The problem with biotech/pharma is that data processing doesn't work if you lack the data to begin with. There are too many holes in science's understanding of how the cell works, how the organism ages, etc., and LLMs can't easily fill these in. Hypotheses can and will be generated, but it will take great lengths of time and comparatively heroic efforts before the picture becomes much clearer.
The contrast with math and CS couldn't be starker, really. Everything that hinges on formal logic or logical relations is done for.
Hm. I think it depends on two things: (1) how sample-efficient AI can become if CS and mathematics becomes "solved", (2) if AI still sucks on this metric compared to biological brains despite that, can it at least self-play its way to solutions?
Given what AI could do with protein folding, I wouldn't bet on biology being a "no" for AI. It might be, but I wouldn't bet on it.
Likewise, if AI can do mathematics so well it solves "just" all of computer science, let alone other branches of mathematics, if this somehow doesn't lead to AI becoming similarly sample-efficient as biological brains, that's very interesting and will say something nice and surprising about the nature of minds and possibly the nature of being alive.
I think Ai understands biology better than humans because it can correlate everything where humans can never know enough to correlate all. But Ai will not just focus on a solution till it is given a runway to solve and deliver.
There is a lot more data than one individual can process. Is there something that humans can know and it wouldn't, I pretty much doubt it. But can it do experiments that are biological? Yes it can order it I think; it probably knows where its knowledge is ambiguous.