ProjectMINERVA – European Support Centre for Scalable AI Research and Deployment
Basic data
Acronym:
MINERVA
Title:
European Support Centre for Scalable AI Research and Deployment
Duration:
01/01/2025 to 31/12/2027
Abstract / short description:
The MINERVA project focuses on advancing HPC-AI knowledge across European machine learning (ML) and AI communities, acting as a central hub for cutting-edge European competences in large-scale ML/AI research and development, including training, customization, management and related knowledge (e.g. datasets, procedures, compliance with regulation). At its core, MINERVA is focused on bridging the existing gaps in HPC utilization by ML/AI communities by facilitating the integration of cutting-edge HPC infrastructure in their workload thanks to a rich service portfolio that includes three different support levels, from support for porting AI applications and workflow on HPC infrastructures to support for the pre-training and customization of large-scale open foundation models. Indeed, special emphasis is placed on the support around research and development of open-source foundation models, as these can bolster competitiveness and foster innovation within the European digital ecosystem, ensuring the reuse of high quality models and datasets. MINERVA's comprehensive framework includes targeted training programs, availability of dataset, procedures and software stack in the participating HPC centres, best practice guides, interaction with the AI communities to collect and address their needs, as well as foster the development of a Community Hub that will bring together AI researchers, developers, users and HPC specialist with the aim of sharing knowledge and bring Europe at the forefront of the AI revolution. The project's outcomes are expected to significantly contribute to the strategic objectives of EuroHPC and the European Commission, positioning Europe as a leader in the digital age through the innovative application of HPC and AI technologies in scientific research, industry applications, and beyond.
Keywords:
machine learning
maschinelles Lernen
artificial intelligence
künstliche Intelligenz
High Performance Computing
Large AI Models
Involved staff
Managers
Faculty of Science
University of Tübingen
University of Tübingen
Institute for Theoretical Physics (ITP)
Department of Physics, Faculty of Science
Department of Physics, Faculty of Science
CRC 1233 - Robust Vision — Inference Principles and Neural Mechanisms
Collaborative research centers and transregios
Collaborative research centers and transregios
Bernstein Center for Computational Neuroscience Tübingen (BCCN)
Interfaculty Institutes
Interfaculty Institutes
Tübingen AI Center
Department of Informatics, Faculty of Science
Department of Informatics, Faculty of Science
Other staff
Institute for Theoretical Physics (ITP)
Department of Physics, Faculty of Science
Department of Physics, Faculty of Science
Institute for Theoretical Physics (ITP)
Department of Physics, Faculty of Science
Department of Physics, Faculty of Science
Institute for Theoretical Physics (ITP)
Department of Physics, Faculty of Science
Department of Physics, Faculty of Science
Department of Informatics
Faculty of Science
Faculty of Science
Local organizational units
Tübingen AI Center
Department of Informatics
Faculty of Science
Faculty of Science
Institute for Theoretical Physics (ITP)
Department of Physics
Faculty of Science
Faculty of Science
Funders
Brüssel, Belgium
Bonn, Nordrhein-Westfalen, Germany
Cooperations
Paris, France
Gif-sur-Yvette, Île-de-France, France
Montpellier, France
Casalecchio di Reno, Bologna, Italy
Milano, Italy
Helsinki, Finland