I think AI is neat.

  • AwkwardLookMonkeyPuppet@lemmy.world
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    10 months ago

    I think AI is the single most powerful tool we’ve ever invented and it is now and will continue completely changing the world. But you’ll get nothing but hate and “iTs Not aCtuaLly AI” replies here on Lemmy.

    • naevaTheRat@lemmy.dbzer0.com
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      10 months ago

      Umm penicillin? anaesthetic? the Haber process? the transistor? the microscope? steel?

      I get it, the models are new and a bit exciting but GPT wont make it so you can survive surgery, or make rocks take the jobs of computers.

      • GeneralVincent@lemmy.world
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        10 months ago

        Very true and valid. Tho, devils advocate for a moment, AI is great at discovering new ways to survive surgery and other cool stuff. Of course it uses the existing scientific discoveries to do that, but still. It could be the tool to find the next biggest thing on the penicillin, anaesthesia, haber process, transistor, microscope, steel list which is pretty cool.

        • naevaTheRat@lemmy.dbzer0.com
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          10 months ago

          Is it? This seems like a big citation needed moment.

          Have LLMs been used to make big strides? I know some trials are going on aiding doctors in diagnosis and stuff but computer vision algorithms have been doing that for ages (shit contrast dyes, pcr, and blood analysis also do that really) but they come with their own risks and we haven’t seen like widespread unknown illnesses being discovered or anything. Is the tech actually doing anything useful atm or is it all still hype?

          We’ve had algorithms help find new drugs and stuff, or plot out synthetic routes for novel compounds; We can run DFT simulations to help determine if we should try make a material. These things have been helpful but not revolutionary, I’m not sure why LLMs would be? I actually worry they’ll hamper scientific progress by aiding fraud (unreproducible results are already a fucking massive problem) or extremely convincingly lying or omitting something if trying to use one to help in a literature review.

          Why do you think LLMs will revolutionise science?

            • naevaTheRat@lemmy.dbzer0.com
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              10 months ago

              This seems like splitting hairs agi doesn’t exist so that can’t be what they mean. AI applies to everything from pathing algorithms for library robots to computer vision and none of those seem to apply.

              The context of this post is LLMs and their applications

              • A_Very_Big_Fan@lemmy.world
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                10 months ago

                The comment you replied to first said “AI”, not “LLMs”. And he even told you himself that he didn’t mean LLMs.

                I’m not saying he’s right, though, because afaik AI hasn’t made any noteworthy progress made in medical science. (Although a quick skim through Google suggests there has been). I’m just saying that’s clearly not what he said.

          • GeneralVincent@lemmy.world
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            10 months ago

            why do you think LLMs will revolutionise science

            Idk it probably won’t. That wasn’t exactly what I was saying, but I’m also not an expert in any scientific field so that’s my bad for unintentionally contributing to the hype by implying AI is more capable than it currently is or has the potential to be

            • naevaTheRat@lemmy.dbzer0.com
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              10 months ago

              Fair enough, I used to be scientist (a very bad one that never amounted to anything) and my perspective has been that the major barriers to progress are:

              • We’ve just got all the low hangingfruit
              • Science education isn’t available to many people, perspectives are quite limited consequently.
              • power structures are exploitative and ossified, driving away many people
              • industry has too much influence, there isn’t much appetite to fund blue sky projects without obvious short term money earning applications
              • patents slow progress
              • publish or perish incentivises excessive volumes of publication, fraud, and splitting discoveries into multiple papers which increases burden on researchers to stay current
              • nobody wants to pay scientists, bright people end up elsewhere