Missing teen's remains found in Lerderderg State Park Is the Australian Defence Force the next big customer for unmanned aerial vehicles? Australia has warned the world that artificially intelligent killer robots "may be closer than many of us had imagined" and nations need to work harder to tackle the future threat they may pose. At a United Nations meeting on "lethal autonomous weapons systems" in Geneva, Switzerland, the Australian delegation on Monday night called on the world to come up with agreed rules about how to handle the rapid pace in technology in military artificial intelligence. The Terminator movies imagined a future where killer robots posed a threat to humanity: some warn that the threat is real. "The development of fully autonomous systems able to conduct military targeting operations which kill and injure combatants or civilians may be closer than many of us had imagined," the delegation's statement said.

The last place you want to learn you have heart failure is where it often winds up being diagnosed: in the emergency room. Researchers analyzing electronic health records are using artificial intelligence and GPUs to get ahead of this curve. They've shown they can predict heart failure as much as nine months before doctors can now deliver the diagnosis. The stakes could hardly be higher. Each year, about 23 million people worldwide, including nearly 6 million Americans, have heart failure, according to the American Heart Association.

Some of the world's most prominent scientists and technology entrepreneurs including physicist Stephen Hawking, Tesla CEO Elon Musk and Apple co-founder Steve Wozniak signed a letter warning about the dangers of autonomous weapons, which they said would be technologically feasible "within years, not decades". Australia has warned the world that artificially intelligent killer robots "may be closer than many of us had imagined" and nations need to work harder to tackle the future threat they may pose. At a United Nations meeting on "lethal autonomous weapons systems" in Geneva, Switzerland, the Australian delegation on Monday night called on the world to come up with agreed rules about how to handle the rapid pace in technology in military artificial intelligence. "The development of fully autonomous systems able to conduct military targeting operations which kill and injure combatants or civilians may be closer than many of us had imagined," the delegation's statement said. "It is an appropriate time to consider the risks of such weapons systems and to make sure we understand fully what might constitute misuse as well as legitimate use of emerging technologies."

HireVue's Chief Data Honcho, Ben Taylor, our Amazing Director of Engineering, Dave Smith, and our Talented Talent Man, John Grotegut had the opportunity to visit Utah State University this tonight and meet with their Computer Engineering students. And they brought a whole lot of pizza with them. If you are curious about the answers to these questions, or are interested in learning more, please reach out to the @VueNation team on social media.

"The robots are coming" is not something Paul Revere said during the American Revolution, but it is certainly something many people have uttered over the years. So have we finally reached the tipping point where artificial intelligence and robots will begin to take over human jobs en masse? Perhaps not, but we are closer to the time when they will be even more essential assets and presences in the workforce, explains Martin Ford, the author of the book "Rise of the Robots." I caught up with Ford at The Economist magazine's Innovation Forum event, which was held earlier this month. He pointed out that artificial intelligence is making its way into sectors that were once manned by only man, including the legal profession, where computer systems such as Watson could muscle in on human territory to provide legal counsel, and even journalism where stories are being written without direct human input about some articles.

Facebook seems to be leaving Google in the dust in certain areas where the search giant should have dominated. Beyond giving Facebook bragging rights, the company's aggressive development of some of these new technologies has the potential to shake up the business landscape. Take Facebook's recent, dramatic push into video live-streaming. Sure, YouTube has broadcasting capabilities. Individuals can do it through its gaming app and the company has live-streamed huge events, like the President's State of the Union address and several debates.

This paper explores the problem of managing movements of aircraft along the surface of busy airports. Airport surface management is a complex logistics problem involving the coordination of humans and machines. The work described here arose from the idea that autonomous towing vehicles for taxiing aircraft could offer a solution to the 'capacity problem' for busy airports, the problem of getting more efficient use of existing surface area to meet increasing demand. Supporting autonomous surface operations requires continuous planning, scheduling and monitoring of operations, as well as systems for optimizing complex human-machine interaction. We identify a set of computational subproblems of the surface management problem that would benefit from recent advances in multi-agent planning and scheduling and probabilistic predictive modeling, and discuss preliminary work at integrating these components into a prototype of a surface management system.

Planning with hybrid domains modelled in PDDL+ has been gaining research interest in the Automated Planning community in recent years. Hybrid domain models capture a more accurate representation of real world problems that involve continuous processes than is possible using discrete systems. However, solving problems represented as PDDL+ domains is very challenging due to the construction of complex system dynamics, including non-linear processes and events. In this paper we introduce DiNo, a new planner capable of tackling complex problems with non-linear system dynamics governing the continuous evolution of states. DiNo is based on the discretise-and-validate approach and uses the novel Staged Relaxed Planning Graph+ (SRPG+) heuristic, which is introduced in this paper. Although several planners have been developed to work with subsets of PDDL+ features, or restricted forms of processes, DiNo is currently the only heuristic planner capable of handling non-linear system dynamics combined with the full PDDL+ feature set.

In a complex adaptive system, diverse agents perform various actions without adherence to a predefined structure. The achievement of joint actions will be a result of continual interactions among them that shape a dynamic network. Agents may form an ad hoc organization based on dynamic network of interactions for the purpose of achieving a long term objective, which is called a Network Organization (NO). For the dominant influences of the network substrate in an NO, multiple effects of it have an impact on the NO behaviors and directions. We envisioned several dimensions of such effects to be synergy, social capital, externality, influence, etc. The focus of this paper is on measuring synergy as one of those possible network effects. Synergy describes different modalities of compatibility among agents when performing a set of coherent and correspondingly different actions. When agents are under no structural obligation to contribute, synergy is quantified through multiple forms of serendipitous agent chosen benevolence among them. The approach of this paper is to measure four types of benevolence and the pursuant synergies from them stemming from agent interactions. We exemplify this approach using a case study of a multiplayer online game.

As the rapid development of e-commerce, reputation model has been proposed to help customers make effective purchase decisions. However, most of reputation models focus only on the overall ratings of products without considering reviews which provided by customers. We believe that textual reviews provided by buyers can express their real opinions more honestly. As so, in this paper, based on word2vector model, we propose a Textual Reputation Model (TRM) to obtain useful information from reviews, and evaluate the trustworthiness of objective product. Experimental results on real data demonstrate the effectiveness of our approach in capturing reputation information from reviews.