筛选结果
10 篇排序
48:55EN → 简体中文Anthropic 的开发者平台一年长出三层,token 也有了分工Katelyn Lesse 和 Angela Jiang 在红杉资本(Sequoia Capital)的《Training Data》播客中讲述,Anthropic 如何从无状态的 Messages API,走到知识、执行和协调三层,同时并不打算自己拥有服务器。
2:25:58EN → 简体中文通用人工智能(AGI)已经到来,造出一个英伟达却还没有嘉宾 Jensen Huang · 主持 Lex FridmanLex Fridman 与黄仁勋聊了两个半小时,话题涵盖极致协同设计、CUDA、四条规模定律,以及为什么做一家价值 10 亿美元的 AI 公司,比做一家能长久存续的公司更容易。
44:26EN → 简体中文AI 应用说到底还是应用MongoDB 的 Sahir Azam 向红杉资本解释,为什么向量搜索是处理非结构化数据的一种新基础构件(primitive),而不是事务的替代品;他还解释了为什么检索质量是让 AI 进入保守型企业的最后一公里。
1:10:07ENSame Intelligence, 1% of the Price: Logan Kilpatrick on Gemini Flash主持 Nathan LabenzA former OpenAI developer-relations lead, now the product manager for Google AI Studio, walks through what Gemini 1.5 Flash actually changes for builders.
39:25ENThree Engineers, Three Weeks: The Internal LLM Tool Half of Stripe Uses Every Week主持 Sarah Guo, Elad GilEmily Glassberg Sands, Stripe's head of information, explains how a non-AI company got generative AI into employees' hands, then into Radar, Sigma, and the products customers actually pay for.
32:34ENTen Thousand Certified Engineers in a Year: Google Cloud's Order of Operations for Enterprise AI主持 Sarah Guo, Elad GilKawal Gandhi, head of generative AI in Google Cloud's Office of the CTO, walks Sarah Guo and Elad Gil through dogfooding, the efficiency-productivity-creativity ladder, and why customer weights are the IP that cannot leak.
3:34:03EN → 简体中文Python 还没有完成:Chris Lattner 谈 Mojo 与硬件的乱局嘉宾 Chris Lattner · 主持 Lex FridmanLLVM 的创造者重返 Lex Fridman 的节目,主张 Python 应当获得接近 C 的性能,而非被迫让人离开这门语言。
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.
57:44EN → 简体中文Kevin Scott:把 AI 当作哈希表来用,用别人赚了多少衡量平台嘉宾 Kevin Scott · 主持 Lex Fridman微软 CTO 谈激进市场、数据尊严和邓巴数,以及当只有少数公司决定 AI 用来做什么时,平台为何会失败。
45:00ENAgents Everywhere: OpenAI's Blueprint for Tool Use, Evals, and Computer-Use Infrastructure主持 Jacob EffronOpenAI's API platform team explains how agents are moving from deterministic workflows to reasoning-driven tool use, and what developers still lack.









