絞り込み結果
100 件並び順
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.
47:07ENGoodfire’s Eric Ho thinks we will decode neural nets by 2028On Sequoia’s Training Data, the interpretability founder argues that sparse autoencoders, model editing, and a third-party lab are how AI stops being grown from data and starts being designed.
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.
48:51ENThe Breakthroughs for AGI Are Already Done, Says OpenAI’s Former Research HeadBob McGrew tells Sequoia’s Training Data that 2025 is the year of reasoning, agents will be priced at the cost of compute, and nothing fundamental will be added to the stack by 2035.
37:45ENCodex Is a Thought Experiment: What If the Agent Worked on Its Own Computer?OpenAI’s Codex team on training o3 to write mergeable PRs, running four copies of a 1 a.m. bug, and why the product only clicks once you stop pairing and start delegating.
53:51ENVeo 3 Took First Place by Beating Veo 2. Google Labs Says Chapter Two Just StartedThree Google Labs leads walk through generative cameras, background computer-use agents, and notebooks that adapt knowledge for an audience of one.
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.
42:05ENAI Can Prep the Meeting in 30 Seconds. It Still Can't Sign the Contract.Gong founder Amit Bendov on why sales AI will eat admin work, not the close, and why CRM is not going anywhere.
47:49ENWorkday Is Onboarding AI Agents the Way It Onboards PeopleWorkday CEO Carl Eschenbach on turning a 70-million-person system of record into the ledger for a mixed workforce of humans and digital workers.
55:40ENTo Solve All Diseases, Isomorphic Labs Needs a Half-Dozen AlphaFoldsMax Jaderberg on turning DeepMind's game-playing research into a general AI engine for drug design—and why prediction alone cannot search a 10^60 molecular universe.
45:30ENA $20,000 AI Agent Replacing a $90,000 SDR: Manny Medina on Pricing in the Agent EraA fully loaded human SDR costs $70,000 to $90,000 a year; one AI SDR pitch is $20,000 per agent for 80% of the work, plus a bonus when targets are hit.
58:11ENPatrick Hsu Wants an App Store for Biology, Not Just Better DrugsThe Arc Institute co-founder argues that Evo 2, trained on genomes rather than proteins, should underpin tools for every step of the scientific method.
1:26:19ENHe turned down a billion dollars for a world with a billion developersReplit CEO Amjad Masad tells Sequoia’s Training Data why a six-person company walked away from a life-changing offer, and why a billion people writing software is a better end state than AGI as universal basic income.
1:11:05ENThe Man Who Took HubSpot CRM to $40 Million Says the Data Model Has to Be Thrown OutDay.ai founder Christopher O’Donnell tells Sequoia’s Pat Grady why classic CRM is compressed pixel art, why full self-driving scared his users, and why every line of code has to make every other line more valuable.
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.
51:16ENGoogle Labs Pops Champagne at 10,000 Weekly UsersJosh Woodward on fifty-day sprints, fading paragraph prompts, and why a number Search would never notice is the point of an AI incubator.
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.
1:04:52ENThe Consumer Playbook That Put Medical AI in 100,000 Exam RoomsOpenEvidence CEO Daniel Nadler explains how a free App Store product, trained only on peer-reviewed literature, reached as much as a quarter of U.S. physicians in a year.
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.
1:00:09ENDeepSeek's Jailbreaks Don't Matter. Giving the Model Arms and Legs DoesPalo Alto Networks CEO Nikesh Arora tells Sequoia's Training Data why cheap brains scramble the AI order, why attackers already move faster than defenders, and why refusing to experiment is the real risk.
44:26ENAn AI Application Is Still an ApplicationMongoDB's Sahir Azam tells Sequoia why vector search is a new primitive for unstructured data, not a replacement for transactions, and why retrieval quality is the last mile that gets AI into conservative enterprises.
54:47ENNinety Thousand Games a Day: Roblox's Bet That AI Should Wash the DishesStef Corazza, head of generative AI at Roblox, tells Sequoia how a free Studio assistant, a community data bargain, and a 3D foundation model are meant to teach AI game development.
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