Brain inspired machines are better at math than expected

Sandia National Laboratories researchers Brad Theilman and Brad Aimone created an algorithm enabling neuromorphic hardware to solve partial differential equations. The advance, published in Nature Machine Intelligence, demonstrates brain-inspired machines can handle mathematically rigorous problems efficiently, opening a path toward the first neuromorphic supercomputer for energy-efficient computing.