A research team at Sandia National Laboratories has successfully used machine learning—computer algorithms that improve themselves by learning patterns in data—to complete cumbersome materials science calculations more than 40,000 times faster than normal, according to a Sandia press release.
Their results, published in the January 4 issue of a journal called npj Computational Materials, could herald a dramatic acceleration in the creation of new technologies for optics, aerospace, energy storage and potentially medicine while simultaneously saving laboratories money on computing costs, according to the press release.