Exploring GraphRAG: AI-Powered Graph Search for Security Data Analysis
Microsoft Developer features Anisha Latchman demonstrating how GraphRAG leverages Azure OpenAI and advanced graph embeddings to transform security data search and analysis in this practical and insightful video.
Exploring GraphRAG: AI-Powered Graph Search for Security Data Analysis
In this episode of Mr. Maeda's Cozy AI Kitchen, Microsoft Security Intern Anisha Latchman takes viewers through a tour of GraphRAG, an open-source Microsoft project that blends Retrieval-Augmented Generation (RAG) with graph-based search approaches to uncover deep patterns within security datasets.
Highlights
- Introduction to GraphRAG: Anisha explains how GraphRAG enhances traditional RAG by using graph context, parsing emails, and building weighted graphs from nodes and relationships.
- Hands-On Demo: Guidance on setting up GraphRAG, feeding input email data, configuring the API, indexing, and interpreting results files.
- Technical Deep-Dive:
- Understanding nodes, relationships, and the importance of weighted graphs in capturing context.
- Entity extraction using prompt engineering.
- Strategies for chunking information in RAG pipelines.
- Comparisons: Evaluations between baseline RAG and GraphRAG performance, with focus on semantic search versus graph traversal.
- Practical Takeaways:
- Advice for aspiring AI builders interested in graph-based search and prompt engineering.
- Insights into community search, subgraphs, and transparency in entity extraction.
What You'll Learn
- How GraphRAG amplifies traditional RAG with graph-based context.
- The role of embeddings and nodes in security data analysis.
- Setting up and operationalizing GraphRAG using open-source Microsoft tools.
- The distinction between semantic (vector-based) and graph (relational) search methodologies.
- Prompt and context engineering best practices for AI solutions.
Resources
Speakers
- Anisha Latchman, Security Intern, Microsoft
LinkedIn - John Maeda, Host
LinkedIn, (https://x.com/johnmaeda)
For more episodes, visit the Cozy AI Kitchen Playlist.