Why We Care About Understanding: Competence through Predictive Compression

The paper explores the link between understanding and compression, arguing that while compression is a useful proxy for robust competence, it is not identical to comprehension. It proposes that true understanding involves a mental model of relational structure that enables prediction, and that this predictive ability underlies compression. The authors further suggest that human understanding is shaped by the need for demonstrability and transmissibility, leading to a preference for principled simplicity.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

• robotics