The service, which is temporarily free, is still in its testing phase and only available in the downtown Las Vegas area. The remotely driven cars will also have a safety driver inside, in case any problems arise. The electric vehicles are controlled through six cameras that stream video directly to the remote pilots at Halo. The car's office, and the pilots' workspace, looks similar to an arcade game with a steering wheel, pedals and large computer screen. Car founder and CEO Anand Nandakumar says the Halo.

The findings are an important step toward building more energy-efficient computing systems that also are capable of learning and adaptation in the real world. They were published last week in a paper in the journal Nature Communications. The researchers, Bipin Rajendran, an associate professor of electrical and computer engineering, and S. R. Nandakumar, a graduate student in electrical engineering, have been developing brain-inspired computing systems that could be used for a wide range of big data applications. Over the past few years, deep learning algorithms have proven to be highly successful in solving complex cognitive tasks such as controlling self-driving cars and language understanding. At the heart of these algorithms are artificial neural networks -- mathematical models of the neurons and synapses of the brain -- that are fed huge amounts of data so that the synaptic strengths are autonomously adjusted to learn the intrinsic features and hidden correlations in these data streams.