Image recognition is a hot area of research using artificial intelligence, and now IBM offers an online demo to let anyone test out the capabilities offered by its Watson cognitive computing system. Six sample photos are provided for illustration, or you can upload your own and ask Watson to analyze them. Either way, the cognitive system will produce a series of "classifiers" offering descriptions of the image's contents along with confidence scores for each of them. You can also create custom classifiers tailored for specific purposes. Watson gained worldwide fame when it won on the quiz show Jeopardy back in 2011, and IBM has been developing commercial applications ever since.

The Supreme Court is staying out of a dispute between game maker Electronic Arts Inc. and former National Football League players who accuse the company of using their likenesses in the popular Madden NFL video game series without approval. The justices on Monday let stand an appeals court ruling that said the company's use of the player's likenesses was not protected as "incidental use" under the First Amendment. The former players sued Electronic Arts in 2010 over the company's use of "historic teams" and players in Madden NFL games from 2001 to 2009. The 9th U.S. Circuit Court of Appeals ruled in 2012 that the player lawsuit could proceed. Electronic Arts previously settled a similar case brought by college football and basketball players for 40 million.

Apple product events typically spark anticipation among tech bloggers and the company's hard-core fans. Monday's event, though, is drawing less excitement than some previous product launches. Apple is expected to announce a smaller, 4-inch iPhone and a smaller version of the iPad Pro tablet. But there's been no hint of any blockbuster developments, such as last year's highly anticipated Apple Watch debut. Despite speculation that Apple is working on a self-driving car or some new virtual-reality device, those are likely years away.

Save the "Star Wars" franchise? Everyone's favorite "Star Wars" actress, Daisy Ridley, told The Hollywood Reporter at this weekend's Empire Awards that there "have been conversations" about her wielding the storied video game heroine's dual pistols in an upcoming reboot. Conversations, however, don't mean that Ridley's casting is a done deal, as the 23-year-old actress has yet to receive an official offer. "I'm waiting for someone to say'I want you, let's do it,'" she said, explaining that the project doesn't have a script yet. But Ridley is committed to the role, even with her busy "Star Wars" schedule -- she is currently filming the eighth installment in the sci-fi epic. If the opportunity presented itself, Ridley would be happy to make time for "Tomb Raider," telling THR that "I'm trying to fill up my calendar."

Domino's latest "deliveryman" stands three feet tall and doesn't need to be tipped. It has ferried pizzas in Brisbane at a top speed of 12 mph, and the company's Australian master franchise said it's excited for what could come next. "We have a relentless passion to push the boundaries of what's possible with pizza delivery," said Michael Gillespie, chief digital officer for Domino's in Australia. "As we get further, it's not hard to believe that we might have a store with a couple of [robots] that are doing deliveries." Domino's has started using a robotic cart named DRU, which stands for Domino's Robotic Unit, to deliver its offerings.

China has been the power engine of global economic growth since the Chinese Communist Party embraced free market economics some 30 years ago. What leveraged China's momentous success has been its people, or - to be more precise - the enormous number of cheap labour that migrated from the rural areas to the cities, some of which had to be built from scratch in order to accommodate millions of new residents. Low wages, foreign investment and open markets made China the manufacturing powerhouse of the world. But things have changed since those halcyon days of easy growth. Labour supply in China has become increasingly scarcer, a fact reflected in the almost exponential rise of wages since the beginning of the 2000s.

Computers are getting pretty good at predicting the future. In many cases they do it better than people. That's why Amazon uses them to figure out what you're likely to buy, how Netflix knows what you might want to watch, the way meteorologists come up with accurate 10-day forecasts. Now a team of scientists has demonstrated that a computer can outperform human judges in predicting who will commit a violent crime. In a paper published last month, they described how they built a system that started with people already arrested for domestic violence, then figured out which of them would be most likely to commit the same crime again.

While not widely understood, machine learning has been easily accessible since Google Prediction API was released in 2011. With many applications in a wide variety of fields, this tutorial by Alex Casalboni on the Cloud Academy blog is a useful place to start learning how to build a machine learning model using Google Prediction API. The API offers a RESTful interface as a means to train a machine learning model, and is considered a "black box" due to the restricted access users have to internal configuration. This leaves users with only the "classification" vs "regression" configuration, or the applying of a PMML (Predictive Model Markup Language) file with weighting parameters for categorical models. This tutorial begins with some brief definitions before beginning on how to upload your dataset to Google Cloud Storage, as required by Google Prediction API.

Deep in the heart of Imperial College, London, a computer is learning how to play Pac-Man. Like many humans, it struggles to get the hang of the classic 1980s video game at first. With time though, experience helps it decide which manoeuvres will allow it to evade the clutches of a relentless gang of animated ghosts. This is just one of dozens of artificial intelligence (AI) projects slowly transforming the UK into the global hub for a technology that elicits fascination and fear in equal measure. The point of teaching a computer to master Pac-Man is to help it "think" and learn like a human.

Congratulations are in order for the folks at Google Deepmind who have mastered Go. However, some of the discussion around this seems like giddy overstatement. Wired says Machines have conquered the last games and Slashdot says We know now that we don't need any big new breakthroughs to get to true AI. The truth is nowhere close. For Go itself, it's been well-known for a decade that Monte Carlo tree search (i.e.