3 ms·

> Coding AIs design software better than me, review code better than me, find hard-to-find bugs better than me, plan long-running projects better than me, make

by bigstrat2003 10mo ago

> Coding AIs design software better than me, review code better than me, find hard-to-find bugs better than me, plan long-running projects better than me, make decisions based on research, literature, and also the state of our projects better than me. That is just not true, assuming you have a modicum of competence (which I assume you do). AIs suck at all these tasks; they are not even as good as an inexperienced human.

gentooflux 10mo ago
LLMs generate the most likely code given the problem they're presented and everything they've been trained on, they don't actually understand how (or even if) it works. I only ever get away with that when I'm writing a parser.
- chii 10mo ago
  > they don't actually understand how but if it empirically works, does it matter if the "intelligence" doesn't "understand" it? Does a chess engine "understand" the moves it makes?
  - jvanderbot 10mo ago
    This is a semantic dead end when discussing results and career choices
  - goatlover 10mo ago
    It matters if AGI is the goal. If it remains a tool to make workers more productive, then it doesn't need to truly understand, since the humans using the tools understand. I'm of the opinion AI should have stood for Augmented (Human) Intelligence outside of science fiction. I believe that's what early pioneers like Douglas Engalbert thought. Clearly that's what Steve Jobs and Alan Kay thought computing was for.
    - victorbjorklund 10mo ago
      AGI is such a meaningless concept. We can’t even fully design what human intelligence is (and when a human fails it meaning they lack human intelligence). It’s just philosophy.
    - theshrike79 10mo ago
      AGI is about as well defined as "full self-driving" :D It's an useless philosophical discussion.
  - gentooflux 10mo ago
    If it empirically works, then sure. If instead every single solution it provides beyond a few trivial lines falls somewhere between "just a little bit off" and "relies entirely on core library functionality that doesn't actually exist" then I'd say it does matter and it's only slightly better than an opaque box that spouts random nonsense (which will soon include ads).
    - simonw 10mo ago
      Those are 2024-era criticisms of LLMs for code. Late 2025 models very rarely hallucinate nonexistent core library functionality - and they run inside coding agent harnesses so if they DO they notice that the code doesn't work and fix it.
      - mrwrong 10mo ago
        get ready to tick those numbers over to 2026!
    - theshrike79 10mo ago
      This sounds like you're copy-pasting code from ChatGPT's web interface, which is very 2024. Agentic LLMs will notice if something is crap and won't compile and will retry, use the tools they have available to figure out what's the correct way, edit and retry again.
embedding-shape 10mo ago
For all we know, you both could comparing using a Nokia 3310 and a workstation PC based on the hardware, but you both just say "this computer is better than that computer". There are a ton of models out there, ran in a ton of different ways, that can be used in different ways with different harnesses, and people use different workflows. There is just so many variables involved, that I don't think it's neither fair nor accurate for anyone to claim "This is obviously better" or "This is obviously impossible". I've been in situations where I hit my head against some hard to find bug for days, then I put "AI" (but what? No one knows) to it and it solves it in 20 minutes. I've also asked "AI" to do trivial work that it still somehow fucked up, even if I could probably have asked a non-programmer friend to do it and they'd be able to. The variance is great, and the fact that system/developer/user prompts matter a lot for what the responses you get, makes it even harder to fairly compare things like this without having the actual chat logs in front of you.
- mrwrong 10mo ago
  > The variance is great this strikes me as a very important thing to reflect on. when the automobile was invented, was the apparent benefit so incredibly variable?
  - throw4847285 10mo ago
    Is this a trick question? Yes it was. A horse could go over any terrain while a car could only really go over very specific terrain designed for it. We had to terraform the world in order to make the automobile so beneficial. And it turned out that this terraforming had many unintended consequences. It's actually a pretty apt comparison to LLMs.
    - mrwrong 10mo ago
      who would I be trying to trick if it was? you didn't answer the question anyways. I'm not wondering whether cars were seen as strictly better than horses in all situations. I'm wondering if people disagreed so vehemently about whether cars were faster road transportation than horses
lelanthran 10mo ago
Depends on how he defined "better". If he uses the word "better" to mean "good enough to not fail immediately, and done in 1/10th of the time", then he's correct.

gentooflux 10mo ago

LLMs generate the most likely code given the problem they're presented and everything they've been trained on, they don't actually understand how (or even if) it works. I only ever get away with that when I'm writing a parser.

chii 10mo ago
> they don't actually understand how but if it empirically works, does it matter if the "intelligence" doesn't "understand" it? Does a chess engine "understand" the moves it makes?
- jvanderbot 10mo ago
  This is a semantic dead end when discussing results and career choices
- goatlover 10mo ago
  It matters if AGI is the goal. If it remains a tool to make workers more productive, then it doesn't need to truly understand, since the humans using the tools understand. I'm of the opinion AI should have stood for Augmented (Human) Intelligence outside of science fiction. I believe that's what early pioneers like Douglas Engalbert thought. Clearly that's what Steve Jobs and Alan Kay thought computing was for.
  - victorbjorklund 10mo ago
    AGI is such a meaningless concept. We can’t even fully design what human intelligence is (and when a human fails it meaning they lack human intelligence). It’s just philosophy.
  - theshrike79 10mo ago
    AGI is about as well defined as "full self-driving" :D It's an useless philosophical discussion.
- gentooflux 10mo ago
  If it empirically works, then sure. If instead every single solution it provides beyond a few trivial lines falls somewhere between "just a little bit off" and "relies entirely on core library functionality that doesn't actually exist" then I'd say it does matter and it's only slightly better than an opaque box that spouts random nonsense (which will soon include ads).
  - simonw 10mo ago
    Those are 2024-era criticisms of LLMs for code. Late 2025 models very rarely hallucinate nonexistent core library functionality - and they run inside coding agent harnesses so if they DO they notice that the code doesn't work and fix it.
    - mrwrong 10mo ago
      get ready to tick those numbers over to 2026!
  - theshrike79 10mo ago
    This sounds like you're copy-pasting code from ChatGPT's web interface, which is very 2024. Agentic LLMs will notice if something is crap and won't compile and will retry, use the tools they have available to figure out what's the correct way, edit and retry again.

embedding-shape 10mo ago

For all we know, you both could comparing using a Nokia 3310 and a workstation PC based on the hardware, but you both just say "this computer is better than that computer". There are a ton of models out there, ran in a ton of different ways, that can be used in different ways with different harnesses, and people use different workflows. There is just so many variables involved, that I don't think it's neither fair nor accurate for anyone to claim "This is obviously better" or "This is obviously impossible". I've been in situations where I hit my head against some hard to find bug for days, then I put "AI" (but what? No one knows) to it and it solves it in 20 minutes. I've also asked "AI" to do trivial work that it still somehow fucked up, even if I could probably have asked a non-programmer friend to do it and they'd be able to. The variance is great, and the fact that system/developer/user prompts matter a lot for what the responses you get, makes it even harder to fairly compare things like this without having the actual chat logs in front of you.

mrwrong 10mo ago
> The variance is great this strikes me as a very important thing to reflect on. when the automobile was invented, was the apparent benefit so incredibly variable?
- throw4847285 10mo ago
  Is this a trick question? Yes it was. A horse could go over any terrain while a car could only really go over very specific terrain designed for it. We had to terraform the world in order to make the automobile so beneficial. And it turned out that this terraforming had many unintended consequences. It's actually a pretty apt comparison to LLMs.
  - mrwrong 10mo ago
    who would I be trying to trick if it was? you didn't answer the question anyways. I'm not wondering whether cars were seen as strictly better than horses in all situations. I'm wondering if people disagreed so vehemently about whether cars were faster road transportation than horses

lelanthran 10mo ago

Depends on how he defined "better". If he uses the word "better" to mean "good enough to not fail immediately, and done in 1/10th of the time", then he's correct.