Comment by D-Machine
19 days 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?
> 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.
> 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.
> 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?
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.
>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.
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