The question of under what conditions it is possible for a neural network to have an evolution function x(t), defined in "closed form", that will predict the output of the network at time t is as old as the concept of neural network itself. I will discuss some recent advances, and I will highlight the connection between this question, ideas of model theory and a topological condition introduced by A. Grothendieck in the 1950s.