[XorNot]

If you distribute a random byte stream, and someone uses that as a one time pad to encrypt a movie, then are you distributing the movie?

The answer is of course not, and the same principle applies if someone uses Stable Diffusion to find a latent space encoding for a copyright image (the 231 byte number - had to go double check what the grid size actually is).

[ifdefdebug]

I think it boils down to one question: can you prompt the model to show mostly unchanged pictures from artists? Then it's definitely problematic. If not, then I don't have enough knowledge of the topic to give a strong opinion. (my previous answer was just an use case that fits your argument)

[XorNot]

I mean no, it doesn't. It's like drawing something in Photoshop which is a copyright'd work: the act of creating it is the violation, it doesn't prove that Photoshop contains the content directly.

The way SD model weights work, if you managed to prompt engineer a recreation of one specific work, it would only have been generated as a product of all the information in the entire training set + noise seed + the prompt. And the prompt wouldn't look anything like a reasonable description of any specific work.

Which is to say, it means nothing because you can equally generate a likeness of works which are known not to be included in the training set (easy, you ask for a latent encoding of the image and it gives you one): equivalent to a JPEG codec.

[ifdefdebug]

> And the prompt wouldn't look anything like a reasonable description of any specific work.

I think this is the most relevant line of your argument. Because if you could just ask it like "show me the latest picture of [artist]" then you'll have a hard time convincing me that this is fundamentally different from a database with a fancy query language and lots of copyrighted work in it.