Armchair Architects: LLMs & Vector Databases (Part 1)

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​ Vector databases are designed to store, manage, and index massive quantities of high-dimensional vector data efficiently that can help different types of queries, such as nearest neighbor. In this episode of the #AzureEnblementShow, Uli, Eric and David discuss how vector databases convert data to integers, cover some of the use cases of vector databases, and the benefits of embedding. This is part one of a two-part series.

• Vector search in Azure AI Search
• Geospatial data processing and analytics
• Microsoft Azure AI Fundamentals: Natural Language Processing
• Azure Database for PostgreSQL
• Vector DB Lookup tool for flows in Azure AI Studio

Related episodes
• Watch more episodes in the Armchair Architects Series
• Watch more episodes in the Well-Architected Series

0:00 Introduction
0:38 Data stored as integers
1:30 Text converted to numerical data
2:29 Vectors are not new
3:47 Use cases
5:02 Benefits of Embedding
7:40 Vectorizing semantic concepts
8:38 Teaser for Part 2   Read More Microsoft Developer 

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