Rich Sutton argues that AI must keep learning from experience

In a Sequoia interview, reinforcement-learning pioneer Rich Sutton and Oak co-founder Karam Javed argue that AI systems should keep learning from their own experience after deployment. They revisit Sutton’s Bitter Lesson, challenge synthetic-data-only approaches through the “big world” perspective, and outline research on continual deep learning, learned abstractions, and planning. The discussion matters because it frames a direct alternative to treating ever-larger, frozen language models as a complete model of intelligence.