> I’m skeptical that biological systems will ever serve as a basis for ML nets in practice
There is no fundamental difference between information processing systems implemented in silico vs in vivo, except architecture. Architecture is what constrains the manifold of internal representations: this is called "inductive bias" in the field of machine learning. The math (technically, the non-equilibrium statistical physics crossed with information theory) is fundamentally the same.
Everything at the functionalist level follows from architecture; what enables these functions is the universal principles of information processing per se. "It worked because it worked" because there is no other way for it to work given the initial conditions of our neighborhood in the universe. I'm not saying "Everything ends up looking like a brain". Rather, I am saying "The brain, attendant nervous and sensory systems, etc. vs neural networks implemented as nonlinear functions are running the same instructions on different hardware, thus resulting in different algorithms."
The way I like to put it is: trust Nature's engineers, they've been at it much longer than any of us have.
There is no fundamental difference between information processing systems implemented in silico vs in vivo, except architecture. Architecture is what constrains the manifold of internal representations: this is called "inductive bias" in the field of machine learning. The math (technically, the non-equilibrium statistical physics crossed with information theory) is fundamentally the same.
Everything at the functionalist level follows from architecture; what enables these functions is the universal principles of information processing per se. "It worked because it worked" because there is no other way for it to work given the initial conditions of our neighborhood in the universe. I'm not saying "Everything ends up looking like a brain". Rather, I am saying "The brain, attendant nervous and sensory systems, etc. vs neural networks implemented as nonlinear functions are running the same instructions on different hardware, thus resulting in different algorithms."
The way I like to put it is: trust Nature's engineers, they've been at it much longer than any of us have.