Trustworthy Unified Robust Intelligent Generative Systems

Digital, Industry & SpaceHORIZON-RIAID: 101215032
EC Contribution
โ‚ฌ74,978
Consortium Size
23 orgs
Start Year
2025
โ–ถSummary

The need to implement complex physics systems is critical across various scientific and engineering domains. However, traditional numerical models for simulating these systems are computationally expensive, requiring significant time, resources, and cost. Recent advancements in AI present a promising alternative, with AI models demonstrating the ability to capture the dynamics of complex physical systems. Despite these successes, AI models suffer from key limitations, including challenges with generalization, vulnerability to bias, ethical concerns, and accuracy, particularly when applied to unseen tasks or variable-range predictions. These limitations are collectively viewed as issues of robustness.The TURING project aims to address these shortcomings by developing robust AI-driven solutions. It integrates multidisciplinary advancements from Machine Learning, Computer Engineering, Physics, and SSH to pre-train generative, multimodal foundation models capable of capturing the physics of dynamic systems that share common properties. Starting with a cautious approach, the models will incorporate representations of increasingly complex physical systems as robustness is ensured.Once pre-trained, these foundation models will be fine-tuned for specific tasks, enhancing their domain-specific robustness. The tasks will target critical engineering and physics problems in nuclear energy, particle physics, and meteorology, which are of high priority for the EU. The task-specific and foundation models, collectively termed ""TURING models"", will be developed in collaboration with partners from India, Canada, and Switzerland.To maximize the impact of TURING models, the project will ensure compliance of its activities with regulations such as the EU AI Act and then publicly release those models, along with the TURING Framework (MLOps SW tools and web-based app with conversational capabilities), enabling developers and end users to leverage this technology for their applications.""

Consortium (23)

๐Ÿ‡ฌ๐Ÿ‡ท EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMATON EPIKOINONION KAI YPOLOGISTONGR
coordinator
๐Ÿ‡ฉ๐Ÿ‡ช AEGIS IT RESEARCH GMBHDE
partner
๐Ÿ‡ซ๐Ÿ‡ท BULL SASFR
partner
๐Ÿ‡ฌ๐Ÿ‡ท DIINEKES S.I. MONOPROSOPI IDIOTIKI KEFALAIOUCHIKI ETAIREIAGR
partner
๐Ÿ‡จ๐Ÿ‡ฆ ECOLE DE TECHNOLOGIE SUPERIEURECA
partner
๐Ÿ‡จ๐Ÿ‡ญ EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICHCH
partner
๐Ÿ‡ธ๐Ÿ‡ฎ FAKULTETA ZA INFORMACIJSKE STUDIJE V NOVEM MESTUSI
partner
๐Ÿ‡ฎ๐Ÿ‡น FONDAZIONE BRUNO KESSLERIT
partner
๐Ÿ‡ฌ๐Ÿ‡ท IDRYMA TECHNOLOGIAS KAI EREVNASGR
partner
๐Ÿ‡ฎ๐Ÿ‡ณ INDRAPRASTHA INSTITUTE OF INFORMATION TECHNOLOGY DEHLIIN
partner
๐Ÿ‡จ๐Ÿ‡พ IOTAM INTERNET OF THINGS APPLICATIONS AND MULTI LAYER DEVELOPMENT LTDCY
partner
๐Ÿ‡ซ๐Ÿ‡ท METEO-FRANCEFR
partner
๐Ÿ‡จ๐Ÿ‡พ ML AND AI DATA CONSULTANTS LTDCY
partner
๐Ÿ‡ฉ๐Ÿ‡ช NEC LABORATORIES EUROPE GMBHDE
partner
๐Ÿ‡ณ๐Ÿ‡ฑ NRG PALLAS BVNL
partner
๐Ÿ‡จ๐Ÿ‡ญ ORGANISATION EUROPEENNE POUR LA RECHERCHE NUCLEAIRECH
partner
๐Ÿ‡ธ๐Ÿ‡ฎ RUDOLFOVO ZNANSTVENO IN TEHNOLOSKO SREDISCE NOVO MESTOSI
partner
๐Ÿ‡ฎ๐Ÿ‡น SCUOLA SUPERIORE DI STUDI UNIVERSITARI E DI PERFEZIONAMENTO S ANNAIT
partner
๐Ÿ‡ธ๐Ÿ‡ฐ SLOVENSKA TECHNICKA UNIVERZITA V BRATISLAVESK
partner
๐Ÿ‡ท๐Ÿ‡ธ University of Novi Sad Faculty of SciencesRS
partner
๐Ÿ‡ฉ๐Ÿ‡ช UNIVERSITY OF STUTTGARTDE
partner
๐Ÿ‡ฌ๐Ÿ‡ท YPOLOGISTIKI MICHANIKI EPOMENIS GENIAS IKEGR
partner
๐Ÿ‡ฌ๐Ÿ‡ท ZELUS IKEGR
partner