This lecture explores how hybrid and causal machine learning can combine physical knowledge with data-driven models to improve understanding and inference in Earth system science. It highlights recent advances toward more consistent, explainable, and physically grounded AI methods for geoscientific analysis.
This workshop explores recent progress in multimodal foundation models that integrate vision, language, audio, and other modalities. Discussions address both the capabilities and limitations of large-scale generative AI systems, including issues of reliability, bias, and societal impact, while highlighting new research directions in multimodal learning and applications.
The AI Excellence Lecture on deep learning and Earth system science explores hybrid modelling approaches that combine machine learning with mechanistic models to improve understanding and prediction of complex Earth systems such as climate, ecosystems, and carbon cycles.
The Joint ELIAS–ELISE Flagship Workshop in Frankfurt brings together researchers, industry leaders, and policymakers to define joint actions on foundation models, sciencepreneurship, and AI innovation, including initiatives for startups, education programmes, and a pan-European AI incubation ecosystem.
The AI Excellence Lecture on learning manipulation skills from instructional videos presents advances in visual intelligence and robotics, focusing on how AI systems can learn object manipulation from human demonstrations and transfer these skills to robotic platforms.