It's "fundamentally geometric" to understand that the Fourier transform diagonalizes a circulant matrix so you can estimate the clock skew between two radios?
I think you get into calculus very quickly once you start dealing with uncertainty. A bit is 0 or 1, a discrete value. A random or unknown bit has some probability of being 1, a continuous value. A process that produces a random bit does too. An unknown such process has a distribution over such probabilities. Things like that are fundamental for things like communication or image classification.
Also, though, a major application of computers is modeling and controlling the calculus-based physical world, just because they are so good at number crunching. Particularly popular examples are ray tracing, music synthesis, and motor control.
I think you get into calculus very quickly once you start dealing with uncertainty. A bit is 0 or 1, a discrete value. A random or unknown bit has some probability of being 1, a continuous value. A process that produces a random bit does too. An unknown such process has a distribution over such probabilities. Things like that are fundamental for things like communication or image classification.
Also, though, a major application of computers is modeling and controlling the calculus-based physical world, just because they are so good at number crunching. Particularly popular examples are ray tracing, music synthesis, and motor control.