peterstjohn
Joined 16 years ago
Joined 16 years ago
Also, a member on our team developed an amazing RNN-based model that still today beats the pants off most embedding models when it comes to speed, and is no slouch on CPU either…
(* I'm being harsh on BM25 - it is a baseline that people often forget in vector search, but it can be a tough one to beat at times)
They still own the underlying IP[^1], so as long as the contract is a decent one, Paramount has to deal with the actual making/distributing the film, and Hasbro just gets the money, and a toy line off the back of the film. Feels like an easier set up than taking the risk on movie-making yourself (which they did attempt with eOne for other properties, but seemingly have decided that it's probably not a good deal with them)
[1] yes, yes, it's a bit more complicated with Takara in the mix too, but you can essentially view it as a Hasbro-owned property
Don't sleep on some of its newer features like multi-vector document fields, either…
But when you start to require filtering or combining the vector search with a lexical search, then something like Pinecone, Vespa, Qdrant, Lucene-based options (e.g. Solr and ES) etc. become a lot more practical than you building all that functionality yourself.
(I can't speak to Milvus 2.x as we are probably not going to upgrade to that for a number of non-performance reasons)
email: ian [at] snappishproductions.com twitter: @carsondial