Comment by senordevnyc
Comment by senordevnyc a day ago
I’m curious what your mental model is for how human cognition works. Is it any less mechanical in your view?
Comment by senordevnyc a day ago
I’m curious what your mental model is for how human cognition works. Is it any less mechanical in your view?
The thesis of "What is Intelligence" is based around intelligence being just that.
> Intelligence is the ability to model, predict, and influence one’s future; it can evolve in relation to other intelligences to create a larger symbiotic intelligence.
The book is worth a read. But I don't believe it limits the type of intelligence we have to humans, by definition. Then again, I'm only halfway through the book :).
[https://mitpress.mit.edu/9780262049955/what-is-intelligence/]
> Intelligence is the ability to model, predict, and influence one’s future
LLM's do pattern match and predict on textual symbols.
Humans brains pattern match and predict beyond mere text.
LLMs also do not learn in the moment, which I would argue is a sign of lack of intelligence.
It seems obvious to me that "the ability to model, predict, and influence one’s future" is far more general and capable than "constrained to pattern recognition and prediction of text and symbols." How do you conclude that those are the same?
I do like that definition because it seems to capture what's different between LLMs and people even when they come up with the same answers. If you give a person a high school physics question about projectile motion, they'll use a mental model that's a combination of explicit physical principles and algebraic equations. They might talk to themselves or use human language to work through it, but one can point to a clear underlying model (principles, laws, and formulas) that are agnostic to the human language they're using to work through them.
I realize some people believe (and it could be) that ultimately it really is the same process. Either the LLM does have such a model encoded implicitly in all those numbers or human thought using those principles and formulas is the same kind of statistical walk that the LLM is doing. At the very least, that seems far from clear. This seems reflected in the results like the OP's.
Human cognition comes bundled with subjective experience.
There is no mechanism known, even in principle, that explains the taste of strawberry.
We have no justifiable reasons to believe that our cognition is in any way similar to a bunch of matrix multiplications.
Animal cognition is comprised of many intricate, quasi-redundant, deeply coupled systems that, among other things, can learn, form memories, interact with its environment, and grow. It is not remotely comparable to a computational neural network in any sense except that they both include "neural" in their jargon, albeit to mean vastly different things.
That's a very difficult question to answer. It's an open problem in academia.
To tease out something often it can be useful to approach problems from the opposite end. For example what is NOT the way in which human cognition works?
We know how LLM's function, humans certainly do not function in a similar fashion. For one I can reason well enough that next year is 2026 without having most all human literary output fed to me. It's amazing how much the human mind does with so little information.