Comment by viraptor
1 day ago
> the CS concepts are very easy for LLMs to recall
They're easy to recall, but you have to know what to recall in the first place. Or even know enough of the territory to realise there's something to recall. Without enough background, you'll get a whole set of amazing tools that you have no idea what to do with.
For example, you may be able to write a long description of your problem with some ideas how to steer the AI to give you possible solutions. And the AI may figure out what the problem is and that the hyperloglog is something that could be useful to you. And you may have the awesome programming skills to implement that. But that's a lot of maybes. It would be much faster/easier if you knew about hyperloglog ahead of time and just asked for the implementation or library recommendation.
Or even if you don't know about the actual solution, you'd have enough of CS vocabulary to ask: "how do I get a fast, approximate distinct count from a multiset". It would take a long imprecise description to get the same thing for a coder with no theory background.
To this point, I use AI programming assistants pretty heavily and find very frequently that they will write extremely inefficient or oddly baroque implementations of what I’m asking for in their first pass, that appear as if they don’t have the “knowledge” or ability to do it better, but then they can be prodded to re-do it very easily. Frequently I look at some generated code and write back the most cursory feedback like “looks o(n^2) can you make more efficient” or “use pointers instead of nested loops” or “how about using X approach” and it will often produce something dramatically better than the initial effort. For now at least I think these tools are still most powerful in the hands of experts. (I am a self-taught programmer but have a fair bit of experience)