> Interestingly though, physical models are usually expressed as mathematical equations. Which is an arbitrary way of modeling Not exactly. The particular symb

> Interestingly though, physical models are usually expressed as mathematical equations. Which is an arbitrary way of modeling Not exactly. The particular symbols used in mathematics may be arbitrary but the mathematical structures and relationships are not. There’s some interesting research on how the limits of predictability may come down to what is mathematically provable in a formal system. That may sound kind of weird, but consider that any computable model can be modeled as a Turing machine, which is essentially a process that manipulates symbols according to a set of rules—not too different than mathematics itself. The difference is that based on certain assumptions of internal consistency (that cannot be proven if the system is in fact consistent), the mathematical manipulation of symbols can be used to make predictions about the behavior of Turing machines. There’s a very deep connection between the two and neural networks are still just another form of this, perhaps not as human-interpretable however.