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35:39ENCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That RatioAnime : Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.
47:22ENFrom One in a Thousand to 15 Percent: Chai Discovery Treats Drug Design as a Scaling ProblemJoshua Meier and Matthew McPartlon tell Sequoia’s Training Data why antibody design is an engineering problem, not a bespoke science, and why they sell a molecular CAD suite instead of their own drugs.
49:12ENThe People Writing the Transformer’s Eulogy Want a Lab That Can Take Vacation Without Themo1’s reasoning lead and a Gemini pre-training lead argue the architecture, not more scale, is now the bottleneck — and that replacing it starts with automating kernel generation.
1:47:38EN19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipAnime : 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.
1:13:33ENA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still MissAnime : 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.
2:25:58ENAGI Is Already Here. Building NVIDIA Is Not.Invité : Jensen Huang · Anime : Lex FridmanLex Fridman sits down with Jensen Huang for two and a half hours on extreme co-design, CUDA, four scaling laws, and why a $1 billion AI company is easier than a durable one.
4:25:13ENThe Architecture Barely Changed. Data, Cost, and Open Weights Did.Anime : 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.
1:03:00ENA Model That Solves New Math Problems Every Week Still Isn't AGIAnime : 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.
37:00ENThe AlphaChip Team That Laid Out Four TPUs Now Wants Every Company to Be DesignlessAnna Goldie and Azalia Mirhoseini tell Sequoia how an RL floorplanner survived TPU-team anger, learned to draw donut-shaped macros, and became a bet that AI will design chips that then feed AI.
8:16ENAI and Erdős Problem 397: A Verified Proof, Prior Work and the Prospect of Self-ImprovementMatthew Berman · Forward FutureMatthew Berman discusses AI-assisted mathematics and argues that algorithmic discoveries could accelerate AI development, while the history of problem 397 adds important context.
1:18:05ENThe Real Bottleneck in AI Research Is Compute, Not IdeasAnime : 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.
11:50ENOpenAI’s Reported “Code Red” and the Debate Over AI PretrainingMatthew Berman, Ilya Sutskever, Mark Chen · Forward FutureMatthew Berman examines reports of a ChatGPT quality push and a model code-named Garlic, alongside differing views on whether pretraining can keep scaling.
39:16EN500 Gloves, 10 Million Trajectories, and a $10,000 Home RobotAnime : Sarah Guo, Elad GilSunday Robotics co-founders Tony Zhao and Cheng Chi map the gap between a scalable imitation-learning recipe and a machine that actually does the dishes.
1:39:05ENThe Summer GPT-5 Disappointed Does Not Mean AI Progress Has StalledAnime : Nathan LabenzNathan Labenz tells Erik Torenberg why the GPT-5 backlash mixed up product mishaps, naming chaos, and a real jump in capabilities.
41:32ENMoore's Law Is Slowing. Nvidia's CTO Still Wants 10× a YearMichael Kagan on why Nvidia's $7 billion Mellanox deal, not just more transistors, is how you turn a data center into one computer.
1:02:05EN$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the MathAnime : 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.
1:09ENA Discussion of GPT-4.5’s Scaling and TrainingA speaker offers an assessment of GPT-4.5’s cost, speed and alleged training challenges.
2:12:04ENFrom a Five-Year Phone Queue to 480 Trillion Tokens a MonthInvité : Sundar Pichai · Anime : Lex FridmanSundar Pichai talks with Lex Fridman about Chennai, the AI package, Search, Chrome, Waymo, and why he stayed calm when the headlines said Google was finished.
51:08ENThe Transformer Co-Author Who Says Scaling Hit a WallAnime : 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.
1:10:23ENA Million Tokens per Dollar: Why Noam Shazeer Thinks Inference Compute Is Still UntappedAnime : 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.
57:41ENA Hundred Million Cells, Four People, Three Days: Biology's ImageNet MomentAnime : Sarah Guo, Elad GilVevo Therapeutics and the Arc Institute open-sourced Tahoe-100M and a 230-million-cell atlas in the same week — and argued that virtual cells, not just protein folders, are the next language model of biology.
21:10ENSam Altman’s 2025 AI Coding Forecast and Three ObservationsMatthew Berman, Sam Altman · Forward FutureMatthew Berman examines predictions about reasoning models, software agents and AI economics, distinguishing competitive-programming results from broader work.
32:29ENNVIDIA at CES 2025: AI Agents, Cosmos and Project DIGITSMatthew Berman, Jensen Huang · Forward FutureMatthew Berman examines Jensen Huang’s keynote, from neural graphics and AI scaling to a desktop system for local model development.
48:18ENNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of HeadroomAnime : Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.
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