Neural networks are some of the most important tools in artificial intelligence (AI): they mimic the operation of the human brain and can reliably recognize texts, language and images, to name but a few. So far, they run on traditional processors in the form of adaptive software, but experts are working on an alternative concept, the 'neuromorphic computer.' In this case, the brain's switching points—the neurons—are not simulated by software but reconstructed in hardware components. A team of researchers at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) has now demonstrated a new approach to such hardware—targeted magnetic waves that are generated and divided in micrometer-sized wafers. Looking to the future, this could mean that optimization tasks and pattern recognition could be completed faster and more energy efficiently. The researchers have presented their results in the journal Physical Review Letters.