[bhouston]

Deep learning will be a great way to do compression for sure, both for audio, video and images. I could see that one could download "knowledge sets" for these decompressors. Looking at Google Earth, download the supplemental "knowledge set" for overhead shots of cities and country side. Looking at people, download the supplemental "knowledge set" for faces and clothing, etc.

Basically each domain you want to do well in you need a knowledge set that is trained on that data. Then you need a discriminator on the compression side to classify an image or subregions of an image into those categories.

If you can make the knowledge sets downloadable on demand and then cached you can be incredibly efficient over the long term, while maintaining very small initial download sets. I think evolveable knowledge sets over time also ensure that the codex is flexible to handle currently not foreseen situations. Nobody wants a future where are DL-based image/video compression tool only knows a few pre-determined sets and is mediocre on everything else.

[thesz]

The "knowledge set" would be a small matrix - the one that allows to decode whatever encoder has put into compressed data. I guess it will be in volume range of 8x8 16-bit floats or so. Maybe three to six such matrices per channel.