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Thank you, I will try this. I suspect we can extract some universal theory of nits and have a base filter to start with, and have it learn per-company preferences on top of that.


You should be able to do that already by taking all of your customers nit embeddings and averaging them to produce a point in space that represents the universal nit. Embeddings are really cool and the fact that they still work when averaging is one of their cool properties.


This is a cool idea - I’ll try this and add it as an appendix to this post.




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