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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"

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.
  - jraph 1y ago
    > I don't know how else one gets information and forms an opinion on the technology except for media consumption or hands-on experience. Okay, I think I got your intent better, thanks for clarifying. You can add discussion with other people outside software media, or opinion pieces outside media (I would not include personal blogs in "media" for instance, but would not be bothered if someone did), including people who tried and people who didn't. Medias are also not uniform in their views. But I hear you, grounded perspectives would be a positive. > That for it to result in good outcomes for humanity, it requires good people to help shape it in its formative years. I hear you as well, makes perfect sense. OTOH, it's difficult to engage into something that feels fundamentally wrong or a dead end, and that's what LLMs feel like to me. It would be also frightening: the risk that, as a good person, you help shape a monster. The only way out I can see is inventing the thing that will make LLMs irrelevant, but also don't have their fatal flaws. That's quite the undertaking though. We'd not be competing on an equal footing: LLM providers have been doing things I would never have dared even considering: ingesting considerable amount of source materials completely disregarding their licenses, hammering everyone servers, spending a crazy amount of energy, sourcing a crazy amount of (very closed) hardware, burning an insane amount of money even on paid plans. It feels very brutal. Can an LLM be built avoiding any of this stuff? Because otherwise, I'm simply not interested. (of course, the discussion has shifted quite a bit! The initial question was if a dev not using the LLMs would remain relevant, but I believe this was addressed at large in other comments already)
    - aeon_ai 1y ago
      My point on the initial discussion remains, but I think that it also seems like we disagree on the foundations/premise of the technology. The actions of a few companies does not invalidate the entire category. There are open models, trained on previously aggregated datasets (which, for what its worth, nobody had a problem with being collected a decade ago!), doing research to make training and usage more efficient. The technology is here. I think your assessment on its relevance is not informed by actual usage, your frame of its origins is black/white (rather than understanding the actual landscape of different model approaches), and that your lack of interest in using it does nothing to change the absolutely massive shift that is happening in the nature of work. I'm a Product Manager, and the Senior Engineer I work with has been reviewing my PRs before they get merged - 60%+ were merged without much comment, and his bar is high. I did half of our last release, while also doing my day job. Safe to say, his opinion has changed based on that. Were they massive changes? No. But these are absolutely impactful in the decision calculus that goes into what it takes to build and maintain software. The premise of my argument is that what you see as "fatal flaws" are an illusion created by bias (which bleeds into the second-hand perspectives you cite just as readily as it does the media), rather than your direct and actual validation that those flaws exist. My suggestion is to be an objective scientist -- use the best model released (regardless of origins) with minor research into 'best practices' to see what is possible, and then ask yourself if the 'origins' issue were addressed by a responsible open-source player in 6-12 months, whether it would change anything about your views on the likely impact of this technology and your willingness to adopt it. I believe that it's coming, not because the hype machine tells me so (and it's WAY hyped) - But because I've used it, seen its flaws and strengths, and forecast how quickly it will change the work that I've been doing for over a decade even if it stopped getting better (and it hasn't stopped yet)
danaris 1y ago
> There's a clear difference between... There's also a clear difference between users of this site that come here for all types of content, and users who have "AI" in their usernames. I think that the latter type might just have a bit of a bias in this matter?
- aeon_ai 1y ago
  I'd be surprised if one needed to refer to my username to make a determination on me viewing the technology more optimistically, although I do chafe a tad at the notion that I don't come here for all types of content.
9rx 1y ago
> The US Beef industry alone far outpaces the impact of AI. Beef has the benefit of seeing an end, though. Populations are stabilizing, and people are only ever going to eat so much. As methane has a 12 year life, in a stable environment the methane emissions today simply replace the emissions from 12 years ago. The carbon lifecycle of animals is neutral, so that is immaterial. It is also easy to fix if we really have to go to extremes: Cull all the cattle and in 12 years it is all gone! Whereas AI, even once stabilized, theoretically has no end to its emissions. Emissions that are essentially permanent, so even if you shut down all AI when you have to take extreme measures, the effects will remain "forever". There is always hope that we'll use technology to avoid that fate, but you know how that usually goes...

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.
- jraph 1y ago
  > I don't know how else one gets information and forms an opinion on the technology except for media consumption or hands-on experience. Okay, I think I got your intent better, thanks for clarifying. You can add discussion with other people outside software media, or opinion pieces outside media (I would not include personal blogs in "media" for instance, but would not be bothered if someone did), including people who tried and people who didn't. Medias are also not uniform in their views. But I hear you, grounded perspectives would be a positive. > That for it to result in good outcomes for humanity, it requires good people to help shape it in its formative years. I hear you as well, makes perfect sense. OTOH, it's difficult to engage into something that feels fundamentally wrong or a dead end, and that's what LLMs feel like to me. It would be also frightening: the risk that, as a good person, you help shape a monster. The only way out I can see is inventing the thing that will make LLMs irrelevant, but also don't have their fatal flaws. That's quite the undertaking though. We'd not be competing on an equal footing: LLM providers have been doing things I would never have dared even considering: ingesting considerable amount of source materials completely disregarding their licenses, hammering everyone servers, spending a crazy amount of energy, sourcing a crazy amount of (very closed) hardware, burning an insane amount of money even on paid plans. It feels very brutal. Can an LLM be built avoiding any of this stuff? Because otherwise, I'm simply not interested. (of course, the discussion has shifted quite a bit! The initial question was if a dev not using the LLMs would remain relevant, but I believe this was addressed at large in other comments already)
  - aeon_ai 1y ago
    My point on the initial discussion remains, but I think that it also seems like we disagree on the foundations/premise of the technology. The actions of a few companies does not invalidate the entire category. There are open models, trained on previously aggregated datasets (which, for what its worth, nobody had a problem with being collected a decade ago!), doing research to make training and usage more efficient. The technology is here. I think your assessment on its relevance is not informed by actual usage, your frame of its origins is black/white (rather than understanding the actual landscape of different model approaches), and that your lack of interest in using it does nothing to change the absolutely massive shift that is happening in the nature of work. I'm a Product Manager, and the Senior Engineer I work with has been reviewing my PRs before they get merged - 60%+ were merged without much comment, and his bar is high. I did half of our last release, while also doing my day job. Safe to say, his opinion has changed based on that. Were they massive changes? No. But these are absolutely impactful in the decision calculus that goes into what it takes to build and maintain software. The premise of my argument is that what you see as "fatal flaws" are an illusion created by bias (which bleeds into the second-hand perspectives you cite just as readily as it does the media), rather than your direct and actual validation that those flaws exist. My suggestion is to be an objective scientist -- use the best model released (regardless of origins) with minor research into 'best practices' to see what is possible, and then ask yourself if the 'origins' issue were addressed by a responsible open-source player in 6-12 months, whether it would change anything about your views on the likely impact of this technology and your willingness to adopt it. I believe that it's coming, not because the hype machine tells me so (and it's WAY hyped) - But because I've used it, seen its flaws and strengths, and forecast how quickly it will change the work that I've been doing for over a decade even if it stopped getting better (and it hasn't stopped yet)

danaris 1y ago

> There's a clear difference between... There's also a clear difference between users of this site that come here for all types of content, and users who have "AI" in their usernames. I think that the latter type might just have a bit of a bias in this matter?

aeon_ai 1y ago
I'd be surprised if one needed to refer to my username to make a determination on me viewing the technology more optimistically, although I do chafe a tad at the notion that I don't come here for all types of content.

9rx 1y ago

> The US Beef industry alone far outpaces the impact of AI. Beef has the benefit of seeing an end, though. Populations are stabilizing, and people are only ever going to eat so much. As methane has a 12 year life, in a stable environment the methane emissions today simply replace the emissions from 12 years ago. The carbon lifecycle of animals is neutral, so that is immaterial. It is also easy to fix if we really have to go to extremes: Cull all the cattle and in 12 years it is all gone! Whereas AI, even once stabilized, theoretically has no end to its emissions. Emissions that are essentially permanent, so even if you shut down all AI when you have to take extreme measures, the effects will remain "forever". There is always hope that we'll use technology to avoid that fate, but you know how that usually goes...