When it makes sense to re-use them, they do. When it makes sense to write new ones, they do that. Nature does that, too. It also re-uses sequences when it would make more sense to write new ones, and it also makes new sequences when re-using an existing one would have done the job. It’s almost as if there is no designer in charge of it at all.
So, in other words, by hand-waving and with no actual statistical analysis you can sketch, let alone walk any of us through. Alright, carry on.
How many universes have you compared to determine that one with wheel re-use is “more efficient” than one without? What does “more effeiciently” even mean, when talking about what ever “the universe operates” means? How is any of this something other than just meaningless jargon you know no means of quantifying?
Rich of you to complain about personal incredulity, considering that is the sum-total of your entire position concerning well-understood biological processes… But regardless, that claim is also just straight-up false. Parsimony is a means of reducing errors. All else being equal, the more assumptions we make, the more likely it is that among them may be found a false one. A model that relies on many assumptions is therefore, again, all else being equal, more fragile than a model that relies only on a few. Rendering predictions is also easier, if there are fewer details to consider or calculations to perform. More parsimonious models are more efficient, a more effective means of advancing the goals of science, than their less parsimonious alternatives. This has nothing to do with methodological naturalism or personal incredulity. The reason we strive to make only as many assumptions as necessary is that we want to not be wrong all of the time like you are.
Evidence the scientific subset of which you cannot actually provide of faults you cannot actually demonstrate… But do go on.
This sentence makes no sense. Parsimony is not a claim. And the claim that one model is more parsimonious than another is a claim that requires no scientific model to substantiate, since a simple accounting of the assumptions underlying both (if necessary, through a measure that weights them) should entirely suffice for that.
You don’t have a clue. Because you have a commitment to reject any and all candidate explanations that do not involve literal magic, no matter how much experimental evidence there is to support them.
It does. It helps us to avoid being wrong all the time like you are.
