I understand Google and Microsoft getting into it as it makes sense as a “better” Google search but for StackOverflow that sounds like they have just given up on their current platform.
Nice choice of logo colors, btw.
Well that explains why they did a 180 on their “no AI” rule, which has the mods in a tizzy.
Who knows, maybe it’ll cut back on the toxicity in the sense that you don’t have to interact with toxic people ¯\_(ツ)_/¯
Like toxic mods
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I look forward to the AI trend fizzling out. It’s only slightly less silly than the cryptocurrency trend was.
AI exists because not everyone frequents a low toxicity forum like Lemmy.
This artificial pseudointelligence exists because there’s the “gee whiz, that’s cool” of a computer talking like a person, and a bunch of hype chasers looking to cash in. Much like cryptocurrency before it, and the dot-com boom before that, there is little substance to it, and most of it will be commercially irrelevant a decade from now.
That would be pretty easy.
return "Why are you even trying to do it this way?\n$link_to_language_spec\nThis should be closed.;Meanwhile language spec:
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Extremely high level description along with some implementation details you don’t care about
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function signature
- extends Object
I love how it was obvious what language I’m talking about without saying anything specific
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Good way to kill your own platform, the whole point is to ask questions to real people
I thought the point was a mental BDSM exercise where you come to others for help and are instead punished for your ignorance.
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I’ve gotten really good results asking chat gpt for programming help. Problem is that it’s wrong like 10% of the time, and when it’s wrong it’s very confidently incorrect. That wasn’t a problem for me because I knew when it was wrong and could course correct it and get the correct solution and it still saved me time and helped me eventually get to the right solution. But if someone who’s still getting started is trying to use chat gpt to learn, they could easily be mislead because they won’t know when its output is wrong.
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Definitely depends on the type of question. I find for documentation type questions I get the 90% good answers, like how do I do something with this library, it’s good, which makes sense because that libraries documentation is probably in the training data. But for more open ended questions, like how do I solve this problem, I see similar performance to what you’re saying. I think it’s a good retrieval and synthesises tool which can really save a ton of time if you already have a high level plan of action and just use it to fill in some specific details.
Agreed. I got ChatGPT to convert python code to JavaScript and I got a buggy code sample back with new bugs.
I’ve found it great for asking documentation questions. It saves me a ton of time having to search through documentation myself. The problem is when it encounters something it doesn’t have information on, it’ll just confidently make shit up, and if you’re not enough of an expert to recognize when that happens, you can be mislead. It still saves me time, but I use it as a recall tool to get me started when I’m learning to do something new, I’d never use the code it puts out without reading through it line by line. I’m also experienced enough to know when it’s wrong and how to refactor its examples. People new to programming could get set down the wrong path by over relying on gpt to teach them.
I feel like a better solution is to have a community answer as generative AI to every new question and have folks upvote or downvote it like normal.
Do we have a term for combination of enshittyfication and LLM?
Maybe add NFTs into the mix too. But don’t tell wsb and the GME gang.
