Vector search is a method that helps you find similar items based on their content rather than exact matches on properties like keywords, tags, or other metadata, as keyword-based search systems do. In this session, we will discuss about vector search with Azure AI Vision and Azure Cosmos DB for PostgreSQL. We will explore how to use Azure AI Vision embedding models and enable the pgvector extension, an open-source vector similarity search extension for PostgreSQL. We will then go on to show how to build an image vector similarity search app that can take advantage of these technologies.
ABOUT SPEAKER
Foteini Savvidou works as a Back-End Engineer at the Cloud Platform team of NET2GRID in Greece. She holds an integrated Master's degree in Electrical and Computer Engineering from the Aristotle University of Thessaloniki and is interested in IoT, AI, cloud technologies, and biomedical engineering. Foteini has been awarded as a Microsoft Most Valuable Professional (MVP) in AI and is actively involved in the Microsoft Learn Student Ambassadors community. She constantly shares her knowledge and passion for technology and runs a technical blog at sfoteini.github.io.
LinkedIn: https://twitter.com/SavvidouFoteini
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