How do you become a robotics researcher? Do you have to study something specific? How do you teach robots to think and act and what does the everyday life of a professor look like? Prof. Sami Haddadin, Director of the Munich School of Robotics and Machine Intelligence (MSRM) at the Technical University of Munich (TUM) answers these questions in a new episode of the video series "Superjob" by ZDF Terra X plus Schule.
Artificial Intelligence (AI)
Whether in medicine, agriculture or the automotive industry: Artificial intelligence (AI) is a key technology that is already shaping our lives significantly. At TUM, we are investigating and developing intelligent systems, while keeping an eye on our responsibility for people and society at all times. Find out what's new in the fields of AI, robotics, machine learning and data science.
Do carebots care? AI for whom? Will the market deliver? In the new online course AI Ethics: Global Perspectives, 20 experts from various disciplines and countries explore ethical questions arising with the development of artificial intelligence. The lecture series, available free of charge to all, was created by the TUM Institute for Ethics in Artificial Intelligence, the New York University and the Global AI Ethics Consortium.
Germany and France aim to strengthen interactions in the field of artificial intelligence (AI). On May 10 and 11, leading scientists will gather virtually at TUM for the First French-German Machine Learning Symposium. Bavaria's Minister President Dr. Markus Söder will open the symposium.
Reflexes protect our bodies – for example when we pull our hand back from a hot stove. These protective mechanisms could also be useful for robots. In this interview, Prof. Sami Haddadin and Johannes Kühn of the Munich School of Robotics and Machine Intelligence (MSRM) of the Technical University of Munich (TUM) explain why giving test subjects a “slap on the hand” could lay the foundations for the robots of the future.
A research team from the Technical University of Munich (TUM) and the Fritz Haber Institute in Berlin uses active machine learning in the search for suitable molecular materials for new organic semiconductors, the basis for organic field effect transistors (OFETs), light-emitting diodes (OLEDs) and organic solar cells (OPVs). To efficiently deal with the myriad of possibilities for candidate molecules, the machine decides for itself which data it needs.
The Technical University of Munich (TUM) will use its interdisciplinary TUM Innovation Networks to create even more space for scientific creativity and groundbreaking developments. The first three TUM Innovation Networks address the diagnosis and treatment of psychological illnesses using Artificial Intelligence (AI), the development of novel materials using machine learning, and investigation of the nature of life using chemical and biophysical experiments in combination with AI and robotics.
A team of researchers at the Technical University of Munich (TUM) has developed a new early warning system for vehicles that uses artificial intelligence to learn from thousands of real traffic situations. A study of the system was carried out in cooperation with the BMW Group. The results show that, if used in today’s self-driving vehicles, it can warn seven seconds in advance against potentially critical situations that the cars cannot handle alone – with over 85% accuracy.
From hologram-based communications to remote-controlled surgical procedures – the 6G wireless standard will make many high-tech applications a reality. A major project now being launched at the Technical University of Munich (TUM) aims to establish the key technical criteria for the new standard. In this interview, project leader Prof. Wolfgang Kellerer explains how 6G will become the most intelligent wireless network, when Germany could take on a leading role and why, in the world of research, new speed records are less important than ensuring 99.999999999% reliability.
With the help of artificial intelligence (AI) a German-American team of scientists deciphered some of the more elusive instructions encoded in DNA. Their neural network trained on high-resolution maps of protein-DNA interactions uncovers subtle DNA sequence patterns throughout the genome, thus providing a deeper understanding of how these sequences are organized to regulate genes.
The ~$1.5MM euro contribution to be made over five years will support the training of scientific talent in the fields of data science and machine learning. Excellent young researchers with doctoral plans as well as students can apply at TUM's MDSI.