After the sort of mediocre results of the first attempt to train ERIS-2 on MLP images, I was itching to try a trick I had thought of. I separated the brightness value of each pixel from its color, and fed those values in separately. Otherwise, the two programs are identical.

As I had hoped, this had some very beneficial effects at first, making it easier for the AI to learn sharper edges and more distinct features (especially eyes!). But, bizarrely, it also caused it to occasionally create images that are basically just a single flat color with a little bit of noise, very strange. In addition, it seemed to create less and less interesting images as it continued to train, sadly. An interesting experiment nonetheless, I'll probably be doing this trick on all my AIs from now on. Though I think I have finally reached the very end of what the ERIS architecture is capable of, and so I have almost finished the next generation of AI architecture. It's a lot more sophisticated than ERIS, so I'm excited to see what it will do! As always, see this journal for the full technical rundown of ERIS.

Full training timeline: http://imgur.com/a/bq4au