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32:59EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年7月24日播客 · 2 人对谈A Hundred People, a Billion in Revenue, and Zero Venture Money主持 Sarah Guo, Elad GilSurge AI founder Edwin Chen on why quality human data is a poetry problem, not a bounding-box problem, and why leaderboards keep training models to write clickbait.评估与可观测性Data quality & curation人工介入验证+3
45:21EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年6月17日播客 · 2 人对谈Applied Intuition Is Worth $15 Billion, Hasn't Spent Its Capital, and Wants to Be the OS for Cars and Tanks主持 Sarah Guo, Elad GilOn No Priors, Qasar Younis and Peter Ludwig explain the Microsoft playbook for vehicles, why they waited for autonomy techniques to converge, and why Waymo's business model is the question that follows the demo.企业与战略Autonomous DrivingCompany Building+3
44:16EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年9月5日播客 · 2 人对谈A perfect demo is ten years from a product you can pay for主持 Sarah Guo, Elad GilAndrej Karpathy uses Waymo's decade-long gap, Tesla's software bet, and a new AI course to argue that autonomous intelligence will stall at product and globalization, not at the first impressive clip.企业与战略Transformers & attentionScaling Laws+3
39:00EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年5月22日播客 · 2 人对谈JPMorgan Has 150 Petabytes. GPT-4 Trained on Less Than One.主持 Sarah Guo, Elad GilScale AI founder Alexandr Wang tells No Priors why easy internet data is exhausted, why expert-plus-model teams still win, and why the path to AGI looks more like curing cancer than inventing a vaccine.基础设施与部署Data quality & curationPost-training+3
3:11:35EN → 简体中文
Lex Fridman· 2023年6月21日播客 · 2 人对谈搜索一直是个权宜之计:Marc Andreessen 谈 AI、真相与下一代互联网嘉宾 Marc Andreessen · 主持 Lex FridmanLex Fridman 与 Mosaic 联合创作者、Andreessen Horowitz 创始人对谈,追问未来十年 Google 搜索、浏览器和开源 AI 能否延续下去。企业与战略Search & retrievalSynthetic data+3
1:14:34EN → 简体中文
Lenny's Podcast播客 · 2 人对谈训练模型更像调 bug:Karina Nguyen 如何靠合成数据把 Canvas 做出来嘉宾 Karina Nguyen · 主持 Lenny RachitskyOpenAI 研究员讲述合成数据、评估如何变成产品规格,以及模型变聪明之后,人和产品团队还剩哪些本事。产品与体验Post-trainingSynthetic data+3