Status: Done


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.

Slides

You can download the slides the the talk here.

Video


Talk given at the Southern Data Science Conference about AI-powered Search and vector embeddings