Science is an epistemic technology (not the only one) that allows us to successfully interact with the world. The real issue is what counts as success? Explanation, prediction, control… these could all be part of a successful paradigm. Is simplicity part of the epistemic paradigm? The real reason today we prefer Copernican to Ptolemaic astronomy is that the former makes physical sense because it accommodates gravitational theory. ( Was either a scientific theory? Or where they mathematical or kinematic descriptions only?)
The paradigm for serious science today is mathematical system analysis. It looks as though in the future, really smart things are going to do computational multiphysics and related activities (computational chemistry and biology), to really figure out the external world. But is this the only way- the paradigm of laws, principles, relations and occasionally (only ) heuristics? Can an intelligent system with enough information gathering power, enough memory, enough experience and sensory sensitivity (resolving power?) work on a different paradigm? Can it be intelligent if it only knows that the current situation is like a previous situation and that thus that the future course of the system is likely to be the same?
Really smart things (RSTs), as the future looks now, will be doing simultaneous ( to save time) multiphysics simulations which interact or are combined under or during conditions of peripheral contact or engagement. In other words, they won’t calculate the whole world or even large pieces of it but rather they will work on different relevant sections at the same time and then integrate these pieces of the puzzle. A key problem here is this little word “relevant”. How do the RSTs know what’s relevant? (Think about climate models. City in an earthquake might be the paradigmatic case here).
We know more or less how computational RSTs work, some thing close is around today. Are there any other kind of RSTs?