Why the future of AI accuracy depends on graph databases
The adoption of generative AI is transforming industries. However, these systems often hallucinate, creating information that seems plausible but is factually incorrect. This issue arises as large language models (LLMs) are primarily trained on vast datasets without a deep understanding of contextual relationships within the data. Neo4j’s director of technology solutions, Kris Payne, told iTnews Asia that knowledge graphs act as a factual repository that complements LLMs.
Read more: https://www.itnews.asia/news/why-the-future-of-ai-accuracy-depends-on-graph-databases-614164
Keywords: Generative AI • Large Language Models • Thought Leadership