Cracking the Code for materials that can learn
While machine learning often conjures up images of algorithms and digital systems, researchers are demonstrating that the potential for learning extends far beyond the digital realm. A team at the University of Michigan (U-M) has developed a mathematical framework showing how physical materials can "learn" and perform computational tasks without electronic or human intervention. Shuaifeng