絞り込み結果
8 件並び順
38:14ENDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Siliconホスト Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.
36:49ENJensen Huang: NVIDIA Is No Longer Building Computers. It Is Building AI Factoriesホスト Sarah Guo, Elad GilOn No Priors, NVIDIA’s CEO walks through hyper Moore’s law, NVLink, a 100,000-GPU cluster stood up in weeks, and why tokens are the new commodity.
38:33ENSpeed Is the Thing You Can Buy: Baseten’s Bet on Inferenceホスト Sarah Guo, Elad GilTuhin Srivastava tells Sarah Guo and Elad Gil why a six-person chatbot company running a billion tokens a day should not be building its own serving stack.
3:08:46ENWho owns the off switch? George Hotz on tinygrad, open-source AI, and Godゲスト George Hotz · ホスト Lex FridmanOn his third Lex Fridman podcast, the comma.ai and tiny corp founder argues that compute, intelligence, and the off switch should live in people's houses, not in a trusted few.
3:34:03ENPython Isn't Finished: Chris Lattner on Mojo and the Hardware Messゲスト Chris Lattner · ホスト Lex FridmanThe LLVM creator returns to Lex Fridman to argue that Python should grow C-like performance instead of forcing people out of the language.
52:11ENJensen Huang: For 25 Years, 99 Percent Were Right. NVIDIA Bet on the 1 Percentホスト Sarah Guo, Elad GilThe NVIDIA CEO tells No Priors how CUDA survived a decade without customers, why the company tries to stay lazy, and what he wants built for drugs and climate.
1:44:11ENA Single GPU Is Enough: Jeremy Howard on Teaching Deep Learningゲスト Jeremy Howard · ホスト Lex FridmanThe fast.ai founder tells Lex Fridman why domain experts, not more papers or more TPUs, will decide whether deep learning actually helps people.
17:19ENFrom Atoms to Data Centers: How a Modern Processor Finds Parallelism in a Serial Programゲスト Jim Keller · ホスト Lex FridmanJim Keller walks through the layers of abstraction in computer design, from transistors to out-of-order execution, branch prediction and deterministic answers.









