Yup. When I was using it, I don't think it was literally every keystroke but it was something pretty granular so that if your contributors were working on the document it was a nightmare to get anything pushed since it kept changing under your feet and causing conflicts. Finish a merge, and another one is waiting.
I was just about to comment something like: worked fine for me... But then I realised that the only time I did this I was 6+ timezones away from my collaborators.
> I completely agree with that, but the problem is finding a supply of people to argue with on niche subjects.
Beyond just subject-wise, finding people who argue in good faith seems to be an issue too. There are people I'm friends with almost specifically because we're able to consistently have good-faith arguments about our strongly opposing views. It doesn't seem to be a common skill, but perhaps that has something to do with my sample set or my own behaviors in arguments.
I dunno, for more niche computer science or math subjects, I don't feel like people argue in bad faith most of the time. The people I've argued with on the Haskell IRC years ago genuinely believe in what they're saying, even if I don't agree with them (I have a lot of negative opinions on Haskell as a language).
Politically? Yeah, nearly impossible to find anyone who argues in good faith.
Politics and related stuff is what I had in mind, yeah. To a lesser extent technical topics as well. But, I meant "good faith" in the sense of both believing what they're saying and also approaching the argument open to the possibility of being wrong themselves and/or treating you as capable of understanding their point. I've had arguments where the other person definitely believed what they were saying, but didn't think I was capable of understanding their point or being right myself and approached the discussion thusly.
> I'll ask it a question about temporal logic or something, it'll say something that sounds accurate but is ultimately wrong or misleading after looking through traditional documentation, and I can fight with it, and see if it refines it to something correct, which I can then check again, etc. I keep doing this for a bunch of iterations and I end up with a pretty good understanding of the topic.
Interesting, that's the basic process I follow myself when learning without ChatGPT. Comparing my mental representation of the thing I'm learning to existing literature/results, finding the disconnects between the two, reworking my understanding, wash rinse repeat.
I guess a large part of it is just kind of the "rubber duck" thing. My thoughts can be pretty disorganized and hard to follow until I'm forced to articulate them. Finding out why ChatGPT is wrong is useful because it's a rubber duck that I can interrogate, not just talk to.
It can be hard for me to directly figure out when my mental model is wrong on something. I'm sure it happens all the time, but a lot of the time I will think I know something until I feel compelled to prove it to someone, and I'll often find out that I'm wrong.
That's actually happened a bunch of times with ChatGPT, where I think it's wrong until I actually interrogate it, look up a credible source, and realize that my understanding was incorrect.
Soon-to-be grad student here. Could you expand a bit? Is there anything you recommend doing ahead of time to weed out some of these tarpits, or is the already mentioned heuristic the best we've got so far?
I think the best way is to seek out the advice of people familiar with what you're trying to do and learn from their past mistakes/take their thoughts on what is a good it bad idea very seriously. My main problem was that I was branching out into techniques that neither my advisor nor any of his collaborators was familiar with. I underestimated the importance of talking to and learning directly from the people who know how to do it. Later I tried to make contact with some of those people, but had limited success because they are protective of their time and expertise (though if you're lucky you might find someone who's unusually generous).
