Some models of reality are bolder than others

Digital physics is the body of mathematical and philosophical work treating the universe and the way it works as a giant digital computer. This is often associated with cellular automata, and names like Konrad Zuse, John Von Neumann, Stephen Wolfram, etc. What I find fascinating about this field is that the models it suggests are making very deep metaphysical claims: if they are true, it means that the underlying structure of the world is much different than we think, and radically simpler in a sense. Take the lattice gas automaton for instance. A version of it is an hexagonal cellular automata with very simple collision rules, not more complicated than the famous Rule 30 or 110, for 1D cellular automata. The impressive thing about it is that a simulation running this rule with many particles can be shown to approximate the Navier-Stokes equations, which are the classical complicated mathematics to describe the dynamics of fluids. Following Wolfram, I find it very appealing to consider the idea that the world is not somehow running “hidden mathematics”, somewhere and somehow, to solve some complicated equations in a seemingly magical way, but rather, that things are radically simpler, in that the world is simply implementing a set of trivially simple rules. The world is not concerned with, or made with mathematics, mathematics just emerges, with inherent and irreducible complexity, from extreme simplicity.

In that sense, I find that the world of digital physics is much bolder, metaphysically speaking, than many other parts of science, which often present models for which it’s clear, a priori, that they can have ultimately no metaphysical bearing on the world. They work well logically, as a mathematical explanation, they can yield useful predictions, but they do not tell us what the world is and how it works, ultimately. Digital physics tells us, boldly: the world is a giant computer, and all the marvelous things that it does can be ultimately conceived as the results of computation.