• MonkderVierte@lemmy.zipEnglish
    74·
    2 个月前

    To be fair, MS says you shouldn’t use it for caculations.

    “Why is it there then?” No clue.

    • 87Six@lemmy.zipEnglish
      3·
      2 个月前

      That is only there to cover their asses not to actually be informative

    • Blackmist@feddit.ukEnglish
      27·
      2 个月前

      The example I saw them use was turning one line text reviews into a simple positive or negative so you can count them.

      So it could be useful for things like that, even if we ignore the “then why not just ask for the star rating” that probably went along with that review…

      MS is now an AI company that sells to excited bosses who would love to fire somebody somewhere to save a few bucks.

      • T156@lemmy.worldEnglish
        9·
        2 个月前

        At the same time, that sounds like something you’d just use old-fashioned sentiment analysis for.

        It’s less accurate, but also far less demanding, and doesn’t risk hallucinating.

        • The Ramen Dutchman@ttrpg.networkEnglish
          1·
          1 个月前

          It’s less accurate

          and doesn’t risk hallucinating

          I might be mistaken, but don’t these two lines mean the exact opposite in this context?

          Is AI more often right, or more often wrong?

          • T156@lemmy.worldEnglish
            1·
            1 个月前

            Both, because the way it’s right and wrong are different.

            Sentiment analysis might misclassify some of the data, but it doesn’t risk making things up wholescale like an LLM would.

      • ChickenLadyLovesLife@lemmy.worldEnglish
        4·
        2 个月前

        I used to work for Comcast as a mobile app developer. We used to get uncountable numbers of reviews along the lines of “I gave this app one star because you can’t give an app zero stars”. Honestly depressing even though I wasn’t personally responsible for the apps or the company.

      • turdcollector69@lemmy.world
        10·
        2 个月前

        “… to save a few bucks.”

        In the short term, people who rushed into AI are finding out that a 1 in 100 error rate is absurdly high when literally every action is done through an LLM.