Models Are Getting Dumber on Purpose

Reasoning scores are climbing while per-token compute shrinks, but the trade-off is deliberate: labs are sacrificing world knowledge for reasoning skill. Facts take space in weights, rot quickly, and are hard to fix, while procedures compress well and stay fresh. The future points to small, reasoning-focused models running locally, with knowledge supplied by the harness at runtime—a shift that could largely solve hallucination.