Understanding Vector Search with Typesense
TLDR In a chat with em1nos and Andrew, Kishore Nallan explained how Vector Search works. He clarified that it can be useful for recommendations and personalization, but it requires machine learning to convert data into vectors before searching.
Sep 11, 2022 (13 months ago)
em1nos
08:01 AMCould you tell us a bit more about Vector Search? Sounds amazing!
How does it work?
What can we expect to be able to do, that we can't do right now with Typesense?
Is the RC publicly available?
I'm guessing the release of Vector Search is a few versions away? We should not expect it soon?
Kishore Nallan
10:11 AMWe've a RC build available already where you can try it out:
typesense/typesense:0.24.0.rcn12https://gist.github.com/kishorenc/f008c3a60ee58cb084b0c33c0dbce148
> What can we expect to be able to do, that we can't do right now with Typesense?
It allows you to do things like recommendations by building an embedding (which are vectors) which can be indexed into Typesense and searched using a vector query for fetching recommended items.
Still need to work on the docs that show how you can build a model that produces vector embeddings etc. if you aren't familiar with that.
em1nos
10:15 AMKishore Nallan
10:16 AMem1nos
10:19 AMem1nos
10:19 AMKishore Nallan
10:20 AMem1nos
10:22 AMem1nos
02:04 PMFor anyone interested in reading more about vector search:
https://www.infoworld.com/article/3634357/what-is-vector-search-better-search-through-ai.html
Or just google it, I guess.
em1nos
02:04 PMSep 12, 2022 (13 months ago)
Andrew
05:03 PMAndrew
05:03 PMSep 13, 2022 (13 months ago)
Kishore Nallan
05:46 AMAndrew
06:23 PM
Typesense
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