Jesús Barrasa, director of Telecom Solutions with Neo4j, discusses ontologies and their relevance in the field of artificial intelligence (AI) and machine learning. He begins by explaining that AI is not limited to machine learning, but also encompasses knowledge representation and reasoning, which is where ontologies come into play. Ontology is a formal representation of knowledge in a domain model, with three key characteristics: it must be machine-readable, explicit, and shareable. Barrasa uses examples from the FIBO ontology and schema.org to illustrate how ontologies can be used to make data smarter and reusable. He also discusses the two main uses of ontologies in Neo4j: interoperability and inferencing. Interoperability involves exposing data according to a shared vocabulary, while inferencing involves using knowledge fragments to derive new facts from existing data. Barrasa demonstrates how to use NeoSemantics to expose data as RDF and run queries on it, and shows an example of how to run inferences using the financial extension of schema.org. He concludes by highlighting the importance of ontologies in building a knowledge graph and provides resources for further learning.