I don't need to comment, and neither do you. We're both just silly people talking about things that we don't understand, because our egos won't let us not say a

I don't need to comment, and neither do you. We're both just silly people talking about things that we don't understand, because our egos won't let us not say anything. You think that, because I haven't read what you've read, your understanding exceeds mine. But I also think the same way; I think that you don't grok some important mathematical concepts. So which of us is right? It sounds like your mind is still pretty small. Let's try one single exercise from one of my "pointlessly reductive" points: Since every formal logic can be expressed in the language of category/topos theory, and topos theory can express the plumbing of modern mathematics, and since the formalization of logic is itself mathematical, we have that logic is mathematics; that is, that any logical expression corresponds to a categorical expression and is fully mathematical. Making sense yet? At some point, philosophers need to study maths sincerely; the stereotype that they know nothing but Bayes is painfully on display today. You skipped entirely over my question about electrons and information. Moreover, you admit that science needs maths. I'm going to take these as a complete concession. Thanks for playing Orange Site. Finally, as a bonus, here's a metric for hardness in the sciences. A theory is harder when it predicts more. But theories always predict infinitely many things, and really we want to know how accurate a prediction is. And a theory is harder when it is smaller; that's Occam's Razor. So we'll take the sum of (the squares of) inaccuracies over all predictions, and scale it by opposite of (the logarithm of) the size of the theory. Of course, we'll have to use bits to measure both the accuracy of predictions and the size of the theory. This may remind you of certain equations in thermodynamics or statistics.