Right, but it isn’t legally enough for there to be creativity in the supervision of the mechanical process - that creativity has to take the form of creative elements which survive in some identifiable form in the end product. The technical skill of managing a mechanical process can involve a great deal of creativity, but that doesn’t legally count as “creative” unless that is directly surfaced in the model output

I think the case is the strongest with RLHF - if your model speaks with a distinctive “voice”, and to make it do so you had to carefully craft training data to give it that voice, such that there are obvious similarities (shared turns of speech, etc) between your RLHF training input and the model outputs - that aspect of the model likely is copyrightable. But if you are trying to improve a model’s performance at mathematics problems, then no matter how much creativity you put into choosing training data, it is unlikely identifiable creative elements from the training data survive in the model output, which suggests that creativity didn’t actually make it into the model in the sense relevant to US copyright law