Awarded Projects

The MOSAIC project (Multimodal Open models for Safe AI in Content generation and retrieval) aims to develop the first large-scale European multimodal foundation models for cross-modal retrieval and image/video generation, with trustworthiness and safety embedded by design.

Understanding if VUS affect proteins and their impact at the molecular level is crucial for expanding our knowledge of cancer, developing personalized prognosis and treatments, or assisting genetic counseling.

The project proposes to better understand the fueling of supermassive black holes from galactic scales using multi-scale numerical modelling.

MultiCellFM aims to develop an advanced Cell Foundational Model (CFM) that leverages cutting-edge artificial intelligence to extract meaningful insights from vast single-cell datasets.

The project team proposes a suite of multilingual continual pretrained Dense and Mixture-of-Expert (MoE) models at different size tiers for different types of workloads that have different inference compute constraints.

With their current computer vision and natural language processing models, the project already manages to process 30% of incoming claims automatically.

This project intends to train a multimodal transformer based model incorporating text, audio, and image modalities for the scandinavian languages (Swedish, Danish, Norwegian, and Icelandic) and English.

Coastal regions are becoming increasingly populated and industrialized, with nearly one-third of humanity residing within 100 kilometres of the coast.

This focused project directly supports the broader EuroLLM and OpenEuroLLM initiatives by addressing a critical bottleneck – the availability of high-quality pre-training data.