This talk provides a brief introduction to vector embeddings, search and storage. In it, I show how to
- Create vector embeddings
- Perform vector similarity locally
- Upload and index vectors in a vector database (Redis + RediSearch).
and also show a couple example of applications that utilize Redis for vector search capability.
You can download the slides the the talk here.