Vector Search in Elasticsearch 8

Explore the fundamentals and applications of Vector Search in Elasticsearch 8 through this 39-minute presentation. Delve into the concept of measuring similarity based on meanings and deeper content representations, enabling advanced applications like image recognition, audio comparisons, and NLP-based relevance ranking. Learn to create indexes for vectorized data using Elastic's dense_vector field type and perform efficient Approximate Nearest Neighbor searches with the Hierarchical Navigable Small World (HNSW) algorithm. Discover how to import and utilize machine learning models in Elasticsearch for inference. Cover topics including Vector Search basics, use cases, vector similarity measurement, scaling Vector Search, and hands-on implementation. Gain insights from Principal Solution Architect Robert Statsinger in this comprehensive overview of Vector Search capabilities in the Elastic Platform.

Vector Search in Elasticsearch 8