GLM-5.2 compressed losslessly to use 25% less memory in new experiment

Researcher Brian Bell published an experiment demonstrating lossless compression of the GLM-5.2 language model's weights, achieving a 25% reduction in memory usage. The technique compresses neural network weights without degrading model accuracy. The project is hosted on GitHub and has sparked discussion in the Hacker News community.