Deep learning models have achieved striking performance across vision, language and time-series tasks, yet their growing depth and parameter counts impose substantial computational and memory demands.

Effective compression is about finding patterns to make data smaller without losing information. When an algorithm or model can accurately guess the next piece of data in a sequence, it shows it’s ...