HONG KONG, July 15, 2016 /PRNewswire-iReach/ -- Today Mills Media Arts LLC (MMA), formerly known as Mills Agency announced the acquisition of Jump City Media, a Hong Kong based mobile media think tank with a core focus on artificial intelligence. The acquisition gives MMA a global reach with offices now in New York, Los Angeles, London and Hong Kong while also adding more depth to the MMA marketing and mobile media expertise. The advanced mobile solutions group will operate in a new division within the company called Mobile Media Arts lab. Through the use of advanced technologies such as augmented reality, artificial intelligence and proximity aware services, the Mobile Media Arts Lab builds and integrates interoperable technology that propels advances in productivity and profoundly changes how people live in ways that they could not have imagined. The Mobile Media Arts Lab includes some of the top graphic artists, developers, engineers and data scientists in the industry.

In this work, we explore theoretical properties of simple non-convex optimization methods for problems that feature prominently in several important areas such as recommendation systems, compressive sensing, computer vision etc.

Remember that old carnival game, the one where you attempt to guess the number of jelly beans in a jar? While it often took some combination of luck and skill for any single person to accurately guess the correct number, it turns out that by averaging all of the guesses of a wide variety of people together, the averaged answer is surprisingly close to the correct response. This phenomenon is an example of what's known as "the wisdom of the crowd," a modeling strategy frequently used in machine learning. Given that you have a diverse enough number of perspectives--each of which must have some measure of signal, but not be correlated to any other perspective (so errors tend to be symmetrically distributed around the truth)--as well as a suitable way of aggregating those perspectives (like averaging), you'll find that in the results of that aggregation, the "rightness stacks up" while the errors tend to cancel each other out. In the case of the jelly bean example, this means you must have a lot of people submit guesses (large number of perspectives), they're all looking at the same jar of jelly beans (must have some measure of signal), and those people can't talk to each other about their guesses (perspectives are not otherwise correlated).

We have seen a number of inventions that make taking the daily dose easier. For example, 3D printed custom pills can combine multiple drugs into a single tablet, while a smart scheduler sends reminders and updates to help people keep on top of their pill routine. Now, Pillo is a smart pill dispenser and health tracker combined, which can safely store and dispense an entire family's medication, using facial and voice recognition to provide the correct pills to the right person. Pillo is a friendly, family healthcare robot with numerous abilities. Built on an intelligent platform, which enables it to learn about multiple users, Pillo's functionalities grow over time. It safely stores medication and vitamins and dispenses them smartly to the right person.

By learning how to pitch his bot idea while driving a robot, Button.ai Organized by VentureBeat, the international botathon took place July 9-10 in New York, Melbourne, Tel Aviv, and San Francisco. A fifth finalist category was made for people participating online elsewhere in the world. Finals for popular vote and judges' categories were held Tuesday in San Francisco at MobileBeat, a two-day gathering of chatbot and AI leaders, held July 12-13 at The Village. Skoolbot won the portion of the competition decided by judges Phil Libin, an investor in bots from General Catalyst; SmarterChild creator Robert Hoffer; and Alfred Lin, an investor at Sequoia Capital.

Geosocial apps are having a bit of a moment. Tinder, Bumble, and a host of other services have emerged in recent years, promising to foster connections with real people, nearby. But online dating paved the way for these apps -- and even supposedly platonic services like Bumble BFF have struggled to shrug off the romantic connotation. So where does that leave people who aren't looking for love, but do want to use new technology to make friends? That question -- or "shower thought," as he puts it -- motivated Antoine Daher to create Patook, an app that connects people based on common interests.

In this talk, I will introduce the audience to the emerging area of computational social science, focusing on how machine learning for social science differs from machine learning in other contexts. I will present two related models -- both based on Bayesian Poisson tensor decomposition -- for uncovering latent structure from count data. The first is for uncovering topics in previously classified government documents, while the second is for uncovering multilateral relations from country-to-country interaction data. Finally, I will talk briefly about the broader ethical implications of analyzing social data. Hanna Wallach is a Senior Researcher at Microsoft Research New York City and an Adjunct Associate Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst.

Today, Pål Sundsøy at Telenor Group Research in Fornebu, Norway, says he's worked out how to determine literacy rates using mobile phone call records. He starts with a standard household survey of 76,000 mobile phone users living in an unidentified developing country in Asia. Sundsøy then matches this data set with call data records from the mobile phone company. "By deriving economic, social, and mobility features for each mobile user we predict individual illiteracy status with 70 percent accuracy," he says, pointing out that this allows areas with low literacy rates to be mapped.

One of the millennium development goals of the United Nations is to eradicate extreme poverty by 2030. That's a complex task, since poverty has many contributing factors. But one of the more significant is the 750 million people around the world who are unable to read and write, two-thirds of which are women. There are plenty of organizations that can help, provided they know where to place their resources. So identifying areas where literacy rates are low is an important challenge.

Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. That's why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments.