A simple visual demonstration of how Graph RAG works using and how it can dramatically improve the results you get from LLMs using generative AI and retrieval augmented generation (RAG) augmented with knowledge graphs. By leveraging large language models and chatbots in innovative ways, we’ll explore a visual approach that makes complex AI interactions more intuitive and effective.
Try it on 🚀
Timecodes:
0:00 What you will learn
1:35 Problem with standard AI and RAG
3:55 How GraphRAG is better: focusing on relations and topics
7:05 Visual demonstration of the technical approach behind GraphRAG
10:42 Finding blind spots using a graph
12:37 Getting topical summaries using GraphRAG (from the Microsoft paper)
14:10 Using GraphRAG in Obsidian for your own content
Read more at
#infranodus #graphrag
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