On Wednesday afternoon in the South Korean capital, Seoul, Lee Se-dol, the 33-year-old master of the ancient Asian board game Go, will sit down to defend humanity. On the other side of the table will be his opponent: Alphago, a programme built by Google subsidiary DeepMind which became, in October, the first machine to beat a professional human Go player, the European champion Fan Hui. That match proved that Alphago could hold its own against the best; this one will demonstrate whether "the best" have to relinquish that title entirely. Related: Google throws down the gauntlet. But can anyone beat its computer at Go? Lee, who is regularly ranked among the top three players alive, has been a Go professional for 21 years; Alphago won its first such match less than 21 weeks ago.

DEDHAM, MA--(Marketwired - Jan 28, 2016) - Rage Frameworks, a provider of knowledge-based automation technology and services, today announced major additions to its pioneering RAGE AI platform, adding two new powerful frameworks to its suite. RAGE AI significantly extends the frontier of deep learning and machine intelligence technology from "natural language processing" to "natural language understanding." RAGE AI incorporates deep linguistic parsing and proprietary innovations to understand meaning in context, which makes its solutions completely transparent, auditable and flexible. The platform facilitates unsupervised to supervised learning and contains several innovations to support automated knowledge acquisition including pragmatic knowledge. RAGE AI is not a black box and does not rely on statistical patterns present in training data.

The successful launch of Europe's first ExoMars mission earlier this month set the stage for a much more ambitious second act: arover landing on the Red Planet. But the timing on that mission may not be so certain. On March 14, the European Space Agency (ESA) and its Russian partners launched the ExoMars 2016 mission, an orbiter and lander that serve as a precursor to a full-blown rover slated to launch as early as May 2018. But funding issues and technical delays could push that ambitious follow-up mission to 2020. Rolf de Groot, ESA's coordinator of robotic exploration, told Space.com that it's going to be "very challenging"to have the mission fully prepared for its 2018 launch window but that program managers will know soon whether they'll have to start seriously thinking about a 2020 launch instead.

Just like nuclear physics, machine learning, AI, and data science can be used either for the better of for the worse. You can make either useful energy or terrible bombs using nuclear fission. The same applies to machine learning, and in my example below, it gets even worse than Hiroshima or Nagasaki. Here I am discussing a potential use of machine learning in military operations. The scenario below is entirely hypothetical.

I am from Kashmir, a region prone to earthquakes and floods. When I was 17 years old, in 2005, 70,000 people lost their lives in an earthquake in my hometown. This event compelled me to study engineering and specifically in 2005, start performing earthquake engineering research. Then, in 2014, a combination of two events on different sides of the world inspired the creation of One Concern. In 2014, during a break from graduate school at Stanford, I was visiting my parents in Kashmir when a large flood engulfed the state.

From the street, through Beijing's heavy smog, it can sometimes be hard to make out IBM's Chinese headquarters: a towering office building with a distinctive undulating architectural flourish and a large company logo at the top. But just a short distance away, on the northeast outskirts of the capital, IBM computer scientists are using artificial intelligence to develop what they think will be a way to manage China's notorious and chronic pollution problem more successfully. The team is using complex computer models and machine learning to calculate how pollution will spread across the city. The researchers can now produce pollution forecasts, with a resolution of a kilometer square, up to 10 days in advance. These predictions can also tell the government how it might act to avoid the worst scenarios--for instance, by shutting certain factories, or by reducing the number of cars on the road.

I had thought my job was safe from automation--a computer couldn't possibly replicate the complex creativity of human language in writing or piece together a coherent story. I may have been wrong. Authors beware, because an AI-written novel just made it past the first round of screening for a national literary prize in Japan. The novel this program co-authored is titled, The Day A Computer Writes A Novel. It was entered into a writing contest for the Hoshi Shinichi Literary Award.

Episodic gaming has long been dominated by narrative-driven puzzle adventures, making it hard to imagine the format being used for anything else. Enter Hitman, a pseudo-reboot of the series that simultaneously refines its stealth-focused gameplay while also delivering bite-sized portions of assassination action. A training mission prologue delves into the origins of Agent 47, the genetically enhanced titular hitman, before turning you loose in Paris to dispatch a fashion designer with designs on exposing undercover MI6 agents. Although missions have specific goals, the game excels by offering almost total freedom in how to execute them. Infiltrate a party in disguise and poison a target, or arrange unfortunate accidents to take them out.

Shortly after walking through the front doors of Baidu in Beijing last November, I was surprised to notice that my face had transformed into that of a cheerful- looking little dog. As I chatted with one of Baidu's AI researchers, the version of me shown on his smartphone had sprouted a very realistic-looking wet snout, fluffy ears, and a big pink tongue. The trick was performed on an app called Face You, released by Baidu last Halloween, which lets you add all sorts of spooky effects or animal characteristics to a digital image of your face. Face You makes use of an AI technique called deep learning to automatically identify key points on a person's face, so that software can then position and stretch a virtual mask with amazing accuracy. Deep learning is driving a lot more than just goofy apps at Baidu, though.

TOKYO Advances in artificial intelligence are blurring the line between humans and robots. As robots interact ever more closely with us, new ethical questions are emerging related to issues from violence to sex and privacy. In February, a video uploaded to YouTube by Boston Dynamics, an American robot developer, sparked controversy. Some viewers were apparently shocked by a scene in which a man knocks down a box that was being lifted by a two-legged humanoid robot, developed by the company, and another scene in which the man knocks the robot down from behind with a stick. "Stop bullying robots," one viewer commented below the video.