#4 Christopher Gwilliams on AI with Supabase, Postgres Configuration, Real-Time Processing, and more
How AI Is Built
Optimizing Database Performance and Scaling with Postgres and Supabase
This chapter explores considerations when working with large data in databases, comparing capabilities between Postgres and Supabase and offering insights into the customer journey with Supabase. It delves into SQL versus Python and JavaScript for querying databases, discusses the Pg vector extension for recommendation engines, and explains the workings of Pg vector for vector search within Postgres. Additionally, it covers index computations, using Postgres as a vector database, various Postgres extensions, and configurations for AI projects.
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