Data Architecture for AI - Micheal Carducci

In this session, Michael Carducci highlights the significance of data architecture in developing robust AI systems. He discusses how linked data, RDF, ontologies, and knowledge graphs can address challenges such as hallucination, inconsistency, and poor interoperability that often plague modern AI applications. By drawing on real-world examples, the speaker illustrates the connection between decades of research in semantic web technologies and contemporary AI and agentic systems. Attendees will gain insights into modeling, linking, and reasoning over data, emphasizing that the future of AI relies on smarter, semantically structured data rather than merely increasing model size.