• jjjalljs@ttrpg.network
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    25 days ago

    I don’t think AI is actually that good at summarizing. It doesn’t understand the text and is prone to hallucinate. I wouldn’t trust an AI summary for anything important.

    Also search just seems like overkill. If I type in “population of london”, i just want to be taken to a reputable site like wikipedia. I don’t want a guessing machine to tell me.

    Other use cases maybe. But there are so many poor uses of AI, it’s hard to take any of it seriously.

      • brognak@lemm.ee
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        25 days ago

        If I understand how AI works (predictive models), kinda seems perfectly suited for translating text. Also exactly how I have been using it with Gemini, translate all the memes in ich_iel 🤣. Unironically it works really well, and the only ones that aren’t understandable are cultural not linguistic.

      • Thisiswritteningerman@midwest.social
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        25 days ago

        Our plant manager likes to use it to summarize meetings (Copilot). It in fact does not summarize to a bullet point list in any useful way. Breakes the notes into a headers for each topic then bullet points The header is a brief summary. The bullet points? The exact same summary but now broken by sentences as individual points. Truly stunning work. Even better with a “Please review the meeting transcript yourself as AI might not be 100% accurate” disclaimer.

        Truely worthless.

        That being said, I’ve a few vision systems using an “AI” to recognize product that doesn’t meet the pre taught pattern. It’s very good at this

      • jjjalljs@ttrpg.network
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        25 days ago

        But if the text you’re working on is small, you could just do it yourself. You don’t need an expensive guessing machine.

        Like, if I built a rube-goldberg machine using twenty rubber ducks, a diesel engine, and a blender to tie my shoes, and it gets it right most of the time, that’s impressive. but also kind of a stupid waste, because I could’ve just tied them with my hands.

    • roude@lemmynsfw.com
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      25 days ago

      I guess this really depends on the solution you’re working with.

      I’ve built a voting system that relays the same query to multiple online and offline LLMs and uses a consensus to complete a task. I chunk a task into smaller more manageable components, and pass those through the system. So one abstract, complex single query becomes a series of simpler asks with a higher chance of success. Is this system perfect? No, but I am not relying on a single LLM to complete it. Deficiencies in one LLM are usually made up for in at least one other LLM, so the system works pretty well. I’ve also reduced the possible kinds of queries down to a much more limited subset, so testing and evaluation of results is easier / possible. This system needs to evaluate the topic and sensitivity of millions of websites. This isn’t something I can do manually, in any reasonable amount of time. A human will be reviewing websites we flag under very specific conditions, but this cuts down on a lot of manual review work.

      When I said search, I meant offline document search. Like "find all software patents related to fly-by-wire aircraft embedded control systems” from a folder of patents. Something like elastic search would usually work well here too, but then I can dive further and get it to reason about results surfaced from the first query. I absolutely agree that AI powered search is a shitshow.