But it's not emergence. Using Gaussian elimination to solve a gigantic system of equations isn't emergence either, even if the numbers are a bit too many to carry in your head at once. (as a matter of fact, solving systems of linear equations is part of the RBM training algo)
And even then, if it was emergence, doesn't automatically imply we don't understand it or that it's "magic". The famous Boids flocking simulation is a classic example of emergence. It's not very mysterious. Yes large-scale behaviour emerges from simple rules, this is amazing that it happens, but it doesn't hold up a barrier for us to understand, analyze and model this large-scale behaviour. Crystallisation is emergence, again we model it with a bunch of very hard combinatorial math.
But in this case, neural networks are not an example of emergence. They are really built in a fairly straight-forward manner from components that we understand, and the whole performs as the sum of the components, like gears in a big machine.
And even then, if it was emergence, doesn't automatically imply we don't understand it or that it's "magic". The famous Boids flocking simulation is a classic example of emergence. It's not very mysterious. Yes large-scale behaviour emerges from simple rules, this is amazing that it happens, but it doesn't hold up a barrier for us to understand, analyze and model this large-scale behaviour. Crystallisation is emergence, again we model it with a bunch of very hard combinatorial math.
But in this case, neural networks are not an example of emergence. They are really built in a fairly straight-forward manner from components that we understand, and the whole performs as the sum of the components, like gears in a big machine.