The research from Purdue University, first spotted by news outlet Futurism, was presented earlier this month at the Computer-Human Interaction Conference in Hawaii and looked at 517 programming questions on Stack Overflow that were then fed to ChatGPT.

“Our analysis shows that 52% of ChatGPT answers contain incorrect information and 77% are verbose,” the new study explained. “Nonetheless, our user study participants still preferred ChatGPT answers 35% of the time due to their comprehensiveness and well-articulated language style.”

Disturbingly, programmers in the study didn’t always catch the mistakes being produced by the AI chatbot.

“However, they also overlooked the misinformation in the ChatGPT answers 39% of the time,” according to the study. “This implies the need to counter misinformation in ChatGPT answers to programming questions and raise awareness of the risks associated with seemingly correct answers.”

  • @otp@sh.itjust.works
    link
    fedilink
    English
    131 month ago

    I appreciate the XKCD comic, but I think you’re exaggerating that other commenter’s intent.

    The tech has been improving, and there’s no obvious reason to assume that we’ve reached the peak already. Nor is the other commenter saying we went from 0 to 1 and so now we’re going to see something 400x as good.

    • @stufkes@lemmy.world
      link
      fedilink
      English
      51 month ago

      I think the one argument for the assumption that we’re near peak already is the entire issue of AI learning from AI input. I think numberphile discussed a maths paper that said that to achieve the accuracy that we want, there is simply not enough data to train it on.

      That’s of course not to say that we can’t find alternative approaches

    • @31337@sh.itjust.works
      link
      fedilink
      English
      21 month ago

      We’re close to peak using current NN architectures and methods. All this started with the discovery of transformer architecture in 2017. Advances in architecture and methods have been fairly small and incremental since then. The advancements in performance has mostly just been throwing more data and compute at the models, and diminishing returns have been observed. GPT-3 costed something like $15 million to train. GPT-4 is a little better and costed something like $100 million to train. If the next model costs $1 billion to train, it will likely be a little better.

    • @14th_cylon@lemm.ee
      link
      fedilink
      English
      0
      edit-2
      1 month ago

      I appreciate the XKCD comic, but I think you’re exaggerating that other commenter’s intent.

      i don’t think so. the other commenter clearly rejects the critic(1) and implies that existence of upward trajectory means it will one day overcome the problem(2).

      while (1) is well documented fact right now, (2) is just wishful thinking right now.

      hence the comic, because “the trajectory” doesn’t really mean anything.

      • @otp@sh.itjust.works
        link
        fedilink
        English
        11 month ago

        In general, “The technology is young and will get better with time” is not just a reasonable argument, but almost a consistent pattern. Note that XKCD’s example is about events, not technology. The comic would be relevant if someone were talking about events happening, or something like sales, but not about technology.

        Here, I’m not saying that you’re necessarily right or they’re necessarily wrong, just that the comic you shared is not a good fit.

        • @14th_cylon@lemm.ee
          link
          fedilink
          English
          01 month ago

          In general, “The technology is young and will get better with time” is not just a reasonable argument, but almost a consistent pattern. Note that XKCD’s example is about events, not technology.

          yeah, no.

          try to compare horse speed with ford t and blindly extrapolate that into the future. look at the moore’s law. technology does not just grow upwards if you give it enough time, most of it has some kind of limit.

          and it is not out of realm of possibility that llms, having already stolen all of human knowledge from the internet, having found it is not enough and spewing out bullshit as a result of that monumental theft, have already reached it.

          that may not be the case for every machine learning tool developed for some specific purpose, but blind assumption it will just grow indiscriminately, because “there is a trend”, is overly optimistic.

          • @otp@sh.itjust.works
            link
            fedilink
            English
            01 month ago

            I don’t think continuing further would be fruitful. I imagine your stance is heavily influenced by your opposition to, or dislike of, AI/LLMs

            • @14th_cylon@lemm.ee
              link
              fedilink
              English
              -11 month ago

              oh sure. when someone says “you can’t just blindly extrapolate a curve”, there must be some conspiracy behind it, it absolutely cannot be because you can’t just blindly extrapolate a curve 😂