Isn't it just learning to map specific words, from the "knife world", to the correct class? If so, a simple dictionary would fit.
What I think is a better way to validate is to split train/validation by words used presented in NER classes (like, it should be able to find new brands never seen before). It is a interesting problem.
That's a key piece of the article. He 'trusts' Gemini to classify the posts, and never hand validates anything.
And he continues building on top of that shakey trust. Is this a good idea?
It just depends on what you're doing: sounds like he's just having fun with a hobby, so it's harmless.
All he's really done is work more efficiently to save token cost and time. But he hasn't validated anything, so there's no telling if he's wasting time or not. It's a hobby though....
bguberfain · · focus · HN ↗
itsalwaysgood · · focus · HN ↗
And he continues building on top of that shakey trust. Is this a good idea?
It just depends on what you're doing: sounds like he's just having fun with a hobby, so it's harmless.
All he's really done is work more efficiently to save token cost and time. But he hasn't validated anything, so there's no telling if he's wasting time or not. It's a hobby though....
p-s-v · · focus · HN ↗
Other problems are:
Brand names that match common English words, brand names that are also item models used by another brand… etc