Back to Earth: SpaceX Capsule Departs International Space Station

As reported by The Guardian: A SpaceX Dragon capsule left the International Space Station on Thursday for return to Earth.

NASA astronaut Scott Kelly, who's spending almost a year on the space station, used the outpost's robotic arm to unhook the gumdrop-shaped spacecraft from its port on the station's Harmony module and release it for the homeward journey.

The capsule, containing more than 3,000lb (1,360kg) of experiments and equipment, aimed for an early afternoon splashdown in the Pacific, off the southern California coast.

The capsule arrived at the orbiting lab last month, bearing much-needed groceries and other goods for the six station residents.

The California-based SpaceX company is Nasa’s only means of getting supplies to the 260-mile-high station, ever since last year’s loss of an Orbital Sciences Corp craft in a Virginia launch explosion.

More recently, a Russian supply ship went into an uncontrollable spin after liftoff and was destroyed upon re-entry earlier this month, its entire contents undelivered.

SpaceX will attempt to launch another shipment on 26 June from Cape Canaveral, Florida.

This was the sixth of 15 scheduled cargo resupply missions that California-based SpaceX is taking on under the terms of a NASA contract. SpaceX launched the Dragon with more than 4,300 pounds of cargo on a Falcon 9 rocket on April 14, making for a 37-day stay at the space station. One of the items on board was the first zero-G espresso machine to go into outer space.

Tesla Gigafactory: Drone Flyover Shows How Huge It Really Is

As reported by Yahoo Autos: The very word "gigafactory" makes Tesla Motors' lithium-ion cell fabrication and battery assembly plant sound quite large.

But how huge it actually is can be hard to comprehend.

Context is provided by diagrams that compare its planned footprint to, say, the largest building for assembling jetliners on Boeing's Washington state campus.

So a new video may help add perspective. Shot just this week, it shows flyover footage of the factory under construction in northern Nevada.

Tesla Motors gigafactory - size comparisons [source: EV Obsession]

Brought to us via the Transport Evolved website, the video was taken not from an airplane but by a remote-controlled drone.

Accompanied by somber music, the 2-minute clip shows the rectangular two-story factory building from a number of angles.

The building appears to have the second-story roof largely completed.

According to the YouTube page, it was posted by a user named "Quick Laptop Cash" (ahem). It's described as follows:

The first 4k ultra-high-definition video of the Tesla Gigafactory. Located 15 minutes east of Reno, Nevada, the Gigafactory is growing at a steady pace and helping fuel the strong economic recovery in Northern Nevada.

The description continues as follows:

To ensure safety this video was recorded while no workers were present and from over 1 mile away with a DJI Phantom 3 Professional Drone utilizing GPS. The drone was in constant visual contact as well as maintaining an altitude of not more than 400 feet above ground level.

Rendering of Tesla battery gigafactory outside Reno, Nevada, Sep 2014

The YouTube page is followed by a promotional link to a site that purports to inform about and list homes in the Reno, Tahoe, and Sparks areas of Nevada.

Interstingly, it appears to have been created and posted by local boosters grateful for the jobs and opportunity the huge plant is expected to provide.

When completed, the gigafactory will provide batteries not only for the Tesla Model 3 electric car expected to launch in 2017 or 2018, but also the Tesla Powerwall home energy-storage battery and similar products intended for commercial and industrial use.

The video ends with a note of thanks to many parties: Tesla CEO Elon Musk, Tesla itself, Nevada governor Brian Sandoval, the construction workers building the factory, EDAWN, and Nevada lawmakers.

"You are creating jobs and helping to redefine our once-struggling local economy" by building the $5 billion gigafactory, it says in closing.

A Map of the World's Buses and Trains Moving in Real Time

As reported by The Verge: Swiss-German IT firm GeOps has collaborated with the University of Freiburg on an interactive map of the world's major mass transit systems, incorporating public data feeds (like the MTA's) offered by train and bus operators to show everything moving in real time. Over 200 systems from around the globe are represented here, and it's absolutely mesmerizing to watch the colorful dots slowly amble their way across the grid.

Of course, not all mass transit authorities offer truly real-time data — GeOps notes that much of the map is based on schedule information, though it incorporated live data where it could. Still, it's incredible to watch.

Silicon Chips That See Are Going to Make Your Car and Smartphone Brilliant

As reported by MIT Technology Review: Many of the devices around us may soon acquire powerful new abilities to understand images and video, thanks to hardware designed for the machine-learning technique called deep learning.

Companies like Google have made breakthroughs in image and face recognition through deep learning, using giant data sets and powerful computers (see “10 Breakthrough Technologies 2013: Deep Learning”). Now two leading chip companies and the Chinese search giant Baidu say hardware is coming that will bring the technique to phones, cars, and more.

Chip manufacturers don’t typically disclose their new features in advance. But at a conference on computer vision Tuesday, Synopsys, a company that licenses software and intellectual property to the biggest names in chip making, showed off a new image-processor core tailored for deep learning. It is expected to be added to chips that power smartphones, cameras, and cars. The core would occupy about one square millimeter of space on a chip made with one of the most commonly used manufacturing technologies.

Pierre Paulin, a director of R&D at Synopsys, told MIT Technology Review that the new processor design will be made available to his company’s customers this summer. Many have expressed strong interest in getting hold of hardware to help deploy deep learning, he said.

Synopsys showed a demo in which the new design recognized speed-limit signs in footage from a car. Paulin also presented results from using the chip to run a deep-learning network trained to recognize faces. It didn’t hit the accuracy levels of the best research results, which have been achieved on powerful computers, but it came pretty close, he said. “For applications like video surveillance it performs very well,” he said. The specialized core uses significantly less power than a conventional chip would need to do the same task.

The new core could add a degree of visual intelligence to many kinds of devices, from phones to cheap security cameras. It wouldn’t allow devices to recognize tens of thousands of objects on their own, but Paulin said they might be able to recognize dozens.

That might lead to novel kinds of camera or photo apps. Paulin said the technology could also enhance car, traffic, and surveillance cameras. For example, a home security camera could start sending data over the Internet only when a human entered the frame. “You can do fancier things like detecting if someone has fallen on the subway,” he said.

Jeff Gehlhaar, vice president of technology at Qualcomm Research, spoke at the event about his company’s work on getting deep learning running on apps for existing phone hardware. He declined to discuss whether the company is planning to build support for deep learning into its chips. But speaking about the industry in general, he said that such chips are surely coming. Being able to use deep learning on mobile chips will be vital to helping robots navigate and interact with the world, he said, and to efforts to develop autonomous cars.

“I think you will see custom hardware emerge to solve these problems,” he said. “Our traditional approaches to silicon are going to run out of gas, and we’ll have to roll up our sleeves and do things differently.” Gehlhaar didn’t indicate how soon that might be. Qualcomm has said that its coming generation of mobile chips will include software designed to bring deep learning to camera and other apps (see “Smartphones Will Soon Learn to Recognize Faces and More”).

Ren Wu, a researcher at Chinese search company Baidu, also said chips that support deep learning are needed for powerful research computers in daily use. “You need to deploy that intelligence everywhere, at any place or any time,” he said.

Being able to do things like analyze images on a device without connecting to the Internet can make apps faster and more energy-efficient because it isn’t necessary to send data to and fro, said Wu. He and Qualcomm’s Gehlhaar both said that making mobile devices more intelligent could temper the privacy implications of some apps by reducing the volume of personal data such as photos transmitted off a device.

“You want the intelligence to filter out the raw data and only send the important information, the metadata, to the cloud,” said Wu.

The First Self-Driving Vehicle You See May Have 18 Wheels

As reported by the NY Times:  Traveling about 55 miles per hour on a Nevada highway, the big rig's driver looked like The Thinker, with his elbow on the arm rest and his hand on his chin. No hands on the steering wheel, no feet on the pedals.

Mark Alvick was in "highway pilot" mode, the wheel moving this way and that as if a ghost were at the helm.

Daimler Trucks North America LLC says its "Inspiration" truck, the first self-driving semi-truck to be licensed to roll on public roads — in this case any highway or interstate in Nevada — is the future of trucking. It's a future that will still need drivers, but they might be called "logistics managers."

"The human brain is still the best computer money can buy," said Daimler Trucks North America LLC CEO Martin Daum on Wednesday.

Although much attention has been paid to autonomous vehicles being developed by Google and traditional car companies, Daimler believes that automated tractor-trailers will be rolling along highways before self-driving cars are cruising around the suburbs.

On freeways there are no intersections, no red lights, no pedestrians, making it a far less complex trip, said Wolfgang Bernhard, a management board member of Germany's Daimler AG, at an event in Las Vegas.

But it will be years before an autonomous truck hits the highway for anything more than tests and demonstrations, the company says.

The industry is watching the developments, said Ted Scott, director of engineering for American Trucking Associations, which represents trucking companies.

He questioned what the economic benefit would be, with companies paying a driver's salary on top of the new technology, even given the potential safety advantages including less-fatigued drivers.

"Being a tired driver is not as big of a problem as it's often made out to be," Scott said.

The group representing truck drivers — the Owner Operator Independent Drivers Association — isn't sure the technology would affect driving jobs, noting the abundance of job openings now and the industry's high turnover.

"We mainly have questions," said Norita Taylor, the group's director of public affairs, citing current laws regulating how long a driver can drive and prohibitions on texting while driving.

Al Pearson, Daimler Trucks' chief engineer of product validation, said all the same laws still apply: No texting, no napping while in motion.

"We need an attentive driver," he said, with the technology removing some of the stress.

Legal and philosophical questions stand in the way, as does perfecting the technology that links radar sensors and cameras to computers that can brake and accelerate the truck and handle any freeway situation.

Public perception of a self-driving car will also be a hurdle. Daum said society might forgive a number of deaths caused by tired truck drivers at the wheel but they would never forgive a single fatal crash blamed on a fully automated big rig.

For now four states, including Nevada, and the District of Columbia, certify testing of autonomous vehicles on public roads as long as a human driver is behind the wheel, and a few others are keen on allowing the tests.

Bernhard said more states need to allow testing of autonomous driving before fleets of self-driving semi-trucks fill U.S. freeways and interstates anytime soon.

The company is still far from taking customer orders for the trucks.

"We're just getting people inspired," he said.

The US Government Wants to Speed Up Deployment of Vehicle-To-Vehicle Communication

As reported by The Verge: Vehicle-to-vehicle (V2V) communication is one of the next big sea changes to hit the auto industry — within a few years, every new car on the road will be wirelessly talking with every other new car on the road, delivering position and speed information that can help prevent accidents. NHTSA had already committed to delivering a set of proposed rules for V2V by next year, but USDOT secretary Anthony Foxx doesn't think that's fast enough: he's asked the agency to "accelerate the timetable" in comments made this week. Additionally, he says that he's gearing up for "rapid testing" in concert with the FCC to make sure that there are no radio interference issues with V2V systems. (Various industry groups have been concerned that efforts to expand Wi-Fi spectrum in the US could cause issues with V2V.)

Even in its most rudimentary form, V2V can make a huge difference in safety by basically allowing drivers (and self-driving cars) to see things beyond their field of vision. I had a chance to test V2V-equipped cars at CES last year, and was immediately impressed: the system warns you of things like cars at intersections that may not be slowing down for a red light and emergency braking beyond the car ahead of you — scenarios that you'd have no way to detect otherwise before a crash was inevitable.

Apple Bought a Company Focused on Super-Accurate GPS

As reported by Engadget: Apple has snapped up more than a few companies that know how to deal with yourlocation data, but it now appears to be focused on improving the accuracy of that data from the get-go. MacRumors has discovered evidence that Apple recently acquired Coherent Navigation, a company specializing in very accurate GPS. It combined the usual GPS positioning with information from Iridium's low-orbit communication satellites to pinpoint your whereabouts within inches, rather than feet.

It's not clear just what the Coherent team is doing under Apple's wing. Its CEO and co-founders have taken positions in Maps and wireless technologies teams, but that's about as far as the revelations go.

We've reached out to Apple to confirm the deal, but it doesn't historically reveal what its plans are following buyouts. However, it could be for more than just ensuring that your Maps directions are on the mark. Apple is rumored to be developing an electric car with self-driving features that, by their nature, would depend on very accurate GPS info to get you around safely. There's no guarantee that Apple took on these new hires with autonomous vehicles in mind, but the move would at least make sense in that light.