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Funny, because riding a bicycle or speaking a language is exactly something people don't have a world model of. Ask someone to explain how riding a bicycle work

Funny, because riding a bicycle or speaking a language is exactly something people don't have a world model of. Ask someone to explain how riding a bicycle works, or an uneducated native speaker to explain the grammar of their language. They have no clue. "Making the right movement at the right time within a narrow boundary of conditions" is a world model, or is it just predicting the next move? > You are falling IMO into exactly the trap of the linguistic reductionist, thinking that language is the be-all and end-all of cognition. I'm not saying that at all. I am saying that any (sufficiently long, varied) coherent speech needs a world model, so if something produces coherent speech, there must be a world model behind. We can agree that the model is lacking as much as the language productions are incoherent: which is very little, these days.

D-Machine 9mo ago
> Funny, because riding a bicycle or speaking a language is exactly something people don't have a world model of. Ask someone to explain how riding a bicycle works, or an uneducated native speaker to explain the grammar of their language. They have no clue This is circular, because you are assuming their world-model of biking can be expressed in language. It can't! EDIT: There are plenty of skilled experts, artists and etc. that clearly and obviously have complex world models that let them produce best-in-the-world outputs, but who can't express very precisely how they do this. I would never claim such people have no world model or understanding of what they do. Perhaps we have a semantic / definitional issue here?
- throw310822 9mo ago
  > This is circular, because you are assuming their world-model of biking can be expressed in language. It can't! Ok. So I think I get it. For me, producing coherent discourse about things requires a world model, because you can't just make up coherent relationships between objects and actions long enough if you don't understand what their properties are and how they relate to each other. You, on the other hand, claim that there are infinite firsthand sensory experiences (maybe we can call them qualia?) that fall in between the cracks of language and are rarely communicated (though we use for that a wealth of metaphors and synesthesia) and can only be understood by those who have experienced them firsthand. I can agree with that if that's what you mean, but at the same time I'm not sure they constitute such a big part of our thought and communication. For example, we are discussing about reality in this thread and yet there are no necessary references to first hand experiences. Any time we talk about history, physics, space, maths, philosophy, we're basically juggling concepts in our heads with zero direct experience of them.
  - D-Machine 9mo ago
    > You, on the other hand, claim that there are infinite firsthand sensory experiences (maybe we can call them qualia?) that fall in between the cracks of language and are rarely communicated (though we use for that a wealth of metaphors and synesthesia) and can only be understood by those who have experienced them firsthand. Well, not infinite, but, yes! I am indeed claiming much world models are patterns and associations between qualia, and that only some qualia are essentially representable as or look like linguistic tokens (specifically, the sounds of those tokens being pronounced, or their visual shapes if e.g. math symbols). E.g. I am claiming that the way one learns to e.g. cook, or "do theoretical math" may be more about forming associations between those non-linguistic qualia than, say, obviously, doing philosophy is. > I'm not sure they constitute such a big part of our thought and communication The communication part is mostly tautological again, but, yes, it remains very much an open question in cognitive science just how exactly thought works. A lot of mathematicians claim to lean heavily on visualization and/or tactile and kinaesthetic modeling for their intuitions (and most deep math is driven by intuition first), but also a lot of mathematicians can produce similar works and disagree about how they think about it intuitively. And we are seeing some progress from e.g. Aristotle using LEAN to generate math proofs in a strictly tokenized / symbolic way, but it remains to be seen if this will ever produce anything truly impressive to mathematicians. So it is really hard to know what actually matters for general human cognition. I think introspection makes it clear there are a LOT of domains where it is obvious the core knowledge is not mostly linguistic. This is easiest to argue for embodied domains and skills (e.g. anything that requires direct physical interaction with the world), and it is areas like these (e.g. self-driving vehicle AI) where LLMs will be (most likely) least useful in isolation, IMO.
- pixl97 9mo ago
  > because you are assuming their world-model of biking can be expressed in language. It can't! So you can't build an AI model that simulates riding a bike? I'm not stating a LLM model, I'm just saying the kind of AI simulation we've been building virtual worlds with for decades. So, now that you agree that we can build AI models of simulations, what are those AI models doing. Are they using a binary language that can be summarized?
  - D-Machine 9mo ago
    Obviously you can build an AI model that rides a bike, just not an LLM that does so. Even the transformer architecture would need significant modification to handle the multiple input sensor streams, and this would be continuous data you don't tokenize, and which might not need self-attention, since sensor data doesn't have long-range dependencies like language does. The biking AI model would almost certainly not resemble an LLM very much. Calling everything "language" is not some gotcha, the middle "L" in LLM means natural language. Binary code is not "language" in this sense, and these terms matter. Robotics AIs are not LLMs, they are just AI.
    - pixl97 9mo ago
      >Binary code is not "language" in this sense Any series of self consistent encoded signals can be language. You could feed an LLM wireless signals if until it learned how to connect to your wifi if you wanted to. Just assign tokens. You're acting like words are something different than encoded information. It's the interconnectivity between those bits of data that matters.
      - D-Machine 9mo ago
        This literally ignores everything I said and you clearly are out of your depth. See my other comment, sensor data can't be handled by LLMs, it is nothing like natural language. https://news.ycombinator.com/item?id=46948266 https://news.ycombinator.com/item?id=46948266
jazzyjackson 9mo ago
> Ask someone to explain how riding a bicycle works, or an uneducated native speaker to explain the grammar of their language. They have no clue. This works against your argument. Someone who can ride a bike clearly knows how to ride a bike, that they cannot express it in tokenized form speaks to the limited scope ofof written word in representing embodiment.
- throw310822 9mo ago
  Yes and no. Riding a bicycle is a skill: your brain is trained to do the right thing and there's some basic feedback loop that keeps you in balance. You could call that a world model if you want, but it's entirely self contained, limited to a very few basic sensory signals (acceleration and balance), and it's outside your conscious knowledge. Plenty of people lack this particular "world model" and can talk about cyclists and bicycles and traffic, and whatnot.
  - jazzyjackson 9mo ago
    Ok so I don’t understand your assertion. Just because an LLM can talk about acceleration and balance doesn’t mean it could actually control a bicycle without training with the sensory input, embedded in a world that includes more than just text tokens. Ergo, the text does not adequately represent the world.
- pixl97 9mo ago
  Um, yea, I call complete bullshit on this. I don't think anyone here on HN is watching what is happening in robotics right now. Nvidia is out building LLM driven models that work with robot models that simulate robot actions. World simulation was a huge part of AI before LLMs became a thing. With a tight coupling between LLMs and robot models we've seen an explosion in robot capabilities in the last few years. You know what robots communicate with their actuators and sensors with. Oh yes, binary data. We quite commonly call that words. When you have a set of actions that simulate riding a bicycle in virtual space that can be summarized and described. Who knows if humans can actually read/understand what the model spits out, but that doesn't mean it's invalid.
imtringued 9mo ago
I don't know how you got this so wrong. In control theory you have to build a dynamical system of your plant (machine, factory, etc). If you have a humanoid robot, you not only need to model the robot itself, which is the easy part actually, you have to model everything the robot is interacting with. Once you understand that, you realize that the human brain has an internal model of almost everything it is interacting with and replicating human level performance requires the entire human brain, not just isolated parts of it. The reason for this is that since we take our brains for granted, we use even the complicated and hard to replicate parts of the brain for tasks that appear seemingly trivial. When I take out the trash, organic waste needs to be thrown into the trash bin without the plastic bag. I need to untie the trash bag, pinch it from the other side and then shake it until the bag is empty. You might say big deal, but when you have tea bags or potato peels inside, they get caught on the bag handles and get stuck. You now need to shake the bag in very particular ways to dislodge the waste. Doing this with a humanoid robot is basically impossible, because you would need to model every scrap of waste inside the plastic bag. The much smarter way is to make the situation robot friendly by having the robot carry the organic waste inside a portable plastic bin without handles.

D-Machine 9mo ago

> Funny, because riding a bicycle or speaking a language is exactly something people don't have a world model of. Ask someone to explain how riding a bicycle works, or an uneducated native speaker to explain the grammar of their language. They have no clue This is circular, because you are assuming their world-model of biking can be expressed in language. It can't! EDIT: There are plenty of skilled experts, artists and etc. that clearly and obviously have complex world models that let them produce best-in-the-world outputs, but who can't express very precisely how they do this. I would never claim such people have no world model or understanding of what they do. Perhaps we have a semantic / definitional issue here?

throw310822 9mo ago
> This is circular, because you are assuming their world-model of biking can be expressed in language. It can't! Ok. So I think I get it. For me, producing coherent discourse about things requires a world model, because you can't just make up coherent relationships between objects and actions long enough if you don't understand what their properties are and how they relate to each other. You, on the other hand, claim that there are infinite firsthand sensory experiences (maybe we can call them qualia?) that fall in between the cracks of language and are rarely communicated (though we use for that a wealth of metaphors and synesthesia) and can only be understood by those who have experienced them firsthand. I can agree with that if that's what you mean, but at the same time I'm not sure they constitute such a big part of our thought and communication. For example, we are discussing about reality in this thread and yet there are no necessary references to first hand experiences. Any time we talk about history, physics, space, maths, philosophy, we're basically juggling concepts in our heads with zero direct experience of them.
- D-Machine 9mo ago
  > You, on the other hand, claim that there are infinite firsthand sensory experiences (maybe we can call them qualia?) that fall in between the cracks of language and are rarely communicated (though we use for that a wealth of metaphors and synesthesia) and can only be understood by those who have experienced them firsthand. Well, not infinite, but, yes! I am indeed claiming much world models are patterns and associations between qualia, and that only some qualia are essentially representable as or look like linguistic tokens (specifically, the sounds of those tokens being pronounced, or their visual shapes if e.g. math symbols). E.g. I am claiming that the way one learns to e.g. cook, or "do theoretical math" may be more about forming associations between those non-linguistic qualia than, say, obviously, doing philosophy is. > I'm not sure they constitute such a big part of our thought and communication The communication part is mostly tautological again, but, yes, it remains very much an open question in cognitive science just how exactly thought works. A lot of mathematicians claim to lean heavily on visualization and/or tactile and kinaesthetic modeling for their intuitions (and most deep math is driven by intuition first), but also a lot of mathematicians can produce similar works and disagree about how they think about it intuitively. And we are seeing some progress from e.g. Aristotle using LEAN to generate math proofs in a strictly tokenized / symbolic way, but it remains to be seen if this will ever produce anything truly impressive to mathematicians. So it is really hard to know what actually matters for general human cognition. I think introspection makes it clear there are a LOT of domains where it is obvious the core knowledge is not mostly linguistic. This is easiest to argue for embodied domains and skills (e.g. anything that requires direct physical interaction with the world), and it is areas like these (e.g. self-driving vehicle AI) where LLMs will be (most likely) least useful in isolation, IMO.
pixl97 9mo ago
> because you are assuming their world-model of biking can be expressed in language. It can't! So you can't build an AI model that simulates riding a bike? I'm not stating a LLM model, I'm just saying the kind of AI simulation we've been building virtual worlds with for decades. So, now that you agree that we can build AI models of simulations, what are those AI models doing. Are they using a binary language that can be summarized?
- D-Machine 9mo ago
  Obviously you can build an AI model that rides a bike, just not an LLM that does so. Even the transformer architecture would need significant modification to handle the multiple input sensor streams, and this would be continuous data you don't tokenize, and which might not need self-attention, since sensor data doesn't have long-range dependencies like language does. The biking AI model would almost certainly not resemble an LLM very much. Calling everything "language" is not some gotcha, the middle "L" in LLM means natural language. Binary code is not "language" in this sense, and these terms matter. Robotics AIs are not LLMs, they are just AI.
  - pixl97 9mo ago
    >Binary code is not "language" in this sense Any series of self consistent encoded signals can be language. You could feed an LLM wireless signals if until it learned how to connect to your wifi if you wanted to. Just assign tokens. You're acting like words are something different than encoded information. It's the interconnectivity between those bits of data that matters.
    - D-Machine 9mo ago
      This literally ignores everything I said and you clearly are out of your depth. See my other comment, sensor data can't be handled by LLMs, it is nothing like natural language. https://news.ycombinator.com/item?id=46948266 https://news.ycombinator.com/item?id=46948266

jazzyjackson 9mo ago

> Ask someone to explain how riding a bicycle works, or an uneducated native speaker to explain the grammar of their language. They have no clue. This works against your argument. Someone who can ride a bike clearly knows how to ride a bike, that they cannot express it in tokenized form speaks to the limited scope ofof written word in representing embodiment.

throw310822 9mo ago
Yes and no. Riding a bicycle is a skill: your brain is trained to do the right thing and there's some basic feedback loop that keeps you in balance. You could call that a world model if you want, but it's entirely self contained, limited to a very few basic sensory signals (acceleration and balance), and it's outside your conscious knowledge. Plenty of people lack this particular "world model" and can talk about cyclists and bicycles and traffic, and whatnot.
- jazzyjackson 9mo ago
  Ok so I don’t understand your assertion. Just because an LLM can talk about acceleration and balance doesn’t mean it could actually control a bicycle without training with the sensory input, embedded in a world that includes more than just text tokens. Ergo, the text does not adequately represent the world.
pixl97 9mo ago
Um, yea, I call complete bullshit on this. I don't think anyone here on HN is watching what is happening in robotics right now. Nvidia is out building LLM driven models that work with robot models that simulate robot actions. World simulation was a huge part of AI before LLMs became a thing. With a tight coupling between LLMs and robot models we've seen an explosion in robot capabilities in the last few years. You know what robots communicate with their actuators and sensors with. Oh yes, binary data. We quite commonly call that words. When you have a set of actions that simulate riding a bicycle in virtual space that can be summarized and described. Who knows if humans can actually read/understand what the model spits out, but that doesn't mean it's invalid.

imtringued 9mo ago

I don't know how you got this so wrong. In control theory you have to build a dynamical system of your plant (machine, factory, etc). If you have a humanoid robot, you not only need to model the robot itself, which is the easy part actually, you have to model everything the robot is interacting with. Once you understand that, you realize that the human brain has an internal model of almost everything it is interacting with and replicating human level performance requires the entire human brain, not just isolated parts of it. The reason for this is that since we take our brains for granted, we use even the complicated and hard to replicate parts of the brain for tasks that appear seemingly trivial. When I take out the trash, organic waste needs to be thrown into the trash bin without the plastic bag. I need to untie the trash bag, pinch it from the other side and then shake it until the bag is empty. You might say big deal, but when you have tea bags or potato peels inside, they get caught on the bag handles and get stuck. You now need to shake the bag in very particular ways to dislodge the waste. Doing this with a humanoid robot is basically impossible, because you would need to model every scrap of waste inside the plastic bag. The much smarter way is to make the situation robot friendly by having the robot carry the organic waste inside a portable plastic bin without handles.