Not sure the current generation of confidently-wrong language models will be of overall good use in summarizing literature, as suggested in the article. Sounds

Not sure the current generation of confidently-wrong language models will be of overall good use in summarizing literature, as suggested in the article. Sounds like the perfect disaster recipe for the "citogenesis" ((C) xkxcd) of spurious facts. Not that they won't be used like that (they probably already are), but that sounds like an expectable outcome, and a net negative to me. There is enough of a replication crisis with things that are stated in published papers already [0], we don't need another one with things that were never originally stated in any papers. One idea that I find interesting is to combine LLMs with formal verification and theorem prover tools like Coq, Lean, etc. Any mistakes by the LLM should be detectable by the verification engine. Maybe this could be useful in automating the currently ongoing efforts of 're-proving' the existing body of mathematical knowledge with theorem provers ('ChatGPT, please take this paper and verify the proofs with Lean'). And who knows, maybe one day the machines will produce some interesting mathematics on their own. Would be curious if anyone has links to works in this direction, or blogs/content by mathematicians discussing this. [0] https://en.wikipedia.org/wiki/Replication_crisis https://en.wikipedia.org/wiki/Replication_crisis