筛选结果
17 篇排序
1:28:08ENThe same H100 costs 3x at AWS, and a four-month-old lab is catching genes the top sequencers missed主持 Nathan LabenzA Cognitive Revolution weekly briefing on a possible U.S.–China AI hotline, why hyperscalers charge two to three times as much for identical chips, co-writing a novel with frontier models, and an AI loop that re-diagnosed a child a premier prenatal lab had cleared.
1:37:43ENCisco wants two extra network layers so agents can share intent主持 Nathan LabenzVijoy Pandey of Outshift by Cisco argues that superintelligence has to scale out through networks of agents, not just up through bigger models.
2:12:31ENMost Caffeine users have no idea they are on a blockchain主持 Nathan LabenzDFINITY's Dominic Williams tells Nathan Labenz why a tamper-proof, unstoppable cloud is the right backend for AI that writes software from a chat box.
2:06:09ENOne ChatGPT query is a second in the microwave主持 Nathan LabenzAndy Masley walks Nathan Labenz through the energy and water math of AI, from a single prompt to an 80-gigawatt buildout.
1:32:47ENA transformer co-author wants a $160 million model no company owns主持 Nathan LabenzIllia Polosukhin tells Nathan Labenz how NEAR turned a payments headache into a stack for private inference, shared-revenue training, and AI agents that still answer to a court.
3:17:35EN → 简体中文一万条评论与 76 吉瓦闲置容量:四个月起草美国 AI 行动计划主持 Nathan LabenzDean W. Ball 在白宫担任高级 AI 顾问四个月,《行动计划》落地时离开。他讲述了这份待办清单是怎样写成的,而写作地点是一栋连 ChatGPT 都跑不起来的建筑。
1:45:00ENAmerica Holds 45% of the World's Data Centers. Everyone Else Must Build, Buy, or Ally主持 Nathan LabenzAnjney Midha of a16z maps what “sovereign AI” actually means for companies and for countries that will never own the talent, data, and compute frontier.
2:10:07ENA $30,000 Operation Could Knock a $10 Billion Superintelligence Data Center Offline for a Year主持 Nathan LabenzGladstone AI’s Jeremy and Edouard Harris inventory what an American Manhattan Project for superintelligence would actually have to secure — and what it would cost in concrete, supply chains, and civil liberties.
54:55ENNew Jersey Cut Phone Waits from 40 Minutes to 90 Seconds主持 Nathan LabenzGovernor Phil Murphy on the state AI assistant, a Princeton hub, and why he wants the best catcher's mitt in the country when superhuman systems arrive.
2:16:17ENA 10B Model Trained Across Three Continents — and an H200 for $1.49 an Hour主持 Nathan LabenzPrime Intellect's founders lay out a four-step plan to turn spare global GPUs into collectively owned intelligence, and argue that reinforcement learning just made their job easier.
2:11:15ENA 50% Chance of Extinction — and a $50 GPT-4 for Everyone主持 Nathan LabenzEmad Mostaque tells Nathan Labenz why he puts p(doom) at even odds, why a five-watt model changes the energy debate, and how the Intelligent Internet would fund universal basic AI with a Bitcoin-like token.
31:04ENThe Risk Is Not China Copying. It Is America Refusing to Use the Tools主持 Nathan LabenzAt the 2024 Hill & Valley Forum, Alex Wang, Jack Clark, and Andrew Ng tell Senator Cory Booker that Chinese labs are inventing, open-source models are already strong, and the Pentagon’s real AI failure is under-adoption.
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.
1:19:52EN1,000 H100s Take 115 Days; 22,000 Take Five主持 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.
1:01:26ENAlexNet Used Two GPUs. GPT-4 Took Twenty Thousand. The Shortage Will Be Back.主持 Nathan LabenzRun:ai CTO Ronen Dar on filling idle accelerators, why H100s can be cheaper per experiment, and why Llama 2 undercuts compute governance.
1:20:49ENA Wafer-Scale Chip So AI Stops Waiting on Amdahl主持 Nathan LabenzAndrew Feldman, CEO of Cerebras, tells Nathan Labenz why one 2.5-trillion-transistor die, sparse linear algebra, and a 16-machine supercomputer are a better shape than a GPU cluster.









