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Yup I think you got it perfectly. Just a small note: yes one isn’t rigidly defining what those characteristics are while finding similar embeddings (aka nearest vectors using some distance metric), but those characteristics are implicitly encoded in the model that creates the embeddings depending on how the model is trained.



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