Is there room for generative AI in science? I am experimenting with this a lot at https://atomictessellator.com , As a computational chemist I found it difficult just to stay on top of all of the papers that are released, I thought it would be cool to have generative AI attempt to reproduce the experiments using simulation tech. Here's a few cool insights I have uncovered while working on this: - Developer tools are…
I would love a system like ChatGPT but targeted specifically at exploring existing literature. A system that can recommend papers to read, that you can chat with about your problem and can recommend approaches that have worked for others and tell you why. That you can prompt and refine and go into detail with while it helps you figure out what do next based on previous work. That can link you to actual papers to read.
With ChatGPT, I get some of this, but I have to be veeery careful how I use it. It is generally good at discussing points at a high level and helping you sort out some ideas, but when you get into detail it is very easy to catch it making mistakes, and when you ask it for references to read further, it almost always makes up some or all of them. Forget asking it to give you actual links. Maybe some of the other GPT systems targeted at the search space are better at this, I don't know I haven't tried them. But I would love a system that actually does this kind of thing well.
Not just for scientific research -- I've used ChatGPT to help understand some legal things, to help understand some government application procedures (cut through the "consulate speak" and explain some steps to me in my son's visa application in plain language. Of course I double-checked everything it told me.)
Having a system that has "read everything" and can explain it back to you after you ask some questions is just fantastic. I just want it to be more reliable.