[zelphirkalt]

Well, you don't get to pick and choose in which situations an LLM is considered similar to a human being and in which not. If you argue that it similarly to a human is lossy, well let's go ahead and get most output checked by organizations and courts for violations of the law and licenses, just like human work is. Oh wait, I forgot, LLMs are run by companies with too much cash to successfully sue them. I guess we just have to live with it then, what a pity.

[philipkglass]

There are a couple of ways to theoretically prevent copyright violations in output. For closed models that aren't distributed as weights, companies could index perceptual hashes of all the training data at a granular level (like individual paragraphs of text) and check/retry output so that no duplicates or near-duplicates of copyrighted training data ever get served as a response to end users.

Another way would be to train an internal model directly on published works, use that model to generate a corpus of sanitary rewritten/reformatted data about the works still under copyright, then use the sanitized corpus to train a final model. For example, the sanitized corpus might describe the Harry Potter books in minute detail but not contain a single sentence taken from the originals. Models trained that way wouldn't be able to reproduce excerpts from Harry Potter books even if the models were distributed as open weights.

[Workaccount2]

Youtube built probably the most complex and proactive copyright system any organization has ever seen, for the sole purpose of appeasing copyright holders. There is no reason to believe they won't do the same thing for LLM output.