Meta’s SPICE framework lets AI systems teach themselves to reason

Researchers at Meta FAIR and the National University of Singapore have developed a new reinforcement learning framework for self-improving AI systems. Called Self-Play In Corpus Environments (SPICE), the framework pits two AI agents against each other, creating its own challenges and gradually improving without human supervision.While currently a proof-of-concept, this self-play mechanism could provide a basis for future AI systems that can dynamically adapt to their environments, making them more robust against the unpredictability of real-world applications.The challenge of self-improving AIThe goal of self-improving AI is to create systems that can enhance their capabilities by interacting with their environment. A common approach is reinforcement learning with verifiable rewards (RLVR), where models are rewarded for providing the correct answers to problems. This is often limited by its reliance on human-curated problem sets and domain-specific reward engineering, which makes it di