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Not sure what your background is. Mine is physics. I spent a long time in academia before moving to software and machine learning. I agree that in some sense ma
by sidlls 9y ago
Not sure what your background is. Mine is physics. I spent a long time in academia before moving to software and machine learning. I agree that in some sense mathematical models are the most efficient means to communicate something about much of physics, and certainly the most important method by which physics is used in applications (e.g. engineering). I would hesitate to go further. There's the empirical part of physics which even as a theoretician I always viewed as more important, and often more subtle, and at least as profound. There is a lot of heuristics, art and intuitive leaps embedded in physics that are not adequately captured by the math.
- whatshisface 9y agoI think the intuitive leaps (How was this discovered? How do we think about this in practice? How should we arrange the concepts in our heads so that we can be useful with them?) are as much about the human brain and the way it works as they are about physics. It's no surprise that math isn't the best notation for them - in an alternate universe, perhaps their study is considered to be a branch of the humanities! If you asked a hyperinteligent dolphin, "how do you think about the universe?" you would receive and answer totally different from what we'd expect and probably involving a lot of fish. If you asked it how to calculate the period of a pendulum, its answer would be equivalent to ours! So in that sense I think the "profound statements," might actually be a lot less profound than the calculations themselves.