Berlin startup Spil.ly had a problem last spring. The company was developing an augmented-reality app akin to a full-body version of Snapchat's selfie filters--hold up your phone and see your friends' bodies transformed with special effects like fur or flames. To make it work, Spil.ly needed to train machine-learning algorithms to closely track human bodies in video. But the scrappy startup didn't have the resources to collect the tens or hundreds of thousands of hand-labeled images typically needed to teach algorithms in such projects. "It's really hard being a startup in AI, we couldn't afford to pay for that much data," says CTO Max Schneider.
It's important not to overstate the security risks of the Amazon Echo and other so-called smart speakers. They're useful, fun, and generally have well thought-out privacy protections. Then again, putting a mic in your home naturally invites questions over whether it can be used for eavesdropping--which is why researchers at the security firm Checkmarx started fiddling with Alexa, to see if they could turn it into a spy device. They did, with no intensive meddling required. The attack, which Amazon has since fixed, follows the intended flow of using and programming an Echo.
Self-driving cars have it rough. They have to detect the world around them in fine detail, learn to recognize signals, and avoid running over pets. But hey, at least they'll spend most of their time dealing with other robot cars, not people. That means interacting with people--lots of people--and dogs and trash and pigeons. Unlike a road, a sidewalk is nearly devoid of structure.
More than a month after a self-driving Uber struck and killed a pedestrian crossing the street in Arizona, it's still not clear what sort of failure might explain the crash--or how to prevent it happening again. While the National Transportation Safety Board investigates, Uber's engineers are sitting on their hands, their cars are parked. The crash and its inconclusive aftermath reflect poorly on a newborn industry predicated on the idea that letting computers take the wheel can save lives, ease congestion, and make travel more pleasant. An industry dashing toward adulthood--Google sister company Waymo plans to launch a robo-taxi service this year, General Motors is aiming for 2019--and now, suddenly, on the verge of being rejected by a public that hasn't even experienced it yet. In other words, AV makers are clearing the technological hurdles and tripping over the psychological ones.
After Uber's fatal self-driving crash last month in Tempe, Arizona, most observers had two basic question: Why did the car not see Elaine Herzberg crossing the street and stop before hitting her? And how can we stop this happening again, to someone else? The ride-hailing company has indefinitely suspended its testing program, and is cooperating with the National Transportation Safety Board's investigation of the crash. The NTSB hasn't revealed any findings yet, but the lidar--the laser-shooting sensor that should have spotted Herzberg, even in the dark--is an obvious focus. Maybe it had a blind spot, or lacked the resolution to identify Herzberg as a pedestrian.
When Amazon first introduced developer tools that let people build stuff for Alexa, the company made a conscious decision to call these functions "skills" rather than apps. It was a subtle way of making Alexa seem capable, and also, suggesting to developers that building these skills would be a low lift. With just a "few lines of code," Amazon promised, "you can build entirely new experiences designed around voice." Amazon says most Echo users in the US have tried these third-party skills at least once, but getting them to work can be tricky. Alexa's voice skills often require super specific queries, and until Amazon started paying attention to the discovery process, taking the time to find new skills felt like a non-essential burden. Now, Amazon has decided to make Alexa's skills all about you: your dad jokes, your homework, your birthday.
Friends, humans, rapidly-evolving robots, the time has finally come: Westworld Season 2 is here. After nearly 17 months, HBO's futuristic thriller about a theme park where the rich can live out their Wild West fantasies with android "hosts" finally returns on Sunday. At the end of the first season, it seemed as though some of the hosts were starting to gain more agency than robots are supposed to have (or were they?) and there were a lot of mysteries left unsolved. In anticipation of the Season 2 debut, WIRED got together some of our biggest Westworld aficionados to hash out our hopes and dreams for the second season. Do we think these violent delights have violent ends?
In the late 1950s, a weapons maker called the Martin Company received a contract to build the first Pershing missile. It was to be the most sophisticated mobile weapons system on earth: 5 tons of metal and precision technology designed to deliver a nuclear warhead from up to 460 miles away. Should it ever be used, there would be no margin for error. It had to be perfect. And the US Army wanted it delivered quickly.
In a hallway of an engineering building at Stanford University, some devilish researchers have built a sprawling obstacle course. To make it through, competitors have to wind over sand, through a door, up some steps, and finally, through a forest of small pillars. Sounds like the Rube Goldbergian machinations of an grad student with too much time and Red Bull on their hands, but no: This is a robot training ground. See, a tracked robot might be able to navigate the sand and the steps, but good luck in the forest. A wheeled automaton could well get stuck in the sand.
And just like that, humanity draws one step closer to the singularity, the moment when the machines grow so advanced that humans become obsolete: A robot has learned to autonomously assemble an Ikea chair without throwing anything or cursing the family dog. Researchers report today in Science Robotics that they've used entirely off-the-shelf parts--two industrial robot arms with force sensors and a 3-D camera--to piece together one of those Stefan Ikea chairs we all had in college before it collapsed after two months of use. From planning to execution, it only took 20 minutes, compared to the human average of a lifetime of misery. It may all seem trivial, but this is in fact a big deal for robots, which struggle mightily to manipulate objects in a world built for human hands. To start, the researchers give the pair of robot arms some basic instructions--like those cartoony illustrations, but in code.