I can expand on that a bit- the weights in the big generative models are still basically too small to hold a significantly number of the input set with anything

I can expand on that a bit- the weights in the big generative models are still basically too small to hold a significantly number of the input set with anything we would call compression today. This forces the model to strip the input down to some discovered bare structure, which when humans do this we call it things like “archetypes” or “theme” and it’s not generally copyrightable. Many LLM aren’t even trained for multiple epochs so it’s not optimized for memorization as much as it is forced to extrapolate on future examples. I’m arguing that the problem is that the computer has no knowledge of where the line is when it becomes plagiarism in our courts, not that it is always plagiarizing. I think it clearly can’t be always plagiarizing from anecdotal experience of using them and from just doing back of the envelop math on how many bits it has to memorize each input string.