Why do you believe reinforcement learning remains indispensable for overcoming the limits of pure pre-training?

Self-supervised pre-training on public internet corpora is essential for broad knowledge acquisition, but it suffers from hallucinations and cannot reliably invent genuinely novel solutions. Grounded reinforcement learning environments, exemplified by our early breakthroughs with AlphaGo and AlphaZero, allow systems to explore hypothesis spaces, self-play, and verify optimal strategies against unambiguous ground truth.