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> LLMs use the same type of "abstract thinking" process as humans It's surprising you say that, considering we don't actually understand the mechanisms behind

> LLMs use the same type of "abstract thinking" process as humans It's surprising you say that, considering we don't actually understand the mechanisms behind how humans think. We do know that human brains are so good at patterns, they'll even see patterns and such that aren't actually there. LLMs are a pile of statistics that can mimic human speech patterns if you don't tax them too hard. Anyone who thinks otherwise is just Clever Hans-ing themselves.

ACCount37 1y ago
We understand the outcomes well enough. LLMs converge onto a similar process by being trained on human-made text. Is LLM reasoning a 1:1 replica of what the human brain does? No, but it does something very similar in function. I see no reason to think that humans are anything more than "a pile of statistics that can mimic human speech patterns if you don't tax them too hard". Humans can get offended when you point it out though. It's too dismissive of their unique human gift of intelligence that a chatbot clearly doesn't have.
- habinero 1y ago
  > We understand the outcomes well enough We do not, in fact, "understand the outcomes well enough" lol. I don't really care if you want to have an AI waifu or whatever. I'm pointing out that you're vastly underestimating the complexity behind human brains and cognition. And that complex human brain of yours is attributing behaviors to a statistical model that the model does not, in fact, possess.
  - ACCount37 1y ago
    [flagged]
    - pferde 1y ago
      > "We don't fully understand how a bird works, and thus: "wind tunnel" is useless, Wright brothers are utter fools, what their crude mechanical contraptions are doing isn't actually flight, and heavier than air flight is obviously unattainable." Completely false equivalency. We did in fact back then completely understand "how a bird works", how the physics of flight work. The problem getting man-made flying vehicles off the ground was mostly about not having good enough materials to build one (plus some economics-related issues). Whereas in case of AI, we are very far from even slightly understanding how our brains work, how the actual thinking happens.
      - manwe150 1y ago
        One of the Wright brothers achievements was to realize the published tables of flight physics was wrong and to carefully redo it with their own wind tunnel until they had a correct model from which to design a flying vehicle https://humansofdata.atlan.com/2019/07/historical-humans-of-data-the-wright-brothers/ https://humansofdata.atlan.com/2019/07/historical-humans-of-...
        pferde 1y ago
        Ok, that's pretty cool. I didn't know that, thanks!
    - suddenlybananas 1y ago
      We have a good definition of flight, we don't have a good definition of intelligence.
    - throwaway0123_5 1y ago
      I think saying that "LLMs can produce outcomes akin to those produced by human intelligence (in many but not all cases)" and "LLMs are intelligent" to both be fairly defensible. > I see no reason whatsoever to believe that what your wet meat brain is doing now is any different from what an LLM does. I don't think this follows though. Birds and planes can both fly, but a bird and a plane are clearly not doing the same thing to achieve flight. Interestingly, both birds and planes excel at different aspects of flight. It seems at least plausible (imo likely) that there are meaningful differences in how intelligence is implemented in LLMs and humans, and that that might manifest as some aspects of intelligence being accessible to LLMs but not humans and vice versa.
      - jimbo808 1y ago
        > It seems at least plausible (imo likely) that there are meaningful differences in how intelligence is implemented in LLMs and humans Intelligence isn’t "implemented" in an LLM at all. The model doesn’t carry a reasoning engine or a mental model of the world. It generates tokens by mathematically matching patterns: each new token is chosen to best fit the statistical patterns it learned from its training data and the immediate context you give it. In effect, it’s producing a compressed, context-aware summary of the most relevant pieces of its training data, one token at a time. The training data is where the intelligence happened, and that's because it was generated by human brains.
        XenophileJKO 1y ago
        I guess to me, how is the ability to represent the statistical distribution of outcomes of almost any combination of scenarios, represented as textual data not a form of world model?
        jimbo808 1y ago
        I think you're looking at it too abstractly. An LLM isn't representing anything, it has a bag of numbers that some other algorithm produced for it. When you give it some numbers, it takes them and does matrix operations with them in order to randomly select a token from a softmax distribution, one at a time, until the EOS token is generated. If they don't have any training data that covers a particular concept, they can't map it onto a world model and make predictions about that concept based on an understanding of the world and how it works. [This video](https://www.youtube.com/watch?v=160F8F8mXlo https://www.youtube.com/watch?v=160F8F8mXlo) illustrates it pretty well. These things may or may not end up being fixed in the models, but that's only because they've been further trained with the specific examples. Brains have world models. Cats see a cup of water, and they know exactly what will happen when you tip it over (and you can bet they're gonna do it).
    - habinero 1y ago
      "Anthropocentric cope >:(" is one of the funniest things I've read this week, so genuinely thank you for that. "LLMs think like people do" is the equivalent of flat earth theory or UFO bros. Flerfers run on ignorance, misunderstanding and oppositional defiant disorder. You can easily prove the earth is round in quite a lot of ways (the Greeks did it) but the flerfers either don't know them or refuse to apply them. There are quite a lot of reasons to believe brains work differently than LLMs (and ways to prove it) you just don't know them or refuse to believe them. It's neat tech, and I use them. They're just wayyyyyyyy overhyped and we don't need to anthropomorphize them lol
- deleted 1y ago
  [deleted]

ACCount37 1y ago

We understand the outcomes well enough. LLMs converge onto a similar process by being trained on human-made text. Is LLM reasoning a 1:1 replica of what the human brain does? No, but it does something very similar in function. I see no reason to think that humans are anything more than "a pile of statistics that can mimic human speech patterns if you don't tax them too hard". Humans can get offended when you point it out though. It's too dismissive of their unique human gift of intelligence that a chatbot clearly doesn't have.

habinero 1y ago
> We understand the outcomes well enough We do not, in fact, "understand the outcomes well enough" lol. I don't really care if you want to have an AI waifu or whatever. I'm pointing out that you're vastly underestimating the complexity behind human brains and cognition. And that complex human brain of yours is attributing behaviors to a statistical model that the model does not, in fact, possess.
- ACCount37 1y ago
  [flagged]
  - pferde 1y ago
    > "We don't fully understand how a bird works, and thus: "wind tunnel" is useless, Wright brothers are utter fools, what their crude mechanical contraptions are doing isn't actually flight, and heavier than air flight is obviously unattainable." Completely false equivalency. We did in fact back then completely understand "how a bird works", how the physics of flight work. The problem getting man-made flying vehicles off the ground was mostly about not having good enough materials to build one (plus some economics-related issues). Whereas in case of AI, we are very far from even slightly understanding how our brains work, how the actual thinking happens.
    - manwe150 1y ago
      One of the Wright brothers achievements was to realize the published tables of flight physics was wrong and to carefully redo it with their own wind tunnel until they had a correct model from which to design a flying vehicle https://humansofdata.atlan.com/2019/07/historical-humans-of-data-the-wright-brothers/ https://humansofdata.atlan.com/2019/07/historical-humans-of-...
      - pferde 1y ago
        Ok, that's pretty cool. I didn't know that, thanks!
  - suddenlybananas 1y ago
    We have a good definition of flight, we don't have a good definition of intelligence.
  - throwaway0123_5 1y ago
    I think saying that "LLMs can produce outcomes akin to those produced by human intelligence (in many but not all cases)" and "LLMs are intelligent" to both be fairly defensible. > I see no reason whatsoever to believe that what your wet meat brain is doing now is any different from what an LLM does. I don't think this follows though. Birds and planes can both fly, but a bird and a plane are clearly not doing the same thing to achieve flight. Interestingly, both birds and planes excel at different aspects of flight. It seems at least plausible (imo likely) that there are meaningful differences in how intelligence is implemented in LLMs and humans, and that that might manifest as some aspects of intelligence being accessible to LLMs but not humans and vice versa.
    - jimbo808 1y ago
      > It seems at least plausible (imo likely) that there are meaningful differences in how intelligence is implemented in LLMs and humans Intelligence isn’t "implemented" in an LLM at all. The model doesn’t carry a reasoning engine or a mental model of the world. It generates tokens by mathematically matching patterns: each new token is chosen to best fit the statistical patterns it learned from its training data and the immediate context you give it. In effect, it’s producing a compressed, context-aware summary of the most relevant pieces of its training data, one token at a time. The training data is where the intelligence happened, and that's because it was generated by human brains.
      - XenophileJKO 1y ago
        I guess to me, how is the ability to represent the statistical distribution of outcomes of almost any combination of scenarios, represented as textual data not a form of world model?
        jimbo808 1y ago
        I think you're looking at it too abstractly. An LLM isn't representing anything, it has a bag of numbers that some other algorithm produced for it. When you give it some numbers, it takes them and does matrix operations with them in order to randomly select a token from a softmax distribution, one at a time, until the EOS token is generated. If they don't have any training data that covers a particular concept, they can't map it onto a world model and make predictions about that concept based on an understanding of the world and how it works. [This video](https://www.youtube.com/watch?v=160F8F8mXlo https://www.youtube.com/watch?v=160F8F8mXlo) illustrates it pretty well. These things may or may not end up being fixed in the models, but that's only because they've been further trained with the specific examples. Brains have world models. Cats see a cup of water, and they know exactly what will happen when you tip it over (and you can bet they're gonna do it).
  - habinero 1y ago
    "Anthropocentric cope >:(" is one of the funniest things I've read this week, so genuinely thank you for that. "LLMs think like people do" is the equivalent of flat earth theory or UFO bros. Flerfers run on ignorance, misunderstanding and oppositional defiant disorder. You can easily prove the earth is round in quite a lot of ways (the Greeks did it) but the flerfers either don't know them or refuse to apply them. There are quite a lot of reasons to believe brains work differently than LLMs (and ways to prove it) you just don't know them or refuse to believe them. It's neat tech, and I use them. They're just wayyyyyyyy overhyped and we don't need to anthropomorphize them lol
deleted 1y ago
[deleted]