The article explores the deep mathematical connection between compression and prediction, showing that minimizing log-loss in probabilistic modeling is equivalent to minimizing encoded bit length via entropy coding. It traces this correspondence from Shannon's classical information theory through adaptive compressors to modern language models, noting that recent LLM results simply instantiate this older principle at scale.
Background
This discussion was sparked by recurring claims on Hacker News and popular 3Blue1Brown videos on entropy and cross-entropy, as well as an ngrok article linking arithmetic coding to language models.
- Source
- Lobsters
- Published
- Aug 15, 2026 at 09:01 PM
- Score
- 6.0 / 10