>Is there some emerging practice on how to determine how close is close "enough" between multiple vectors for the purpose of similarity searches? IMO you can't

>Is there some emerging practice on how to determine how close is close "enough" between multiple vectors for the purpose of similarity searches? IMO you can't avoid empirically evaluating what threshold is close enough or not. Two phrases or encoded entities may have .98 similarity with one embedding model and .59 with another. It is entirely determined by the weights and model you are using.