TUM professor develops energy-saving AI chip
The basic idea is simple: unlike previous chips, where only calculations were carried out on transistors, they are now the location of data storage as well. That saves time and energy. “As a result, the performance of the chips is also boosted,” says Hussam Amrouch, a professor of AI processor design at the Technical University of Munich (TUM). The transistors on which he performs calculations and stores data measure just 28 nanometers, with millions of them placed on each of the new AI chips. The chips of the future will have to be faster and more efficient than earlier ones. Consequently, ...













