take any physical process at all, and you should be able to simulate it using a universal computer. It’s an amazing, Inception-like idea, that one machine can effectively contain within itself everything conceivable within the laws of physics. Want to simulate a supernova? Or the formation of a black hole? Or even the Big Bang? Deutsch’s principle tells you that the universal computer can simulate all of these. In a sense, if you had a complete understanding of the machine, you’d understand all physical processes. Deutsch’s principle goes well beyond Turing’s earlier informal arguments. If the principle is true, then it automatically follows that the universal computer can simulate any algorithmic process, since algorithmic processes are ultimately physical processes. You can use the universal computer to simulate addition on an abacus, run a flight simulator on a silicon chip, or do anything else you choose.

2022-06-23: And now the reverse, trying to get the universe to do our computations.

McMahon and a band of like-minded physicists champion an unorthodox approach: Get the universe to crunch the numbers for us. “Many physical systems can naturally do some computation way more efficiently or faster than a computer can”. He cites wind tunnels: When engineers design a plane, they might digitize the blueprints and spend hours on a supercomputer simulating how air flows around the wings. Or they can stick the vehicle in a wind tunnel and see if it flies. From a computational perspective, the wind tunnel instantly “calculates” how wings interact with air. The physicists building these systems suspect that digital neural networks — as mighty as they seem today — will eventually appear slow and inadequate next to their analog cousins. Digital neural networks can only scale up so much before getting bogged down by excessive computation, but bigger physical networks need not do anything but be themselves.