It's a device that brings to mind the bodyless hand, Thing, from The Addams Family: a human-like robotic hand, engineered by scientists at the University of Washington, that can learn on its own as it handles a specific task. The hand has five fingers, tendons, joints, over a hundred sensors, and is capable of moving faster than its human counterpart. In a video the university released, the hand can be seen delicately rotating a tube full of coffee beans-- an activity that the robot can improve iteratively, the university said. "Hand manipulation is one of the hardest problems that roboticists have to solve," Vikash Kumar, a doctoral student at the University of Washington and the lead author on a new paper about the robot hand, said in a statement. "A lot of robots today have pretty capable arms but the hand is as simple as a suction cup or maybe a claw or a gripper."

While it has taken over 50000 pounds and a large collection of artists to hand-paint each frame of a the Van Gogh movie: Loving Vincent, recent advances in neural algorithms artistic style (Gatys et al.) allow one to capture his art style on a computer. Although the work of Gatys et al. worked well on images, the naive method for extending it to movies does not produce great results. The video below shows a new method of rendering movies in a given art style using optical flow to move the textures with the objects in the scene. A technical report will appear soon on arxiv. Now that the code is written, the movie is generated with little human input.

Google DeepDream didn't just create a bunch of trippy, fascinating, slightly schizophrenic images -- it also inspired an entirely new research project within Google, and it's called Google Magenta. Starting the first of June, a small team of Google researchers will use the company's TensorFlow AI platform to develop an AI artist capable of creating its own visual art. The resulting artwork could eventually be made public through an app where anyone can browse creations as imagined by machines. Google Magenta was recently announced by researcher Douglas Eck, one of the individuals taking part in the program. Speaking at the music and tech festival Moogfest, Eck said that DeepDream directly inspired Magenta, which will also apparently be used to create some music, though details on that are vague.

Non-negative matrix factorization models based on a hierarchical Gamma-Poisson structure capture user and item behavior effectively in extremely sparse data sets, making them the ideal choice for collaborative filtering applications. Hierarchical Poisson factorization (HPF) in particular has proved successful for scalable recommendation systems with extreme sparsity. HPF, however, suffers from a tight coupling of sparsity model (absence of a rating) and response model (the value of the rating), which limits the expressiveness of the latter. Here, we introduce hierarchical compound Poisson factorization (HCPF) that has the favorable Gamma-Poisson structure and scalability of HPF to high-dimensional extremely sparse matrices. More importantly, HCPF decouples the sparsity model from the response model, allowing us to choose the most suitable distribution for the response. HCPF can capture binary, non-negative discrete, non-negative continuous, and zero-inflated continuous responses. We compare HCPF with HPF on nine discrete and three continuous data sets and conclude that HCPF captures the relationship between sparsity and response better than HPF.

In his book The Singularity Is Near, American computer scientist Ray Kurzweil had predicted a decade ago that by 2045 non-biological intelligence will have exceeded biological intelligence on Earth due to exponential changes in infotech, biotech and nanotech. Basically, man and machine will become one. But Murray Shanahan, a London-based cognitive robotics professor, disagrees with Kurzweil's theory in his more recent book, Technological Singularity. "Kurzweil was very precise (about time)," Shanahan tells China Daily in an interview in Beijing. "Technological singularity has a very dramatic impact on humanity."

One-fifth of the films and television shows offered in the European Union by on-demand providers like Netflix, iTunes and Amazon would have to be Europe-made under new proposals issued Wednesday. The quota would match one that already exists for TV networks in European countries and aims to protect the film industry, culture and national languages of the EU's 28 states in an increasingly globalized world dominated by programs in English and from the U.S. The proposal, however, is not popular in the industry and was immediately criticized by some. "Cultural quotas are outdated and unnecessary -- video-on-demand providers are already investing heavily into European local content," said James Waterworth, vice president of Europe operations for the CCIA computer and Internet industry association. Officials from the European Commission, the EU executive branch that made the proposal Wednesday, noted that Netflix's library is already made up of 21% European content, while other providers have up to 30%. "These percentages are not going to represent a major effort," said Guenther Oettinger, the commissioner responsible for Europe's digital market. "We are providing a certain degree of security for the European film industry."

Despite major advancements in artificial intelligence (AI) in a number of sectors, like the AI that beat the world champion at Go, its progress in the creative realm has yet to be fully proven. Once in awhile, news about an AI getting shortlisted for a literary prize will come up (no, seriously), but so far, achievements and milestones in the arts are few and far between. Alas, we don't have a fantastic robot-Picasso just yet, but Google is working to fix that. They just announced Magenta--a research project that will explore how AI can be used to produce art. According to a member of the research team, the group will first study what algorithms will be able to generate music.

The feature has also ended up being a decent hook for keeping listeners engaged. Spotify says over half of Discover Weekly users come back the following week, and a similar amount saves at least one song to their own libraries. I suppose that shouldn't be too surprising though -- having millions of tracks to stream is both a blessing and a curse. So something like Discover Weekly, which knows your habits and can apply it to Spotify's entire library with machine intelligence, can be a huge help for finding music you'd actually like. Spotify says the feature has also helped smaller artists get discovered.

Welcome to Mossberg, a weekly commentary and reviews column on The Verge and Recode by veteran tech journalist Walt Mossberg, now an Executive Editor at The Verge and Editor at Large of Recode. Fifteen years ago, when the time became ripe for post-PC devices that put a premium on integrating software and hardware, Apple was the best-positioned company to lead the charge -- and it did. The company's vertical integration, its attention to detail and innovation in both software and hardware, and its willingness to make big bets gave it an edge. And it used that edge to reel off its now-familiar string of game-changing products like the iPod, the iPhone, the MacBook Air, and the iPad. Now, the iPod is essentially gone, and the other products are in mature or maturing markets, with either pretty flat or dropping sales.

To address this problem, Cogitai is committed to developing systems that learn continually from their experience. "Our continual-learning technology will allow computer systems to build knowledge and skills simply through interacting with the world around them," said Dr. Mark Ring, CEO of Cogitai. "Simple knowledge and skills gained through early experience will allow development of more complex knowledge and skills in a powerful cycle of never-ending self-improvement. Though this ambition has always been one of the major goals of AI, it has never been considered feasible in the near term by those knowledgeable in the field, but our team believes it sees a path toward this dream." "Our company will build upon decades of research in the fields of Reinforcement Learning and Deep Learning, harnessing recent progress, but going well beyond current technology to create systems that learn for themselves how the world works in ways reminiscent of how human children do," said Dr. Satinder Singh, Chief Scientist of Cogitai.