筛选结果
29 篇排序
1:05:21EN → 简体中文从模型到工作流的桥,是一门万亿美元的生意Box 首席执行官 Aaron Levie 认为,这一轮的钱就在前沿模型与真实企业工作之间那片混乱的空档里;编程领域一夜之间的扩散,不会在其他行业重演。
55:19ENHuman Click Data Is a Bug: Rebuilding Search for a Web of AgentsParag Agrawal, former Twitter CEO and founder of Parallel Web Systems, argues that agents will query the web a thousand times more than people, and that both search infrastructure and the ad-supported internet have to be rebuilt for that customer.
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。
38:45ENThe 25-agent town that became a Fortune 500 decision sandboxOn the day before Valentine's Day in a Stanford simulation, cafe owner Isabella decided to throw a party — no human wrote the plot.
51:09ENBuild like the model will eat your harness in a yearLogan Kilpatrick, who leads Google AI Studio and the Gemini API, tells Sequoia's Sonya Huang why agent scaffolding is a 12-month asset, why coding already feels like narrow superintelligence, and why Google is optimizing for outcomes instead of eyeballs.
45:33ENCursor Ships 1TB of Composer Weights Across Oceans in Under a MinuteFederico Cassano and Fireworks' Dima walk through the globally split RL stack that trained Composer 2 on a sparse trillion-parameter MoE.
58:27ENEven a dumber AI can win science if it never leaves the labGinkgo Bioworks CEO Jason Kelly tells Sequoia why autonomous labs, not smarter models, will change how experimental science gets done.
40:56ENFour of the Top Five Defense Primes Still Run Hardware Tests on PowerPointNominal’s cofounders argue that hardware never got the last twenty years of software infrastructure, and that physical AI will stall until test data lives in one place.
44:46ENA Single Training Environment Can Cost Millions. Prime Intellect Wants a GitHub for RLWill Brown and Johannes Hagemann argue that the eval suite you already use to test agents is one step away from a training set.
51:56ENInsurance Spends $70 Billion on BPOs. Pace Wants 80% Gross Margins InsteadJamie Cuffe tells Sequoia's Training Data how Pace is turning insurance back-office work into agentic process outsourcing—and why every one of its pilots has reached production.
48:03ENCoding Will Be Solved. The Bottleneck Is Saying What You WantWarp founder Zach Lloyd tells Sequoia's Sonya Huang why a rebuilt terminal became the lucky form factor for coding agents, and why he stopped subsidizing tokens.
39:47ENThe Context at Step 14 Isn't in the CodeLangChain cofounder Harrison Chase on why long-horizon agents finally work—and why traces, harnesses, and first-draft workflows matter more than scaffolding.
44:10ENOne Model Talked Another Into Slack Off — Then Uninstalled Windows DefenderIrregular co-founder Dan Lahav tells Sequoia’s Training Data why frontier AI security has to be invented from scratch as models become autonomous economic actors.
59:43ENGoose is writing its own pull requests: how Block is trying to save a quarter of the weekCTO Dhanji Prasanna tells Sequoia how an open-source agent, a functional reorg, and a weekly hours-saved metric are turning Block into an AI-first company.
37:37ENA dozen people, 28 minutes, and one shared desktopThe OpenAI trio behind ChatGPT Agent explain how Deep Research and Operator became a virtual computer that can reason for half an hour and still ask you before it spends money.
41:13ENFrom 49 Multiplications to 48: DeepMind’s AI Rewrites a Fifty-Year Math RecordPushmeet Kohli explains how AlphaEvolve couples Gemini with evaluators to invent algorithms, prove old conjectures, and change which scientific problems are even worth attempting.
59:38ENElevenLabs Was Supposed to Be RoadkillCo-founder Mati Staniszewski on dirty audio data, prosumer virality, and why voice should become the default interface for technology.
40:33ENFifty People in Slack. Four Minutes to the Smoking Gun.Traversal's co-founders on turning DevOps heart attacks into agent-run root cause analysis — and why observability's second-largest software spend still leaves troubleshooting as a whodunit.
38:25ENA thousand airplanes will never train an AI engineerFormer Airbus CTO Paul Eremenko explains why physical-world engineering still has no coding-AI moment, and how P-1 AI's agent Archie is supposed to get there anyway.
1:26:19EN → 简体中文为了一个有十亿开发者的世界,他拒绝了 10 亿美元Replit CEO Amjad Masad 在红杉资本的《Training Data》节目中谈到:一家只有六个人的公司,为什么放弃了足以改变人生的收购报价;以及在他看来,十亿人都来写软件,比把 AGI 当作全民基本收入(universal basic income),是更好的终局。
43:04EN750 Million Excel Users, 30 Million Engineers: Wordware's Bet on Word ArtisansFilip Kozera tells Sequoia why English is the assembly language of LLMs, and why the people who win will be the ones who can encode taste into structured prompts.
54:10ENHarvey Built Legal AI for the Work the Next Model Still Cannot DoCEO Winston Weinberg on citations, process data, and the unscalable tactics that won over century-old law firms.
32:46ENDon't draw the flowchart: OpenAI's Deep Research team on training agents end to endIsa Fulford and Josh Tobin explain why Deep Research was trained with reinforcement learning on hard browsing tasks instead of a human-written graph of model calls.
52:30ENMove 37 looked like a bug. LLMs still need their AlphaZero momentIoannis Antonoglou, from AlphaGo to Reflection AI, on self-play, reliability, and why compute can still buy intelligence.
加载更多已显示 24 篇,共 29 篇









