Earlier quoted context omitted.
But there is a difference between memoization and dynamic programming. Memoization or otherwise indiscriminately storing the results of computations will blow up your memory use on many problems, where a dynamic programming approach would not. Dynamic programming does not mean saving the results of computations, it is about saving the _minimal_ number of results, without having to recompute already solved subproblems…
Your previous comment: dynamic programming will keep around previous subproblem solutions Your comment here: Dynamic programming does not mean saving the results of computations indiscriminately storing the results of computations This is not something that happens. No is out there storing a bunch of stuff they don't need on purpose, running out of memory, then calling it a day. That's like saying "some people walk s…
There are a lot of people (such as my students) that would take a DP problem, solve with recursion, throw some caching [0] in and call it a day. They are often surprised by the 1000x speedups using a DP algorithm instead, no caching needed.
[0] https://docs.python.org/3/library/functools.html#functools.c...
> Again, this is just what programming is some times. You save results instead of recomputing stuff.
I'm sorry, but I still don't get the argument you are making. That DP is part of programming? Well, yes?