4 ms·

I keep hearing this non sequitur argument a lot. It's like saying "humans just pick the next work to string together into a sentence, they're not actually dutif

by stavros 11mo ago

I keep hearing this non sequitur argument a lot. It's like saying "humans just pick the next work to string together into a sentence, they're not actually dutiful agents". The non sequitur is in assuming that somehow the mechanism of operation dictates the output, which isn't necessarily true. It's like saying "humans can't be thinking, their brains are just cells that transmit electric impulses". Maybe it's accidentally true that they can't think, but the premise doesn't necessarily logically lead to truth

grey-area 11mo ago
No it’s not like saying that, because that is not at all what humans do when they think. This is self-evident when comparing human responses to problems be LLMs and you have been taken in by the marketing of ‘agents’ etc.
- stavros 11mo ago
  You've misunderstood what I'm saying. Regardless of whether LLMs think or not, the sentence "LLMs don't think because they predict the next token" is logically as wrong as "fleas can't jump because they have short legs".
  - stevenhuang 11mo ago
    > not at all what humans do when they think. Parent commentator should probably square with the fact we know little about our own cognition, and it's really an open question how is it we think. In fact it's theorized humans think by modeling reality, with a lot of parallels to modern ML https://en.wikipedia.org/wiki/Predictive_coding https://en.wikipedia.org/wiki/Predictive_coding
    - stavros 11mo ago
      That's the issue, we don't really know enough about how LLMs work to say, and we definitely don't know enough about how humans work.
      - grey-area 11mo ago
        We absolutely do, we know exactly how LLMs work. They generate plausible text from a corpus. They don't accurately reproduce data/text, don't think, they don't have a world view or a world model, and they sometimes generate plausible yet incorrect data.
        stavros 11mo ago
        How do they generate the text? Because to me it sounds like "we know how humans work, they make sounds with their mouths, they don't think, have a model of the world..."
  - Arkhaine_kupo 11mo ago
    > the sentence "LLMs don't think because they predict the next token" is logically as wrong it isn't, depending on the deifinition of "THINK". If you believe that thought is the process for where an agent with a world model, takes in input, analysies the circumstances and predicts an outcome and models their beaviour due to that prediction. Then the sentence of "LLMs dont think because they predict a token" is entirely correct. They cannot have a world model, they could in some way be said to receive a sensory input through the prompt. But they are neither analysing that prompt against its own subjectivity, nor predicting outcomes, coming up with a plan or changing its action/response/behaviour due to it. Any definition of "Think" that requieres agency or a world model (which as far as I know are all of them) would exclude an LLM by definition.
    - ToValueFunfetti 11mo ago
      I think Anthropic has established that LLMs have at least a rudimentary world model (regions of tensors that represent concepts and relationships between them) and that they modify behavior due to a prediction (putting a word at the end of the second line of a poem based on the rhyme they need for the last). Maybe they come up short on 'analyzing the circumstances'; not really sure how to define that in a way that is not trivial. This may not be enough to convince you that they do think. It hasn't convinced me either. But I don't think your confident assertions that they don't are borne out by any evidence. We really don't know how these things tick (otherwise we could reimplement their matrices in code and save $$$). If you put a person in charge of predicting which direction a fish will be facing in 5 minutes, they'll need to produce a mental model of how the fish thinks in order to be any good at it. Even though their output will just be N/E/S/W, they'll need to keep track internally of how hungry or tired the fish is. Or maybe they just memorize a daily routine and repeat it. The open question is what needs to be internalized in order to predict ~all human text with a low error rate. The fact that the task is 'predict next token' doesn't tell us very much at all about the internals. The resulting weights are uninterpretable. We really don't know what they're doing, and there's no fundamental reason it can't be 'thinking', for any definition.
      - Arkhaine_kupo 11mo ago
Antibabelic 11mo ago
> The non sequitur is in assuming that somehow the mechanism of operation dictates the output, which isn't necessarily true. Where does the output come from if not the mechanism?
- stavros 11mo ago
  So you agree humans can't really think because it's all just electrical impulses?
  - Antibabelic 11mo ago
    Human "thought" is the way it is because "electrical impulses" (wildly inaccurate description of how the brain works, but I'll let it pass for the sake of the argument) implement it. They are its mechanism. LLMs are not implemented like a human brain, so if they do have anything similar to "thought", it's a qualitatively different thing, since the mechanism is different.
    - socialcommenter 11mo ago
      Mature sunflowers reliably point due east, needles on a compass point north. They implement different things using different mechanisms, yet are really the same.
      - Antibabelic 11mo ago
        You can get the same output from different mechanisms, like in your example. Another would be that it's equally possible to quickly do addition on a modern pocket calculator and an arithmometer, despite them fundamentally being different. However. 1. You can infer the output from the mechanism. (Because it is implemented by it). 2. You can't infer the mechanism from the output. (Because different mechanisms can easily produce the same output). My point here is 1, in response to the parent commenter's "the mechanism of operation dictates the output, which isn't necessarily true". The mechanism of operation (whether of LLMs or sunflowers) absolutely dictates their output, and we can make valid inferences about that output based on how we understand that mechanism operates.
swatcoder 11mo ago
There's nothing said here that suggests they can't think. That's an entirely different discussion. My comment is specifically written so that you can take it for granted that they think. What's being discussed is that if you do so, you need to consider how they think, because this is indeed dictated by how they operate. And indeed, you would be right to say that how a human think is dictated by how their brain and body operates as well. Thinking, whatever it's taken to be, isn't some binary mode. It's a rich and faceted process that can present and unfold in many different ways. Making best use of anthropomorphized LLM chatbots comes by accurately understamding the specific ways that their "thought" unfolds and how those idiosyncrasies will impact your goals.
samdoesnothing 11mo ago
I never got the impression they were saying that the mechanism of operation dictates the output. It seemed more like they were making a direct observation about the output.

by stavros 11mo ago

grey-area 11mo ago

No it’s not like saying that, because that is not at all what humans do when they think. This is self-evident when comparing human responses to problems be LLMs and you have been taken in by the marketing of ‘agents’ etc.

stavros 11mo ago
You've misunderstood what I'm saying. Regardless of whether LLMs think or not, the sentence "LLMs don't think because they predict the next token" is logically as wrong as "fleas can't jump because they have short legs".
- stevenhuang 11mo ago
  > not at all what humans do when they think. Parent commentator should probably square with the fact we know little about our own cognition, and it's really an open question how is it we think. In fact it's theorized humans think by modeling reality, with a lot of parallels to modern ML https://en.wikipedia.org/wiki/Predictive_coding https://en.wikipedia.org/wiki/Predictive_coding
  - stavros 11mo ago
    That's the issue, we don't really know enough about how LLMs work to say, and we definitely don't know enough about how humans work.
    - grey-area 11mo ago
      We absolutely do, we know exactly how LLMs work. They generate plausible text from a corpus. They don't accurately reproduce data/text, don't think, they don't have a world view or a world model, and they sometimes generate plausible yet incorrect data.
      - stavros 11mo ago
        How do they generate the text? Because to me it sounds like "we know how humans work, they make sounds with their mouths, they don't think, have a model of the world..."
- Arkhaine_kupo 11mo ago
  > the sentence "LLMs don't think because they predict the next token" is logically as wrong it isn't, depending on the deifinition of "THINK". If you believe that thought is the process for where an agent with a world model, takes in input, analysies the circumstances and predicts an outcome and models their beaviour due to that prediction. Then the sentence of "LLMs dont think because they predict a token" is entirely correct. They cannot have a world model, they could in some way be said to receive a sensory input through the prompt. But they are neither analysing that prompt against its own subjectivity, nor predicting outcomes, coming up with a plan or changing its action/response/behaviour due to it. Any definition of "Think" that requieres agency or a world model (which as far as I know are all of them) would exclude an LLM by definition.
  - ToValueFunfetti 11mo ago
    I think Anthropic has established that LLMs have at least a rudimentary world model (regions of tensors that represent concepts and relationships between them) and that they modify behavior due to a prediction (putting a word at the end of the second line of a poem based on the rhyme they need for the last). Maybe they come up short on 'analyzing the circumstances'; not really sure how to define that in a way that is not trivial. This may not be enough to convince you that they do think. It hasn't convinced me either. But I don't think your confident assertions that they don't are borne out by any evidence. We really don't know how these things tick (otherwise we could reimplement their matrices in code and save $$$). If you put a person in charge of predicting which direction a fish will be facing in 5 minutes, they'll need to produce a mental model of how the fish thinks in order to be any good at it. Even though their output will just be N/E/S/W, they'll need to keep track internally of how hungry or tired the fish is. Or maybe they just memorize a daily routine and repeat it. The open question is what needs to be internalized in order to predict ~all human text with a low error rate. The fact that the task is 'predict next token' doesn't tell us very much at all about the internals. The resulting weights are uninterpretable. We really don't know what they're doing, and there's no fundamental reason it can't be 'thinking', for any definition.
    - Arkhaine_kupo 11mo ago

Antibabelic 11mo ago

> The non sequitur is in assuming that somehow the mechanism of operation dictates the output, which isn't necessarily true. Where does the output come from if not the mechanism?

stavros 11mo ago
So you agree humans can't really think because it's all just electrical impulses?
- Antibabelic 11mo ago
  Human "thought" is the way it is because "electrical impulses" (wildly inaccurate description of how the brain works, but I'll let it pass for the sake of the argument) implement it. They are its mechanism. LLMs are not implemented like a human brain, so if they do have anything similar to "thought", it's a qualitatively different thing, since the mechanism is different.
  - socialcommenter 11mo ago
    Mature sunflowers reliably point due east, needles on a compass point north. They implement different things using different mechanisms, yet are really the same.
    - Antibabelic 11mo ago
      You can get the same output from different mechanisms, like in your example. Another would be that it's equally possible to quickly do addition on a modern pocket calculator and an arithmometer, despite them fundamentally being different. However. 1. You can infer the output from the mechanism. (Because it is implemented by it). 2. You can't infer the mechanism from the output. (Because different mechanisms can easily produce the same output). My point here is 1, in response to the parent commenter's "the mechanism of operation dictates the output, which isn't necessarily true". The mechanism of operation (whether of LLMs or sunflowers) absolutely dictates their output, and we can make valid inferences about that output based on how we understand that mechanism operates.

swatcoder 11mo ago

There's nothing said here that suggests they can't think. That's an entirely different discussion. My comment is specifically written so that you can take it for granted that they think. What's being discussed is that if you do so, you need to consider how they think, because this is indeed dictated by how they operate. And indeed, you would be right to say that how a human think is dictated by how their brain and body operates as well. Thinking, whatever it's taken to be, isn't some binary mode. It's a rich and faceted process that can present and unfold in many different ways. Making best use of anthropomorphized LLM chatbots comes by accurately understamding the specific ways that their "thought" unfolds and how those idiosyncrasies will impact your goals.

samdoesnothing 11mo ago

I never got the impression they were saying that the mechanism of operation dictates the output. It seemed more like they were making a direct observation about the output.