It’s also programmers who work with average and bad programmers and finally have a way to not waste time with them anymore. I work on the hard stuff, gpt generate the rest (I don’t have to waste time and energy to try to pull dead horses) and my colleagues go do something else. It’s a reality today and will improve further. Sure it cannot do what I do, but that might improve; gpt4 is noticeably better than 3.5 at slightly harder things, especially if you work properly iterative with it and having it fix it’s own errors. But no, it cannot do hard things it never saw; however it can give me all the boilerplate around the hard things so I only have to do the hard things. My days are simply 3-5 in 1 now, as I also don’t have the overhead of explaining jira tasks to others who are never going to really grasp what they are doing anyway.

So I am not average and I am enamoured with gpt, simply because it presents high value to me now, more than some actual real humans. For me that’s enough revolutionary.

It is not just those who are working on hard problems who are of that opinion.

Good luck having a ML model understand a 20 year old undocumented dataformat developed inhouse at a specific research lab to be used in their proprietary systems which are also undocumented and are a part of a spiderweb of interconnected systems at that lab (I have worked at this particular lab).

It will be a long time (if ever) until a ML model will be able to handle these situations (and I hazard a guess that most of the worlds active code is something akin to this).

As a supporting tool for the software engineers working there, sure. Just like a linter.

Very far imo.. I mean it delivers what it is, an average of much content out there.. and it is good at it, yes. So in a way, maybe the better future stack overflow with a nicer interface (however what could it do if there weren't stackoverflow to start with?)

But on the other hand in new uncharted territory, it sometimes fails on the simplest shit: Asked it recently how to do one thing with enlighten (that I knew was possible with tqdm, but was almost sure not possible with enlighten). It just hallucinated up parameters to functions that didn't exist. Several rounds continued where it had that from, if different version. I asked it even for the reference where it meant it had that from.. and it referenced me fully confident a readthedocs url with tqdm and enlighten mixed, that didn't exist.. it is hilarious how it confidenlty can tell you one bullshit answer after the next.. dialogues always "hey are you really sure about xxx, did you look it up" "yeees, very certain, I did!" "But this doesn't exist" "Oooh, Im very sorry, you are correct and I am wrong, the next bullshit answer is: ..."

The history disappeared I hope I get it back once, but the dialogue til getting to "No, it may be not possible with this library" was amazing, I'm really scared for our futures building up on that and what will happen if everything from business presentations to lawyer letter exchanges will build up on that..(:

OK, most of us are average by definition, what's your point again? And - I think if it can replace my average ass it will sooner than you imagine be able to solve Linux Kernel bugs. I just don't see a huge difference in the computation required between CRUD and Kernel development: It's just statistics for the machine.