• gravitas_deficiency@sh.itjust.works
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    1 年前

    Short term yes; long term probably not. All the dipshit c-suites pushing the “AI” worker replacement initiatives are going to destroy their workforces and then realize that LLMs can’t actually reliably replace any of the workers they fired. And I love that for management.

    • MxM111@kbin.social
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      1 年前

      That’s not what is going to happen. Copilot will simply increase productivity over, and where before they needed 10 people, gradually, through attrition they will need only 9, then 8, and so on. That does not mean higher unemployment though, it means more product.

      • slaacaa@lemmy.world
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        1 年前

        Businesses want to grow, not keep stable. They might fire a few ppl in the short term, but in the long term it’s more likely the group of 10 would just do now the work of a 12-13 group with AI, producing hugher outputs for the same money they were getting before, meaning extra profit for the shareholders.

        • MxM111@kbin.social
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          1 年前

          That’s exactly what I meant by

          That does not mean higher unemployment though, it means more product.

      • just another dev@lemmy.my-box.dev
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        1 年前
        • “AI means there will be fewer people required to do the same amount of work”

        • “this does not mean higher unemployment”

        I think you left out a steep off reasoning there. At least, I don’t follow.

        • MxM111@kbin.social
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          1 年前

          When productivity increases (as it has been doing for ages) the manufacturing output increases. That’s what normally happens.

            • MxM111@kbin.social
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              1 年前

              Well, the price goes down, or/end the salaries go up, or resources are freed for new investments…

                • MxM111@kbin.social
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                  1 年前

                  Prices going down leads to increased demand and expansion. Salaries (everywhere) going up lead to increased demand and expansion.

      • gravitas_deficiency@sh.itjust.works
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        1 年前

        Short term? Sure.

        Long term? Not a chance that equation works out favorably.

        But then again, c-suites these days only seem to give a shit about short-term implications.

    • 3volver@lemmy.world
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      1 年前

      You’re referring to something that is changing and getting better constantly. In the long term LLMs are going to be even better than they are now. It’s ridiculous to think that it won’t be able to replace any of the workers that were fired. LLMs are going to allow 1 person to do the job of multiple people. Will it replace all people? No. But even if it allows 1 person to do the job of 2 people, that’s 50% of the workforce unemployed. This isn’t even mentioning how good robotics have gotten over the past 10 years.

      • JeffKerman1999@sopuli.xyz
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        1 年前

        You must have one person constantly checking for hallucinations in everything that is generated: how is that going to be faster?

          • Muehe@lemmy.ml
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            1 年前

            (not actually everything, but I get your hyperbole)

            How is it hyperbole? All artificial neural networks have “hallucinations”, no matter their size. What’s your magic way of knowing when that happens?

          • JeffKerman1999@sopuli.xyz
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            1 年前

            LLMs now are trained on data generated by other LLMs. If you look at the “writing prompt” stuff 90% is machine generated (or so bad that I assume it’s machine generated) and that’s the data that is being bought right now.

          • SupraMario@lemmy.world
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            1 年前

            It’s hard to improve when the data in is human and the data out cannot be error checked back against its own data in. It’s like trying to solve a math problem with two calculators that both think 2+2 = 6 because the data they were given said that it’s true.

      • MeanEYE@lemmy.world
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        1 年前

        There is a plateau to be hit at some point. How close it is, depends who you ask. Some say we are close, others say we are not but it definitely exists. LLMs suffer, just like other forms of machine learning, from data overload. You simply can’t be infinitely feeding it data and keep getting better and better results. ChatGPT’s models got famous because value function for learning had humans involved who helped curate quality of responses.

    • foggy@lemmy.world
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      1 年前

      They’re gonna realize the two jobs it can actually replace is HR and the C suite.

    • fidodo@lemmy.world
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      1 年前

      It can potentially allow 1 worker to do the job of 10. For 9 of those workers, they have been replaced. I don’t think they will care that much for the nuance that they technically weren’t replaced by AI, but by 1 co-worker who is using AI to be more efficient.

      That doesn’t necessarily mean that we won’t have enough jobs any more, because when in human history have we ever become more efficient and said “ok, good enough, let’s just coast now”? We will just increase the ambition and scope of what we will build, which will require more workers working more efficiently.

      But that still really sucks because it’s not going to be the same exact jobs and it will require re-training. These disruptions are becoming more frequent in human history and it is exhausting.

      We still need to spread these gains so we can all do less and also help those whose lives have been disrupted. Unfortunately that doesn’t come for free. When workers got the 40 hour work week it was taken by force.

      • AProfessional@lemmy.world
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        1 年前

        My colleagues are starting to use AI, it just makes their code worse and harder to review. I honestly can’t imagine that changing, AI doesn’t actually understand anything.

        • Yggnar@lemmy.world
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          1 年前

          This comment has similar vibes to a boomer in the 80s saying that the Internet is useless and full of nothing but nerds arguing on forums, and he doesn’t see that changing.

          • AProfessional@lemmy.world
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            1 年前

            Probably. I’m just not seeing it actually doing any logic or problem solving. It’s a pattern matching machine today. A new technology could certainly happen.