In an unassuming two-storey Victorian town house in Bristol, the occupants are being filmed, monitored, and tracked by invisible sensors as they go about their business, 24 hours a day. What they lose in privacy could be our gain in life expectancy, if the long-term data bears out. Pivotal to the 15-million Sensor Platform for Healthcare in a Residential Environment (SPHERE) project, the house has been invisibly fitted with dozens of cameras and sensors while its occupants are asked to don wearable devices. The aim is to reveal how health is related to everyday lifestyle and living conditions over time. The smart home observes how long the occupants slouch in front of the TV as opposed to sitting or walking or exercising.

Doha, Qatar - Faced with shrinking budgets, greater competition and increasingly selective audiences, leaders of international media organisations gathering vowed to share ideas about how best to gather and present news. "We are 20 years into the digital revolution of the media," Gary Pruitt, president of the Associated Press news agency, told a gathering in Doha of around 300 journalists from across the world. "Demand for news will only grow from here, but the supply of news will also grow. Much of it will not be of very high quality." He said that "a key component to innovation at AP is to increase work and investment into media and technology startups", adding that the agency has tested drones for news gathering purposes, and has used "robot journalism" to produce reports without human intervention.

JUDY WOODRUFF: A movie thriller being released nationally today delves into the practical, legal and moral issues surrounding drone warfare. HELEN MIRREN, Actress: We need to put a Hellfire through that roof right now. JEFFREY BROWN: It's a new kind of warfare, advanced technology that tracks, identifies, and has the power to destroy enemies by remote control from thousands of miles away. HELEN MIRREN: We have two suicide vests with explosives inside that house. JEFFREY BROWN: But as the film "Eye in the Sky" asks, should it be used?

Video Friday is your weekly selection of awesome robotics videos, collected by your mysophobic Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. XDog is a small electric quadruped designed and built by Xing Wang, a graduate student at Shanghai University, with support from his adviser Jia Wenchuan. The robot has 12 motors (each leg has 3 DoF), and uses force sensors on each foot, IMU, and joint-angle sensors for control.

On cold, dark days it is tempting to imagine shutting yourself away until the warmer weather returns. Many animals do it by entering a state known as torpor, which reduces their bodily functions to a minimum and uses fat stores in their body for energy, but could humans ever hibernate in the same way? Vladyslav Vyazovskiy, associate professor of neuroscience at the University of Oxford has explained what torpor does to the body and how it could affect the human body in an article for The Conversation. An expert has explained what torpor - or the act of shutting the body down during hibernation - does to the body and how it could affect humans. A'therapeutic torpor' could make a manned mission to Mars more feasible.

In a world with more mobile phones than flush toilets, digital devices are now standard equipment among even the world's poorest and most remote people. Farmers in these areas are getting tools for their devices that help deliver water, nutrients, and medicine to plants as needed; test for crop diseases and malnourishment; and survey their soil for future planning. In some cases, these emerging apps are the biggest new technologies resource-poor farms have seen in hundreds of years. That is not very surprising to Rajiv "Raj" Khosla, professor of Precision Agriculture at the College of Agricultural Sciences of Colorado State University. "What we're finding is that many small-scale farmers in resource-poor environments are still farming in the 1500s. They're looking for leapfrog technologies," he said.

This paper and use of autonomous weapons systems has been will discuss the moral and ethical questions that arise in the one of the outcomes of the counterterrorism and counterinsurgency use of lethally autonomous technology for military purposes operations in Iraq and Afghanistan. The asymmetrical and how the forms of subjectivity and moral agency that battlefields of these theaters, where no frontline it creates could be highly counterproductive to mission provides a buffer between combatants and civilians and effectiveness, diplomacy and conflict resolution and prevention.

The Maximum Satisfiability (MaxSAT) problem is the problem of finding a truth assignment that maximizes the number of satisfied clauses of a given Boolean formula in Conjunctive Normal Form (CNF). Many exact solvers for MaxSAT have been developed during recent years, and many of them were presented in the well-known SAT conference. Algorithms for MaxSAT generally fall into two categories: (1) branch and bound algorithms and (2) algorithms that use successive calls to a SAT solver (SAT- based), which this paper in on. In practical problems, SAT-based algorithms have been shown to be more efficient. This paper provides an experimental investigation to compare the performance of recent SAT-based and branch and bound algorithms on the benchmarks of the MaxSAT Evaluations.

In machine learning, there is an ongoing revival of the use of variational Bayes (VB) to deal with complex probabilistic models with hidden variables. The revival is driven by the use of stochastic methods to approximate the VB lower bound and associated gradients. See for example [1, 2, 5]. The advantages include automated inference [3] and also that they are applicable to a much wider class of probabilistic models. While the basic recipes are limited in the flexibility of the approximate hidden-variable posteriors, there are ongoing efforts to make them more flexible.

Understanding the demographics of users of online social networks has important applications for health, marketing, and public messaging. Whereas most prior approaches rely on a supervised learning approach, in which individual users are labeled with demographics for training, we instead create a distantly labeled dataset by collecting audience measurement data for 1,500 websites (e.g., 50% of visitors to gizmodo.com are estimated to have a bachelor's degree). We then fit a regression model to predict these demographics from information about the followers of each website on Twitter. Using patterns derived both from textual content and the social network of each user, our final model produces an average held-out correlation of .77 across seven different variables (age, gender, education, ethnicity, income, parental status, and political preference). We then apply this model to classify individual Twitter users by ethnicity, gender, and political preference, finding performance that is surprisingly competitive with a fully supervised approach.