What do people in Baden-Württemberg think about AI and what would they like to tell politicians and researchers? The University of Tübingen established the "AI and Freedom" citizens' council to answer precisely these questions. In this interview, Anika Kaiser and Patrick Klügel from the project team discuss what the council can achieve but also the limits of its influence.

Can we build neural networks whose structure and computational abilities match a real brain? We are not quite there yet, but our new work shows a strategy for getting closer to this goal.

There are still far fewer women than men working in the field of machine learning. This has significant consequences. Among other things, women are less visible and they often feel isolated. Claire Vernade, a research group leader in the Cluster of Excellence “Machine Learning”, wants to change that. Together with nine female colleagues, she has founded the group "Tübingen Women in Machine Learning".

Synchrotron sources produce intense X-rays that are indispensable for many fields of modern science. The essential information, which is often buried in an ocean of experimental data, can be extracted using machine learning. But such models still lack important insights about the structure of the systems being studied. By allowing experimentalists to provide such insights to adaptive neural networks, we were able to instantly obtain more accurate results.