I’ve seen this argument way to often and it is completely pointless. The argument that this will succeed because something in the past succeeded is exactly the same as arguing it will fail because something in the past failed.
If you want to draw the conclusion that they’re similar enough to use history in prediction, you’ll have to show that they’re similar and make a case for why those similarities are relevant.
I haven’t seen anyone making this argument bother with this exercise, but I have seen people that actually look at the economics discuss why they’re different animals.
There is also the enterprise itself.
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internet - connect everything together across vast distances. Obvious limitless possibilities.
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smart phones (you didn’t mention here but this is the other one people use for this argument most frequently) - Anything a computer can do in the palm of your hand.
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llms - can do some powerful stuff like rifle through and summarize text, or generate text, or generate code… Except you can’t really trust it to do any of these things accurately, and that is a fundamental aspect of how the technology works rather than something that can be fixed, so it can’t be used responsibly for anything critical.
sculd@beehaw.org 3 weeks ago
People immediately knew how internet could help us even during the dot com bubble. Anyone who had used Google (or before that, Yahoo) would immediately fall in love with them with how they help their live. AI (LLM)? Not so.
HakFoo@lemmy.sdf.org 3 weeks ago
The Internet boom didn’t have the weird you’re-holding-it-wrong vibe too. Legit “It doesn’t help with my use case concerns” seem to all too often get answered with choruses of “but have you tried this week’s model? Have you spent enough time trying to play with it and tweak it to get something more like you want?” Don’t admit limits to the tech, just keep hitting the gacha.
I’ve had people say I’m not approaching AI in “good faith”. I say that you didn’t need “good faith” to see that Lotus 1-2-3 was more flexible and faster than tallying up inventory on paper, or that AltaVista was faster than browsing a card catalog.
DragonSidedD@monero.town 3 weeks ago
Perhaps you are unaware that AI has solved the Proteome. This was expected to be a 100 year project.
Feyd@programming.dev 3 weeks ago
I’m unaware of machine learning being used in all kinds of science, but it is not llms and therefore not the topic of discussion here.
DragonSidedD@monero.town 3 weeks ago
Au contraire. The proteome was solved by LLM transformers trained on genetic strings
en.wikipedia.org/wiki/AlphaFold