What will you learn?
In this talk, we'll offer a brief introduction to Graph RAG and how to integrate knowledge graphs into RAG systems, discussing the benefits, challenges, and solutions. Knowledge graphs provide a robust and flexible semantic representation of your data, enhancing the reliability, completeness, and accuracy of RAG systems. They help to reduce the opacity of RAG pipelines, increasing visibility, control, and determinism in retrieval workflows. When combined with vector databases, you get the best of both worlds: scalable storage of metadata-rich embeddings with a powerful, adaptable semantic layer.
At WhyHow, we develop tooling that enables developers to build, manage, and integrate knowledge graphs into RAG systems for more accurate and deterministic information retrieval. During this session, we'll share key findings, common patterns we've observed, and what we think the future holds for Graph RAG. We will also explore architectures and workflows showcasing how graphs provide an elegant solution for scalable and precise information retrieval.
Topics Covered
- Introduction to Graph RAG
- Common patterns in building, managing, and integrating knowledge graphs into RAG systems
- What the future holds for Graph RAG
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5 июн 2024
