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Unsupervised LearningAuthor: by Redpoint Ventures
We probe the sharpest minds in AI in search for the truth about whats real today, what will be real in the future and what it all means for businesses and the world. If youre a builder, researcher or investor navigating the AI world, this podcast will help you deconstruct and understand the most important breakthroughs and see a clearer picture of reality. Follow this show and consider enabling notifications to stay up to date on our latest episodes. Unsupervised Learning is a podcast by Redpoint Ventures, an early-stage venture capital fund that has invested in companies like Snowflake, Stripe, and Mistral. Hosted by Redpoint investor Jacob Effron alongside Patrick Chase, Jordan Segall and Erica Brescia. Language: en Genres: Technology Contact email: Get it Feed URL: Get it iTunes ID: Get it Trailer: |
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Ep 81: Ex-OpenAI Researcher On Why He Left, His Honest AGI Timeline, & The Limits of Scaling RL
Episode 82
Thursday, 29 January, 2026
This episode features Jerry Tworek, a key architect behind OpenAI's breakthrough reasoning models (o1, o3) and Codex, discussing the current state and future of AI. Jerry explores the real limits and promise of scaling pre-training and reinforcement learning, arguing that while these paradigms deliver predictable improvements, they're fundamentally constrained by data availability and struggle with generalization beyond their training objectives. He reveals his updated belief that continual learning—the ability for models to update themselves based on failure and work through problems autonomously—is necessary for AGI, as current models hit walls and become "hopeless" when stuck. Jerry discusses the convergence of major labs toward similar approaches driven by economic forces, the tension between exploration and exploitation in research, and why he left OpenAI to pursue new research directions. He offers candid insights on the competitive dynamics between labs, the focus required to win in specific domains like coding, what makes great AI researchers, and his surprisingly near-term predictions for robotics (2-3 years) while warning about the societal implications of widespread work automation that we're not adequately preparing for. (0:00) Intro(1:26) Scaling Paradigms in AI(3:36) Challenges in Reinforcement Learning(11:48) AGI Timelines(18:36) Converging Labs(25:05) Jerry’s Departure from OpenAI(31:18) Pivotal Decisions in OpenAI’s Journey(35:06) Balancing Research and Product Development(38:42) The Future of AI Coding(41:33) Specialization vs. Generalization in AI(48:47) Hiring and Building Research Teams(55:21) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint
