Azure AI search provides great capabilities for keyword search and AI skillsets, and now has the capability for text embedding and vector-based searches. Vector-based searches can be used in many other scenarios besides text. If you can embed, convert data items to numbers, you can search for similar items, and this includes images, sounds, video and even music.

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?