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1. LLMs are transformers, and transformers are next state predictors. LLMs are not Language models (in the sense you are trying to imply) because even when trai

1. LLMs are transformers, and transformers are next state predictors. LLMs are not Language models (in the sense you are trying to imply) because even when training is restricted to only text, text is much more than language. 2. People need to let go of this strange and erroneous idea that humans somehow have this privileged access to the 'real world'. You don't. You run on a heavily filtered, tiny slice of reality. You think you understand electro-magnetism ? Tell that to the birds that innately navigate by sensing the earth's magnetic field. To them, your brain only somewhat models the real world, and evidently quite incompletely. You'll never truly understand electro-magnetism, they might say.

tbrownaw 9mo ago
> 2. People need to let go of this strange and erroneous idea that humans somehow have this privileged access to 'the real world'. You don't. You are denouncing a claim that the comment you're replying to did not make.
- famouswaffles 9mo ago
  They made it implicitly, otherwise this: >(2) language only somewhat models the world is completely irrelevant. Everyone is only 'somewhat modeling' the world. Humans, Animals, and LLMs.
  - D-Machine 9mo ago
    Completely relevant, because LLMs only "somewhat model" humans' "somewhat modeling" of the world...
    - famouswaffles 9mo ago
      LLMs aren't modeling "humans modeling the world" - they're modeling patterns in data that reflect the world directly. When an LLM learns physics from textbooks, scientific papers, and code, it's learning the same compressed representations of reality that humans use, not a "model of a model." Your argument would suggest that because you learned about quantum mechanics through language (textbooks, lectures), you only have access to "humans' modeling of humans' modeling of quantum mechanics" - an infinite regress that's clearly absurd.
      - D-Machine 9mo ago
        > LLMs aren't modeling "humans modeling the world" - they're modeling patterns in data that reflect the world directly. This is a deranged and factually and tautologically (definitionally) false claim. LLMs can only work with tokenizations of texts written by people who produce those text to represent their actual models. All this removal and all these intermediate representational steps make LLMs a priori obviously even more distant from reality than humans. This is all definitional, what you are saying is just nonsense. > When an LLM learns physics from textbooks, scientific papers, and code, it's learning the same compressed representations of reality that humans use, not a "model of a model." A model is a compressed representation of reality. Physics is a model of the mechanics of various parts of the universe, i.e. "learning physics" is "learning a physical model". So, clarifying, the above sentence is > When an LLM learns physical models from textbooks, scientific papers, and code, it's learning the model of reality that humans use, not a "model of a model." This is clearly factually wrong, as the model that humans actually use is not the summaries written in textbooks, but the actual embodied and symbolic model that they use in reality, and which they only translate in corrupted and simplified, limited form to text (and that latter diminished form of all things is all the LLM can see). It is also not clear the LLM learns to actually do physics: it only learns how to write about physics like how humans do, but it doesn't mean it can run labs, interpret experiments, or apply models to novel contexts like humans can, or operate at the same level as humans. It clearly is learning something different from humans because it doesn't have the same sources of info. > Your argument would suggest that because you learned about quantum mechanics through language (textbooks, lectures), you only have access to "humans' modeling of humans' modeling of quantum mechanics" - an infinite regress that's clearly absurd. There is no infinite regress: humans actually verify that the things they learn and say are correct and provide effects, and update models accordingly. They do this by trying behaviours consistent with the learned model, and seeing how reality (other people, the physical world) responds (in degree and kind). LLMs have no conception of correctness or truth (not in any of the loss functions), and are trained and then done. Humans can't learn solely from digesting texts either. Anyone who has done math knows that reading a textbook doesn't teach you almost anything, you have to actually solve the problems (and attempted-solving is not in much/any texts) and discuss your solutions and reasoning with others. Other domains involving embodied skills, like cooking, require other kinds of feedback from the environment and others. But LLMs are imprisoned in tokens. EDIT: No serious researcher thinks LLMs are the way to AGI, this hasn't been a controversial opinion even among enthusiasts since about mid-2025 or so. This stuff about language is all trivial and basic stuff accepted by people in the field, and why things like V-JEPA-2 are being researched. So the comments here attempting to argue otherwise are really quite embarrassing.
  - canadiantim 9mo ago
    You're wrong about this: "People need to let go of this strange and erroneous idea that humans somehow have this privileged access to the 'real world'. You don't." People do have a privileged access to the 'real world' compared to, for example, LLMs and any future AI. It's called: Consciousness and it is how we experience and come to know and understand the world. Consciousness is the privileged access that AI will never have.
    - pixl97 9mo ago
      > It's called: Consciousness Ok, explain its mechanism and why it gives privileged access. Furthermore I'd go for the Nobel prize and describe the elementary mechanics of consciousness and where the state change from non-conscious versus conscious occurs. It would be enlightening to read your paper.
      - canadiantim 9mo ago
        Actually consciousness has been well studied and many papers already exist describing the elementary mechanics of consciousness. Look up neuroscience papers on qualia, for example and you’ll find your answers as to why consciousness is a privileged access not available to AI or any machine. Eg humans have qualia, which are fundamentally irreducible, while AI does not and cannot.
        pixl97 9mo ago
        >which are fundamentally irreducible Just no, please stop making things up because you feel like it. Trying to say one of the most hotly debated ideals in neuroscience has been decided or even well understood is absolutely insane. Even then you get into, animals have qualia right? But they are not expressive as human qualia, which means it is reducible.
        canadiantim 9mo ago
        It's literally part of the definition. Qualia is a well recognized term in neuroscience. I suspect maybe you haven't done much research into this area? Qualia is pretty well established and has been for a long time. Animals may have qualia, that's true. Though we can only be sure of our own qualia, because that's all we have access to. Qualia is the constituent parts that make up our subjective conscious experience, the atomized subjective experience, like the color red or the taste of sour.
D-Machine 9mo ago
LLMs are language models, something being a transformer or next-state predictor does not make it a language model. You can also have e.g. convolutional language models or LSTM-based language models. This is a basic point that anyone with any proper understanding of these models would know. Even if you disagree with these semantics, the major LLMs today are primarily trained on natural language. But, yes, as I said in another comment on this thread, it isn't that simple, because LLMs today are trained on tokens from tokenizers, and these tokenizers are trained on text that includes e.g. natural language, mathematical symbolism, and code. Yes, humans have incredibly limited access to the real world. But they experience and model this world with far more tools and machinery than language. Sometimes, in certain cases, they attempt to messily translate this messy, multimodal understanding into tokens, and then make those tokens available on the internet. An LLM (in the sense everyone means it, which, again, is largely a natural language model, but certainly just a tokenized text model) has access only to these messy tokens, so, yes, far less capacity than humanity collectively. And though the LLM can integrate knowledge from a massive amount of tokens from a huge amount of humans, even a single human has more different kinds of sensory information and modality-specific knowledge than the LLM. So humans DO have more privileged access to the real world than LLMs (even though we can barely access a slice of reality at all).
- famouswaffles 9mo ago
  >LLMs are language models, something being a transformer or next-state predictors does not make it a language model. You can also have e.g. convolutional language models or LSTM-based language models. This is a basic point that anyone with any proper understanding of these models would know. 'Language Model' has no inherent meaning beyond 'predicts natural language sequences'. You are trying to make it mean more than that. You can certainly make something you'd call a language model with convolution or LSTMs, but that's just a semantics game. In practice, they would not work like transformers and would in fact perform much worse than them with the same compute budget. >Even if you disagree with these semantics, the major LLMs today are primarily trained on natural language. The major LLMs today are trained on trillions of tokens of text, much of which has nothing to do with language beyond the means of communication, millions of images and million(s) of hours of audio. The problem as I tried to explain is that you're packing more meaning into 'Language Model' than you should. Being trained on text does not mean all your responses are modelled via language as you seem to imply. Even for a model trained on text, only the first and last few layers of a LLM concerns language.
rockinghigh 9mo ago
A language model in computer science is a model that predicts the probability of a sentence or a word given a sentence. This definition predates LLMs.
- famouswaffles 9mo ago
  A 'language model' only has meaning in so far as it tells you this thing 'predicts natural language sequences'. It does not tell you how these sequences are being predicted or any anything about what's going on inside, so all the extra meaning OP is trying to place by calling them Language Models is well...misplaced. That's the point I was trying to make.
phailhaus 9mo ago
> People need to let go of this strange and erroneous idea that humans somehow have this privileged access to the 'real world'. This is irrelevant, the point is that you do have access to a world which LLMs don't, at all. They only get the text we produce after we interact with the world. It is working with "compressed data" at all times, and have absolutely no idea what we subconsciously internalized that we decided not to write down or why.
- famouswaffles 9mo ago
  All of the SOTA LLMs today are trained on more than text. It doesn't matter whether LLMs have "complete" (nothing does) or human-like world access, but whether the compression in text is lossy in ways that fundamentally prevent useful world modeling or reconstruction. And empirically... it doesn't seem to be. Text contains an enormous amount of implicit structure about how the world works, precisely because humans writing it did interact with the world and encoded those patterns. And your subconscious is far leakier than you imagine. Your internal state will bleed into your writing, one way or another whether you're aware of it or not. Models can learn to reconstruct arithmetic algorithms given just operation and answer with no instruction. What sort of things have LLMs reconstructed after being trained on trillions of tokens of data ?

tbrownaw 9mo ago

> 2. People need to let go of this strange and erroneous idea that humans somehow have this privileged access to 'the real world'. You don't. You are denouncing a claim that the comment you're replying to did not make.

famouswaffles 9mo ago
They made it implicitly, otherwise this: >(2) language only somewhat models the world is completely irrelevant. Everyone is only 'somewhat modeling' the world. Humans, Animals, and LLMs.
- D-Machine 9mo ago
  Completely relevant, because LLMs only "somewhat model" humans' "somewhat modeling" of the world...
  - famouswaffles 9mo ago
    LLMs aren't modeling "humans modeling the world" - they're modeling patterns in data that reflect the world directly. When an LLM learns physics from textbooks, scientific papers, and code, it's learning the same compressed representations of reality that humans use, not a "model of a model." Your argument would suggest that because you learned about quantum mechanics through language (textbooks, lectures), you only have access to "humans' modeling of humans' modeling of quantum mechanics" - an infinite regress that's clearly absurd.
    - D-Machine 9mo ago
      > LLMs aren't modeling "humans modeling the world" - they're modeling patterns in data that reflect the world directly. This is a deranged and factually and tautologically (definitionally) false claim. LLMs can only work with tokenizations of texts written by people who produce those text to represent their actual models. All this removal and all these intermediate representational steps make LLMs a priori obviously even more distant from reality than humans. This is all definitional, what you are saying is just nonsense. > When an LLM learns physics from textbooks, scientific papers, and code, it's learning the same compressed representations of reality that humans use, not a "model of a model." A model is a compressed representation of reality. Physics is a model of the mechanics of various parts of the universe, i.e. "learning physics" is "learning a physical model". So, clarifying, the above sentence is > When an LLM learns physical models from textbooks, scientific papers, and code, it's learning the model of reality that humans use, not a "model of a model." This is clearly factually wrong, as the model that humans actually use is not the summaries written in textbooks, but the actual embodied and symbolic model that they use in reality, and which they only translate in corrupted and simplified, limited form to text (and that latter diminished form of all things is all the LLM can see). It is also not clear the LLM learns to actually do physics: it only learns how to write about physics like how humans do, but it doesn't mean it can run labs, interpret experiments, or apply models to novel contexts like humans can, or operate at the same level as humans. It clearly is learning something different from humans because it doesn't have the same sources of info. > Your argument would suggest that because you learned about quantum mechanics through language (textbooks, lectures), you only have access to "humans' modeling of humans' modeling of quantum mechanics" - an infinite regress that's clearly absurd. There is no infinite regress: humans actually verify that the things they learn and say are correct and provide effects, and update models accordingly. They do this by trying behaviours consistent with the learned model, and seeing how reality (other people, the physical world) responds (in degree and kind). LLMs have no conception of correctness or truth (not in any of the loss functions), and are trained and then done. Humans can't learn solely from digesting texts either. Anyone who has done math knows that reading a textbook doesn't teach you almost anything, you have to actually solve the problems (and attempted-solving is not in much/any texts) and discuss your solutions and reasoning with others. Other domains involving embodied skills, like cooking, require other kinds of feedback from the environment and others. But LLMs are imprisoned in tokens. EDIT: No serious researcher thinks LLMs are the way to AGI, this hasn't been a controversial opinion even among enthusiasts since about mid-2025 or so. This stuff about language is all trivial and basic stuff accepted by people in the field, and why things like V-JEPA-2 are being researched. So the comments here attempting to argue otherwise are really quite embarrassing.
- canadiantim 9mo ago
  You're wrong about this: "People need to let go of this strange and erroneous idea that humans somehow have this privileged access to the 'real world'. You don't." People do have a privileged access to the 'real world' compared to, for example, LLMs and any future AI. It's called: Consciousness and it is how we experience and come to know and understand the world. Consciousness is the privileged access that AI will never have.
  - pixl97 9mo ago
    > It's called: Consciousness Ok, explain its mechanism and why it gives privileged access. Furthermore I'd go for the Nobel prize and describe the elementary mechanics of consciousness and where the state change from non-conscious versus conscious occurs. It would be enlightening to read your paper.
    - canadiantim 9mo ago
      Actually consciousness has been well studied and many papers already exist describing the elementary mechanics of consciousness. Look up neuroscience papers on qualia, for example and you’ll find your answers as to why consciousness is a privileged access not available to AI or any machine. Eg humans have qualia, which are fundamentally irreducible, while AI does not and cannot.
      - pixl97 9mo ago
        >which are fundamentally irreducible Just no, please stop making things up because you feel like it. Trying to say one of the most hotly debated ideals in neuroscience has been decided or even well understood is absolutely insane. Even then you get into, animals have qualia right? But they are not expressive as human qualia, which means it is reducible.
        canadiantim 9mo ago
        It's literally part of the definition. Qualia is a well recognized term in neuroscience. I suspect maybe you haven't done much research into this area? Qualia is pretty well established and has been for a long time. Animals may have qualia, that's true. Though we can only be sure of our own qualia, because that's all we have access to. Qualia is the constituent parts that make up our subjective conscious experience, the atomized subjective experience, like the color red or the taste of sour.

D-Machine 9mo ago

LLMs are language models, something being a transformer or next-state predictor does not make it a language model. You can also have e.g. convolutional language models or LSTM-based language models. This is a basic point that anyone with any proper understanding of these models would know. Even if you disagree with these semantics, the major LLMs today are primarily trained on natural language. But, yes, as I said in another comment on this thread, it isn't that simple, because LLMs today are trained on tokens from tokenizers, and these tokenizers are trained on text that includes e.g. natural language, mathematical symbolism, and code. Yes, humans have incredibly limited access to the real world. But they experience and model this world with far more tools and machinery than language. Sometimes, in certain cases, they attempt to messily translate this messy, multimodal understanding into tokens, and then make those tokens available on the internet. An LLM (in the sense everyone means it, which, again, is largely a natural language model, but certainly just a tokenized text model) has access only to these messy tokens, so, yes, far less capacity than humanity collectively. And though the LLM can integrate knowledge from a massive amount of tokens from a huge amount of humans, even a single human has more different kinds of sensory information and modality-specific knowledge than the LLM. So humans DO have more privileged access to the real world than LLMs (even though we can barely access a slice of reality at all).

famouswaffles 9mo ago
>LLMs are language models, something being a transformer or next-state predictors does not make it a language model. You can also have e.g. convolutional language models or LSTM-based language models. This is a basic point that anyone with any proper understanding of these models would know. 'Language Model' has no inherent meaning beyond 'predicts natural language sequences'. You are trying to make it mean more than that. You can certainly make something you'd call a language model with convolution or LSTMs, but that's just a semantics game. In practice, they would not work like transformers and would in fact perform much worse than them with the same compute budget. >Even if you disagree with these semantics, the major LLMs today are primarily trained on natural language. The major LLMs today are trained on trillions of tokens of text, much of which has nothing to do with language beyond the means of communication, millions of images and million(s) of hours of audio. The problem as I tried to explain is that you're packing more meaning into 'Language Model' than you should. Being trained on text does not mean all your responses are modelled via language as you seem to imply. Even for a model trained on text, only the first and last few layers of a LLM concerns language.

rockinghigh 9mo ago

A language model in computer science is a model that predicts the probability of a sentence or a word given a sentence. This definition predates LLMs.

famouswaffles 9mo ago
A 'language model' only has meaning in so far as it tells you this thing 'predicts natural language sequences'. It does not tell you how these sequences are being predicted or any anything about what's going on inside, so all the extra meaning OP is trying to place by calling them Language Models is well...misplaced. That's the point I was trying to make.

phailhaus 9mo ago

> People need to let go of this strange and erroneous idea that humans somehow have this privileged access to the 'real world'. This is irrelevant, the point is that you do have access to a world which LLMs don't, at all. They only get the text we produce after we interact with the world. It is working with "compressed data" at all times, and have absolutely no idea what we subconsciously internalized that we decided not to write down or why.

famouswaffles 9mo ago
All of the SOTA LLMs today are trained on more than text. It doesn't matter whether LLMs have "complete" (nothing does) or human-like world access, but whether the compression in text is lossy in ways that fundamentally prevent useful world modeling or reconstruction. And empirically... it doesn't seem to be. Text contains an enormous amount of implicit structure about how the world works, precisely because humans writing it did interact with the world and encoded those patterns. And your subconscious is far leakier than you imagine. Your internal state will bleed into your writing, one way or another whether you're aware of it or not. Models can learn to reconstruct arithmetic algorithms given just operation and answer with no instruction. What sort of things have LLMs reconstructed after being trained on trillions of tokens of data ?