# Supabase — Implementing semantic image search with Amazon Titan and Supabase Vector

- Company: Supabase (supabase.com)
- Announced: 2024-03-26
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://supabase.com/blog/semantic-image-search-amazon-bedrock
- Record: https://forck.live/items/21443-implementing-semantic-image-search-with-amazon-titan-and-supabase-vector
- Subject: Supabase

Supabase published a guide demonstrating how to implement semantic image search using the Amazon Titan multimodal model via Amazon Bedrock and Supabase Vector in Python. The post walks through creating embeddings for images, storing them in a Postgres database with pgvector, and querying them with text or image inputs.

## Evidence

Verbatim from https://supabase.com/blog/semantic-image-search-amazon-bedrock:

> In this post we'll look at how we can get started with Amazon Bedrock and Supabase Vector in Python using the Amazon Titan multimodal model and the vecs client .

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Record: https://forck.live/items/21443-implementing-semantic-image-search-with-amazon-titan-and-supabase-vector
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