Trustworthy Unified Robust Intelligent Generative Systems (TURING)

Project TURING is a European research and innovation initiative under the Horizon Europe programme (Call: HORIZON-CL4-2024-HUMAN-03-02 – Explainable and Robust AI), aimed at developing explainable, reliable, and sustainable artificial intelligence (AI) solutions. The main goal of the project is to enhance the robustness, explainability, and trustworthiness of generative AI models (genAI) through the use of mathematically and physically grounded methods. The project develops so-called TURING models – generative and multimodal foundation models capable of accurately representing complex physical phenomena. These models will be integrated into the TURING Framework, an open-source platform that enables users to interact with models, validate them, and develop new applications. The project brings together research from the fields of machine learning, physics, computer science, and data science. TURING addresses key challenges of modern artificial intelligence, such as model reliability under real-world conditions, regulatory compliance (GDPR, AI Act), energy efficiency, explainability of decisions, and bias prevention. The system leverages physics-informed constraints, meta-learning methodologies, federated learning, and distributed computing to improve model robustness. The results will be applied in three high-tech domains: nuclear energy, particle physics, and meteorology. The project will enable model validation on real-world data, enhance predictive accuracy, reduce simulation costs, and accelerate innovation.

The TURING project develops novel AI approaches enabling robust modelling of complex physical systems. It integrates computer science, physics, engineering, and social sciences to create generative multimodal models grounded in physical laws. This contributes to scientific computing advancements and opens new opportunities for understanding natural phenomena and engineering processes.

The project enables Slovenian researchers to collaborate within a leading European network in artificial intelligence and scientific computing. It enhances access to new modelling methods and tools, strengthens digital competencies, and contributes to the development of robust technologies applicable in industry, energy, and meteorology.