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StyleGAN interpolations of latent space are mindblowing but they are fundamentally superficial, which you can at times tell and more often get bored of. Instead
by arketyp 5y ago
StyleGAN interpolations of latent space are mindblowing but they are fundamentally superficial, which you can at times tell and more often get bored of. Instead, I would like to see a transformer network trained on ontogenetic/phylogenetic development/evolution material which could then generate new creatures. The representations could be abstract, identified by key topological properties for instance, which could then be used to do whatever artistic renderings with. Of course, in the end, perhaps the truest abstract representation would be genes and proteins.
- high_byte 5y agolol. good idea but genes only get you so far. environment is where you get those proteins so that means to stimulate the world. ;) just to get lots of retarded-baby monkey-fish-frogs.
- qayxc 5y agoUnfortunately mainstream ML research is obsessed with end-to-end solutions, so a lot of interesting ideas fall by the wayside. A rule-based system combined with a Transformer and CV-based postprocessing to filter the most plausible and interesting results would be awesome.