Capgemini's "Knowledge Graphs improve Gen AI" article discusses how knowledge graphs enhance the accuracy and reliability of generative AI (GenAI) outputs. It addresses the limitations of unstructured data in Large Language Models (LLMs) and proposes using knowledge graphs to store complex, structured data. The solution involves query templates that guide LLMs to interact with knowledge graphs, improving retrieval accuracy and efficiency. Tailored templates allow organizations to address specific challenges, and LLMs can dynamically select multiple templates for complex business scenarios. The article highlights benefits such as explainable results, better-informed decisions, and democratized data access, suggesting that knowledge graphs are crucial for improving GenAI.
