The latest in the drumbeat of news about artificial intelligence advances came from Seoul, where machine learning algorithms recently beat the world champion in a game of "Go." A Scientific American article explains why this is so impressive, but the implications run far deeper than a match of wits between man and machine. Soon, our workplaces will be transformed by artificial intelligence, with a wide range of processes and roles becoming redefined as some of the tasks comprising them are taken over by machines. Travelers are seeing early signs of this phenomenon. For example, in many US airports these days, instead of standing in a long line to have an immigration officer eyeball us, we scan our passport at a self-service kiosk, answer a few questions, get photographed, and then hand our photo receipt and passport to an agent who quickly verifies that everything checks out.

Rembrandt van Rijn was one of the most influential classical painters, and the world lost his amazing talent when he died nearly four centuries ago. And yet his newest masterpiece was unveiled only yesterday. By scanning and analyzing Rembrandt's works, a computer was able to create a new painting in near-perfect mimicry of Rembrandt's style. It has been named, appropriately, 'The Next Rembrandt'. The Next Rembrandt project began when, in October 2014, the Dutch financial institution ING spoke with J. Walter Thompson Amsterdam advertising agency about creating a project that would show innovation in Dutch art.

We've covered robot writers before, but to date it has never been much of a concern for actual writers. Robots just aren't that good at doing what we do; although Microsoft's'Tay' did prove to be pretty great at going from zero to off-the-rails after dealing with some nasty Twitter comments -- something any writer can relate to. Until now, "robot writers" -- artificial intelligence programs taught to write -- were mainly only good at penning quick stories based on data-heavy reports. Box scores, stock reports, and the like were basically all the programs were capable of doing well. This year's edition of TNW Conference in Amsterdam includes some of the biggest names in tech.

WASHINGTON – A Boeing company manager convicted of child pornography charges in December says he has a right to know what arguments the government used to obtain the warrant from the Foreign Intelligence Surveillance Court. Now, the Los Angeles case is testing a defendant's ability to access information about himself presented to the nation's secretive intelligence court, which issued the warrant that let agents scour his computers. At issue is how the government uses evidence derived through the Foreign Intelligence Surveillance Court and under what circumstances that information should be seen by defendants, particularly when it's repurposed for a routine criminal prosecution that has nothing to do with national security. Gartenlaub and his lawyers say they have a right to know the government's arguments that were used to obtain the warrant, and fight them. "You can't base a search on lies," the 47-year-old said in an interview with The Associated Press.

There are five main schools of thought in machine learning, and each has its own master algorithm – a general-purpose learner that can in principle be applied to any domain. The symbolists have inverse deduction, the connectionists have backpropagation, the evolutionaries have genetic programming, the Bayesians have probabilistic inference, and the analogizers have support vector machines. What we really need, however, is a single algorithm combining the key features of all of them. In this webinar I will summarize the five paradigms and describe my work toward unifying them, including in particular Markov logic networks. I will conclude by speculating on the new applications that a universal learner will enable, and how society will change as a result.

Last week, the robots finally came for that which we humans hold most dear: Our ability to write the Great [insert country or region here] Novel. The Japan News reported, and various American outlets picked up, the news that a short novel co-written by a computer program and homo sapiens had almost won a literary prize. The prize, the Nikkei Hoshi Shinichi Literary Award, accepts entries written by robots, though this was reportedly the first year that any such entries had been submitted. Of several submissions written with AI programs, one entry scored a remarkable victory: It made it through a single round of screening. Okay, so "nearly won," as Bustle put it, might be a slight exaggeration of how well this artificial novelist performed.

A few days before Thanksgiving, George Hotz, a 26-year-old hacker, invites me to his house in San Francisco to check out a project he's been working on. He says it's a self-driving car that he had built in about a month. But when I turn up that morning, in his garage there's a white 2016 Acura ILX outfitted with a laser-based radar (lidar) system on the roof and a camera mounted near the rearview mirror. A tangle of electronics is attached to a wooden board where the glove compartment used to be, a joystick protrudes where you'd usually find a gearshift, and a 21.5-inch screen is attached to the center of the dash. "Tesla only has a 17-inch screen," Hotz says. He's been keeping the project to himself and is dying to show it off. Hotz fires up the vehicle's computer, which runs a version of the Linux operating system, and strings of numbers fill the screen. When he turns the wheel or puts the blinker on, a few numbers change, demonstrating that he's tapped into the Acura's internal controls. After about 20 minutes of this, and sensing my skepticism, Hotz decides there's really only one way to show what his creation can do. "Screw it," he says, turning on the engine. As a scrawny 17-year-old known online as "geohot," Hotz was the first person to hack Apple's iPhone, allowing anyone--well, anyone with a soldering iron and some software smarts--to use the phone on networks other than AT&T's.

I have 34 years as an engineer here at Intel. Almost all but about the last, I don't know, four or five has been mainly on the manufacturing side; all of our silicon manufacturing. Which, in many ways makes you a maker because you're producing a million chips a day. When I look at a 3D printer, I look at it as not only what can I build with it, but I understand exactly how that machine works. I could take it apart and put it back together.

Microsoft CEO Satya Nadella has reshaped the company since taking over two years ago. Windows is still important, but it's no longer the only platform that matters: Microsoft is releasing software and supporting app development for Apple's iOS, Google's Android, and even its old enemy Linux. The infighting and aggressive dismissal of competitors is mostly gone. And Nadella has embraced cloud computing -- the idea that some customers don't want to run their own technology but would prefer to outsource it -- turning Microsoft into the clear No. 2 in the category after Amazon. We caught up with Nadella fresh off the company's Build conference for developers last week in San Francisco and ahead of the new Envision conference for business leaders, which kicks off Monday in New Orleans. Matt Rosoff: There was a lot of talk last week at Build about chatbots and artificial agents and "conversation as a platform." That idea is not new, right? I think I heard Bill Gates talking about it 15 years ago.

Dr. Quoc Viet Le is a research scientist at Google Brain known for his path-breaking work on deep neural networks (DNN). He is especially famous for his Ph.D work in image processing under Andrew Ng, one of the pioneers of the DNN revolution. Le's and Ng's work demonstrated how computers could be used to learn complicated features and patterns in a way similar to how the mammalian brain learns. This revolutionized the interest in DNNs, and got the current giants of the computer industry such as Google, Facebook and Microsoft in a race to incorporate AI techniques into their software. DNNs perform effectively in tasks such as image processing, handwriting recognition and game-playing, and are being explored for solutions to other problems such as self-driving cars, robotics, medical diagnosis and environmental and social problems.