The idea of a device that can materialize one's memories out of thin air seems like it could only exist in science fiction. But in a new study, researchers were able to pretty accurately sketch out the thoughts of participants simply by scanning their brains. It's helping scientists understand how memory works in the human brain, and it may be a first step toward the futuristic ability to read minds. Researchers at the University of Oregon showed a group of participants, all strapped into an MRI machine, a series of photos of human faces. They followed the participants' brain activity as they looked at each image, mapping neural activity to a code of numbers that correspond to the characteristics of each face.

A key specification for exchanging sensor data between vehicles has found a new sponsor, in a move that may help future drivers avoid dangers before they see them. New vehicles are increasingly laden with sensors -- accelerometers, thermometers, radar and lidar (light detection and range) -- and the best of them can use the streams of incoming data to warn of or even avoid hazards such as ice or obstacles. But what if they could share information about changes to a road since the map was last updated or even warn one another of a stopped vehicle hidden by a blind curve? Vehicles might then be able to choose more efficient routes or avoid the need for sudden braking. That was the plan of digital mapping company Here when it published its specification for Sensoris (Sensor Ingestion Interface Specification) a year ago.

Data centers store a tremendous -- some would say, ridiculous -- amount of logs. There is too much data for the smartest administrator to make immediate sense of. For analytics to continue to be helpful, it needs to be smarter than it is now. If this much logging on a granular scale is to be of use to anyone -- before, during, or after a network event -- logic needs to be capable of ascertaining causes and effects as they happen. Machine learning could be one thing that could provide such an intelligence.

As Silicon Valley investors and tech giants continue to pour cash into burgeoning artificial intelligence technologies such as machine learning and chatbots, the relatively nascent A.I. industry is emerging as the latest mega-hot new ticket in town--the heir to online delivery apps, anything-hailing services, and virtual reality start-ups. But much like another buzz-worthy predecessor, Big Data, many A.I. cheerleaders and investment check signatories probably don't quite understand it. But in Silicon Valley, when has that ever stopped anyone? The obsession in the Valley with artificial intelligence is almost palpable. Just last week, Twitter announced its acquisition of London-based machine learning start-up Magic Pony Technology.

The tsunami of innovation and waves of disruption are not slowing down,

One side effect of talking about the risk of killer robots so much is that everyone is now rushing to assure us exactly how they would prevent this. Microsoft CEO Satya Nadella is the latest to reassure us, in an extremely vague way. Earlier this month, Google engineers published a paper outlining five principles of safety. Their principles were things like "avoid negative side effects" which, while not earth-shaking, at least were fairly concrete and illustrated with examples from a cleaning robot. Nadella's, as outlined in Slate, are filled with jargon.

Justine Cassell has taken her virtual assistant Sara on a road trip. They're in Tianjin, China, where Carnegie Mellon University's associate dean of technology strategy and impact traveled to offer a glimpse of tomorrow at this week's Annual Meeting of New Champions. Sara, for "socially aware robot assistant," has spent the past several days greeting hundreds of people coming to the event, hosted by the World Economic Forum, at a station showcasing the office of the future. A life-size face and torso on a big-screen TV, Sara served as the front end to the event app. That presentation might make you think of Max Headroom, the stuttering AI character from the 1980s show.

Last month, the White House announced a series of actions as part of a new White House Future of Artificial Intelligence initiative, designed to learn more about the benefits and risks of AI. Since making that announcement, the White House Office of Science and Technology Policy (OSTP) has co-hosted two public workshops on opposite ends of the country--the first in Seattle at the University of Washington, focused on the legal and governance implications of AI, and the second here recently in Washington, DC, where we heard about AI for public good. This month and next, we will be in Pittsburgh on June 28 to discuss safety and control for AI, and New York City on July 7 to explore AI's social and economic implications. You can join these events in person (subject to venue constraints) by registering via the event websites, or you can follow the discussion via livestream and social media, where we will be using the hashtag #FutureofAI. Today, we are announcing another action to build on these efforts and expand the opportunity for public participation in this conversation.

What's the first thing you think of when you hear the phrase "artificial intelligence"? While those are indeed examples of artificial intelligence, examples of AI in the real world of today are a bit more mundane and a whole lot less sinister. In fact, many of us use AI, in one form or another, in our everyday lives. The personal assistant on your smartphone that helps you locate information, the facial recognition software on Facebook photos, and even the gesture control on your favourite video game are all examples of practical AI applications. Rather than being a part of a dystopian world view in which the machines take over, current AI makes our lives a whole lot more convenient by carrying out simple tasks for us. This means that in the near future, we could see even more practical uses for AI, from smart robots to smart drones and more.

ARLINGTON, Va.--With support from the Office of Naval Research (ONR), researchers at the Georgia Institute of Technology have created an artificial intelligence software program named Quixote to teach robots to read stories, learn acceptable behavior and understand successful ways to conduct themselves in diverse social situations. "For years, researchers have debated how to teach robots to act in ways that are appropriate, non-intrusive and trustworthy," said Marc Steinberg, an ONR program manager who oversees the research. "One important question is how to explain complex concepts such as policies, values or ethics to robots. Humans are really good at using narrative stories to make sense of the world and communicate to other people. This could one day be an effective way to interact with robots."