For improving the capabilities of general-purpose AI models and for extending their applicability to domains where the temporal dimension – among several others – is of importance, we will target the development of the next generation of Multimodal Space-Time Foundation Models (MSTFMs). These will combine spatio-temporal understanding, which is important even for modalities such as the visual one that have already been introduced in large generative models, with the effective management of new time-relevant modalities that are yet to be supported in foundation models, such as industrial time series data, remote sensing data and health-related measurements. Real and synthetic data, to mitigate data scarcity, will be leveraged for training general-purpose MSTFMs and for further adapting them for specific downstream tasks. Real data used for training will include data directly provided by members of the consortium as well as data from relevant European Data Spaces, while complementary synthetic data will be generated by exploiting existing generative AI capabilities as well as new ones developed in the project. European HPC infrastructure is directly included in the consortium to ensure the availability of the necessary computing resources.

We live in a crucial historical moment, with tremendous challenges ahead, from climate change to the energy crisis. ELIAS emerges from the belief that AI will be a key discipline to help us tackle these challenges. At the same time, the development of AI entails deep ethical and societal concerns that need to be addressed. As for fundamental research, ELIAS will address key scientific questions about how AI can reduce computational costs, serves to model effects of policy decisions on society, and impacts individuals. ELIAS will strive for a deep integration of the fundamental research that takes place in academia and the more applications-focused research from industry. ELIAS builds on and expands the highly successful and internationally recognized European Laboratory for Learning and Intelligent Systems (ELLIS). ELIAS will further develop the excellence criteria and the pillars in ELLIS and implement actions that will support AI researchers and young talents at different stages of their careers. Furthermore, ELIAS will develop a Sciencentrepreneurship track, with the purpose of attracting and empowering talents at the interface of scientific innovation and business and establish original AI solutions that move towards a sustainable long-term future for our planet, contribute to a cohesive society, and respect individual rights. The outcome of ELIAS will be to establish Europe as a leader in AI research in which impact on the environment, society and the individual are integral considerations during development. We will measure the success of this endeavor in terms of key indicators, including the number of new cross-institutional collaborations, the number of cross-disciplinary collaborations, the number of industry-academic partnerships, publications in top conferences and journals, patents, and the number of projects that have resulted in deployed technologies.