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Close-up of a camera and a press card © Harald Richter​/​Shotshop.com
Germany aims to be a global leader in artificial intelligence

Competence Center Machine Learning Launched at TU Dortmund University

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In the foreground four drones are flying, in the background two people can be seen © Oliver Schaper​/​TU Dortmund
The innovations were presented in the hall of the Fraunhofer Institute for Material Flow and Logistics.
With the “Competence Center Machine Learning Rhine-Ruhr” (ML2R), a network of research institutions in North Rhine-Westphalia has been selected as one of four hubs in Germany for cutting-edge research and transfer in the area of Artificial Intelligence. The Federal Ministry of Education and Research awarded the contract already in autumn 2018; on January 23rd the Competence Center celebrated its launch in a kick-off event on the LogistikCampus of TU Dortmund University. Internationally renowned scientists gave insights into the current state of research and future issues; companies in the region impressively demonstrated how they are already successfully using the new technologies.

“It is a special distinction for our scientists and for the entire region that we have brought the competence center to the locations Dortmund, Bonn and Sankt Augustin,” said Professor Ursula Gather, President of TU Dortmund University, in her welcome address. Together, TU Dortmund University, the University of Bonn and the Fraunhofer Institutes for Intelligent Analysis and Information Systems IAIS in Sankt Augustin and for Material Flow and Logistics IML in Dortmund will conduct cutting-edge research. The speakers of the Center are Professor Katharina Morik of TU Dortmund University and Professor Stefan Wrobel of the University of Bonn and the Fraunhofer IAIS.

One focus of the center is human-oriented machine learning. “We want to design machine learning processes so that the decisions made with artificial intelligence become understandable, traceable and validatable for human beings,” said Professor Katharina Morik. The scientists want to develop a kind of “wash tag” for algorithms: Simple symbols and “traffic light” status indicators should show which quality, energy and memory consumption algorithms have. After all, different criteria apply to different applications, according to Morik. Autonomous driving, for example, requires the highest quality class.

Another focus of the competence center is machine learning under resource constraints, which enables calculations even on small devices such as smartphones or directly in sensors. In addition, a third focus will combine machine learning with complex knowledge: Knowledge from different sources will be integrated into learning systems in order to ensure reliable results even with small or insecure data sets.

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