[baryphonic]

Going a step further, weights, i.e. coefficients, aren't produced by a person at all – they're produced by machine algorithms. Because a human did not create the weights, the weights have no author. Thus they are ineligible for copyright in the first place and are in the public domain. Whether the model architecture is copyrightable is more of an open question, but I think a solid argument could be that the model architecture is simply a mathematical expression – albeit a complex one –, though Python or other source code is almost certainly copyrighted. But I imagine clean-room methods could avoid problems there, and with much less effort than most software.

IANAL, but I have serious doubts about the applicability of current copyright law to existing AI models. I imagine the courts will decide the same.

[jonpo]

You can say the same about compiled executable code though.

[baryphonic]

Each compiled executable has a one-to-one relation with its source code, which has an author (except for LLM code and/or infinite monkeys). Thus compiled executables are derivative works.

There is an argument also that LLMs are derivative works of the training data, which I'm somewhat sympathetic to, though clearly there's a difference and lots of ambiguity about which contributions to which weights correspond to any particular source work.

Again IANAL, and this is my opinion based on reading the law & precedents. Consult a real copyright attorney for real advice.