In this demo-intensive session Alan will explore the concepts of embedding and nearest-neighbor search. The analysis and embedding of data will be explained, along with techniques to vectorize text, images and music. He will then demonstrate how vector-based indexes can be created in Azure AI Search using both the Azure portal and programmatically. Alan will show how text and image embedding can be leveraged, and then show the techniques used to create an index using the beat signatures in music. The search index can then be used to find similar sounding beat patterns in songs, allowing code to mix tracks seamlessly, creating a stunning AI-augmented audio experience.

Well, that’s the theory, can this work in practice? Join this session and learn about the power and versatility of vector-based searching.

Ya’ll ready for this?