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> cognitive augmentation that allows developers to navigate complexity at scales human cognition wasn't designed for I don't think you should use LLMs for some

by jraph 1y ago

> cognitive augmentation that allows developers to navigate complexity at scales human cognition wasn't designed for I don't think you should use LLMs for something you can't master without. > will find themselves unable to compete I'd wait a bit more before concluding so affirmatively. The AI bubble would very much like us to believe this, but we don't yet know very well the long term effects of using LLMs on code, both for the project and for the developer, and we don't even know how available and in which conditions the LLMs will be in a few months as evidenced by this HN post. That's not a very solid basis to build on.

laughingcurve 1y ago
“I don’t think you should pay others for something you can’t master without [paying].” is one a hell of an argument to make. Good luck trying.
- jraph 1y ago
  > is one a hell of an argument to make. I agree, but it's not mine.
aeon_ai 1y ago
Two masters go head to head. One uses AI tools (wisely - after all, they're a master!), the other refuses to. Which one wins? To your second point -- With as much capital as is going into data center buildout, the increasing availability of local coding LLMs that near the performance of today's closed models, and the continued innovation on both open/closed models, you're going to hang your hat on the possibility that LLMs are going to be only available in a 'limited or degraded' state? I think we simply don't have similar mental models for predicting the future.
- jraph 1y ago
  > Which one wins? We don't really know yet, that's my point. There are contradictory studies on the topic. See for instance [1] that sees productivity decrease when AI is used. Other studies show the opposite. We are also seeing the first wave of blog posts from developers abandoning the LLMs. What's more, most people are not masters. This is critically important. If only masters see a productivity increase, others should not use it... and will still get employed because the masters won't fill in all the positions. In this hypothetical world, masters not using LLMs also have a place by construction. > With as much capital as is going into Yes, we are in a bubble. And some are predicting it will burst. > the continued innovation That's what I'm not seeing. We are seeing small but very costly improvements on a paradigm that I consider fundamentally flawed for the tasks we are using it for. LLMs still cannot reason, and that's IMHO a major limitation. > you're going to hang your hat on the possibility that LLMs are going to be only available in a 'limited or degraded' state? I didn't say I was going to, but since you are asking: oh yes, I'm not putting my eggs in a box that could abruptly disappear or become very costly. I simply don't see how this thing is going to be cost efficient. The major SaaS LLM providers can't seem to manage profitability, and maybe at some point the investors will get bored and stop sending billions of dollars towards them? I'll reconsider when and if LLMs become economically viable. But that's not my strongest reason to avoid the LLMs anyway: - I don't want to increase my reliance on SaaS (or very costly hardware) - I have not caved in yet in participating in this environmental disaster, and in this work pillaging phenomenon (well, that last part, I guess I don't really have a choice, I see the dumb AI bots hammering my forgejo instance). [1] https://www.sciencedirect.com/science/article/pii/S0166497223000755 https://www.sciencedirect.com/science/article/pii/S016649722...
  - aeon_ai 1y ago
    There's a clear difference between "I have used these tools, tested their limits, and have opinions" and "I am consuming media narratives about why AI is bad" AI presently has a far lower footprint on the globe than the meat industry -- The US Beef industry alone far outpaces the impact of AI. As far as "work pillaging" - There is cognitive dissonance in supporting the freedom of information/cultural progress and simultaneously desiring to restrict a transformative use (as it has been deemed by multiple US judges) of that information. We don't see eye to eye, and I think that's ok. We can re-evaluate our predictions in a year!
    - jraph 1y ago
      > consuming media narratives about why AI is bad That's quite uncharitable. I don't need to use it to make these points. While I might show a lack of perspective, I don't need to do X to reasonably think X can be bad. You can replace X with all sorts of horrible things, I'll let the creativity of the readers fill in the gap. > AI presently has a far lower footprint on the globe than [X] We see the same kind of arguments for planes, cars, anything with a big impact really. It still has a huge (and growing) environmental impact, and the question is do the advantages outweigh the drawbacks? For instance, if a video call tool allowed you to have a meeting without taking a plane, the video call tool had a positive impact. But then there's also the ripple effect: if without the tool, the meeting hadn't happened at all, the positive impact is less clear. And/or if the meeting was about burning huge amounts of fuel, the positive impact is even less clear, just like LLMs might just allow us to produce attention-seeking, energy-greedy shitty software at a faster speed (if they indeed work well in the long run). And while I can see how things like ML can help (predicting weather, etc), I'm more skeptical about LLMs. And I'm all for stopping the meat disaster as well. > We don't see eye to eye, and I think that's ok. We can re-evaluate our predictions in a year! Yep :-)
      - aeon_ai 1y ago
        It's not intended to be uncharitable - You clearly value many things I do (the world needs less attention-seeking, energy greedy shitty software). I don't know how else one gets information and forms an opinion on the technology except for media consumption or hands-on experience. Note that I count "social media" as media. My proposition is that without hands-on experience, your information is limited to media narratives, and it seems like the "AI is net bad" narrative seems to be the source of perspectives. Skepticism is warranted, and there are a million ways this technology could be built for terrible ends. But, I'm of the opinion that: A) The technology is not hype, and is getting better B) That it can, and will, be built -- Time horizon debatable. C) That for it to result in good outcomes for humanity, it requires good people to help shape it in its formative years. If anything, more people like you need to be engaging it to have grounded perspectives on what it could become.
- deleted 1y ago
  [deleted]
diggan 1y ago
> I don't think you should use LLMs for something you can't master without. I'm not sure, I frequently use LLMs for well-scoped math-heavy functions (mostly for game development) where I don't neccessarly understand what's going on inside the function, but I know what output I expect given some inputs, so it's easy for me to kind of blackbox test it with unit tests and iterate on the "magic" inside with an LLM. I guess if I really stopped and focused on math for a year or two I'd be able to code that myself too, but every time I tried to get deeper into math it's either way too complex for me to feel like it's time well spent, and it's also boring. So why bother?
- jraph 1y ago
  I can't comment on your well-scoped case. I can still see it backfire (in terms of maintenance) but it does seem you are precocious and are limiting the potential damages, with your unit tests you are increasing at least the level of confidence you can have on the LLM output and it's on a very specific part of your code. I didn't have such cases in mind, was replying to the "navigate complexity at scales human cognition wasn't designed for" aspect.

by jraph 1y ago

laughingcurve 1y ago

“I don’t think you should pay others for something you can’t master without [paying].” is one a hell of an argument to make. Good luck trying.

jraph 1y ago
> is one a hell of an argument to make. I agree, but it's not mine.

aeon_ai 1y ago

Two masters go head to head. One uses AI tools (wisely - after all, they're a master!), the other refuses to. Which one wins? To your second point -- With as much capital as is going into data center buildout, the increasing availability of local coding LLMs that near the performance of today's closed models, and the continued innovation on both open/closed models, you're going to hang your hat on the possibility that LLMs are going to be only available in a 'limited or degraded' state? I think we simply don't have similar mental models for predicting the future.

jraph 1y ago
> Which one wins? We don't really know yet, that's my point. There are contradictory studies on the topic. See for instance [1] that sees productivity decrease when AI is used. Other studies show the opposite. We are also seeing the first wave of blog posts from developers abandoning the LLMs. What's more, most people are not masters. This is critically important. If only masters see a productivity increase, others should not use it... and will still get employed because the masters won't fill in all the positions. In this hypothetical world, masters not using LLMs also have a place by construction. > With as much capital as is going into Yes, we are in a bubble. And some are predicting it will burst. > the continued innovation That's what I'm not seeing. We are seeing small but very costly improvements on a paradigm that I consider fundamentally flawed for the tasks we are using it for. LLMs still cannot reason, and that's IMHO a major limitation. > you're going to hang your hat on the possibility that LLMs are going to be only available in a 'limited or degraded' state? I didn't say I was going to, but since you are asking: oh yes, I'm not putting my eggs in a box that could abruptly disappear or become very costly. I simply don't see how this thing is going to be cost efficient. The major SaaS LLM providers can't seem to manage profitability, and maybe at some point the investors will get bored and stop sending billions of dollars towards them? I'll reconsider when and if LLMs become economically viable. But that's not my strongest reason to avoid the LLMs anyway: - I don't want to increase my reliance on SaaS (or very costly hardware) - I have not caved in yet in participating in this environmental disaster, and in this work pillaging phenomenon (well, that last part, I guess I don't really have a choice, I see the dumb AI bots hammering my forgejo instance). [1] https://www.sciencedirect.com/science/article/pii/S0166497223000755 https://www.sciencedirect.com/science/article/pii/S016649722...
- aeon_ai 1y ago
  There's a clear difference between "I have used these tools, tested their limits, and have opinions" and "I am consuming media narratives about why AI is bad" AI presently has a far lower footprint on the globe than the meat industry -- The US Beef industry alone far outpaces the impact of AI. As far as "work pillaging" - There is cognitive dissonance in supporting the freedom of information/cultural progress and simultaneously desiring to restrict a transformative use (as it has been deemed by multiple US judges) of that information. We don't see eye to eye, and I think that's ok. We can re-evaluate our predictions in a year!
  - jraph 1y ago
    > consuming media narratives about why AI is bad That's quite uncharitable. I don't need to use it to make these points. While I might show a lack of perspective, I don't need to do X to reasonably think X can be bad. You can replace X with all sorts of horrible things, I'll let the creativity of the readers fill in the gap. > AI presently has a far lower footprint on the globe than [X] We see the same kind of arguments for planes, cars, anything with a big impact really. It still has a huge (and growing) environmental impact, and the question is do the advantages outweigh the drawbacks? For instance, if a video call tool allowed you to have a meeting without taking a plane, the video call tool had a positive impact. But then there's also the ripple effect: if without the tool, the meeting hadn't happened at all, the positive impact is less clear. And/or if the meeting was about burning huge amounts of fuel, the positive impact is even less clear, just like LLMs might just allow us to produce attention-seeking, energy-greedy shitty software at a faster speed (if they indeed work well in the long run). And while I can see how things like ML can help (predicting weather, etc), I'm more skeptical about LLMs. And I'm all for stopping the meat disaster as well. > We don't see eye to eye, and I think that's ok. We can re-evaluate our predictions in a year! Yep :-)
    - aeon_ai 1y ago
      It's not intended to be uncharitable - You clearly value many things I do (the world needs less attention-seeking, energy greedy shitty software). I don't know how else one gets information and forms an opinion on the technology except for media consumption or hands-on experience. Note that I count "social media" as media. My proposition is that without hands-on experience, your information is limited to media narratives, and it seems like the "AI is net bad" narrative seems to be the source of perspectives. Skepticism is warranted, and there are a million ways this technology could be built for terrible ends. But, I'm of the opinion that: A) The technology is not hype, and is getting better B) That it can, and will, be built -- Time horizon debatable. C) That for it to result in good outcomes for humanity, it requires good people to help shape it in its formative years. If anything, more people like you need to be engaging it to have grounded perspectives on what it could become.
deleted 1y ago
[deleted]

diggan 1y ago

> I don't think you should use LLMs for something you can't master without. I'm not sure, I frequently use LLMs for well-scoped math-heavy functions (mostly for game development) where I don't neccessarly understand what's going on inside the function, but I know what output I expect given some inputs, so it's easy for me to kind of blackbox test it with unit tests and iterate on the "magic" inside with an LLM. I guess if I really stopped and focused on math for a year or two I'd be able to code that myself too, but every time I tried to get deeper into math it's either way too complex for me to feel like it's time well spent, and it's also boring. So why bother?

jraph 1y ago
I can't comment on your well-scoped case. I can still see it backfire (in terms of maintenance) but it does seem you are precocious and are limiting the potential damages, with your unit tests you are increasing at least the level of confidence you can have on the LLM output and it's on a very specific part of your code. I didn't have such cases in mind, was replying to the "navigate complexity at scales human cognition wasn't designed for" aspect.