ChatGPT has meltdown and starts sending alarming messages to users::AI system has started speaking nonsense, talking Spanglish without prompting, and worrying users by suggesting it is in the room with them

  • Coreidan@lemmy.world
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    10 months ago

    We call just about anything “AI” these days. There is nothing intelligent about large language models. They are terrible at being right because their only job is to predict what you’ll say next.

  • Buffalox@lemmy.world
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    10 months ago

    “It does this as the good work of a web of art for the country, a mouse of science, an easy draw of a sad few, and finally, the global house of art, just in one job in the total rest,”

    Wow that sounds very much like a Phil Collins tune, just ad Oh Lord, and people will probably say it’s deep! But it’s a ChatGPT answer to the question “What is a computer?”

  • Pratai@lemmy.cafe
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    10 months ago

    That shit should never have existed to begin with. At least not before it could be regulated/limited in function.

  • Sanctus@lemmy.world
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    10 months ago

    Its being trained on us. Of course its acting unexpectedly. The problem with building a mirror is proding the guy on the other end doesnt work out.

    • snooggums@midwest.social
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      10 months ago

      To be honest this is the kind of outcome I expected.

      Garbage in, garbage out. Making the system more complex doesn’t solve that problem.

      • Ekky@sopuli.xyz
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        10 months ago

        It appears, that with the increase in popularity of machine learning, the percentage of people who properly source and sanitize their training data has steeply decreased.

        As you stated, a MLAI can only be as good as the data it was trained on, and is usually way worse. The popularity and application of MLAIs built with questionable practices scare me, though, at least their fuckups will keep me employed and likely more busy than ever.

        • Paragone@lemmy.world
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          10 months ago

          LLM’s are not “machine learning”, they are neural-networks.

          Different category.

          ML is small potatoes, ttbomk.

          Decision-tree stuff.

          Neural-nets are black-boxes, with back-propagation training of the neural-net to get closer to ( layer by layer, training-instance by training-instance ) the intended result.

          ML is what one does on one’s own machine with some python libraries,

          ChatGPT ( 3, 3.5, or 4, don’t know which ) cost something like $100,000,000 to rent the machines required for mixing the training-data & the model ( I’m assuming about $20/hr per machine, so an OCEAN of machines, to do it )

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      • thehatfox@lemmy.world
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        10 months ago

        The development of LLMs is possibly becoming self defeating, because the training data is being filled not just with human garbage, but also AI garbage from previous, cruder LLMs.

        We may well end up with a machine learning equivalent of Kessler syndrome, with our pool of available knowledge eventually becoming too full of junk to progress.

        • Paragone@lemmy.world
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          10 months ago

          Damn.

          Thank you VERY much for that insight: AI’s version of Kessler-syndrome.

          EXACTLY.

          Damn, damn, damn, that gets the truth right in its marrow.

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