In the era of big data, large language models (LLMs) are becoming increasingly important for tasks like question answering, document analysis, and chatbot development. However, traditional LLMs can often struggle with factual accuracy, reasoning, and handling complex information.
This talk introduces GraphRAG, a novel technique that leverages the power of knowledge graphs to empower LLMs. We’ll delve into the limitations of traditional LLMs and vector-only approach of RAG and explore how GraphRAG bridges the gap. GraphRAG equips LLMs with a deeper understanding of the world by utilizing enterprise data, boosting their accuracy, reasoning abilities, and handling of complex information.
This talk will explore the exciting world of GraphRAG, showcasing its potential to revolutionize various fields. We will also discuss real-world applications and case studies using SEC EDGAR dataset to illustrate the benefits of GraphRAG for practitioners in comparison to a vector-only approach.
Technical Level: High Level/overview
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