Is language the same as intelligence? The AI industry desperately needs it to be
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The AI boom is based on a fundamental mistake.
  • pticrix ( pticrix@lemmy.ca ) English
    6·
    11 months ago

    I keep saying that those llm peddlers are selling us a brain, when at most they only deliver Wernicke’s + Broca’s area of a brain.

    Sure, they are necessary for a human like brain, but it’s only 10% of the job done my guys.

    • krooklochurm ( krooklochurm@lemmy.ca ) English
      3·
      11 months ago

      LLMs are actually very, very useful for certain things.

      The problem isn’t that they lack utility. It’s that they’re constantly being shoehorned into area where they aren’t useful.

      They’re great at surfacing nee knowledge for things you don’t have a complete picture of. You can’t take that knowledge at face value but a framework that you can validate with external sources can be a massive timesaver

      They’re good at summarizing text. They’re good at finding solutions to very narrow and specific coding challenges.

      They’re not useful at providing support. They are not useful at detailing specific, technical issues. They are not good friends.

  • chicken ( chicken@lemmy.dbzer0.com ) English
    5·
    11 months ago

    LLMs are simply tools that emulate the communicative function of language, not the separate and distinct cognitive process of thinking and reasoning …

    Take away our ability to speak, and we can still think, reason, form beliefs, fall in love, and move about the world; our range of what we can experience and think about remains vast.

    But take away language from a large language model, and you are left with literally nothing at all.

    The author seems to be making the assumption that a LLM is the equivalent of the language processing parts of the brain (which according to the cited research supposedly focus on language specifically and the other parts of the brain do reasoning) but that isn’t really how it works. LLMs have to internally model more than just the structure of language because text contains information that isn’t just about the structure of language. The existence of Multimodal models makes this kind of obvious; they train on more input types than just text, whatever it’s doing internally is more abstract than only being about language.

    Not to say the research on the human brain they’re talking about is wrong, it’s just that the way they are trying to tie it in to AI doesn’t make any sense.

  • sinwell ( Septimaeus@infosec.pub ) English
    1·
    11 months ago

    Because what we call intelligence (the human kind) usually is just an emergent property of the wielding of various combinations of fist or second-hand experience by “consciousness” which itself is…

    What we like to call the tip of a huge fucking iceberg of constant lifelong internal dialogues, overlapping and integrating experiences all the way back to the memories (engrams, assemblies, neurons that wired together to represent something), even the ones so old or deep we can’t even summon them any longer, but often are still measurable, still there, integrating like lego bricks with other assemblies.

    Humans continuously, reflexively, recursively tell and re-tell our own stories to ourselves all day, and even at night, just to make sense of the connections we made today, how to use them tomorrow, to know how they relate to connections we made a lifetime ago, and how it fits in the larger story of us. That “context integration window” absolutely DWARFS even the deepest language model, even though our own organic “neural net” is low-power, lacks back-propagation, etc etc, and it is all done using language.

    So yes, language is not the same as intelligence (though at some point some would ask “who can tell the difference?”) HOWEVER… The semantic taxonomies, symbolic cognition, and various other mental tools that are enabled by language are absolutely, verifiably required for this gargantuan context integration to take place.