I've been working on NLP stuff using LLMs for a while, and it's not that the problems aren't somewhat interesting, but solving them is ridiculously tedious.
Most of the time on that project I've just played around with different prompts to make it do what I'm hoping for, with almost no mental process for understanding problems and solutions, mostly just randomly coming up with experiments and reading the results very carefully, checking how consistent they are.
I moved towards finding and isolating the parts LLMs are good (and reliable!) at and using deterministic approaches for everything I possibly can. That part is not too tedious, but all this black box trial and error (with all the waiting and errors)...
Luckily the client doesn't expect LLMs to be what the hype says and mainly just wants some reasonably useful features so they can say they use AI - wouldn't enjoy dealing with someone thinking it's super easy and I just need to write a few scripts because they tried this in ChatGPT once.
Most of the time on that project I've just played around with different prompts to make it do what I'm hoping for, with almost no mental process for understanding problems and solutions, mostly just randomly coming up with experiments and reading the results very carefully, checking how consistent they are.
I moved towards finding and isolating the parts LLMs are good (and reliable!) at and using deterministic approaches for everything I possibly can. That part is not too tedious, but all this black box trial and error (with all the waiting and errors)...
Luckily the client doesn't expect LLMs to be what the hype says and mainly just wants some reasonably useful features so they can say they use AI - wouldn't enjoy dealing with someone thinking it's super easy and I just need to write a few scripts because they tried this in ChatGPT once.