Raw LLM Responses

I'm a writer and an applied mathematician. I know how art and AI both work. I've never really bought any of the other arguments about how training a generative network is somehow fundamentally different than learning to make art or being inspired by the art of others. But you draw such a salient distinction here. The problem isn't the learning process--it's the generation process. Even though the way a generative network learns is not really fundamentally different than how we learn (it's just missing half the process, the negative feedback), the way a generative network generates art means the generated information can only ever be theft. The individual touches a human puts into their art is what allows it to be distinct, even if it is heavily inspired. A generative algorithm cannot possibly do that, so it is always simply grifting. This really should have been something I realized a lot faster, considering how much effort I've spent trying to explain the difference between productive sets and creative sets (and how machines *cannot* access creative sets), but it's just another example of why collaboration and different perspectives are so important. Even if you know the same information, sometimes you need to hear how someone else understands it to really get a grasp on it yourself. Thank you for clearing up that problem for me.