Accenture AI Leaders Podcast AI Leaders Podcast #69: Knowledge Graphs in the Age of Gen AI
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Feb 17, 2025 Tony Romito, Technology Consulting Director at Accenture, and Navin Sharma, Head of Product at Stardog, dive into the intriguing world of knowledge graphs. They explain how these tools enhance data management and reasoning, particularly in the age of generative AI. Discover how knowledge graphs tackle issues like hallucinations in language models, their role in enterprise architecture, and their importance in decision-making across industries. The conversation also debunks myths surrounding knowledge graphs, showcasing their continued relevance and value.
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Knowledge Graph Relevance
- Knowledge graphs are increasingly relevant due to new technology, data scale, and advanced AI.
- They provide context and relationships, crucial for accurate and relevant insights, unlike large language models.
Knowledge Graphs as Conceptual Maps
- Knowledge graphs represent information as interconnected concepts, like people, places, or orders.
- This elevates data to knowledge by representing it at a business level for easier understanding and use.
Knowledge Graphs Enhance LLM Accuracy
- Large language models (LLMs) hallucinate because they use statistics, lacking semantic understanding.
- Knowledge graphs add context, improving LLM accuracy by connecting related information and concepts.