Solving competitive programming problems is essentially solving hard combinatorial optimization problems. Throwing a massive amount of compute and gradient descent at the problem has always been possible. If I'm not mistaken what this does is reduce the representation of the problem to a state where it can run gradient descent and then tune parameters. The real magic is in finding structurally new approaches. If anything I'd say algorithms and math continue to be the core of programming. The particular syntax or level of abstraction don't matter so much.
> Solving competitive programming problems is essentially solving hard combinatorial optimization problems.
True, but if you relax your hard requirements of optimality to admit "good enough" solutions, you can use heuristic approaches that are much more tractable. High quality heuristic solutions to NP-hard problems, enabled by ML, are going to be a big topic over the next decade, I think.
I should correct myself, this isn't even that. This is just text analysis on codeforces solutions, which makes it even worse than I thought. Very pessimistic about it's generalizability.
> If anything I'd say algorithms and math continue to be the core of programming.
I disagree; I think the core of programming is analyzing things people want and expressing solutions to those wants clearly, unambiguously, and in a way that is easy to change in the future. I'd say algorithms and math are a very small part of this work.
That's not programming, that's called being a good employee. Any person in any role should be doing that. Programming is about algorithms and math. Now a good employee who's in a technical role should have both.
You've simply restated your opinion without providing any supporting arguments, and as I already said, I disagree. The vast majority of programming I see (and as a consultant, I see a fairly wide variety) is not about algorithms and math, but instead gluing together systems and expressing domain logic.
Now, I suppose you could argue that domain logic is "algorithms and math," but in my experience, it's less about the specific algorithms and more about precisely describing fuzzy human behavior.
It's that "precisely describing" and "easy to change in the future" parts that makes what programmers do different than what any good employee does.
(I do agree that there is some programming that is focused on algorithms and math, but it's in the minority, in my experience. Perhaps the type of work you do is focused on algorithms and math, but I believe that's a relatively small part of the software development ecosystem.)
No I'm not talking about programming that requires calculations or programs written to solve mathematical problems. Programming at its core is about defining precise logical relationships between abstract objects and then writing algorithms to understand and modify these objects. This is a mathematical process and you should use mathematical thinking to do this.It may not always seem like it when the objects and relationships appear to be simple but that is the core of programming.
