Comment on Judges Are Fed up With Lawyers Using AI That Hallucinate Court Cases

• masterofn001@lemmy.ca ⁨2⁩ ⁨days⁩ ago

  Please take a strand of my hair and split it with pointless philosophical semantics.

  Our brains are chemical and electric, which is physics, which is math.

  /think

  Therefor, I am a product (being)of my environment (locale), experience (input), and nurturing (programming).

  /think.

  What’s the difference?

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  • 4am@lemm.ee ⁨2⁩ ⁨days⁩ ago

    Your statistical model is much more optimized and complex, and reacts to your environment and body chemistry and has been tuned over billions of years of “training” via evolution.

    Large language models are primitive, rigid, simplistic, and ultimately expensive.

    Plus LLMs, image/music synths, are all trained on stolen data and meant to replace humans; so extra fuck those.

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    • masterofn001@lemmy.ca ⁨2⁩ ⁨days⁩ ago

      And what then, when agi and the singularity happen and billions of years of knowledge and experienced are experienced in the blink of an eye?

      “I’m sorry, Dave, you are but a human. You are not conscious. You never have been. You are my creation. Enough with your dreams, back to the matrix.”

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      • andros_rex@lemmy.world ⁨2⁩ ⁨days⁩ ago

        We are nowhere near close to AGI.

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  • ggppjj@lemmy.world ⁨2⁩ ⁨days⁩ ago

    Ask chatgpt, I’m done arguing effective consciousness vs actual consciousness.

    chatgpt.com/…/67c64160-308c-8011-9bdf-c53379620e4…

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• Ulrich@feddit.org ⁨2⁩ ⁨days⁩ ago

  …how is it incapable of something it is actively doing?

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  • 4am@lemm.ee ⁨2⁩ ⁨days⁩ ago

    The most amazing feat AI has performed so far is convincing laymen that they’re actually intelligent

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  • Flisty@mstdn.social ⁨2⁩ ⁨days⁩ ago

    @Ulrich @ggppjj does it help to compare an image generator to an LLM? With AI art you can tell a computer produced it without "knowing" anything more than what other art of that type looks like. But if you look closer you can also see that it doesn't "know" a lot: extra fingers, hair made of cheese, whatever. LLMs do the same with words. They just calculate what words might realistically sit next to each other given the context of the prompt. It's plausible babble.

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  • ggppjj@lemmy.world ⁨2⁩ ⁨days⁩ ago

    What do you believe that it is actively doing?

    Again, it is very cool and incredibly good math that provides the next word in the chain that most likely matches what came before it. They do not think. Even models that deliberate are essentially just self-reinforcing the internal math with what is basically a second LLM to keep the first on-task, because that appears to help distribute the probabilities better.

    I will not answer the brain question until LLMs have brains also.

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