I love working with LLM text embeddings. The idea of a list of numbers being able to encode semantic information and being able to do math on them is magic to me.
Unfortunately, it seems like they are neglected other than being an afterthought in building semantic searches, and don't get the attention they deserve as tools to build things with.
I went ahead and embedded the entire The Online Plain Text English Dictionary (OPTED), using OpenAI's `text-embedding-3-large` and uploaded it to kaggle, but it seems to me it has no traction. Reenforcing my view that embeddings don't get the love they deserve.
Unfortunately, it seems like they are neglected other than being an afterthought in building semantic searches, and don't get the attention they deserve as tools to build things with.
I went ahead and embedded the entire The Online Plain Text English Dictionary (OPTED), using OpenAI's `text-embedding-3-large` and uploaded it to kaggle, but it seems to me it has no traction. Reenforcing my view that embeddings don't get the love they deserve.