Learn how MyPart revolutionized song search by using vector embeddings, and how to implement efficient Vector Search with OpenSearch yourself. Webinar coming up July 25th 5pm UTC!

TV/Film, ad creatives and even DJs can use some help finding the perfect song. Can we solve such an intricate problem with Machine Learning and AWS OpenSearch? Absolutely!

Join MyPart's CEO and Chief Architect Matan Kollenscher, and Itamar Syn-Hershko, CTO and Founder of BigData Boutique, to learn how MyPart revolutionized song search using Vector Embedding and OpenSearch.

In this session, we'll discuss MyPart's unique use-case and multi-dimensional approach that slices up sounds, lyrics and musical compositions into vectors that make sense to a computer. With that information stored in a Vector Database, MyPart can run intelligent, low-latency queries on huge music catalogs, without compromising accuracy or functionality.

We will then dive into the intricacies of Vector Search with OpenSearch, learning ML techniques that apply to a wide range of projects. As we get more technical, we’ll discuss how OpenSearch makes searching through vector data easy and efficient:

  • Vector embeddings and vector search algorithms
  • Use-cases for Vector Search
  • OpenSearch and its vector search features
  • Common bottlenecks and optimizations

If you’d like to understand how AI can help your business, how KNN navigates a vector database, or just how technology can make a science out of crate digging, join us on July 25th for the whole story.