13 professors appointed

Researchers from ETH Zurich, the University of Zurich and Empa have developed a new material for an electronic component that can be used in a wider range of applications than its predecessors. Such components will help create electronic circuits that emulate the human brain and that are more efficient at performing machine-learning tasks. Compared with computers, the human brain is incredibly energy efficient. Scientists are therefore drawing on how the brain and its interconnected neurons function for inspiration in designing innovative computing technologies. They foresee that these brain-inspired computing systems, will be more energy efficient than conventional ones, as well as better at performing machine-learning tasks. Much like neurons, which are responsible for both data storage and data processing in the brain, scientists want to combine storage and processing in a single electronic component type, known as a memristor. Their hope is that this will help to achieve greater efficiency, because moving data between the processor and the storage, as conventional computers do, is the main reason for the high energy consumption in machine learning applications.