Researchers have developed a deep learning algorithm capable of successfully predicting what will happen in a video clip based on one still clip from the footage. The Computer Science and Artificial Intelligence Laboratory at Massachusetts Institute of Technology (MIT) made the breakthrough in predictive vision by training an algorithm using 600 hundred hours of YouTube videos. By searching for patterns and recognizable objects like hands and faces, the algorithm was able to predict human interactions such as hugging, kissing, shaking hands or high fiving. The research is set to be presented this week at the International Conference on Computer Vision and Pattern Recognition (CVPR). "Humans automatically learn to anticipate actions through experience, which is what made us interested in trying to imbue computers with the same sort of common sense," said MIT PhD student and the paper's first author Carl Vondrick.

In the coming decade, as X Prize strives to achieve its impact mission through incentive competitions and crowd-sourcing, we see tremendous opportunity in this emerging generation of problem solvers to use AI to solve humanitys grandest challenges," X Prize CEO Marcus Shingles said in a statement. "The IBM Watson AI X Prize is intended to promote and progress the notion of AI for impact among the global bold innovator crowd, both the established community of practitioners, as well as encourage newcomers to experiment and ultimately demonstrate how AI can be used as a tool for good.

The machine was, and still is, my constant partner. I need her in order to translate the creative thoughts in my head into tangible ideas I can share with the world. Transitioning to design from a modern dance career in my twenties, I never thought a machine would be my accomplice for innovation. Machines have rapidly developed intelligence in this generation and their capabilities are changing the products we design. The process in which they are designed will also need to evolve.

Streaming service Sling TV is now available on Apple TV's fourth-generation set-top box. Apple is buffing up its Apple TV set-top box in hopes of making it a more popular choice for cord cutters. The purveyor of iPhones and iPads is playing catch-up in the Net video streaming device competition. But some Apple TV advances announced last week could give it a boost. Sling just added Comedy Central to that basic package.

Every time our customers visit the Zalando Fashion Store, we want to serve them personalised product recommendations, depending on their preferences. Others love ankle boots, while some prefer sneakers. Whilst some follow the latest trends and others prefer the classic style. In a nutshell, the task of a personalised recommender system involves building user profiles from their behavior and predicting which product recommendations will be most relevant to such profiles. Intuitively, the user profile specifies properties such as how much interest the customer has in sportswear, or whether flat heels are preferred over high heel shoes.

First let's create a very simple dataset. We have some class labels y. 500 are from class 0, and 500 are from class 1, and they are randomly ordered. And we have 100 variables x that we want to use to predict y. 99 of them are just random noise, but one of them is highly correlated with the class label. Now let's say we want to classify the points using linear discriminant analysis. The final 1 in the output indicates that variable 100 is, as expected, the best predictor of y among the variables in x.

Twitter has bought London-based AI startup Magic Pony Technology for a reported 150m ( 102m) as the company moves to strengthen its position in image-sharing, video and live video. Founded in 2014, Magic Pony uses machine learning to build improved systems for visual processing. The company said it was excited to be joining forces with Twitter "to improve the visual experiences that are delivered across their apps". Twitter's chief executive, Jack Dorsey, said Magic Pony's technology would be used to enhance live and video offerings and "opens up a whole lot of exciting creative possibilities for Twitter". Dorsey said the team included "11 PhDs with expertise across computer vision, machine learning, high-performance computing and computational neuroscience".

AS DOOMSDAY SCENARIOS go, it does not sound terribly frightening. The "paperclip maximiser" is a thought experiment proposed by Nick Bostrom, a philosopher at Oxford University. Imagine an artificial intelligence, he says, which decides to amass as many paperclips as possible. It devotes all its energy to acquiring paperclips, and to improving itself so that it can get paperclips in new ways, while resisting any attempt to divert it from this goal. Eventually it "starts transforming first all of Earth and then increasing portions of space into paperclip manufacturing facilities". This apparently silly scenario is intended to make the serious point that AIs need not have human-like motives or psyches.

In his quest to transform the way the Pentagon wages war, Defense Secretary Ashton Carter has turned to Silicon Valley, hoping its experimental culture, innovation and sense of urgency would rub off on the rigid bureaucracy he runs. Carter has made several trips to the region and appointed Eric Schmidt, the chairman of Google's parent company to an advisory board. And recently he sat down at the Pentagon with Elon Musk to see what suggestions the billionaire founder of Tesla and SpaceX might have to make the nation's military more efficient and daring. "Having an incentive structure that rewards innovation is extremely important," he said in an interview after the meeting. Whatever you reward will happen." The Pentagon finds itself in a new arms race, struggling to keep pace with forms of combat that are fought with bytes as well as bullets. The technological advancements disrupting established business sectors are now shaking up the world of war - where robots, swarming drones and ...

IBM Watson joined forces with the X Prize Foundation to launch an open 5 million challenge to build an artificial intelligence app for healthcare that could also be used in other industries, including education, energy, the environment, global development or even exploration. "In the coming decade, as X Prize strives to achieve its impact mission through incentive competitions and crowd-sourcing, we see tremendous opportunity in this emerging generation of problem solvers to use AI to solve humanity's grandest challenges," X Prize CEO Marcus Shingles said in a statement. "The IBM Watson AI X Prize is intended to promote and progress the notion of'AI for impact' among the global bold innovator crowd, both the established community of practitioners, as well as encourage newcomers to experiment and ultimately demonstrate how AI can be used as a tool for good." Unlike previous X Prizes, including the Tricorder X Prize, in which companies are vying to develop a handheld medical scanner, and the original Ansari X Prize for suborbital flight, this contest allows the participants to define their own goals and to focus on solving different problems. "Rather than set a single, universal goal for all teams, this competition allows teams to define their own challenges and demonstrate their solutions, encouraging myriad problem-solving approaches," Amir Banifatemi, X Prize lead for the IBM Watson AI competition, said in a statement.