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Irina Loghin – Developer Relations @ Neo4j

In this talk, you will learn about GraphRAG, a technique that combines graph databases with generative AI to improve the quality of LLM-generated content. We will explore the terms Retrieval-Augmented Generation (RAG) and Context Engineering, and how GraphRAG can be used in both scenarios. The topic is aimed at Generative AI practitioners who are familiar with vector-based Retrieval-Augmented Generation (RAG) and would like to understand how the approach of GraphRAG can improve the quality of LLM-generated content.

graphrag graph databases generative ai retrieval-augmented generation (rag) context engineering llms
GenAI Loft London - Day 6: Code. Scale. Disrupt
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