news 2021

A new algorithm has been designed to help discover previously unknown material compounds. It was developed by a team from Martin Luther University Halle-Wittenberg (MLU), Friedrich Schiller University Jena and Lund University in Sweden. The researchers designed a form of artificial intelligence (AI) based on machine learning that can perform complex calculations within a very short space of time.

While the number of qubits and the stability of quantum states are still limiting current quantum computing devices, there are questions where these processors are already able to leverage their enormous computing power. In collaboration with the Google Quantum AI team scientists from the Technical University of Munich (TUM) and the University of Nottingham used a quantum processor to simulate the ground state of a so-called toric code Hamiltonian - an archetypical model system in modern condensed matter physics, which was originally proposed in the context of quantum error correction.

Bioinformatics team develops method that enables fast and confident identification of small molecules Life More than a third of all medicines available today are based on active substances from nature and a research team from the University of Jena has developed a procedure to identify small active substance molecules much more quickly and easily.

New software helps determine the movements of large wild animals thereby minimising conflicts with people. The software is simpler than measurements obtained using radio transmitters and can be used where conventional methods fail. An international team led by the German Centre for Integrative Biodiversity Research (iDiv), the Friedrich Schiller University Jena, Aarhus University and the University of Oxford has published a description of the new software in the journal Methods in Ecology and Evolution.

Researchers from Heidelberg and Bern develop a new training approach for spiking neural networks Developing a machine that processes information as efficiently as the human brain has been a long-standing research goal towards true artificial intelligence. An interdisciplinary research team at Heidelberg University and the University of Bern (Switzerland) led by Dr Mihai Petrovici is tackling this problem with the help of biologically-inspired artificial neural networks.

More than a third of all medicines available today are based on active substances from nature and a research team from the University of Jena has developed a procedure to identify small active substance molecules much more quickly and easily. Secondary natural substances that occur in numerous plants, bacteria and fungi can be anti-inflammatory, can ward off pathogens or even prevent the growth of cancer cells.

New AI algorithm as a tool for economists Using a new machine learning algorithm, a team at the Technical University of Munich (TUM) has succeeded in analyzing complex markets and their equilibrium strategies. Until now, such analyses were limited to very simple auction markets. The new numerical method opens up new possibilities for economic theory and new applications as in wireless spectrum auctions, among others.

Chip with secure encryption will help in fight against hackers A team at the Technical University of Munich (TUM) has designed and commissioned the production of a computer chip that implements post-quantum cryptography very efficiently. Such chips could provide protection against future hacker attacks using quantum computers.

First comprehensive measurements of sea level changes in the Baltic Sea and the North Sea Researchers working under the leadership of the Technical University of Munich (TUM) have conducted the first precise and comprehensive measurements of sea level rises in the Baltic Sea and the North Sea. A new method now makes it possible to determine sea level changes with millimeter accuracy even in coastal areas and in case of sea ice coverage.

Cancer, Alzheimer's, diabetes or cardiovascular diseases are what are known as non-communicable diseases, which are responsible for the majority of deaths worldwide - in Germany, an estimated 91 percent of all deaths are the result of these diseases, and it is a rising trend. Epidemiologists have been studying the development and distribution of these epidemiological diseases, as well as the measures to combat them and what their social consequences are.

Fewer requirements let artificial intelligence discover new materials 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).

Date: April 26, 2021, No. DFG approves new priority program coordinated by the University of Stuttgart Design Assistants in Mechanics and Dynamics are the topic of a new priority program (PP) of the German Research Foundation (DFG) that aims to bring more artificial intelligence (AI) into the design process of technical systems.

New Heidelberg approach: analysing movement patterns through machine learning The way we move says a lot about the state of our brain. While normal motor behaviour points to a healthy brain function, deviations can indicate impairments owing to neurological diseases. The observation and evaluation of movement patterns is therefore part of basic research, and is likewise one of the most important instruments for non-invasive diagnostics in clinical applications.

Deep learning algorithms reveal the rules of gene regulation 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.

Artificial intelligence (AI) is seen as a key technology with fields of application in a wide variety of areas in society. However, researching, developing and, in particular, using AI systems presents enormous challenges for the computing power and storage capacity needed to process large data volumes.

Spatial and temporal distribution of primordial germ cells (stained in red) in zebrafish embryos. Normally, with the help of an attractant produced in the environment, the cells migrate in a targeted and coordinated manner through the developing embryo and reach the regions where the sex organs are formed (left).

In the digital age, data traffic is growing at an exponential rate. The demands on computing power for applications in artificial intelligence such as pattern and speech recognition in particular, or for self-driving vehicles, often exceeds the capacities of conventional computer processors. Working together with an international team, researchers at the University of Münster are developing new approaches and process architectures which can cope with these tasks extremely efficient.