This article explains how ontology-based semantic layers work and advocates for their use as versatile enterprise tools. They add shared meaning, context, and governance to data, improving integration, analytics, oversight, and AI reliability across organizational systems.
We present an AI-assisted framework that uses LLMs to map unstructured organizational communications to a domain-specific metamodel and corresponding enterprise process activities. By linking messages to affected and dependent processes, the framework supports real-time situational awareness and proactive risk identifi...
This lesson introduces Wikidata and its underlying data structure. It shows how to navigate and query Wikidata using the Query Builder and SPARQL, and how its data model can be used to explore historical data.
We present a disjunctive Datalog encoding of the problem of query entailment over RDFS knowledge graphs under the metamodeling semantics.
This article examines an approach to formalizing the description of intelligent transportation systems (ITS) based on semantic modeling, including the concept of cooperative intelligent transportation systems and the "vehicular cloud".
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
In a new book, Professor Eric So explores how the technology affects our thinking skills.
Earth AI
GPT-Lab
· gpt-lab.eu
Oct 14, 2026
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
