AI in the world - most important events from July 21, 2026

Today's Daily AI World Brief gathers the most important news about artificial intelligence from key regions of the world.

The focus is on business implementations, regulations, security, and the development of AI models.

Europe OntoExtend: A Framework for Requirement-driven and Scalable Ontology Extension with LLMs arXiv:2607.17963v1 Announce Type: new Abstract: Ontology extension refers to the process of enriching an existing ontology in response to emerging requirements, making it more complete.

This task is a resource-intensive and error-prone process.

Large Language Models (LLMs) have shown promising performance on generating ontologies from scratch, but current approaches rarely tie ontology extension explicitly to requirements or reusable core models, and offer limited, systematic evaluation of LLM outputs.

This paper introduces OntoExtend, a requirements-driven framework for ontology extension with LLMs.

It uses retrieval-augmented generation (RAG) over relevant input ontologies and requirements in the form of competency questions to propose grounded extensions.

We evaluate OntoExtend on 39 CQs from two use cases: a public EU-project ontology, Onto-DESIDE, and an industrial ontology from Bosch.