Google Investing in Drone Autopilot Systems
Google’s venture capital arm announced yesterday that it is investing $10.7 million in a company that makes drone brains. The company, Airware, builds autopilots for unmanned aerial systems.
Because space and weight are at a premium on drones, especially small ones, Airware’s systems can get pretty tiny—one model weighs 32 grams, or about the same as a pocketful of coins.
Airware made news in January (under their previous name of Unmanned Innovations, Inc.) when a Kenyan wildlife conservation group purchased one of its drones to fly over a nature preserve and watch for poachers.
(via Google Bets $10.7 Million On Drone Intelligence | Popular Science)
Phone Companies Investing in Speech-to-Text and Predictive Search to Snoop on Your Calls, Sell You Stuff
The technology is being built by a small San Francisco startup, Expect Labs, which is announcing strategic investments from the venture capital arms of three weighty backers today: Samsung, Intel, and Telefónica Digital, the business unit the telecom company launched in 2011 to unearth new revenue opportunities. The size of the investments was not disclosed.
Expect Labs has attracted attention because its technology is in line with the general direction that search technology has been taking with the advent of wearable computers such as watches and glasses, and Internet-connected cars and TVs. Rather than wait for users to search for something, the new technology offers up info that it thinks the user might need. The Google Now software for mobile devices, for example, already monitors its users’ locations, search history, and e-mail to call up traffic reports and other information. But Google Now doesn’t mine old-fashioned voice conversations yet. In October, Google Ventures invested in Expect Labs as part of a $2.4 million financing round by the startup.
Expect Labs has spent more than two years developing artificial intelligence technology that can parse the meaning of real-time conversations (Apple’s Siri, in contrast, can interpret only relatively simple spoken commands). Expect Labs’s “anticipatory computing engine” extracts the most relevant terms and uses them to offer potentially helpful information (see “Smart Assistant Listens to You Talk, Fetches Info Automatically”). For example, if two friends are having a discussion about grabbing some Thai food, it might call up reviews of nearby restaurants. If a company’s revenue comes up in a videoconference, it could display recent revenue charts. Expect Labs has built an app, called MindMeld, to demonstrate to partners how this works.
South Dakota Students Testing Fingerprint-Based Payment System
More than 50 students and faculty members at the School of Mines and Technology in South Dakota are part of that pilot programme which uses biocryptology – biometrics and cryptology combined – to allow them to buy items at campus shops.
Users must first set up an account in person, bringing with them identification, banking information and their index fingers. To buy an item, students enter their birthday, as an extra identification step, and then put their index finger into scanner, which encrypts the fingerprint and sends the data over the intranet to a secure system that checks it against their records.
The scan goes beneath the top layers of skin to detect haemoglobin in the blood, meaning a pulse must be detected before the purchase is allowed.
(via South Dakota School First To Buy Things With Fingerprints - Business Insider)
DARPA Can Spot a CD from 20,000 Feet, Monitor the Entire Island of Manhattan with Two Drones
DARPA and the US Army have taken the wraps off ARGUS-IS, a 1.8-gigapixel video surveillance platform that can resolve details as small as six inches from an altitude of 20,000 feet (6km).
ARGUS is by far the highest-resolution surveillance platform in the world, and probably the highest-resolution camera in the world, period. ARGUS, which would be attached to some kind of unmanned UAV (such as the Predator) and flown at an altitude of around 20,000 feet, can observe an area of 25 square kilometers (10sqmi) at any one time.
If ARGUS was hovering over New York City, it could observe half of Manhattan. Two ARGUS-equipped drones, and the US could keep an eye on the entirety of Manhattan, 24/7. It is the definition of “observe” in this case that will blow your mind, though.
With an imaging unit that totals 1.8 billion pixels, ARGUS captures video (12 fps) that is detailed enough to pick out birds flying through the sky, or a lost toddler wandering around. These 1.8 gigapixels are provided via 368 smaller sensors, which DARPA/BAE says are just 5-megapixel smartphone camera sensors. These 368 sensors are focused on the ground via four image-stabilized telescopic lenses.
Creator of CV Dazzle Debuts Anti-Surveillance Clothing Line
Brooklyn-based artist Adam Harvey is scheduled to unveil a line of fashion called Stealth Wear at a London studio. Working in collaboration with fashion designer Johanna Bloomfield, Harvey used materials designed to disguise and protect the wearer from thermal imaging, X-rays, and other technologies commonly used in surveillance. The garments include “an anti-drone hoodie and matching scarf…and a pocket protector that he says blocks cell phones from sending and receiving signals.” At the exhibit, each garment will be accompanied by information about the relevant technology and counter-technology behind its creation.
(via Worried About Drones? Try Wearing This Hoodie | IdeaFeed | Big Think)
NYPD Closer to Deploying Teraherz Radiation Scanners on The Street
The device is small enough to fit inside a police car or on a street corner where gun violence is common, Rocco Parascandola of The NY Daily News reports.
It works by testing for terahertz radiation, which is the natural energy that both people and inanimate objects emit.
“If something is obstructing the flow of that radiation, for example a weapon, the device will highlight that object,” NYPD Commissioner Raymond Kelly said Wednesday.
The NYPD hopes to deploy these devices soon, but Kelly said that there are still “a number of trials to run” before that actually happens.
(via New Technology Helps Cops See Hidden Guns From Far Away)
Tethered Drones: The Future of Indefinite Surveillance
A new venture from an iRobot co-founder called CyPhy Works has borne fruit in the form of two flying drones dedicated to surveillance duty.
The first, called Ease, is a mere foot in diameter by 16-inches tall and can fly safely in tight spaces or through open windows or doors, thanks to its petite size and ducted rotors. It packs a pair of HD cameras along with a thermal imager and can stay aloft permanently, in theory, thanks to a microfilament tether attached to a ground station — which also makes it impervious to weather, tracking and interception at the same time, according to CyPhy.
The second drone, an insect-like quadrotor called Parc, is designed for higher flying missions thanks to its larger size and maximum 1,000-foot altitude. It also uses a tether and can stay aloft for 12-hours on a single ground-station battery, letting it spy from afar with on-board HD, night-vision and thermal cameras. The company’s yet to take any orders, but thanks to investors and government grants, the snoopy little bots could be getting up into your business one day soon — as creepily shown in the video after the break.
(via CyPhy Works reveals tethered flying bots that can spy on you indefinitely (video))
Lehmann Aviation Debuts the $1,200 Personal Drone
Lehmann Aviation calls the device, whose full name is the LA100, “the world’s first aircraft designed for the users with no piloting background.” How does it work? Simple. Connect the battery and launch it. Wait five minutes for the drone to come back. You’re done. Assuming you strapped a GoPro camera up there–it can be mounted in one of two positions, either atop the wing for oblique images, or below the wing for vertical ones–then you’ve also got a card full of pictures.
The device has a 92 cm wingspan and weighs just 850 grams, made of foam and carbon fiber. The device is rugged and can handle temperatures as low as -25 degrees Celsius. Lehmann Aviation promises regular hardware and software upgrades on its site.
Microsoft Patents Method To Count People In a Room Using Kinect, Charge Per Viewer for Content
A U.S. Patent and Trademark Office filing by Microsoft reveals that the company is devising a means for your Xbox peripheral to count the number of people in the room and even identify who they are in order to assess licensing fees for content based on the number of people in the room.
“In Soviet Union, TV Watches You”
Algorithm Mines Contact Data to Build Map of Social Relationships, Even Hidden Ones
…The ability to automatically create circles from a user’s contacts list is certainly valuable, The algorithm also has the ability to add new contacts to appropriate circles.
An important limitation, however, is the scalability of the approach. McAuley and Leskovec admit their algorithm is not particularly efficient, taking about an hour to identify ten circles from a list of 1000 Facebook contacts. That’s a lot of hours of processing for Facebook’s 1 billion users. However, they say that the technique should be quicker as broader patterns become clear once all users contacts have been taken into account.
For example, it may be possible to identify the set of all people on Facebook who went to a particular university. Then one person’s circle might consist of the intersection between this set and their contact list. Just how much of a speed up this would allow isn’t clear though.
Another important question for the future is how well in principle automatically-generated circles can be made to match ground truth circles, using only the information available in contact profiles and so on. It may be that many circles are created using information that users do not explicitly make available on social networks, such as a circle of ‘best friends’. If that’s the case, then these algorithms will never be able to reconstruct the ground truth circles perfectly. But perhaps this doesn’t matter if they provide a reasonable approximation to ground truth circles that users can tinker with at their leisure.
Another interesting approach is to look for patterns of links between contacts that users do not turn into circles—in other words connections between people that users have not recognised or want to keep hidden. Such a pattern might be linked with criminal activity, for example, or point to marketing information that could be sold.
(via Algorithm Predicts Circles of Friends Using Contacts Data | MIT Technology Review)
