3 ms·

Is this just a feeling you have or is this downstream of actual use cases you've applied AI to observed and measured reliability on?

by extr 1y ago

lionkor 1y ago
Not OP but using LLMs in any professional setting, like programming, editing or writing technical specifications, OP is correct. Without extensive promoting and injectimg my own knowledge and experience, LLMs generate absolute unusable garbage (on average). Anyone who disagrees very likely is not someone who would produce good quality work by themselves (on average). That's not a clever quip; that's a very sad reality. SO MANY people cannot be bothered to learn anything if they can help it.
- extr 1y ago
  I would completely disagree. I use LLMs daily for coding. They are quite far from AGI and it does not appear they are replacing Senior or Staff Engineers any time soon. But they are incredible machines that are perfectly capable of performing some economically valuable tasks in a fraction of the time it would have taken a human. If you deny this your head is in the sand.
  - lionkor 1y ago
    Capable, yeah, but not reliable, that's my point. They can one shot fantastic code, or they can one shot the code I then have to review and pull my hair out over for a week, because it's such crap (and the person who pushed it is my boss, for example, so I can't just tell him to try again). That's not consistent.
    - wahnfrieden 1y ago
      You can ask your boss to submit PRs using Codex’s “try 5 variations of the same task and select the one you like most though
      - zxor 1y ago
        Surely at that point they could write the code themselves faster than they can review 5 PRs. Producing more slop for someone else to work through is not the solution you think it is.
    - extr 1y ago
      Have you never used one to hunt down an obscure bug and found the answer quicker than you likely would have yourself?
      - lionkor 1y ago
        Actually, yeah, a couple of times, but that was a rubber-ducky approach; the AI said something utterly stupid, but while trying to explain things, I figured it out. I don't think an LLM has solved any difficult problem for me before. However, I think I'm likely an outlier because I do solve most issues myself anyways.
    - chrisweekly 1y ago
      Why do you frame the options as "one shot... or... one shot"?
      - lionkor 1y ago
        Because lazy people will use it like that, and we are all inherently lazy
        dns_snek 1y ago
        It's not much better with planning either. The amount of time I spent planning, clarifying requirements, hand-holding implementation details always offset any potential savings.
- visarga 1y ago
  The triad of LLM dependencies in my view: initiation of tasks, experience based feedback, and consequence sink. They can do none of these, they all connect to the outer context which sits with the user, not the model. You know what? This is also not unlike hiring a human, they need the hirer party tell them what to do, give feedback, and assume the outcomes. It's all about context which is non-fungible and distributed, not related to intelligence but to the reason we need intelligence for.
- KronisLV 1y ago
  > Anyone who disagrees very likely is not someone who would produce good quality work by themselves (on average). So for those producing slop and not knowing any better (or not caring), AI just improved the speed at which they work! Sounds like a great investment for them! For many mastering any given craft might not be the goal, but rather just pushing stuff out the door and paying bills. A case of mismatched incentives, one might say.
mbesto 1y ago
Not the parent poster, but this is pretty much the foundation of LLMs. They are by their nature probabilistic, not deterministic. This is precisely what the parent is referring to.
- extr 1y ago
  All processes in reality, everywhere, are probablistic. The entire reason "engineering" is not the same as theoretical mathematics is about managing these probabilities to an acceptable level for the task you're trying to perform. You are getting a "probablistic" output from a human too. Human beings are not guaranteeing theoretically optimal excel output when they send their boss Final_Final_v2.xlsx. You are using your mental model of their capabilities to inform how much you trust the result. Building a process to get a similar confidence in LLM output is part of the game.
  - jbs789 1y ago
    Yup. It becomes clearer to me when I think about the existing validators. Can these be improved, for sure. It’s when people make the leaps to the multi-year endgame and in their effort to monetise by building overconfidence in the product where I see the inherent conflict. It’s going to be a slog… the detailed implementations. And if anyone is a bit more realistic about managing expectations I think Anthropic is doing it a little better.
  - mbesto 1y ago
    > All processes in reality, everywhere, are probablistic. If we want to go in philosophy then sure, you're correct, but this not what we're saying. For example, an LLM is capable (and it's highly plausible for it to do so) of creating a reference to a non-existent source. Humans generally don't do that when their goal is clear and aligned (hence deterministic). > Building a process to get a similar confidence in LLM output is part of the game. Which is precisely my point. LLMs are supposed to be better than humans. We're (currently) shoehorning the technology.
    - extr 1y ago

Is this just a feeling you have or is this downstream of actual use cases you've applied AI to observed and measured reliability on?

by extr 1y ago

Is this just a feeling you have or is this downstream of actual use cases you've applied AI to observed and measured reliability on?

lionkor 1y ago

Not OP but using LLMs in any professional setting, like programming, editing or writing technical specifications, OP is correct. Without extensive promoting and injectimg my own knowledge and experience, LLMs generate absolute unusable garbage (on average). Anyone who disagrees very likely is not someone who would produce good quality work by themselves (on average). That's not a clever quip; that's a very sad reality. SO MANY people cannot be bothered to learn anything if they can help it.

extr 1y ago
I would completely disagree. I use LLMs daily for coding. They are quite far from AGI and it does not appear they are replacing Senior or Staff Engineers any time soon. But they are incredible machines that are perfectly capable of performing some economically valuable tasks in a fraction of the time it would have taken a human. If you deny this your head is in the sand.
- lionkor 1y ago
  Capable, yeah, but not reliable, that's my point. They can one shot fantastic code, or they can one shot the code I then have to review and pull my hair out over for a week, because it's such crap (and the person who pushed it is my boss, for example, so I can't just tell him to try again). That's not consistent.
  - wahnfrieden 1y ago
    You can ask your boss to submit PRs using Codex’s “try 5 variations of the same task and select the one you like most though
    - zxor 1y ago
      Surely at that point they could write the code themselves faster than they can review 5 PRs. Producing more slop for someone else to work through is not the solution you think it is.
  - extr 1y ago
    Have you never used one to hunt down an obscure bug and found the answer quicker than you likely would have yourself?
    - lionkor 1y ago
      Actually, yeah, a couple of times, but that was a rubber-ducky approach; the AI said something utterly stupid, but while trying to explain things, I figured it out. I don't think an LLM has solved any difficult problem for me before. However, I think I'm likely an outlier because I do solve most issues myself anyways.
  - chrisweekly 1y ago
    Why do you frame the options as "one shot... or... one shot"?
    - lionkor 1y ago
      Because lazy people will use it like that, and we are all inherently lazy
      - dns_snek 1y ago
        It's not much better with planning either. The amount of time I spent planning, clarifying requirements, hand-holding implementation details always offset any potential savings.
visarga 1y ago
The triad of LLM dependencies in my view: initiation of tasks, experience based feedback, and consequence sink. They can do none of these, they all connect to the outer context which sits with the user, not the model. You know what? This is also not unlike hiring a human, they need the hirer party tell them what to do, give feedback, and assume the outcomes. It's all about context which is non-fungible and distributed, not related to intelligence but to the reason we need intelligence for.
KronisLV 1y ago
> Anyone who disagrees very likely is not someone who would produce good quality work by themselves (on average). So for those producing slop and not knowing any better (or not caring), AI just improved the speed at which they work! Sounds like a great investment for them! For many mastering any given craft might not be the goal, but rather just pushing stuff out the door and paying bills. A case of mismatched incentives, one might say.

mbesto 1y ago

Not the parent poster, but this is pretty much the foundation of LLMs. They are by their nature probabilistic, not deterministic. This is precisely what the parent is referring to.

extr 1y ago
All processes in reality, everywhere, are probablistic. The entire reason "engineering" is not the same as theoretical mathematics is about managing these probabilities to an acceptable level for the task you're trying to perform. You are getting a "probablistic" output from a human too. Human beings are not guaranteeing theoretically optimal excel output when they send their boss Final_Final_v2.xlsx. You are using your mental model of their capabilities to inform how much you trust the result. Building a process to get a similar confidence in LLM output is part of the game.
- jbs789 1y ago
  Yup. It becomes clearer to me when I think about the existing validators. Can these be improved, for sure. It’s when people make the leaps to the multi-year endgame and in their effort to monetise by building overconfidence in the product where I see the inherent conflict. It’s going to be a slog… the detailed implementations. And if anyone is a bit more realistic about managing expectations I think Anthropic is doing it a little better.
- mbesto 1y ago
  > All processes in reality, everywhere, are probablistic. If we want to go in philosophy then sure, you're correct, but this not what we're saying. For example, an LLM is capable (and it's highly plausible for it to do so) of creating a reference to a non-existent source. Humans generally don't do that when their goal is clear and aligned (hence deterministic). > Building a process to get a similar confidence in LLM output is part of the game. Which is precisely my point. LLMs are supposed to be better than humans. We're (currently) shoehorning the technology.
  - extr 1y ago