3 ms·

> They’re closed source black boxes, not even the people who built them really know what’s happening under the hood. Please explain

iswapna_ 1y ago
LLMs are trained to predict a bunch of tokens (GenAI produces text) from all the previous seen tokens, based on the data it was trained on. It does not understand anything about the spatial relationships like lines, objects etc in an image. "Not even the people who built them" - We have no real understanding of how LLMs work, yet. Traditional ML theory (classification/regression/clustering) largely does not apply to LLM's emergent capabilities like coding, arithmetic and reasoning. No such theory exists today. People are trying.
- chistev 1y ago
  If I understand you, you're saying people how built them have no idea why they work?
  - muzani 1y ago
    Yup, it's emergent behavior. This has been going for a while in ML, I believe. To be fair, we know how brains work, but we don't understand why consciousness either.
    - yawpitch 1y ago
      To be truly fair, we barely know how flatworm and fruit fly brains work… we haven’t the slightest clue how human brains work. Understanding consciousness is a long way off.
      - iswapna_ 1y ago
        :) yea and here we are talking abut UPI
yawpitch 1y ago
Imagine an equation several miles long, comprised of billions of variables, billions of constants, and billions of exponents. You know none of the variables. None of the constants. None of the exponents. No one does, really, but even if you did it wouldn’t help, because no one bothered to write down the operators and the parentheses are randomly shifted around every time the equation is resolved. All you know is that if you ask it for tea, it will always, invariably, and forever, give you back something that is almost, but not quite entirely, unlike tea. Sometimes it might be more unlike coffee, some times more unlike vodka and cow urine. What you’ll never, ever, ever reliably know is what’s in the cup. That’s about the best way I know to explain black box abstractions. In a few decades we might have a workable theory as to why these things function, to the degree that they do, though I’ll bet a rather large amount of money that we won’t.

iswapna_ 1y ago

LLMs are trained to predict a bunch of tokens (GenAI produces text) from all the previous seen tokens, based on the data it was trained on. It does not understand anything about the spatial relationships like lines, objects etc in an image. "Not even the people who built them" - We have no real understanding of how LLMs work, yet. Traditional ML theory (classification/regression/clustering) largely does not apply to LLM's emergent capabilities like coding, arithmetic and reasoning. No such theory exists today. People are trying.

chistev 1y ago
If I understand you, you're saying people how built them have no idea why they work?
- muzani 1y ago
  Yup, it's emergent behavior. This has been going for a while in ML, I believe. To be fair, we know how brains work, but we don't understand why consciousness either.
  - yawpitch 1y ago
    To be truly fair, we barely know how flatworm and fruit fly brains work… we haven’t the slightest clue how human brains work. Understanding consciousness is a long way off.
    - iswapna_ 1y ago
      :) yea and here we are talking abut UPI

yawpitch 1y ago

Imagine an equation several miles long, comprised of billions of variables, billions of constants, and billions of exponents. You know none of the variables. None of the constants. None of the exponents. No one does, really, but even if you did it wouldn’t help, because no one bothered to write down the operators and the parentheses are randomly shifted around every time the equation is resolved. All you know is that if you ask it for tea, it will always, invariably, and forever, give you back something that is almost, but not quite entirely, unlike tea. Sometimes it might be more unlike coffee, some times more unlike vodka and cow urine. What you’ll never, ever, ever reliably know is what’s in the cup. That’s about the best way I know to explain black box abstractions. In a few decades we might have a workable theory as to why these things function, to the degree that they do, though I’ll bet a rather large amount of money that we won’t.