You’ve probably seen it, but here’s the documentation for our vector functions: https://docs.memsql.com/sql-reference/v6.8/vector-functions/. It talks about the available functions, and how to insert vectors from an application as binary fields. JSON_ARRAY_PACK can also be used to convert json arrays of floats to vectors, for convenience.
I don’t have anything else more specific to offer. I have heard of one other customer prospect who was going to try to do fuzzy full text search to query a product catalog, using a word vector model from a pre-trained deep neural network like word2vec (not sure which one). The idea was to create a vector for each product description, and convert a set of query words to a vector, then do cosine similarity match with dot_product. That way, if you searched for “cat beds” you still might find “dog beds” (ranked high) even if no cat collars were for sale. The word vectors for a product description or query were to be averaged together (normalized) to form product description vectors of length 1 before the similarity matching.