Machine Learning: New Perspectives for Science

Picture: The interactive art exhibit
The interactive art exhibit "IN ML OUT" addresses the relationship between climate change and renewable energy and demonstrates the potential of machine learning. (© Machine Learning for Science)
Clusters of Excellence
The aim of this cluster is to enable machine learning to take a central role in all aspects of scientific discovery and to understand how such a transformation will impact the scientific approach as a whole.

The rise of “intelligent” technology is transforming engineering, industry and the economy at an increasing pace and on an unprecedented scale. At the core of this revolution are breakthroughs in the field of machine learning which allow machines to perform tasks that, until recently, could only be performed by humans. Less prominently discussed, developments in machine learning have the potential to transform science at an equally fundamental level. While machine learning methods have been used in the past to tackle isolated prediction problems, recent breakthroughs open up an exciting new opportunity: Automated inference methods will become increasingly useful in the process of scientific discovery itself, supporting scientists in identifying which hypotheses to test, which experiments to perform, and how to extract principles describing a broad range of phenomena.

Involved Institutions:

  • Leibniz-Institut für Wissensmedien (IWM)
  • Max-Planck-Institut für Intelligente Systeme (MPI)