Recursive Compression is a foundational mechanism describing how systems reduce complexity into representations and iteratively reuse those representations over time. Through repeated cycles of compression, storage, and recursion, systems generate increasingly efficient internal models, enabling scale, coordination, and intelligence. This process underlies physical, biological, cognitive, and symbolic systems. The paper also examines how degradation of fidelity within this process leads to drift, as systems increasingly operate on representations of prior representations rather than direct inputs from reality.
A. Jacobs (2026) studied this question.