Learn how to use Firestore's new Vector Embedding support to power semantic search and recommendations in your Firebase app! In this episode of Firebase Deep Dives, Nohe covers: -What vector embeddings are and how they work -Why you would want to use vector embeddings in your app -How to generate vector embeddings using Vertex AI and Cloud Functions -How to query your Firestore data using vector embeddings and k-nearest neighbors search Don't forget to like and subscribe for more Firebase Deep Dives! Resources: Embeddings API → Firestore Vector Support → Embeddings Gecko Documentation → Watch more Firebase Release Notes Deep Dive → Subscribe to Firebase → #FirebaseReleaseNotes Speaker: Alexander Nohe Products Mentioned: Firebase |
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