The Nevada Institute for Autonomous Systems (NIAS), in partnership with NASA UTM, conducted multiple drone tests at the Nevada UAS test site at the Reno-Stead Airport. The technology capability level 3 (TCL 3) focused on airspace management technologies seeking to enable the safe integration of UAS into the National Airspace Systems. The research areas during the testing covered UAS ground control interfacing to locally manage operations, communication, navigation, surveillance, human factors, data exchange, network solutions and BVLOS architecture. "The state of Nevada will be known for its significant contribution in this journey through its pioneering work with the FAA, NASA and private partners like ourselves, facilitating safe and effective integration into national airspace," says Mike Richards, President and CEO of Drone America. NASA, FAA and its partners, and NIAS are working on the innovations and the industry growth while respecting aviation safety traditions.
Aeronautics researchers at MIT have developed a manned-to-unmanned aircraft guidance system that allows a pilot in one plane to guide another unmanned airplane by speaking commands in English. In a flight test, the pilotless vehicle, called a UAV (unmanned aerial vehicle), responded to sudden changes in plan and avoided unexpected threats en route to its destination, in real time. "The system allows the pilot to interface with the UAV at a high level--not just'turn right, turn left' but'fly to this region and perform this task,'" said Mario Valenti, a flight controls engineer for Boeing who is on leave to pursue a Ph.D. in electrical engineering and computer science at MIT. "The pilot essentially treats the UAV as a wingman," said Valenti, comparing the UAV to a companion pilot in a fighter-plane squadron. Tom Schouwenaars, a Ph.D. candidate in aeronautics and astronautics, and Valenti are principal researchers on the guidance system, which is part of the capstone demonstration of the Software Enabled Control (SEC) program. Professors Eric Feron and Jonathan How of the Department of Aeronautics and Astronautics (aero/astro) are among the principal investigators on the SEC program.
When it comes to artificial intelligence and jobs, the prognostications are grim. The conventional wisdom is that A.I. might soon put millions of people out of work -- that it stands poised to do to clerical and white collar workers over the next two decades what mechanization did to factory workers over the past two. And that is to say nothing of the truckers and taxi drivers who will find themselves unemployed or underemployed as self-driving cars take over our roads. But it's time we start thinking about A.I.'s potential benefits for society as well as its drawbacks. The big-data and A.I. revolutions could also help fight poverty and promote economic stability.
While this reality has become more tangible in recent years through consumer technology, such as Amazon's Alexa or Apple's Siri, the applications of AI software are already widespread, ranging from credit card fraud detection at VISA to payload scheduling operations at NASA to insider trading surveillance on the NASDAQ. Broadly defined as the imitation of human cognition by a machine, recent interest in AI has been driven by advances in machine learning, in which computer algorithms learn from data without human direction.1 Most sophisticated processes that involve some form of prediction generated from a large data set use this type of AI, including image recognition, web-search, speech-to-text language processing, and e-commerce product recommendations.2 AI is increasingly incorporated into devices that consumers keep with them at all times, such as smartphones, and powers consumer technologies on the horizon, such as self-driving cars. And there is anticipation that these advances will continue to accelerate: a recent survey of leading AI researchers predicted that, within the next 10 years, AI will outperform humans in transcribing speech, translating languages, and driving a truck.3
The terms "machine learning" and "artificial intelligence" (AI) conjure up feelings that are equal parts fear and fascination. Until recently, the prospect of a piece of software making human-like decisions resided safely in the far-fetched expectations of 1960s-era computer scientists or the plot lines of science fiction novels. Today, however, after decades of unmet expectations, we finally have AI systems that are beginning to influence our lives in tangible ways. Voice recognition systems like Amazon's Echo and Apple's Siri, and once-unimaginable fantasies like self-driving cars, are on the market for consumers, with more exciting life-like systems to come. We have also seen a few early signs of robotic autonomy that makes us feel uneasy, like the Russian robot that learned how to escape the lab!