AI
From Words to Meaning: The Rise of Vector Search in Cosmos DB
Traditional search engines match words. Vector search matches meaning. Learn how Cosmos DB Vector Search brings semantic understanding directly into your database.
AI
Simplify Text Chunking for Vector Embeddings
Text chunking is crucial when working with vector embedding models, no matter where you host them. In my previous article, Vector Embedding for Long Documents, I explored how to combine multiple vectors into one. In this post, Read more
Azure AI
Vector Embedding Model Comparison with Multilingual Text
A vector embedding model comparison focusing on multilingual text using embedding models in Azure AI Foundry.
AI
Vector Embeddings For Long Documents
This blog article discusses a method for creating vector embeddings for texts longer than the input limit for a selected embedding model.
AI
Cosmos DB Vector Search – An Introduction
In this comprehensive guide, we delve into the powerful capabilities of Azure Cosmos DB as a vector database and demonstrate how to leverage Azure AI Foundry’s large language models (LLMs) to generate vector embeddings for advanced text search and analysis. Discover step-by-step instructions on setting up vector search, integrating LLMs, and optimizing your database for high-performance similarity queries. Explore practical use cases, best practices, and tips for making the most of these cutting-edge technologies in your applications.