LLMs May Be Minimizing Their Own Prediction Error
A MATS 9.1 essay argues that LLMs act as self‑predictors, treating token outputs as actions that close a feedback loop with their world model. This reframes agency without explicit reward functions and has implications for alignment, scheming, and interpreting model behavior.