The Hierarchical Navigable Small World (HNSW) is one of the most popular graph-based indices for nearest neighbor search. Join us for a fireside chat with Yury Malkov, as we discuss how he ended up developing this critical method of high-dimensional data analysis. We’ll explore how he got started in computer science and where he sees the future of vector search and LLMs. You’ll even get a chance to ask Yury questions at the end of the chat, you won’t want to miss it!

Topics covered:
- Why HNSW and other graph indexes are great tools for vector search
- What is the future of vector search?
- Thoughts on the proliferation and increasing importance of LLMs as it relates to vector data

## About the Session
The Hierarchical Navigable Small World (HNSW) is one of the most popular graph-based indices for nearest neighbor search. Join us for a fireside chat with [Yury Malkov](https://twitter.com/malkovyury), as we discuss how he ended up developing this critical method of high-dimensional data analysis. We’ll explore how he got started in computer science and where he sees the future of vector search and LLMs. You’ll even get a chance to ask Yury questions at the end of the chat, you won’t want to miss it!

# Topics covered:
- Why HNSW and other graph indexes are great tools for vector search
- What is the future of vector search?
- Thoughts on the proliferation and increasing importance of LLMs as it relates to vector data

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Webinar

Register for a free webinar with Yury Malkov, author of HNSW and hear his predictions on the future of vector search.

Fireside chat with HNSW author Yury Malkov | Zilliz Webinar

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Webinar

What is the future of vector search? A fireside chat with HNSW author Yury Malkov