The idea isn’t new. Physicists and philosophers have been asking for decades whether the universe might be some kind of computer—processing information, updating states, and evolving according to rules. At first glance, the answer seems obvious: the universe looks nothing like our machines. There’s no central processor, no clock, no memory bus, no lines of code being executed step by step. Atoms don’t behave like logic gates, and spacetime doesn’t resemble a motherboard. So if the universe is doing something like computation, it clearly isn’t doing it the way our computers do.
But that turns out to be the wrong comparison. Our computers are engineered artifacts, optimised for human convenience, error correction, and programmability—not for fundamental efficiency. If instead you ask a different question—what would the most efficient possible way to compute look like, given the constraints of physics itself?—the picture changes dramatically. Modern physics already hints at the answer. Black holes saturate information bounds. Quantum theory strips away unobservable detail. Renormalisation throws out microscopic structure that doesn’t affect predictions. Over and over, nature behaves like a system that keeps only the distinctions that matter and discards everything else.
This is where the informational physics framework begins. The idea is not that the universe is literally a computer, but that its laws are isomorphic to optimal information processing. If you require finite information capacity, no unobservable structure, local causal updates, and reversible microscopic laws, then the “state” of the universe reduces to a set of distinguishable differences—nothing more, nothing less. Time becomes the accumulation of resolved distinctions. Change becomes the local update of those distinctions. And remarkably, once you impose these constraints, the space of possible architectures collapses.
What emerges is something very unlike a laptop or a supercomputer—but very much like an optimal one. The universe updates locally, not globally. It conserves information rather than creating or destroying it. It uses the minimal number of degrees of freedom needed to support isotropy and causality: three spatial directions and one emergent temporal ordering. And it updates in the smallest possible steps—one irreducible “tick” per completed distinction. In information-theoretic terms, this is a system with minimal description length, minimal overhead, and no surplus structure.
The conclusion is subtle but powerful. The universe doesn’t run on a computer, and it doesn’t look like one of ours. But if you were tasked with designing the most efficient possible way to compute under the constraints that physics itself seems to obey—finite information, locality, reversibility, and no wasted structure—you would end up with something strikingly similar to the architecture we observe. In that sense, the universe isn’t a computer in the everyday sense. It’s something far more radical: the optimal solution to the problem of computation itself, discovered rather than designed.