Comment by estearum
6 hours ago
Probabilistic and deterministic are not opposites.
The brain is deterministic at the level of specific interactions, which process inputs in a highly chaotic (but still deterministic) manner into probabilistic outcomes.
The opposite of deterministic is random, i.e. in the quantum sense of truly no relationship between input and output.
There are probably some quantum effects in the brain here and there, but the vast majority of it is just traditional deterministic interactions networked together in such a complex system that the resulting behavior is much, much easier to predict in probabilistic terms than otherwise.
Ok right, but then I don't see the original point. Or like, you don't seem to be appealing to a hard science/soft science distinction here if the question revolves around what conceptual model is most "useful" to us. Useful for what? For predicting future actions? That makes sense, but does actually that speak to op's (possibly still fraught) metaphysical/semantic point here? It just feels like you are speaking over it, right? They could just as easily counter that a probabilistic model of the physical brain is not a very useful description of human intelligence, so why use it? You can't appeal to materialism here because you are already practicing some implied pragmatism in your commitments. You pretty much have as much ground to stand on as they do!
I am saying that there is no categorical distinction to be made on functional grounds between artificial intelligence and brains.
You cannot say an AI model cannot be intelligent because it's a probability machine, when all available evidence points toward natural intelligence also being generated by probability machines (much more complex ones, called brains).
But brains do much more than just predict tokens based on previously seen tokens. I think all the other things brains do are probably important for our intelligence.
So, LLM are just next token predictors, brains are next token predictors + many other things in addition, and that makes people still feel LLM are dumb even when they solve a lot of problems using tokens.
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This seems fine but things being the same "on functional grounds" is just one way things can be the same. Why should we privilege this framing as something definitive versus another conceivable one?
On functional grounds my bike has not a lot of distinction from a horse, but just, like, saying that doesn't tell me much about either. Or at least, it seems to leave out a lot of otherwise crucial details and differences..
What does it mean to you, this point of view? Are you truly coming from like a 20th century pragmatism point of view? Where what is most useful is what is right? Or are your trying to make a larger claim about nature? I think being clear about that would help focus your critique here.