With Jacob Effron· 17 mar 2025PódcastA Million Tokens per Dollar: Why Noam Shazeer Thinks Inference Compute Is Still UntappedPresenta: Jacob EffronThe Transformer co-inventor and Gemini researcher Jack Rae walk through test-time compute, Ilya Sutskever's AGI critique, and a four-year-old who now lectures his teacher about lizards.Modelos y entrenamientoReasoning & test-time computeScaling Laws+3
48:18EN
Unsupervised Learning: With Jacob Effron· 6 dic 2024PódcastNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of HeadroomPresenta: Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.Modelos y entrenamientoReasoning & test-time computeAGI+3
2:40:58EN
Cognitive Revolution "How AI Changes Everything"· 16 nov 2024PódcastZvi Mowshowitz Still Puts P(doom) at 60%—and Says Not Updating Is Self-DeceptionPresenta: Nathan LabenzA six-month recap with the Don't Worry About the Vase author covering Ilya’s SSI, OpenAI’s o1, Claude’s computer use, the SB 1047 veto, and Trump’s return.Empresa y estrategiaSeguridad y gobernanzaAI Strategy+3
1:18:32EN
Cognitive Revolution "How AI Changes Everything"· 20 sept 2024PódcastA DNA Model That Can Tell Which Genes You Cannot TouchPresenta: Nathan LabenzStanford's Brian Hie walks through hybrid architectures, a genome-scale language model trained only on DNA, and an antibody that binds 25 times tighter than nature.Modelos y entrenamientoAI for scienceComputational Biology+3
1:23:57EN
Cognitive Revolution "How AI Changes Everything"· 4 sept 2024PódcastA Training Run Is a Particle Collider—and the China Contest Is a Fifty-Year RacePresenta: Nathan LabenzSamo Burja tells Nathan Labenz why ChatGPT's virality may have slowed AI science, and why Washington should treat Beijing as an economic rival rather than a military one.Empresa y estrategiaGeopoliticsAI Strategy+3
1:01:55EN
Cognitive Revolution "How AI Changes Everything"· 1 jun 2024PódcastA $9 AI nurse, an 86 on the medical boards, and a 10% extinction linePresenta: Nathan LabenzNathan Labenz’s solo scouting report walks from medical state of the art through how models actually learn, then to live players, scaling trends, and a control plan that still does not exist.Empresa y estrategiaAI StrategyScaling Laws+3
1:01:39EN
Cognitive Revolution "How AI Changes Everything"· 13 abr 2024PódcastGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?Presenta: Nathan LabenzTraining GPT-3 took about a trillion tokens; GPT-4 took about ten trillion. The next jump is a data question as much as a compute one.Modelos y entrenamientoScaling LawsSynthetic data+3
1:19:52EN
Cognitive Revolution "How AI Changes Everything"· 18 oct 2023Pódcast1,000 H100s Take 115 Days; 22,000 Take FivePresenta: Nathan LabenzNathan Labenz and Trey Kollmer walk through cluster math that turns GPT-4-scale training into a weekly experiment, then four papers on search-augmented models, recursive code improvers, spatial maps inside Llama 2, and what networks do when they have no idea.Modelos y entrenamientoAI researchModel Interpretability+3
1:33:56EN
Cognitive Revolution "How AI Changes Everything"· 6 jul 2023PódcastThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models UnderstandPresenta: 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.Modelos y entrenamientoFundamentos de MLScaling Laws+3
1:32:22EN
Cognitive Revolution "How AI Changes Everything"· 29 jun 2023PódcastA Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer AwayPresenta: 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.Modelos y entrenamientoMultimodal AITransformers & attention+3
26:02EN
Lex Fridman· 9 feb 2020PódcastMoore’s Law Is Not Dead—It Is a Cascade of S-CurvesPresenta: Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.Infraestructura y despliegueSemiconductorsScaling Laws+3
1:10:19EN
Unsupervised Learning: With Jacob EffronPódcastThe Robot That Folded the Laundry: Physical Intelligence’s Three FrontiersPresenta: Jacob EffronKarol Hausman and Danny Driess explain how robot foundation models moved from coded primitives to web-scale pretraining, and why performance is now the hard gate.Modelos y entrenamientoRoboticsAI research+3
1:14:59EN
Lenny's PodcastPódcastWhy Anthropic's Ben Mann Thinks the Exponential Hasn't Slowed, and Why He Still Worries About SafetyPresenta: Lenny RachitskyThe Anthropic co-founder on the AI talent war, scaling laws, the economic Turing test, jobs, leaving OpenAI, constitutional AI and how he forecasts the risk of superintelligence.SeguridadSeguridad y gobernanzaAGI Timelines+3
1:19:48EN
Lex FridmanPódcastBigger Models, Cleaner Splits and Human Baselines: Andrew Ng's Practical Recipe for Applied Deep LearningPresenta: Lex FridmanIn a 2016 Deep Learning School talk, Andrew Ng distills lessons from leading Baidu's AI team into a workflow for diagnosing models, handling data and building a career.Modelos y entrenamientoFundamentos de MLDeep Learning+3
1:13:40EN
Unsupervised Learning: With Jacob EffronPódcastThe Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing MomentPresenta: Jacob EffronVincent, a distinguished engineer at Waymo, explains how foundation models became teachers for self-driving, why the long tail and causality are the real frontier, and where robotics still lacks its generalist proof point.Autonomous DrivingRoboticsMultimodal AI+3