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AlphaGo was trained on millions of professional Go matches. AlphaGo Zero trained purely by playing itself, with no exposure whatsoever to human play; it ended u
by jdietrich 3y ago
AlphaGo was trained on millions of professional Go matches. AlphaGo Zero trained purely by playing itself, with no exposure whatsoever to human play; it ended up being easier to train and much stronger.
I'm not saying that we will soon have a state-of-the-art image generation model that relies on self training, supervised learning or adversarial learning rather than a scraped data set, but I think it's a highly likely outcome within the next few years. Anyone making the argument that AI art is just copying might be in for a rude awakening. If that comes to pass, will you eagerly embrace AI art?
- brucethemoose2 3y agoThats not really equivalent, as image diffusion models are training on "real world" styles and topics, not a constrained game. Additionally, AlphaGo outputs are quantifiably "flawless," whereas GenAI models have all sorts of artifacts and distortion in their output that can't possibly be reliably filtered, even with an army of humans to do it. My experience with ESRGAN is that it really does not like to train on its own output. It amplifies all sorts of wierd artifacts you can barely see I'd you go back and squint at the finetuning dataset. And there was a paper suggesting newer generative models are similar.
- Devasta 3y agoOf course I won't. Art at some level is meant to be communication between the artist and the observer/reader/listener. What communication is there in AI art besides "The algorithm did it"?
- eru 3y agoNot all 'art' does this kind of communication. Sometimes you just need some textures to make your game's level look pretty. Whether you call that art or not is in the eye of the beholder. Compare https://en.wikipedia.org/wiki/Applied_arts https://en.wikipedia.org/wiki/Applied_arts
- numpad0 3y agoThis comment reminded me that AlphaGo exists. …