Researchers from the University of Pennsylvania have come up with an interesting approach to machine learning that could help to address the field's ever-growing power demands: taking the processor out of the picture and working directly on an analog network of resistors."Standard deep learning algorithms require differentiating large non-linear networks, a process that is slow and power-hungry," the researchers explain. "Electronic learning metamaterials offer potentially fast, efficient, and f...