More on the native vector search released over the summer.
The goal is to make it easier to quickly find contextually-related information. It is now fully integrated into Neo4j AuraDB and Neo4j Graph Database, and enables users to utilize vector search to get insights from generative AI applications by semantics rather than matching keywords.
To learn more about it:
Documentation on Vector Search
Blog Vector Search Deeper Insights
Neo4j x LangChain: Deep dive into the new Vector index implementation
Why Vectors Should Be Stored Together with Knowledge Graph?
Explore OpenAI vector embedding with Neo4j, LangChain, and Wikipedia
Neo4jās Vector Search: Unlocking Deeper Insights for AI-Powered Applications