To be clear, I’m not trying to make the argument that it can only produce exactly what it’s seen, I recognize that this argument is frankly overstated in media. (The interviews with Adam Conover are great examples; he’s not wrong per se, but he does oversimplify things to the point that I think a lot of people misunderstand what’s being discussed)

The ability to recombine what it’s seen in different ways as an emergent property is interesting and provocative, but isn’t really what OP is asking about.

A better example of how LLMs can be useful in research like what OP described would be asking it to coalesce information from multiple existing studies about what properties correlate with superconducting in order to help accelerate research in collaboration with actual material scientists. This is all research that could be done without LLMs, or even without ML, but having a general way to parse and filter these kinds of documents is still incredibly powerful, and will be a sort of force multiplication for these researchers going forward.