[[Neural nets|Modern technology]] has allowed converting many [[things]] to [[vectors]], allowing things related to other things to be found through finding records with the highest/highest/lowest dot product/cosine similarity/L2 distance with/to/from queries. This can be done exactly through brute force, but this is obviously not particularly efficient. [[Algorithms]] allow sublinear runtime scaling wrt. record count, with some possibility of missing the best (as determined by brute-force) match. The main techniques are:
* graph-based
* product quantization (lossy compression)
* inverted lists (split vectors into clusters, search a subset of the clusters)
