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I actually tend to agree. In the article, I didn't see the strong argument highlighting what powerful feature exactly people were missing in relation to embeddi
by vindex10 2y ago
I actually tend to agree. In the article, I didn't see the strong argument highlighting what powerful feature exactly people were missing in relation to embeddings. Those who work in ML they probably know these basics.
It is a nice read though - explaining the basics of vector spaces, similarity and how it is used in modern ML applications.
- kaycebasques 2y ago> Hopefully it's clear from the domain name and intro that I'm suggesting technical writers are underrating how useful embeddings can be in our work. I know ML practitioners do not underrate them. https://news.ycombinator.com/item?id=42014036 https://news.ycombinator.com/item?id=42014036 > I didn't see the strong argument highlighting what powerful feature exactly people were missing in relation to embeddings I had to leave out specific applications as "an exercise for the reader" for various reasons. Long story short, embeddings provide a path to make progress on some of the fundamental problems of technical writing.
- vindex10 2y agothank you for explanation, yes I later encountered your answer and upvoted it. > I had to leave out specific applications as "an exercise for the reader" this is very unfortunate. would be very interesting to hear some intel :)