French inventor Frank Zapata grabbed headlines around the world this summer when he flew his hoverboard across the English channel from Pas de Calais, France, to the famous white cliffs of Dover. But Bay Area commuters may soon do Zapata one better by skimming above San Francisco Bay on autonomous, single-passenger drones being developed by a Peninsula start-up company with ties to Google. The automated drones are electrically powered, capable of vertical takeoff and landing, and would fly 10 feet above the water at 20 mph along a pre-determined flight path not subject to passenger controls. The drones' rotors are able to shift from vertical to horizontal alignment for efficient forward movement after takeoff. The company behind all this, three-year-old Kitty Hawk Corp., has personal financial backing from Google founder Larry Page, now CEO of Google's parent, Alphabet, who has long been interested in autonomous forms of transportation.
The capability and spread of such systems have reached the point where they are beginning to touch much of everyday life. However, regulators grapple with how to deal with autonomous systems, for example how could we certify an Unmanned Aerial System for autonomous use in civilian airspace? We here analyse what is needed in order to provide verified reliable behaviour of an autonomous system, analyse what can be done as the state-of-the-art in automated verification, and propose a roadmap towards developing regulatory guidelines, including articulating challenges to researchers, to engineers, and to regulators. Case studies in seven distinct domains illustrate the article. Keywords: autonomous systems; certification; verification; Artificial Intelligence 1 Introduction Since the dawn of human history, humans have designed, implemented and adopted tools to make it easier to perform tasks, often improving efficiency, safety, or security.
Rolnick, David, Donti, Priya L., Kaack, Lynn H., Kochanski, Kelly, Lacoste, Alexandre, Sankaran, Kris, Ross, Andrew Slavin, Milojevic-Dupont, Nikola, Jaques, Natasha, Waldman-Brown, Anna, Luccioni, Alexandra, Maharaj, Tegan, Sherwin, Evan D., Mukkavilli, S. Karthik, Kording, Konrad P., Gomes, Carla, Ng, Andrew Y., Hassabis, Demis, Platt, John C., Creutzig, Felix, Chayes, Jennifer, Bengio, Yoshua
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.
A scale model of a flying drone-car mashup has been unveiled which could provide a preview of future taxis. The'Pop.Up Next' prototype drone was driven and hovered across an Amsterdam exhibition hall. It is made in partnership with aviation giant Airbus, automaker Audi and Italdesign design house. The revolutionary design is is made up of three separate modules - a chassis with wheels, a two-seat capsule for passengers and a four-rotor drone. A scale model of a flying drone-car mashup has been unveiled which could provide a preview of future taxis.