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plokiju | 2 years ago
That's a big statement. Anything that can be effectively described with math, can be described using Turing machines and algorithms. Any Turing-complete system is equivalent. As far as we know, all of physics can be described by equations, therefore is (theoretically) computable. What makes you think brains are special? Are there any other physical systems that you think are uncomputable?
The only arguments I've found for why the brain can't be described by algorithms go into unconvincing pseudo-scientific arguments about the magic of quantum mechanics, which I find very unconvincing (quantum algorithms are still algorithms, and describable through math after all). Do you have a better one?
> Would you call an ants colony a computer? A tree? A government? But they all obviously processes information and seemingly perform computations, don’t they?
Yes, absolutely. You can use ant colonies or slime molds as biological computers to solve real-world finding problems: https://www.youtube.com/watch?v=BZUQQmcR5-g&t=1s
Some of your other examples are more complicated, but all of them can be described through the computational lens, and modeled as Turing machines. you will find many scientific papers filled with equations trying to describe the algorithms behind each of them
aristofun|2 years ago
then what's the point in using this term if it doesn't differentiate anything?
it becomes meaningless, therefore there is no value in calling the brain a computer - it gives zero information about how brain actually works
case closed )
plokiju|2 years ago
Can the brain solve NP problems in polynomial time? The brain itself is a mystery, but we know some things about computation, so it's pretty safe to say no, it cannot.
Maybe on HN it's consensus that all living things are computers in this way, but plenty of people think the brain is literally supernatural. By saying "the brain nothing in common with a computer. We don't know what it's doing", those people will be nodding their heads. But we do know some things about computation, so we can apply those insights to the brain