Brendan Tierney continues a series on vector databases:
Searching semantic similarity in a data set is now equivalent to searching for nearest neighbors in a vector space instead of using traditional keyword searches using query predicates. The distance between “dog” and “wolf” in this vector space is shorter than the distance between “dog” and “kitten”. A “dog” is more similar to a “wolf” than it is to a “kitten”.
Click through to learn more about some of the common techniques for performing similarity searches against vectorized data.