This smart doll demonstrates a new cheap, privacy-oriented computer vision platform in action. OK, let's get this out the way up top: A robot doll that can sense your child's emotions and change how it behaves accordingly sounds like the kind of high-concept horror movie a Hollywood screenwriter would pitch after binge-watching Westworld and a Chucky marathon. In reality, it describes research being carried out by investigators at the University of Castilla-La Mancha in Ciudad Real, Spain. What they've built as a proof of concept is an artificially intelligent doll that can recognize eight different emotions and runs on an AI chip costing just 115 euros (around $130). Emotion recognition is carried out through facial-recognition technology, via a camera hidden in the doll's mouth.

The chief executive of west London's Kensington and Chelsea Council - who's been among the officials and politicians facing criticism over the Grenfell Tower fire - has resigned. Nicholas Holgate called the disaster, in which at least 79 people died, "heart-breaking", adding that remaining in office would be a "distraction". He also said that Local Government Secretary Sajid Javid had asked him to quit, but Mr Javid hasn't yet commented on the claim. Prime Minister Theresa May announced on Wednesday that 68 social housing flats in Kensington Row, about 1.5 miles away from Grenfell Tower, would be made available to survivors. It's clear from the Queen's Speech that Theresa May's main priority over the next couple of years is most definitely going to be Brexit.

When "Minority Report" hit theaters on June 21, 2002, it arrived to an America -- and a world -- that feels equal parts familiar and alien. We were less than a year into a post-9/11 climate of increased surveillance and color-coded terror alerts. But smartphones, social media and cloud computing were only at their most nascent forms: the iPod and Windows XP were less than a year old, after all. The film, in which police use psychic "precogs" to arrest people for crimes they haven't yet committed, was based on a Philip K. Dick short story from 1956. But it was set in the year 2054.

The Navya Arma, a 15-passenger electric shuttle takes members of the media on a two loop tour of the streets of Mcity on the campus of the University of Michigan in Ann Arbor, Michigan on Friday, December 9, 2016. Mcity will launch a driverless shuttle service on the University of Michigan's North Campus in Ann Arbor beginning in the fall of 2017. The electric shuttles are made by French startup NAVYA and are on display on June 21, 2017. The service will use two fully-automated, 15-passenger, all-electric shuttles manufactured by French firm Navya to transport students, faculty, and staff between U-M's engineering campus and the university's North Campus Research Complex. The driverless shuttles, the first of their kind in Michigan, will drive on University of Michigan roadways, putting them in the mix at times with regular vehicles driven by the public as they traverse a 2-mile circular route every 10 minutes.

This article was written by James Le. It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix's algorithms to make movie suggestions based on movies you have watched in the past or Amazon's algorithms that recommend books based on books you have bought before. So if you want to learn more about machine learning, how do you start?

There are flying cars and Concorde's would-be supersonic successor, a company offering to deliver cargo to the Moon - for a mere $1.2 million per kilogram - and the latest in funky futuristic aviation ideas, both big and small. No doubt about it: the Paris Air Show is an aerospace geek's paradise. But with everything from the smallest drones to the largest passenger jets on display, it's tough to sift through it all. So here's a guide to some of the cool things that caught our eye this week. Visitors looks at the flying car Pegasus 1, built by French entrepreneur Jerome Dauffy at Paris Air Show, in Le Bourget, east of Paris, France, Tuesday, June 20, 2017 in Paris.

A car that can drive itself around a city and even respond to traffic lights is unveiled today – and could be on the roads in a matter of months. The Range Rover Sport's space-age technology even lets it negotiate T-junctions and roundabouts – and make way for approaching emergency vehicles. It is part of a £20million Government-backed project designed to keep Britain in the forefront of driverless car design. The Sport is one of a series of vehicles being demonstrated today at the Horiba Mira testing ground in Nuneaton before going on to official road trials later this year. The Range Rover Sport's space-age technology even lets it negotiate T-junctions and roundabouts Jaguar Land Rover's Autonomous Urban Drive technology brings the UK car-maker a step closer to achieving so-called'level four' autonomy within the next decade.

Two months before the first total solar eclipse to cross the continental United States in a century, NASA has revealed its plans to study and promote a celestial show that will darken skies from Oregon to South Carolina. During the Aug. 21 eclipse, the moon will pass between the sun and Earth, blocking the face of the sun and leaving only its outer atmosphere, or corona, visible in the sky. It is the first coast-to-coast total eclipse since 1918 - and NASA has creraqted a pair of eclipse posters to celebrate the occasion. To celebrate the upcoming eclipse, NASA has also created these retro posters to mark the occasion,. The space agency said viewers around the world will be provided a wealth of images captured before, during, and after the eclipse by 11 spacecraft, at least three NASA aircraft, more than 50 high-altitude balloons, and the astronauts aboard the International Space Station – each offering a unique vantage point for the celestial event.

We consider settings where owners of electric vehicles (EVs) participate in a market mechanism to charge their vehicles. Existing work on such mechanisms has typically assumed that participants are fully rational and can report their preferences accurately via some interface to the mechanism or to a software agent participating on their behalf. However, this may not be reasonable in settings with non-expert human end-users.Thus, our overarching aim in this paper is to determine experimentally if a fully expressive market interface that enables accurate preference reports is suitable for the EV charging domain, or, alternatively, if a simpler, restricted interface that reduces the space of possible options is preferable. In doing this, we measure the performance of an interface both in terms of how it helps participants maximise their utility and how it affects deliberation time. Our secondary objective is to contrast two different types of restricted interfaces that vary in how they restrict the space of preferences that can be reported. To enable this analysis, we develop a novel game that replicates key features of an abstract EV charging scenario. In two experiments with over 300 users, we show that restricting the users' preferences significantly reduces the time they spend deliberating (by up to half in some cases). An extensive usability survey confirms that this restriction is furthermore associated with a lower perceived cognitive burden on the users. More surprisingly, at the same time, using restricted interfaces leads to an increase in the users' performance compared to the fully expressive interface (by up to 70%). We also show that some restricted interfaces have the desirable effect of reducing the energy consumption of their users by up to 20% while achieving the same utility as other interfaces. Finally, we find that a reinforcement learning agent displays similar performance trends to human users, enabling a novel methodology for evaluating market interfaces.

We study computational problems for two popular parliamentary voting procedures: the amendment procedure and the successive procedure. They work in multiple stages where the result of each stage may influence the result of the next stage. Both procedures proceed according to a given linear order of the alternatives, an agenda. We obtain the following results for both voting procedures: On the one hand, deciding whether one can make a specific alternative win by reporting insincere preferences by the fewest number of voters, the Coalitional Manipulation problem, or whether there is a suitable ordering of the agenda, the Agenda Control problem, takes polynomial time. On the other hand, our experimental studies with real-world data indicate that most preference profiles cannot be manipulated by only few voters and a successful agenda control is typically impossible. If the voters' preferences are incomplete, then deciding whether an alternative can possibly win is NP-hard for both procedures. Whilst deciding whether an alternative necessarily wins is coNP-hard for the amendment procedure, it is polynomial-time solvable for the successive procedure.