The air begins to leak out of the overinflated AI bubble - eviltoast
  • UnderpantsWeevil@lemmy.world
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    4 months ago

    crypto is very niche in real world applications at the moment whereas AI does have real world usages.

    Crypto has a very real niche use for money laundering that it does exceptionally well.

    AI does not appear to do anything significantly more effectively than a Google search circa 2018.

    But neither can justify a multi billion dollar market cap on these terms.

    The game and media industry are very much trialling for voice and image synthesis for improving environmental design (texture synthesis) and providing dynamic voice synthesis based off actors likenesses. We have had peoples likenesses in movies for decades via cgi but it’s only really now we can do the same but for voices and this isn’t getting into logistics and/or financial where it is also seeing a lot of application.

    Voice actors simply don’t cost that much money. Procedural world building has existed for decades, but it’s generally recognized as lackluster beside bespoke design and development.

    These tools let you build bad digital experiences quickly.

    For logistics and finance, a lot of what you’re exploring is solved with the technology that underpins AI (modern graph theory). But LLMs don’t get you that. They’re an extraneous layer that takes enormous resources to compile and offers very little new value.

      • UnderpantsWeevil@lemmy.world
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        4 months ago

        there are loads of white papers detailing applications of AI in various industries

        And loads more of its ineffectual nature and wastefulness.

        • Grofit@lemmy.world
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          3 months ago

          Are you talking specifically about LLMs or Neural Network style AI in general? Super computers have been doing this sort of stuff for decades without much problem, and tbh the main issue is on training for LLMs inference is pretty computationally cheap

          • UnderpantsWeevil@lemmy.world
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            3 months ago

            Super computers have been doing this sort of stuff for decades without much problem

            Idk if I’d point at a supercomputer system and suggest it was constructed “without much problem”. Cray has significantly lagged the computer market as a whole.

            the main issue is on training for LLMs inference is pretty computationally cheap

            Again, I would not consider anything in the LLM marketplace particularly cheap. Seems like they’re losing money rapidly.