Provided by The Next Web China this week announced an AI-powered unmanned police station will open in one of its capitol cities, proving once again that no other country quite embraces artificial intelligence like it does. The station appears to be designed with driver and vehicle related matters in mind, making it more like a Department of Motor Vehicles (DMV) than a cop shop. It will provide driver's examinations via simulator, registration services, and feature advanced face-scanning technology developed by Tencent, according to a report from Chinese financial paper Caijing Neican. Setting aside the myriad of law enforcement related implications, there's still plenty to unpack concerning the idea of unmanned government buildings. This station will be open to the public 24/7, and since citizens will presumably be dealing with dedicated hardware there should be far less points of failure than web-based solutions tend to have.

Collecting labeled data is costly and thus a critical bottleneck in real-world classification tasks. To mitigate this problem, we propose a novel setting, namely learning from complementary labels for multi-class classification. A complementary label specifies a class that a pattern does not belong to. Collecting complementary labels would be less laborious than collecting ordinary labels, since users do not have to carefully choose the correct class from a long list of candidate classes. However, complementary labels are less informative than ordinary labels and thus a suitable approach is needed to better learn from them. In this paper, we show that an unbiased estimator to the classification risk can be obtained only from complementarily labeled data, if a loss function satisfies a particular symmetric condition. We derive estimation error bounds for the proposed method and prove that the optimal parametric convergence rate is achieved. We further show that learning from complementary labels can be easily combined with learning from ordinary labels (i.e., ordinary supervised learning), providing a highly practical implementation of the proposed method. Finally, we experimentally demonstrate the usefulness of the proposed methods.

In March 2016, Google's Alphago artificial intelligence (AI) program stunned the world by beating the human world champion Go player in front of 200 million spectators. This was living proof of the potential in AI technology and the level of maturity reached by neural network and deep learning technologies. Those astounded by the success included quite a few engineers and managers who have been leading the AI revolution in the world in recent years. One of these was Intel VP Naveen Rao, general manager of the company's Artificial Intelligence Products Group, which was founded last year. "When I studied at college in the 1990s, we regarded artificial intelligence as'creative work'," Rao relates.

JERUSALEM – The Israeli military says it has shot down an unmanned aircraft that attempted to infiltrate Israeli airspace from neighboring Syria. In a statement, the military said it intercepted the drone Saturday above the Golan Heights using a Patriot missile. It was not immediately clear if the drone had reached the Israeli-controlled side of the Golan when it was shot down. It also was not known who was operating the drone. In September, Israel also shot down an Iranian-made drone sent by the Lebanese militant group Hezbollah in the same area. Both Iranian and Hezbollah forces have been backing Syrian President Bashar Assad in the Syrian civil war.

True, everyone born before Aug. 4, 1900, has proved mortal (the world's oldest-known living person, a Japanese woman named Nabi Tajima, was born on that date). But the past is only an imperfect guide to the future, as the effervescent present is ceaselessly teaching us. But our children, our grandchildren -- or if not them, theirs -- may, conceivably, be the beneficiaries of the greatest revolution ever: the conquest of death. Immortality is an ancient dream. A Chinese king of the third century B.C. dispatched a sage, Xu Fu by name, on a quest for the elixir of life.

For Peter Cao, who has dedicated 16 years of his career to teaching chemistry in a high school in central China's Anhui province, in every teacher there lives a "doctor". He spends two to three hours a day grading assignments, a process the 38-year-old describes as "diagnosing". "By reviewing the homework of my pupils, I can have an overall picture about their understanding of the lessons I give," Cao said, adding that this "diagnosis" helps him draw up a teaching plan for the following day. But if the Chinese online education start-up Master Learner has its way, Cao and his 14 million fellow teachers in China will be able to hand this time-consuming review process to a "super teacher", a powerful "brain" capable of answering nearly 500 million of the most tested questions in China's middle schools as well as scoring high points in each Gaokao test, China's life-changing college entrance exam, for the past 30 years. If the super teacher sounds too smart to be human, that is because it is not.

In September, Israel also shot down an Iranian-made drone sent by the Lebanese militant group Hezbollah in the same area. Both Iranian and Hezbollah forces have been backing Syrian President Bashar Assad in the Syrian civil war.

In late October, Saudi Arabia announced that Sophia, a humanoid developed by Hanson Robotics, is the first-ever robot citizen. Sophia recently spoke at the Future Investment Initiative, held in Riyadh, about its desire to live peacefully among humans. The comments belied Sophia's past remarks about wishing to "destroy humans." Prestigious as the title may be, Hanson Robotics has developed several humanoids in addition to Sophia. Here's what else makes up Sophia's robot family.

The technology and development will not be limited - Europe can regulate and protect but we need to stay ahead of the game with #AI #FacialRecognition.

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