Gotta ask. Has anyone worked on image compression using machine learning? (that sounds like an obvious thing to do). It would be funny to end up with an algorithm no one understands.
Given both the financial value of image compression (given the amount of video shoved down the net) and the asymmetry of codec (it's OK to use resources to compress, not so much for decompress), I'd expect some real money to be spent in this area.
Dunno about the state of the art, but pretty much every ml tutorial has a section titled "Image Compression Using Autoencoders" right at the beginning. It's the Hello World of ml. The perceptual quality vs file size curve for such a simple network is pretty mediocre, but I'm sure you could do better if that was your goal.
Tangentially related is the crash bandicoot game on the playstation. The developers figured out that untextured polygons were way faster to draw than textured polygons, and so they made the player character model out of tons of tiny colored polygons rather than fewer larger textured polygons. The result was a significantly better looking graphic for the same rendering time.