Project Helios
A multi-modal foundation model trained on scientific literature, code, and experimental data. Helios can reason about novel hypotheses and design experimental protocols for verification.
European AI Research Laboratory
At the frontier of artificial intelligence, we pursue research that redefines what machines can understand, reason about, and create.
Who we are
EUWL is a collective of researchers, engineers, and theorists united by a single conviction: that artificial intelligence should be developed openly, rigorously, and with deep respect for its societal impact.
We operate across five European cities, combining the continent's strongest traditions in mathematics, philosophy, and computer science to build AI systems that are not just powerful — but principled.
340+
Researchers
6
Years active
5
Labs
Core Capabilities
Systems that decompose complex problems, formulate multi-step plans, and execute decisions with minimal human oversight.
Unified models that process and connect text, images, audio, and structured data within a single coherent representation.
Federated and distributed training paradigms that scale across geographies while preserving data privacy and sovereignty.
Rigorous alignment methods ensuring AI systems remain interpretable, controllable, and aligned with human values at every scale.
By the numbers
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Parameters
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Researchers
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Publications
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Patents
Active Projects
A multi-modal foundation model trained on scientific literature, code, and experimental data. Helios can reason about novel hypotheses and design experimental protocols for verification.
Privacy-preserving federated learning at European scale. Nyx enables collaborative model training across institutions without centralizing sensitive data, respecting GDPR by design.
Next-generation alignment research combining constitutional AI with formal verification. Aether aims to provide mathematical guarantees about model behavior in safety-critical domains.
Temporal reasoning and long-horizon planning. Kronos develops architectures capable of understanding cause and effect across extended timeframes for autonomous decision-making.
Publications
M. Volkmann, K. Iosifidis, A. Reinholt, T. Okafor
NeurIPS 2024
L. Petrova, S. Balachandran, J. Hämäläinen
ICML 2024
D. Osei, R. Castellano, F. Lindqvist, P. Nkemelu
ICLR 2024
A. Reinholt, D. Osei, R. Castellano
AAAI 2024
We're hiring researchers, engineers, and policy specialists across all five EUWL laboratories.