Hacker News Reader

Comment by okasaki | Hacker News Reader

My experience is that gpt-oss doesn't know much about obscure topics, so if you're using it for anything except puzzles or coding in popular languages, it won't do well as the bigger models.

It's knowledge seems to be lacking even compared to gpt3.

No idea how you'd benchmark this though.

View on HN

> My experience is that gpt-oss doesn't know much about obscure topics

That is the point of these small models. Remove the bloat of obscure information (address that with RAG), leaving behind a core “reasoning” skeleton.

Yeah I guess. Just wanted to say the size difference might be accounted for by the model knowing more.

Seems more user-friendly to bake it in.

Something I was doing informally that seems very effective is asking for details about smaller cities and towns and lesser points of interest around the world. Bigger models tend to have a much better understanding and knowledge base for the more obscure places.

I would really love if they figured out how to train a model that doesn't have any such knowledge baked it, but knows where to look for it. Maybe even has a clever database for that. Knowing this kind of trivia like this consistently of the top of your head is a sign of deranged mind, artificial or not.

Would that work as well? If I ask a big model to write like Shakespeare it just knows intuitively how to do that. If it didn't and had to look up how to do that, I'm not sure it would do a good job.

The problem is that these models can't reason about what they do and do not know, so right now you basically need to tune it to: 1) always look up all trivia, or 2) occasionally look up trivia when it "seems complex" enough.

Reply on news.ycombinator.com