If anything is overhyped in AI it's deep reinforcement learning and its achievements in video games or the millionth GAN that can generate some image. But when it solves a big scientific problem that was considered a decade away, that's pretty magical.
I believe modelling the space of images deserves a bit more appreciation, and the approach is so unexpected - the generator never gets to see a real image.
The GANs are backdooring their way into really interesting outcomes, though. They're fantastic for compression: You compress the hell out of an input image or audio, then use the compressed features as conditioning for the GAN. This works great for super-resolution on images and speech compression.
