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1:06:45EN
20VC with Harry Stebbings· 27 jul 2026Pódcast · 2 vocesMatt Murphy on Anthropic, Open Models and the New Venture PlaybookInvitado: Matt Murphy · Presenta: Harry StebbingsThe Menlo Ventures partner explains his investments in Anthropic, Lovable and Legora, and debates AI margins, model competition and venture fund strategy.
40:46EN
No Priors: AI, Machine Learning, Tech, & Startups· 19 dic 2025Pódcast · 2 vocesDoctors Are Rushing to AI. Robotics Will Take a Beating First.Presenta: Sarah Guo, Elad GilSarah Guo and Elad Gil’s 2026 forecast for foundation models, IPOs, robotics, consumer agents, and the bets that are not about AI at all.
2:06:16ZH
Zhang Xiaojun Podcast· 28 nov 2025Pódcast · 2 voces谭捷：机器人通用智能的瓶颈在数据，通用形态仍需时间Invitado: 谭捷 · Presenta: 张小珺Google DeepMind 机器人研究科学家谭捷回顾了从计算机图形学到机器人、从强化学习到 Gemini Robotics 的研究路径。他认为机器人基础模型尚未成为独立学科，数据规模与覆盖度、跨本体迁移、实时推理和安全仍是走向真实应用的关键。
1:14:39EN20VC with Harry Stebbings· 1 sept 2025Pódcast · 2 vocesNick Frosst on Cohere’s Enterprise AI Strategy and the Limits of HypeInvitado: Nick Frosst · Presenta: Harry StebbingsThe Cohere co-founder discusses data, benchmarks, workplace automation and why he challenges popular claims about AGI.
1:03:27EN20VC with Harry Stebbings· 5 may 2025Pódcast · 2 vocesBucky Moore on Venture Platforms, AI and Early-Stage InvestingInvitado: Bucky Moore · Presenta: Harry StebbingsThe new Lightspeed partner discusses capital-intensive model companies, seed valuations, founder selection and the role of large venture firms.
40:58ENNo Priors: AI, Machine Learning, Tech, & Startups· 25 ene 2024Pódcast · 2 voces99% of Factory Robots Are Dumb. Covariant Wants the Smart Ones Working in Warehouses FirstPresenta: Sarah Guo, Elad GilFormer OpenAI researcher Peter Chen explains why robot foundation models have to be trained on production floors, not in labs.
53:37ENNo Priors: AI, Machine Learning, Tech, & Startups· 9 mar 2023Pódcast · 2 voces30 models, 42 scenarios, 7 metrics: Percy Liang's public checkup for language modelsPresenta: Sarah Guo, Elad GilA PubMed-only model once led the U.S. medical licensing exam — until a system roughly 200 times larger overtook it.