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__chilldude22__ t1_iw5fah6 wrote

Reply to comment by abc-5233 in Ai art is a mixed bag by Nintell

How would no human artwork input work? The only reason that works for chess is that the rules of the game can be hardcoded into the system and nothing else is needed to learn it. That isn't possible for art, a software that has no idea what the real world looks like won't spontaneously come up with anything resembling it. At best all its paintings would look like Pollock or Mondrian. You'd need at least photographs, usually taken by humans.

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abc-5233 t1_iw5j1sj wrote

I believe is going to come from robot vision. Meaning, a robot with cameras is going to explore the world, finding interesting things, being curious, looking at things in different angles, and in different lighting conditions.

Looking and interacting with paint, pigments and materials.

And this will not be one robot’s experience, but an army of hundreds experiencing the world simultaneously.

Basically, speedrun the process that humans took 5000 years, it will do in one.

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BearStorms t1_iw5ja2b wrote

>How would no human artwork input work?

Just train on the good results of AI produced art.

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AkaneTori t1_iw5x8lu wrote

I imagine the Ship of Theseus is going to become an extremely common comparison in AI development.

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visarga t1_iw90hqd wrote

What would happen if we loop this a few times?

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-ZeroRelevance- t1_iwbijk5 wrote

Artefacts from the original model will be amplified, and the generations will gradually become more divorced from reality with each loop. This can only really be solved with either some kind of teacher agent, or giving the AI much more real training data than synthetic training data.

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visarga t1_iwdz0jc wrote

But if you have a selection process it might become a virtuous cycle. An evolutionary art system based on humans and AI.

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-ZeroRelevance- t1_iwe0va9 wrote

I suppose you could train a GAN to differentiate between real and artificial art, and then only train the next model on the art it thought was real, but it probably won’t mitigate the problem entirely. It’ll definitely help though.

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visarga t1_iwh8n84 wrote

I would first collect examples of frequent issues: double heads, noodle hands, deformities. These are the negative examples. I would collect positive examples from the training set because those images are supposedly normal, but match them as well as possible to the negative examples with cosine similarity. Train a rejection model.

To generate prompts I would finetune gpt-2 on a large collection of prompts crawled from the net. Put the prompts into SD, reject deformed images. Rank the images with an image quality model (probably easy to find), keep only the high quality ones.

You can generate as many images as you like. They would be un-copyrightable because they have been generated end-to-end without human supervision. So just great for making a huge training set for AI art.

You could also replace all known artist names with semantic hashes to keep the capability of selecting styles without needing to name anyone. We would have style codes or style embeddings instead of artist names.

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