• tsonfeir@lemmy.world
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          5 months ago

          Nope, just gotta know what it IS, what it ISN’T, and how to correctly write prompts for it to return data that you can use to formulate your own conclusion.

          When using AI, it’s only as smart as the operator.

              • Zos_Kia@lemmynsfw.com
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                5 months ago

                No you don’t understand. The word AI, which was invented to describe this kind of technology, should not be used to describe this technology. It should instead be reserved for some imaginary magical technology that may exist in the future.

            • msage@programming.dev
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              5 months ago

              As much as I hate to do this, it is AI, as ML is a part of Artificial Intelligence.

              It isn’t AGI, some might say it may be, but they are wrong. But the model is learning.

              • SpaceNoodle@lemmy.world
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                5 months ago

                An LLM is not capable of learning. It won’t hallucinate less with additional training input.

                • msage@programming.dev
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                  5 months ago

                  Just the notion of a computer having hallucinations should suggest that it’s doing more than just basic code.

                  It’s not ‘intelligent’, but it has ‘learned’ enough beyond standard CPU instructions.

                  That’s why it’s not a General AI, but it’s still an AI.

                  • SpaceNoodle@lemmy.world
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                    5 months ago

                    I also talk about gremlins inside CPUs, but that doesn’t mean I think there are magical critters turning a crank inside them.

                    It’s called a metaphor, brother.

                    Regardless, it’s all code that’s eventually run on a CPU, so there isn’t any step where magic is injected.

    • capital@lemmy.world
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      5 months ago

      This question betrays either your non-use or misuse of the products available. You’re either just reading the headlines of the screw-ups or you’re just bad at using the tool.

      To directly answer your question:

      • Quick scripts in a variety of languages. Tested before being used on real data/systems.
      • Creating visual graphs of data in python and Jupyter notebooks with no prior knowledge of python itself or the tools it’s running. In this case, I was able to update the way I wanted it to look in natural language, have it suggest code changes, and immediately try them in the notebook with great results.
      • Improving the sentiment of correspondence. Proofread before sending. It has better grammar and flow than a surprising number of correspondences I’ve come across at work. Sure, English may be their second language but it doesn’t change the fact.
      • Quickly finding documentation pertaining to the query which, yes, you need to go read to verify any answers any LLM provides. Anyone using it regularly should know this by now.
      • Quick “do this in command line. What options are required” which is then immediately tested.
      • In one case, a news story was referenced in passing in a podcast I listen to. It stuck with me days later and I wanted to find actual articles written about it. I was able to describe what I was looking for in natural language and included as many details as I could remember and asked it to find articles for me. I found exactly what I was after.

      But were you actually looking for a real response to your question?

      • SpaceNoodle@lemmy.world
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        5 months ago

        It’s worse at all programming tasks except boilerplate, especially with its tendency to inject booby traps. Not knowing how to use the programming language it emits becomes a significant problem.

        Comparing a language model to an idiot is unfair to the idiot.

        A normal search engine works for everything else.

        Any well-defined query I’ve ever made of an LLM has resulted in hilariously bad results, but I suppose I was expecting it to do something that I couldn’t already do better myself.

    • brbposting@sh.itjust.works
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      5 months ago

      Can absolutely never blindly trust the hallucinating plagiarism machine.

      It’s great where either facts don’t matter or you’re personally in a position to vet all of its “factual” output 100%. Text revision, prompting for additional perspectives, prompting to challenge beliefs and identify gaps. Reformatting, quick and easy data extraction, outlining, brainstorming.

      • SpaceNoodle@lemmy.world
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        5 months ago

        Reformatting and outlining as long as you go over and revise it again anyway, seemingly making that moot.

        Data extraction as long as you don’t care if the data is mangled.

        Brainstorming is a good one, since off-the-wall ideas can be useful in that context.

        • sugar_in_your_tea@sh.itjust.works
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          5 months ago

          In most cases I’ve seen AI used, the person spends as much time correcting it than they would if they just did the work without AI. So maybe it makes you feel more productive because a bunch of stuff happens all at once, but at least for text generation, I think it’s more of a placebo.