Wow, they managed to get an LLM (and a small one no less) that can acknowledge that it doesn't know details about obscure data structures

> Alternatively, perhaps using a wavelet tree or similar structure that can efficiently represent and query for subset membership. These structures are designed for range queries and could potentially handle this scenario better.

> But I'm not very familiar with all the details of these data structures, so maybe I should look into other approaches.

This is a few dozen lines in to a query asking DeepSeek-R1-Distill-Qwen-1.5B-GGUF:F16 to solve what I think is an impossible CS problem, "I need a datastructure that given a fairly large universe of elements (10s of thousands or millions) and a bunch of sets of those elements (10s of thousands or millions) of reason able size (up to roughly 100 elements in a set) can quickly find a list of subsets for a given set. "

I'm also impressed that it immediately started thinking about tries and, which are the best solutions that I know of/stackoverflow came up with for basically the same problem (https://stackoverflow.com/questions/6512400/fast-data-struct...). It didn't actually return anything using those, but then I wouldn't really expect it to since the solution using them isn't exactly "fast" just "maybe less slow".

PS. If anyone knows an actually good solution to this, I'd appreciate knowing about it. I'm only mostly sure it's impossible.