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52:27EN
Sequoia Capital· 1 sept. 2026PodcastAfter Two Dozen Police Departments Said No, They Built an Anti-Network-Effect AI CompanyA Wisconsin county had 300 gigabytes sitting on a cold case—and Peregrine's founders still refuse to take the credit.SécuritéForward-deployed engineeringCompany Building+3
40:56EN
Sequoia Capital· 10 mars 2026PodcastFour 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.Infrastructure et déploiementData quality & curationObservabilité et fiabilité+3
41:36EN
Sequoia Capital· 18 nov. 2025PodcastFour Months to Drive Tokyo: How Wayve Bet the Company on One End-to-End NetworkWayve CEO Alex Kendall tells Sequoia’s Training Data why AV 2.0 ditches HD maps and hand-written stacks for a foundation model that can adapt to a new car and a new country in weeks.Modèles et entraînementAutonomous DrivingWorld models+3
32:46EN
Sequoia Capital· 25 févr. 2025PodcastDon'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.AgentsIngénierie d’agentsReinforcement Learning+3
59:30EN
Sequoia Capital· 8 oct. 2024PodcastGPT-4 Gets Half Your Data Questions Wrong. Snowflake's Answer Is Systems DesignUsing an off-the-shelf model on enterprise data yields about 45% reliability—one wrong answer out of every two.Entreprise et stratégieIA en entrepriseAI Strategy+3
50:33EN
Sequoia Capital· 20 août 2024PodcastThe 40% data-center save started with an email that ended in a question markPhaidra founder Jim Gao tells Sequoia how an AlphaGo-inspired bet at Google became reinforcement learning that runs billion-dollar plants.Infrastructure et déploiementReinforcement LearningData quality & curation+3
1:00:28EN
Sequoia Capital· 9 juil. 2024PodcastScaling Laws Aren't Done. Don't Lock Yourself Into Yesterday's Architecture.Microsoft CTO Kevin Scott on why the exponential is still compounding, why inference will dwarf training, and why a language model is the world's crappiest database.Entreprise et stratégieScaling LawsInference+3
45:12EN
Sequoia CapitalPodcastInside a Robot Data Factory: How Mecka Sensorizes Humans to Train RobotsMecka AI founder Josh Gao explains how a company collects, quality-checks and licenses egocentric human data, and why robotics will arrive as a steady unlock of tasks rather than a single breakthrough.Modèles et entraînementRoboticsData quality & curation+2