An exploration of using gzip compression as a language model for text generation. The author demonstrates that gzip can generate text through beam search decoding, showing that compression and prediction are equivalent tasks. While gzip produces repetitive results compared to neural language models, it reveals interesting structural patterns when given proper search horizons.