Does SD have to recreate the entire image for it to violate copyright?

As a thought experiment, imagine a variant of something like SD was used for music generation rather than images. It was trained on all music on spotify and it is marketed as a paid tool for producers and artists. If the model reproduces specific sounds from certain songs, e.g. the specific beat from a song, hook, or melody, it would seem pretty straightforward that the generated content was derivative, even though only a feature of it was precisely reproduced. I could be wrong but as far as i am aware you need to get permission to use samples. Even if the content is not published those sounds are being sold by the company as inspiration, and therefore that should violate copyright. The training data is paramount because if you trained the model on stuff you generated yourself or on stuff with appropriate CC license, the resulting work would not violate copyright, or you could at least argue independent creation.

In the feature space of images and art, SD is doing something very similar, so i can see the argument that it violates copyright even without reproducing the whole training data.

Overall, i think we will ultimately need to decide how we want these technologies used, what restrictions should be on the training data, etc, and then create new laws specifically for the new technology, rather than trying to shoehorn it into existing copyright law.

Do you know that the final trained model is only 2GB? There is no way it can reproduce anything verbatim. There is also Riffusion that can generate music after being trained on FFTs of music.

I think there's a chance they might be able to recreate some simpler work if they make the prompts specific enough. When you set up a prompt you're essentially telling the system what you want it to generate - if you prompt it with enough specificity you might be able to just recreate the image you had.

Kind of like recreating your image one object at a time. It might not be exact, but close enough.

People have tried, unless the thing you want to recreat has been seen by it a lot (over trained) you won't get the same image. You don't have that much fine grained control via text only.

Best you can do is to mask and keep inpainting the area that looks different until it doesn't.

> if you prompt it with enough specificity you might be able to just recreate the image you had

At some point the input must be considered part of the work. At the limit you could just describe every pixel, but that certainly wouldn’t mean the model contained the work.