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From experience with traditional mathematical models, however, one might then assume that this would inevitably imply that all plants and animals would have forms that look quite similar.
But if the ultimate rule for the universe is at all simple, then it follows that every part of this rule must in a sense be responsible for a great many different features of the universe.
For even though the individual cells in the array might be extremely small, one might still imagine that one would for example see all sorts of signs of the overall orientation of the array.
And the point is that causal invariance then implies that the same underlying rules can be used to update the network in all such cases.
The sequence of outputs from all the nerve cells can be used as a hash code, whose value tends to be the same for inputs that differ only by small changes.
So might one day some new method of perception and analysis be invented that would in a sense manage to recognize all possible regularities, and thus be able to tell immediately if any particular piece of data could be generated from any kind of simple description?
After all, one might think that biological evolution would inevitably have made us as good as possible at handling data associated with any of the systems that we commonly encounter in nature.
And in the context of such models what I have discovered is that there is indeed all sorts of evidence for the Principle of Computational Equivalence.
So what all of this suggests is that systems in nature do not perform computations that are more sophisticated than the Principle of Computational Equivalence allows.
So given this, can theoretical science still be useful at all?
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