It's a problem that has no perfect solution, only incremental improvements. So it's really not like your example at all.

I feel like if that question was asked when calculators were invented, and someone was claiming humans were still better at arithmetic than machines, that it would be appropriate.

I was surprised reading through this problem that the machine solved it well at all.

I get that it’s a leet code style question but it’s got a lot of specifics and I assumed the corpus of training data on optimizing this type of problem was several orders of magnitude too small to train an LLM on and have good results.

It's more the equivalent of "why would anyone race the 400m on a standard track, you just wind up back where you started!"

Say you have a bunch of warehouse robots, some which work on different sections in the warehouse. Maybe one section has less things to do, while another section has more things to do - and thus needs more help. So you need to move a bunch of robots there, in groups.

Something like that.

It’s a coding contest not a fiverr programming task. If it seems like a challenge for challenge sake, it’s probably because it’s a challenge for challenge sake.

As someone with a degree in computer science it reminds me of almost every course I took. As someone who has worked at multiple FAANG and adjacent companies with high expectations, I’ve encountered things like this in most interviews and have devised similar problems to be given as interviews. The point isn’t to make something objectively useful in the question itself but to provide a toy example of a specific class of problem that absolutely shows up in practical situations, although by in large most IT programmers would never see such a problem in their careers. This does not however mean such problems don’t exist in the world and are not solved by computer scientists professionally at work in practical uses. Beyond that they also are tests of how well people have learned computer science, discrete math, and complex programming as a proxy for general technical intelligence (albeit not testing any specific technology or toolkit, as is emphasized in IT work). This seems surprising to me when people belly ache about computer science being asked in any context - at school, work, or in a programming contest as if the only worthwhile things to do are systems programming questions.