A new tool for working with big data: GraphRAG from Microsoft

Microsoft introduced a new technology called GraphRAG that allows chatbots and search engines to work with big data much more efficiently. GraphRAG significantly outperforms standard RAG (Retrieval-Augmented Generation), a technology that allows large language models (LLMs) to use a searchable index-like database as the basis for answering questions.

"GraphRAG creates knowledge from indexed documents, also known as unstructured data. An obvious example of unstructured data is web pages. So when GraphRAG creates a knowledge graph, it creates a 'structured' representation of the relationships between different 'entities' (like people, places, concepts and things) that are then more easily understood by machines."

🚀 GraphRAG creates what Microsoft calls "communities" of general topics (at a high level) and more detailed topics (at a low level). The LLM then creates a summary of each of these communities, a "hierarchical data summary", which is then used to answer the questions. This is a breakthrough because it allows the chatbot to answer questions based more on knowledge (summary) than on embedding dependencies.

• 📌 GraphRAG allows LLM to answer questions based on a common data set.
• 📌 GraphRAG creates a knowledge graph from indexed documents such as web pages.
• 📌 GraphRAG creates "communities" of general topics (at a high level) and more detailed topics (at a low level).
• 📌 LLM creates a summary of each of these communities, a "hierarchical data summary", which is then used to answer questions.
• 📌 GraphRAG is available for public use on GitHub.