AIM for Science
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Artifical Intelligence Münster for Science - Integrating Arificial Intelligence in the Scientific Process

Due to the rapid development in the field of hardware, the increasing availability of large amounts of data and recent methodological developments, artificial intelligence (AI), realized through the methods of machine learning (ML), has developed into a versatile, ubiquitously applicable tool in recent years. The systematic integration of these methods into the scientific process - from the planning and control of experiments to algorithmically supported hypothesis generation and data-driven model development - has the potential to revolutionize the knowledge process in all disciplines in the long term.
The program “AIM for Science” aims to bundle the existing strengths and structures at the University of Münster in order to systematically integrate AI methods into all areas of science. By networking the relevant working groups, an environment is to be created that reduces the barriers to integrating AI into the research process and at the same time enables new synergies between the disciplines.

 

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AIM for

"AIM for" is the interdisciplinary workshop series of the “Artificial Intelligence Münster for Science” initiative. It connects researchers at the University of Münster who use artificial intelligence and machine learning in their research or whose work may benefit from these methods in the future, and is enriched by contributions from external experts. Each edition focuses on a scientific topic in which AI opens up new methodological approaches.

  • AIM for The Brain

    From artificial to natural intelligence: As machine learning systems become increasingly powerful at recognizing patterns and modeling complex dynamics, they are also being used more and more in cognitive neuroscience to investigate fundamental questions: How does the brain generate thoughts, memories, perception, and actions? And how can data-driven models help uncover the underlying principles of these processes? Ultimately, could artificial intelligence help us better understand natural intelligence?

    Link to the workshop