筛选结果
16 篇排序
38:14ENDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Silicon主持 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.
1:10:15ENThe 100x lives between the layers: Dylan Patel on co-design and a 60x yearSemiAnalysis’s founder argues that matching models, kernels, and silicon is what turns a 2x here and a 2x there into 100x, while equivalent-quality inference has gotten about 60 times cheaper in a year.
59:06ENInference Costs Fell 100x. Tri Dao Says There's Another 10x — and NVIDIA's 90% Won't Hold主持 Jacob EffronThe FlashAttention author and Together AI chief scientist on why hardware portability is a myth, how Claude Code made him 1.5x faster, and why workloads will split the chip market.
46:35ENThey trained a real-time video model in 20 hours and skipped the game engineDecart CEO Dean Leitersdorf tells Sequoia how Oasis runs live on H100s, why ChatGPT is a fallen wall rather than a pain point, and why the next trillion-dollar company may be a generated experience.
36:49ENJensen Huang: NVIDIA Is No Longer Building Computers. It Is Building AI Factories主持 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.
39:18ENOpen and Closed Will Tie at the Same Size: PyTorch's Former Lead on Fast InferenceA six-month library swap at Meta became a five-year rebuild. Lin Qiao wants the rest of the industry to get that stack in five weeks.
1:52:18ENTwo Weeks, Thirty Compiles: How Adam Majmudar Wrote a GPU From Scratch主持 Nathan LabenzA Cognitive Revolution walkthrough of TinyGPU, from SIMD kernels and memory latency to an open-source chip flow that runs on a laptop.
1:42:17ENThe Cheapest Inference Provider Is the Most Dangerous主持 Nathan LabenzFireworks AI cofounders Lin Qiao and Dmytro Ivchenko explain why subsidized GPU bills vanish, how LoRA serving can cut cost a hundredfold, and why OpenAI is the rival that actually matters.
38:33ENSpeed Is the Thing You Can Buy: Baseten’s Bet on Inference主持 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.
2:30:06ENTrained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home Turf主持 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.
3:08:46ENWho owns the off switch? George Hotz on tinygrad, open-source AI, and God嘉宾 George Hotz · 主持 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嘉宾 Chris Lattner · 主持 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主持 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嘉宾 Jeremy Howard · 主持 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.
1:01:23ENJensen Huang on AI Factories, Digital Workers and Why the Build-Out Has Barely BegunNvidia's CEO tells a room of institutional investors how accelerated computing led to AI factories, and where agentic AI, robotics and sovereign AI go next.
17:19ENFrom Atoms to Data Centers: How a Modern Processor Finds Parallelism in a Serial Program嘉宾 Jim Keller · 主持 Lex FridmanJim Keller walks through the layers of abstraction in computer design, from transistors to out-of-order execution, branch prediction and deterministic answers.






