U.S. Army leaders want future armored vehicles to make decisions instantly about terrain navigation, identifying targets, and incoming enemy fire. In fact, the military wants this to happen in a matter of seconds and all without every nuance of control by humans. It is a known and often discussed concept, rapidly gaining traction as new technologies continue to emerge at rocket speed. The kinds of initiatives are now taking on a newer, more advanced character as artificial intelligence (AI)-enabled sensors, computers and targeting systems increasingly process and organize information more quickly, enabling ever-advancing measures of autonomy. Commercial applications of autonomy, such as those for driverless cars, have been advancing for quite some time, however Army developers have been taking on something quite different. Combat vehicles need autonomy not just for linear navigation but rather for an integrated series of complex, fast-changing variables such as incoming attacks, rocky terrain, air integration, and means to optimize methods of attack.

A team from the University of Virginia School of Medicine is leveraging the power of quantum computing to gain better insight into genetic diseases with machine learning. Although quantum computers are still in their infancy, the researchers noted that when they do advance, they could offer computing power on a scale that's unimaginable on traditional computers. "We developed and implemented a genetic sample classification algorithm that is fundamental to the field of machine learning on a quantum computer in a very natural way using the inherent strengths of quantum computers," said Stefan Bekiranov, PhD. "This is certainly the first published quantum computer study funded by the National Institute of Mental Health and may be the first study using a so-called universal quantum computer funded by the National Institutes of Health." Quantum computers can consider significantly more possibilities than traditional computer programs.