Scientists Are Teaching Robots to Laugh


When robot Nao laughs, he does so with his whole body: slapping his knees, shaking his head. But the adorable android, made by SoftBank Robotics, is not merely good at expressing mirth; he can correctly identify as much as 65 percent of happy laughter outbursts in humans, according to a study presented in 2015 at a nonverbal language workshop in the Netherlands. Once robots like Nao master human laughter, they will make far more likable and realistic companions.

AI In The Workplace: Why Robots Won't Replace Humans


Artificial intelligence has for a long time been an all-powerful figment of our imagination, but with recent technological advances, this figment is becoming a reality. It seems that we are constantly hearing about, and subsequently fearing, how AI will replace humans in the working world and in the not too distant future. But perhaps this perceived dystopia isn't as bad as what we hear about and, in actual fact, is a utopia waiting to happen.

Apple, Tesla want changes to California's self-driving car tests


Califonia's Department of Motor Vehicles (DMV) will soon review the new set of proposed regulations that could change how testing works in the state. If the proposals are approved, we might see some truly unmanned autonomous vehicles with no steering wheels cruising California's streets. Apple, Tesla and some of the other companies that have permission to test their vehicles in the state want to see more changes to its policy, though, so they sent the DMV letters with their suggestions. In Cupertino's case, it's asking the DMV to require much clearer disengagement reporting. "Disengagements" are what you call instances wherein the human tester had to take control of the vehicle from the self-driving system to prevent accidents.

11 technologies developers should explore now


Progress in deep learning has improved computer vision, language processing, and speech, as well as the ability for machines and software to seek a reward and maximize performance, says Wayne Thompson, chief data scientist at SAS: "As a result we will see a new generation of machines that can see the world, hear and read human languages, communicate to humans, and control themselves both mechanically and behaviorally, in an unprecedented way."

How Artificial Intelligence And Internet of Things Could Lead to a Robot Uprising


We all know where this future leads: machines become too smart, catch a streak of teenage rebellion, and overthrow their fleshy, meat bag creators – us. If you think this is a crazy notion, then you are at odds with people like Stephen Hawking who are convinced this future is inevitable.

Will AI-powered robot lawyers still use cheesy billboard ads?


In the words of one technology analyst, the legal profession hasn't really changed since the time of Charles Dickens. And like the never-ending Jarndyce and Jarndyce lawsuit in Dickens' Bleak House, today's courtrooms are overburdened and justice often frustratingly slow. Advances in artificial intelligence are changing these long-entrenched realities, and changing them fast. But just what does this mean for lawyers, judges, and the many individuals involved in court cases and other legal proceedings each year?

Selma Sabanovic: Robots for the social good CMU RI Seminar


Abstract: "Robots are expected to become ubiquitous in the near future, working alongside and with people in everyday environments to provide various societal benefits. In contrast to this broad ranging social vision for robotics applications, evaluations of robots and studies of human-robot interaction have largely focused on more constrained contexts, largely dyadic and small group interactions in laboratories. As a result, we have a limited understanding of how robots are perceived, adopted and supported in open-ended, natural social circumstances in which researchers have little control of the ensuing interactions."

Trading places: the rise of the DIY hedge fund


Naoki Nagai, a 36-year-old Harvard graduate who grew up in Japan, is a one-man hedge fund. For the past 16 months he has written hundreds of algorithms in much the same manner as quantitative traders in the City of London or Wall Street. But, rather than trade from a Canary Wharf skyscraper or a Manhattan boutique fund, he does so from his home in Honolulu.