Takeo Kanade has spent his career trying to help computers understand what is around them. The robotics pioneer joined the faculty of Carnegie Mellon University (CMU) in 1980, and his computer vision research underscores everything from medical robotics technology to self-driving cars. This year, to his long list of accolades, he adds the Kyoto Prize.

Biologically based computational modeling promises virtual characters capable of face-to-face human interaction. Of all the experiences we have in life, face-to-face interaction fills many of our most meaningful moments. The complex interplay of facial expressions, eye gaze, head movements, and vocalizations in quickly evolving "social interaction loops" has enormous influence on how a situation will unfold. From birth, these interactions are a fundamental element of learning and lay the foundation for successful social and emotional functioning through life. What are the underlying processes from which this most human form of interaction emerges? Will we be able to interact with computers in a face-to-face way that feels natural? This article discusses the unique challenges of realistically simulating the appearance and behavior of the face to create interactive autonomous virtual human models that support naturalistic learning and have the "illusion of life." We describe our recent progress toward this goal with "BabyX," an autonomously animated psycho-biological model of a virtual infant. While we explore drivers of facial behavior, we also expect this foundational approach has the potential for more "human" computer interfaces. We also describe our work on our "Auckland Face Simulator" we are developing to broaden this work beyond infants and give a more realistic face and a greater biological basis to adult conversational agents. Simulating the face has great potential for human-computer interaction (HCI), as it increases the available communication channels between humans and machines in an intuitive, accessible way. But it is also a vehicle with which to explore our own nature.

A full-body virtual autopsy of an ancient Egyptian mummy showed visitors he was likely murdered. By combining visualization techniques with interactive multi-touch tables and intuitive user interfaces, visitors to museums and science centers can conduct self-guided tours of large volumetric image data. In an interactive learning experience, visitors become the explorers of otherwise invisible interiors of unique artifacts and subjects. Here, we take as our starting point the state of the art in scanning technologies, then discuss the latest research on high-quality interactive volume rendering and how it can be tailored to meet the specific demands of public venues. We then describe our approach to the creation of interactive stories and the design principles on which they are based and interaction with domain experts. The article is based on experience from several application domains but uses a 2012 public installation of an ancient mummy at the British Museum as its primary example. We also present the results of an evaluation of the installation showing the utility of the developed solutions. Visitors walk into Gallery 64, the Early Egypt Gallery at the British Museum, eager to see and learn about one of the most famous and oldest mummies in the collection. Known as the Gebelein Man, he was buried in a crouched position in a shallow grave during the late pre-dynastic period at the site of Gebelein in Upper Egypt.

Nations consider using defense systems that can make their own lethal decisions. Most reasonable people can see the benefits of using fully autonomous systems, particularly to help prevent injuries or death, as is the case with advanced driver assistance systems increasingly found in automobiles. When it comes to autonomous systems that are designed to take life rather than preserve it, there is significantly more debate. Currently, the U.S. and other nations do not have any weapons systems that can operate fully autonomously, which is defined in military parlance as selecting, aiming, and firing at a target without a human being "in the loop," or somehow in control of the weapon system. However, a variety of military weapons systems operate semiautonomously, requiring some human control or input to select or choose targets, but relying on pre-programmed algorithms to execute a strike.

In each issue of Communications, we'll publish selected posts or excerpts. Early September saw the 2016 International Computing Education Research (ICER) conference in Melbourne, Australia. The conference was terrific, as is usual for ICER. Two of its papers were meta-papers studying the ICER community itself. They found the community has healthy levels of newcomers and collaboration, and features methodological rigor and strong theoretical foundations.

Changing geopolitical strategy and rapid technological progress are also conspiring to render the term military increasingly incoherent. The United States--the one power to emerge unscathed from World War II and ascendant from the Cold War, and the one power that invests the greatest amount of resources in its battle-hardened military--possesses such overwhelming conventional military superiority over anyone else that potential adversaries instead embrace asymmetric warfare. Thus, Gen. Valery Gerasimov, chief of the General Staff of the Armed Forces of Russia, wrote in a seminal article in 2014 that "the very'rules of war' have changed. The role of nonmilitary means of achieving political and strategic goals has ... in many cases ... exceeded the power of force of weapons in their effectiveness." He also spoke of the need for "the broad use of political, economic, informational, humanitarian, and other nonmilitary measures," with conventional force "resorted to ... primarily for the achievement of final success in the conflict."

The U.S. Internet giant announced that Google Translate has been switched to a new system called Neural Machine Translation (NMT), an end-to-end learning framework that learns from millions of examples. The multilingual system is based on machine learning that provides computers with the ability to learn without being explicitly programmed. Unlike the current translation system that was adopted 10 years ago, the new system considers the entire sentence as one unit. Previous systems translated words and phrases independently within a sentence. Google said the NMT interprets entire sentences, making the translation not only sound much more like a native speaker of the language but more accurate.

"We need everybody to contribute to artificial intelligence," Joaquin Quiñonero Candela, the head of Facebook's Applied Machine Learning (AML) research division, tells Business Insider. Candela is speaking about Facebook itself, sure, as the social network is racing against the other major tech titans to hire as many artificial intelligence and machine learning experts as it can all over the world, even as it makes AI crucial to the way it builds products and does business. But he's also speaking broadly: As Facebook, Google, Microsoft and even Elon Musk make big bets that artificial intelligence is integral to the future of computing, there literally aren't enough experts with the right skills available to hire. "You can't hire enough people who are machine learning experts in the world," says Candela. The company has a new outreach campaign that explains how artificial intelligence is neither scary nor incomprehensible -- it's just another tool in the programmers' toolbelt that can help them build "new experiences," and a set of skills that are going to be incredibly valuable in the future.

Using a combination of artificial intelligence (AI) and brain scanning technology, a team of researchers has developed a novel method that can help remove specific fears from the brain. The new technique that could read and identify a fear memory can pave way of treating patients with conditions such as post-traumatic stress disorder (PTSD) and phobias, the study said. Neuroscientists, from the University of Tokyo, developed'Decoded Neurofeedback' -- which used brain scanning to monitor activity in the brain, and identify complex patterns of activity that resembled a specific fear memory. In the study, the team included 17 healthy volunteers in whom a fear memory was created by administering a brief electric shock when they saw a certain computer image. Using brain scanner, the researchers monitored the volunteers' mental activity and were able to spot signs of that specific fear memory. Using AI algorithms, they also developed a fast and accurate method of reading the fear.

Meet'Baby Boom': The supersonic passenger airliner that can fly Sydney to Los Angeles in just SIX HOURS Subscale XB-1 Supersonic Demonstrator prototype was created by aerospace firm Boom New jet would cut the long haul journey from Sydney to Los Angeles to just six hours in total Jet is nicknamed'Baby Boom' and will be scaled up as a passenger plane for 45 passengers It will reach speeds of up to 2,335 km/h and travel from New York to London in 3.5 hours Jet is nicknamed'Baby Boom' and will be scaled up as a passenger plane for 45 passengers It will reach speeds of up to 2,335 km/h and travel from New York to London in 3.5 hours A sub-scale prototype of a futuristic supersonic passenger airliner could make travel even easier, making flights from Sydney to Los Angeles just six hours in the future. Claimed to be the'world's fastest civil aircraft ever made', the XB-1 Supersonic Demonstrator is due to take off on its first test flight in late 2017 and journey from Sydney to Los Angeles to just six hours in total Millions of devastated Tinder users are forced to spend a... Is Spotify damaging your hard drive? A bug that could harm... Google's self-driving cars can now perform tricky... The smartwatch that NEVER needs charging: Timepiece draws... Millions of devastated Tinder users are forced to spend a... Is Spotify damaging your hard drive? A bug that could harm... Google's self-driving cars can now perform tricky...