Great explanation, but wouldn't it be hard (essentially impossible) to train on "likely things people take pictures of"? The alternative would be "pure static"

Great explanation, but wouldn't it be hard (essentially impossible) to train on "likely things people take pictures of"? The alternative would be "pure static". Though if you tried, my guess would be that it would associate various color-change gradients and frequency of hard edges etc with real photos. If so, if you fed it a real photo and said "interpret", it would just give you the same photo back. If you fed it static, then you'd probably get some kind of abstract art back. The question becomes interesting if you start with "things a baby would see" (probably mostly happy faces and eyes (wonderfully geometric) up close), which would train for certain aspects, and then moved on from there.