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AI conversations often focus on models, yet the real foundation of intelligence lies in data architecture. Modern AI systems remain fragile because they lack context, semantics, and shared understanding. In this session, Michael Carducci explores how linked data, RDF, ontologies, and knowledge graphs address issues such as hallucination, inconsistency, and poor interoperability. Drawing from real-world examples, he connects decades of research in semantic web technologies to today’s AI and agentic systems. Attendees will learn how meaning can be modeled, linked, and reasoned over, and why the future of AI depends not on larger models, but on smarter, semantically structured data.
What You Will Learn
How data architecture shapes the intelligence and reliability of AI systems
The roles of linked data, RDF, ontologies, and knowledge graphs in solving context and consistency problems
Practical insights into designing smarter, interoperable data foundations for modern AI
Who Should Attend
AI engineers, data architects, software developers, and technology leaders interested in building robust, context-aware AI systems through strong semantic data design.