Cute idea, but about half of these have given me very weird/unrealistic results. For instance this[1] one which, while amusing as hell, isn't exactly convincing. https://i.imgur.com/g5bHmH6.png
I wish researchers were using these examples to further understand what this network does, how it fails and what are its fundamental limitations. However, such digging would undermine the hype, so I'm not particularly hopeful. Most of the issues are just written off as kinks to be ironed out.
Another thing that really bothers me is that no one tries to replicate any of these results without neural networks[1]. To most people here this is the natural result of deep neural networks being the bestest algorithm ever. To me, this indicates that much of the current ML research fails to generate true insight.
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[1] For example, what would GAN-like architecture look with gcForests? No one seems to care about questions like this, even though gcForests have tons of practical advantages over neural nets.
