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AI Strategy for Earth system data

Artificial intelligence (AI) methods are currently experiencing rapid development and are also being used more and more frequently in the context of environmental data. However, this use is often in the context of isolated solutions. The systematic use of modern AI methods is not yet established in environmental and Earth system sciences. In particular, there is often a discrepancy between the requirements of a solid and technically sound environmental data analysis and the applicability of modern AI methods such as deep learning for researchers.

The KI:STE project (AI strategy for Earth system data) closes this gap with a sophisticated strategy that combines the development of diverse AI applications on different socially relevant aspects of environmental and Earth system research with a strong training and network concept. It creates the technical prerequisites to make high-performance AI applications on environmental data portable for future users and to establish environmental AI as a key technology.

Forschungszentrum Jülich GmbH, Germany
The contact person is Scarlet Stadtler
Project Coordinator

RWTH Aachen University, Germany

University of Cologne, Germany

Universität Bonn, Germany

52 North, Germany

Ambrosys GmbH, Germany

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KI:STE is funded by the German Federal Ministry for the Environment, Nature Conservaion and Nuclear Safety (BMU) under grant agreement 67 KI2043A-F.

The grant period is November 2020 until October 2023.

More detailed information about the project is available at the project's homepage.