PID control is the classic example, but at a far enough abstraction any looping algorithm can be argued to be an implementation of the concepts underpinning calculus. If you’re ever doing any statistical analysis or anything in game design having to do with motion, those are both calculus too. Data science is pure calculus, ground up and injected into your eyeballs, and any string manipulation or Regex is going to be built on lambda calculus (though a very correct argument can be made that literally all computer science is built of lambda calculus so that might be cheating to include it)
Lambda calculus has no relation to calculus calculus, though.
Data science is pure calculus, ground up and injected into your eyeballs
Lol, I like that. I mean, there’s more calculus-y things, but it’s kind of unusual in that you can’t really interpret the non-calculus aspects of a neural net.
I think the issue here might be the overloading of terms - lambda calculus is both the system of notation and the common name for the conceptual underpinnings of computational theory. While there is little to no similarity between the abstracted study of change over a domain and a notational system, the idea of function composition or continuous function theory (or even just computation as a concept) are all closely related with basic concepts from “calculus calculus” like limit theory and integral progression.
Graphics programming is the most obvious one and it uses it plenty, but really any application that can be modeled as a series of discrete changes will mostly likely be using calculus.
Time series data is the most common form of this, where derivatives are the rate of change from one time step to the next and integrals are summing the changes across a range of time.
But it can even be more abstract than that. For example, there’s a recent-ish paper on applying signal processing techniques (which use calculus themselves, btw) to databases for the purposes of achieving efficient incremental view maintenance: https://arxiv.org/abs/2203.16684
The idea is that a database is a sequence of transactions that apply a set of changes to said database. Integrating gets you the current state of the database by applying all of the changes.
that can’t be right. maybe they meant lambda calculus? programmers are definitely good at applied logic, graph theory, certain kinds of discrete math etc. but you’re not whipping out integrals to write a backend.
Any function that relies on change over a domain is reliant on concepts that are fundementally calculus. Control systems, statistical analysis, data science, absolutely everything in networking that doesn’t involve calling people on the phone to convince them to give you their password, that is all calculus.
Many things that work with time series data use calculus all the time. Both derivatives and integrals are very useful in that context: derivatives being the rate of change at some particular time step, and integrals being the sum of the changes across a range of time steps.
If you write them yourself. Then you actually need a bit of math.
But claiming that you need math skills as a programmer because some kinds of programs need you to know maths is like claiming every programmer needs to know a lot about logistics because some people write software for warehouses.
Serious question; how does Calculus apply to programming? I’ve never understood.
PID control is the classic example, but at a far enough abstraction any looping algorithm can be argued to be an implementation of the concepts underpinning calculus. If you’re ever doing any statistical analysis or anything in game design having to do with motion, those are both calculus too. Data science is pure calculus, ground up and injected into your eyeballs, and any string manipulation or Regex is going to be built on lambda calculus (though a very correct argument can be made that literally all computer science is built of lambda calculus so that might be cheating to include it)
Lambda calculus has no relation to calculus calculus, though.
Lol, I like that. I mean, there’s more calculus-y things, but it’s kind of unusual in that you can’t really interpret the non-calculus aspects of a neural net.
I wanna fight your math teachers. No seriously, what did they tell you calculus is if it’s got nothing in common with lambda calculus?
Is there some connection I’ve just been missing? It’s a pretty straight rewriting system, it seems Newton wouldn’t have had much use for it.
Lot’s of things get called “calculus”. Originally, calculus calculus was “the infinitesimal calculus” IIRC.
I think the issue here might be the overloading of terms - lambda calculus is both the system of notation and the common name for the conceptual underpinnings of computational theory. While there is little to no similarity between the abstracted study of change over a domain and a notational system, the idea of function composition or continuous function theory (or even just computation as a concept) are all closely related with basic concepts from “calculus calculus” like limit theory and integral progression.
edit: clarity
Graphics programming is the most obvious one and it uses it plenty, but really any application that can be modeled as a series of discrete changes will mostly likely be using calculus.
Time series data is the most common form of this, where derivatives are the rate of change from one time step to the next and integrals are summing the changes across a range of time.
But it can even be more abstract than that. For example, there’s a recent-ish paper on applying signal processing techniques (which use calculus themselves, btw) to databases for the purposes of achieving efficient incremental view maintenance: https://arxiv.org/abs/2203.16684
The idea is that a database is a sequence of transactions that apply a set of changes to said database. Integrating gets you the current state of the database by applying all of the changes.
Lotta infinite sums in loops
that can’t be right. maybe they meant lambda calculus? programmers are definitely good at applied logic, graph theory, certain kinds of discrete math etc. but you’re not whipping out integrals to write a backend.
Any function that relies on change over a domain is reliant on concepts that are fundementally calculus. Control systems, statistical analysis, data science, absolutely everything in networking that doesn’t involve calling people on the phone to convince them to give you their password, that is all calculus.
Many things that work with time series data use calculus all the time. Both derivatives and integrals are very useful in that context: derivatives being the rate of change at some particular time step, and integrals being the sum of the changes across a range of time steps.
There’s a pretty wide range of applications.
Computers are just big calculators so to program them you need calculus.
good physics/graphics engine require calculus
How?
Again, legit question.
If you write them yourself. Then you actually need a bit of math.
But claiming that you need math skills as a programmer because some kinds of programs need you to know maths is like claiming every programmer needs to know a lot about logistics because some people write software for warehouses.