Artificial Intelligence · 30.07.2026, 11:33 UTC
Ontologies Are So Back: Why AI Agents Are Reviving the Semantic Web
| Schweregrad | info |
|---|---|
| Kategorie | Artificial Intelligence |
| Quelle | Latent Space ↗ |
| Veröffentlicht | 30.07.2026 UTC |
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One of the most watched videos from the recent AI Engineer World’s Fair is a 20-minute talk by Frank Coyle, a professor of computer science who currently teaches generative AI and LLMs at UC Berkeley. Drawing on his decades of experience, Coyle re-introduced the concept and practice of ontologies to today’s AI engineers.Coyle argued that while LLMs are very effective at providing probabilistic reasoning, for agentic systems to be truly effective they need “logical guardrails” — by which he means ontologies.UC Berkeley professor Frank Coyle speaking at AIEWF 2026.In computer science, an ontology is “a description of data structure – of classes, properties, and relationships in a domain of knowledge” (as nicely defined by Oxford Semantic Technologies). Coyle himself defined an ontology as simply “data as graphs.” He added that ontologies as a concept go right back to Aristotle, and have been used throughout the history of Artificial Intelligence.The company Neo4j, known for its graph database systems, is also using ontologies in its agentic products.In a keynote session at AIEWF, Neo4j CEO Emil Eifrem talked about three different types of ontologies to enable a “smarter shared substrate” to run agents at scale. The first is a business-facing ontology, describing the key concepts in an organization; next is a technical ontology, which Eifrem described as “all the metadata of all the data sources and data assets in your enterprise ecosystem”; and finally execution traces, which are “the runtime signals out of your agent.”Neo4j’s ontology-based semantic layerWhat’s Old is New …