The case for simple AI rewards in complex worlds

Sequoia highlights Silver's argument that AI agents need simple objectives in complex worlds, rather than a reward function specifying “science.” In an October 2026 post describing a conversation with Silver, an interviewer says his lab aims to build a “super learner” that discovers knowledge through its own experience. The post also says Silver predicts “true superintelligence” within three years.