For knowing that a particular rule is universal just tells one that it is possible to set up initial conditions that will cause a sophisticated computation to occur. But it does not tell one what will happen if, for example, one starts from typical simple initial conditions.

Yet the Principle of Computational Equivalence asserts that even in such a case, whenever the behavior one sees is not obviously simple, it will almost always correspond to a computation of equivalent sophistication.

So what this means is that even, say, in cellular automata that start from very simple initial conditions, one can expect that those aspects of their behavior that do not look obviously simple will usually correspond to computations of equivalent sophistication.

According to the Principle of Computational Equivalence therefore it does not matter how simple or complicated either the rules or the initial conditions for a process are: so long as the process itself does not look obviously simple, then it will almost always correspond to a computation of equivalent sophistication.

And what this suggests is that a fundamental unity exists across a vast range of processes in nature and elsewhere: despite all their detailed differences every process can be viewed as corresponding to a computation that is ultimately equivalent in its sophistication.

## The Content of the Principle

Like many other fundamental principles in science, the Principle of Computational Equivalence can be viewed in part as a new law of nature, in part as an abstract fact and in part as a definition. For in one sense it tells us what kinds of computations can and cannot happen in our universe, yet it also summarizes purely abstract deductions about possible computations, and provides foundations for more general definitions of the very concept of computation.

Without the Principle of Computational Equivalence one might assume that different systems would always be able to perform completely different computations, and that in particular there would be no upper limit on the sophistication of computations that systems with sufficiently complicated structures would be able to perform.