Artificial intelligence is an important field of research and teaching at our department. For example, deep neural networks (deep learning) can significantly improve previous (often only linear) problem-solving approaches in many areas. Neural networks therefore play an important role in medical technology, for example, and can provide good services to our medical partners in diagnoses and analyses.

In addition to classic supervised learning (which is probably the most frequently used method in our company), unsupervised learning (e.g. for data compression or for detecting unusual signal or data areas) and reinforcement learning are also playing an increasingly important role. The latter can be used primarily for control and regulation purposes, as it can also be used to learn successful control and regulation strategies over the long term.

In addition to these more application-related aspects, the institute is also looking at the energy balance of systems with artificial intelligence. This aspect will play an important role in the future due to the ever-increasing use of artificial intelligence. The Collaborative Research Center 1461 "Neuroelectronics: Biologically Inspired Information Processing" is therefore also increasingly looking at and researching analog variants of artificial intelligence.