•  hex   ( @hex@programming.dev ) 
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    4215 days ago

    Facts are not a data type for LLMs

    I kind of like this because it highlights the way LLMs operate kind of blind and drunk, they’re just really good at predicting the next word.

  •  swlabr   ( @swlabr@awful.systems ) 
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    3815 days ago

    ATTN: If you’re coming into this thread to say, “The output of AI is bad because your prompts suck,” I’m just proud that you managed to figure out how to use the internet at all. Good job, you!

  • Made strange choices about what to highlight.

    They certainly do. For a while it was common to see AI-generated summaries under links to articles on lemmy, so I got a feel for them. Seems to me you would not need any fancy artificial intelligence to do equally well: Just take random excerpts, or maybe just read every third sentence.

  • I had GPT 3.5 break down 6x 45-minute verbatim interviews into bulleted summaries and it did great. I even asked it to anonymize people’s names and it did that too. I did re-read the summaries to make sure no duplicate info or hallucinations existed and it only needed a couple of corrections.

    Beats manually summarizing that info myself.

    Maybe their prompt sucks?

  • Is it only me, or is the linked article not super long on details & is reaching a conclusion from 2 examples? This is important & I need to hear more, & I’m generally biased against AI at this point— but the article isn’t doing enough to convince me

  •  Lvxferre   ( @lvxferre@mander.xyz ) 
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    15 days ago

    You could use them to know what the text is about, and if it’s worth your reading time. In this situation, it’s fine if the AI makes shit up, as you aren’t reading its output for the information itself anyway; and the distinction between summary and shortened version becomes moot.

    However, here’s the catch. If the text is long enough to warrant the question “should I spend my time reading this?”, it should contain an introduction for that very purpose. In other words if the text is well-written you don’t need this sort of “Gemini/ChatGPT, tell me what this text is about” on first place.

    EDIT: I’m not addressing documents in this. My bad, I know. [In my defence I’m reading shit in a screen the size of an ant.]

      • (For clarity I’ll re-emphasise that my top comment is the result of misreading the word “documents” out, so I’m speaking on general grounds about AI “summaries”, not just about AI “summaries” of documents.)

        The key here is that the LLM is likely to hallucinate the claims of the text being shortened, but not the topic. So provided that you care about the later but not the former, in order to decide if you’re going to read the whole thing, it’s good enough.

        And that is useful in a few situations. For example, if you have a metaphorical pile of a hundred or so scientific papers, and you only need the ones about a specific topic (like “Indo-European urheimat” or “Argiope spiders” or “banana bonds”).

        That backtracks to the OP. The issue with using AI summaries for documents is that you typically know the topic at hand, and you want the content instead. That’s bad because then the hallucinations won’t be “harmless”.

        • But the claims of the text are often why you read it in the first place! If you have a hundred scientific papers you’re going to read the ones that make claims either supporting or contradicting your research.

          You might as well just skim the titles and guess.

          • But the claims of the text are often why you read it in the first place!

            By “not caring about the former” [claims], I mean in the LLM output, because you know that the LLM will fuck them up. But it’ll still somewhat accurately represent the topic of the text, and you can use this to your advantage.

            You might as well just skim the titles and guess.

            Nirvana fallacy.

              • not reading the fucking sidebar

                Yeah, I get that this is a place to vent. And I get why to vent about this. LLMs and other A"I" systems (with quotation marks because this shite is not intelligent!) are being shoved down every bloody where, regardless of actual usefulness, safety, or user desire. Telling you to put glue on your pizza, to eat poisonous mushrooms, that “cherish” has five letters, that Latin had no [w], that the Chinese are inferior to Westerners.

                While a crowd of irrationals tell you “it is intelligent, you can’t prove otherwise! CHRUST IT YOU DIRTY SCEPTIC/INFIDEL/LUDDITE REEEE! LALALA I’M PRETENDING TO NOT SEE THE HALLUCINATION LALALA”.

                I also get the privacy nightmare that this shit is. And the whole deal behind “we’re using your content as training data, and then selling the result back to you”. Or that it’s eating electricity like there’s no tomorrow, in a planet where global warming is a present issue.

                I get it. I get it all. That’s why I’m here. And if you (or anyone else) think that I’m here for any other reason, by all means, check my profile - you’ll find plenty pieces of criticism against those stupid corporate AI takes from vulture capital. (And plenty instances of me calling HN “Redditors LARPing as Hax0rz”. )

                However. Pretending that there’s no use case ever for LLMs is the wrong way to go.

                and thinking this is high school debate club fallacy

                If calling it “nirvana fallacy” rubs you the wrong way, here’s an alternative: “this argument is fucking stupid, in a very specific way: it pretends that either something is perfect or it’s useless, with no middle ground.”

                The other user however does not deserve the unnecessary abrasiveness so I’ll keep simply calling it “nirvana fallacy”.

            • Unless it doesn’t accurately represent the topic, which happens, and then a researcher chooses not to read the text based on the chatbot’s summary.

              Nirvana fallacy.

              All these chatbots do is guess. I’m just saying a researcher might as well cut out the hallucinating middleman.

    • if the text is well-written you don’t need this sort of “Gemini/ChatGPT, tell me what this text is about” on first place.

      And if it’s badly written then the LLM will shit itself.

      Now let’s ask ourselves how much of the text in the world is “well-written”?

      Or even better, you could apply this to Copilot. How much code in the world is good code? The answer is fucking none, mate.

      • No, it’s just rambling. My bad.

        I focused too much on using AI to summarise and ended not talking about it summarising documents, even if the text is about the later.

        And… well, the later is such a dumb idea that I don’t feel like telling people “the text is right, don’t do that”, it’s obvious.

  • I keep having to remind people. Chatgpt is only as good as the prompt you give it. I am astounded as the amount of garbage that some people get, but I also know that it’s generally because their prompts are garbage.

    Sometimes it’s output sucks, even with good input. But likely, if the output is bad, the input was bad.