The article OP linked is inspired by Gzip+Knn paper that was released a few months ago, compression is not intended to make things harder but to extract useful

The article OP linked is inspired by Gzip+Knn paper that was released a few months ago, compression is not intended to make things harder but to extract useful features that can be used by simple algorithms like Knn or SVG etc... For example it would be almost impossible to distinguish cat and dog images by using SVG or Knn directly on the data but it would be much easier if the images were first passed into an image encoder and a small embeddings vector would be used for each one instead. In the article OP linked it doesn't seem that Gzip is very good at extracting useful patterns for the MNIST dataset.