Same. I note in-advance that I'm not sure whether you yourself are referring to use of LLM tools in your research or rather the results of your own domain speci

Same. I note in-advance that I'm not sure whether you yourself are referring to use of LLM tools in your research or rather the results of your own domain specific application of deep learning etc -- here, I assume the former. I feel like the common refrain of most LLM success stories over the past year is that these tools are of significantly greater help to specialists with "skin in the game", so to speak, than they are to complete amateurs. I think a lot of complaints about hallucinations reflect the experience of people who aren't working at the edge of a field where they've read all the existing literature and there simply aren't other places to turn for further leads. At the frontier, moreover, the probability that there exists a paper or book that covers the exact combination of topics that interests you is actually rather low; peer discussions are terrific, but everyone is time-starved. Thus I find the synthetic ability of LLMs to tie together one's own field of focus with those you've never thought about or are less familiar with to be of incomparable utility. On top of that, the ability to help formulate potential hypotheses and leads -- where of course you the researcher are ultimately going to carry out the investigation or, in the best case, attempt to replicate results. Conversely, when I'm uncertain of my own conclusions, I often find myself feeding the best LLM I have access to the data I reasoned from to see whether it independently gets to the same place. I'm not concerned about hallucinations because I know there's nobody but me ultimately responsible for error -- and, at the fringe of knowledge, even a total fabrication can inspire a new (correct) approach to the matter at hand. I think if I had to succinctly describe my own experience it would be that I never get stuck any more for days, weeks, months without even a hint of where to turn next. Related, there's an ancient Palantir blog post (2010!) that always stuck in my memory about a chess tournament that allowed computers, grandmasters, amateurs and any combination of the above to enter [0]. At that time, the winning combination turned out to be amateurs with the best workflow for interfacing with machine. The moral of the story is probably still true (workflow is everything), but I think these new tools for the first time are really biased towards experts, i.e. the best workflow now is no longer "content neutral" but always emerges from a particular domain. [0] https://web.archive.org/web/20120916051031/http://www.palantir.com/2010/03/friction-in-human-computer-symbiosis-kasparov-on-chess/ https://web.archive.org/web/20120916051031/http://www.palant...