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Google Buys Nest Labs for $3.2B

Google has purchased Nest Labs, the maker of smart thermostats and smoke alarms, for $3.2 billion.

Nest Labs, founded by Apple alums, first came on the scene in 2011 with its digital learning thermostat that has since shaken up the staid world of residential temperature control.

The move by Google pushes it further into the burgeoning world of connected homes, and raises privacy questions for those who have installed Nest thermostats in their homes.

“Google likes to know everything they can about us, so I suppose devices that are monitoring what’s going on in our homes is another excellent way for them to gather that information,” Danny Sullivan, a Google analyst, told The New York Times. Nest’s CEO, Tony Fadell, has said that Google will honor Nest’s privacy policy, which says the company will use customer information only for its product and services.

So far, Nest has tackled only thermostats and smoke detectors, but it has far larger plans that aren’t entirely clear at this time. Last fall, the company opened up its closed system with a developer program that will launch this year. The first partner is Control4, a home automation company, but many other companies will likely want to integrate with the darling of the thermostat market.

The reality is that the thermostat is just the beginning. Nest would ideally like to be the platform for the entire connected home. Some have speculated that the Nest Protect smoke detector, which would be in more rooms than the thermostats, could act as networking hubs.

“Google has the business resources, global scale and platform reach to accelerate Nest growth across hardware, software and services for the home globally,” Fadell said in a statement on Monday. “And our company visions are well aligned—we both believe in letting technology do the hard work behind the scenes so people can get on with the things that matter in life.”

Nest is already a direct threat to legacy thermostat companies, such as Honeywell, which sued Nest for patent infringement. Other companies that build digital smart thermostats that can be controlled from a smart phone might view Nest’s high profile and Google backing as a benefit because they will likely raise the awareness of the entire market. If Nest's prices stay high, consumers could take a closer look at other products with similar features at lower price points. 

But Google did not give up more than $3 billion just to dominate the thermostat market. Google previously had a home energy efficiency platform, PowerMeter, which it closed down in 2011. Home energy, however, is just one small piece of the puzzle. Google wants a stake in the coming Internet of Things, which is mostly about comfort, convenience and control throughout the home—even if the two companies wouldn’t speculate what that may look like when the deal was announced.

Nest will now pit itself against home networking providers. Security companies like ADT and have offerings that include smart thermostats, lighting and security features that can all be controlled from a smartphone, as do cable providers such as Comcast and Time Warner Cable.

Even with Nest's big brains and Google's deep pockets, building a seamless home network that allows disparate devices to talk to each other is still off on the horizon. Various groups, such as the AllSeen Alliance and the Internet of Things (IoT) Consortium are working on open-source standards to move the market forward.

“This is really early days,” Nest co-founder Matt Rogers said last week at a panel discussion about the connected home at CES 2014. “It reminds me of the days when we use to have these Internet portals. Now, there’s all these other services, like Google Now, where it just sends you an alert that you need to go to the airport now. That experience hasn’t transferred to the home yet, but it will in the next few years.”

The acquisition of Nest is Google’s second largest to date. The largest was the 2011 purchase of Motorola Mobility for $12.5 billion.

Photo: Nest Labs


Samsung Aims to Recruit Best of South Korea's Military

When Israel founded the Talpiot program to give the Israel Defense Forces a technological edge, it spawned new classes of tech-savvy warriors who went on to build the nation's booming tech sector. Now South Korea hopes to mimic the Talpiot program's success on a less ambitious scale by placing the best South Korean soldiers with tech giant Samsung.

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RAMBO Takes a 30-Tesla Magnetic Grip on the Benchtop

Some call it RAMBO—the Rice Advanced Magnet with Broadband Optics—though its builders often omit the name from the papers they send out for peer review. It’s a benchtop rig that combines single-digit-Kelvin temperatures, 30-Tesla pulsed magnetic fields, and spectroscopy in a compact package. The fields it generates dwarf those of common medical magnetic resonance imaging scanners (1.5 to 3 Tesla), and even that of the INUMAC MRI (11.74 Tesla) Tech Talk recently covered.

Rambo was built to shoulder some of the work previously possible only with the massive magnets of the U.S. National High Magnetic Field Laboratory, instruments weighing in at nearly 1000 times RAMBO’s bulk. These include the 32 000-kilogram constant-field 45-Tesla Hybrid in Tallahassee, Fla., and the new, 8200-kg, 100-Tesla pulsed field installation at Los Alamos. Think of Rambo as a lone warrior challenging a regiment.

As they report in the Review of Scientific Instruments, Rice University’s G. Timothy Noe—with principal investigator Junichiro Kono, and colleagues at Rice, Tohoku University in Sendai, Japan, and the Laboratoire National des Champs Magnétique Intenses in Toulouse, France—built RAMBO to study superfluorescence, a spontaneous flash of confined, incoherently excited atoms that suddenly and simultaneously release their color-coordinated photons in a sort of chain reaction of light.

The Kono laboratory’s superfluorescence work currently focuses on properties of condensed matter, including optical properties of exotic materials and magneto plasmas at terahertz frequencies, and the  “many-body interactions and Coulomb correlations” of super-cooled semiconductors, whose conductivity becomes very exactly quantized—the quantum Hall effect

RAMBO was designed with spectroscopy in mind: the benchtop is specifically an optical bench. In addition to the laser and a 9-kilojoule capacitor bank, the device consists of two cryostats (relatively slim cylinders less than three-quarters of a meter long, mounted on a heavy plate that precisely maintains their positions). One cryostat, slightly larger in diameter, holds the magnet, a sliver-and-copper-wire-wrapped, 43-mm-diameter doughnut with an inner bore of 12 mm. The smaller cryostat, cooled by liquid helium down to around 7 Kelvin, extends the sample, mounted on a sapphire “cold-finger” into the maw of the magnet.

The system is designed with two optically clear ports, so that a beam—laser or LED light, depending on the experiment's demands—can pass through the sample into a spectrometer (or other optical device) mounted on the bench outside the cold environment.

After it’s triggered, the magnet takes about 1.9 milliseconds to reach peak field intensity. During this time, the researchers can use the light source in a variety of ways. The Kono lab has tested several configurations, including:

  • a time-resolved mode, in which the sample is laser-illuminated several times as the magnetic field ramps up, to produce data for a range of magnetic field strengths;
  • a time-integrated mode, which uses a single laser pulse at maximum field strength; and
  • a transmission mode, using an 880-nanometer infrared LED.

Using RAMBO, the Kono team has been able to extend their studies of high-density electron-hole plasma in semiconductor quantum wells to encompass higher magnetic field strengths with better time resolution. They see the technique as opening doors to many new kinds of experiments on condensed matter in high magnetic fields.

Harnessing Alpha Particles to Spot Aircraft Icing

Given North America’s recent record-breaking cold with its thousands of cancelled airline flights, ice and aviation are very much in the news—especially the ice that cakes up on wings and tails, requiring trips to de-icing stations on the ground and constant vigilance aloft. Now a research team from the University of West Florida (UWF) and West Virginia University (WVU) has extended the principles of the household smoke detector to build and test a new way of warning fliers of impending danger.

Aloft, ice forms as super cooled water flows around an airfoil’s leading edge (it also forms deadly embolisms in engines, but that’s a different story). The crystallization starts at the most tightly curved part of the surface and works its way outward into plaque that can kill the wing’s lift or jam control surfaces. Most icing is easily visible from the cockpit: according to a handy NOAA primer on aircraft icing, grainy, white rime ice accounts for 72 percent of in-flight ice buildup.  About 21 percent of the time, however, water freezes into clear ice, which is nearly invisible. (The remaining cases are mostly mixtures of rime and clear ice).

To be sure, there are already instruments that help solve the problem: over the past decade, the avionics industry has developed several acoustic and optic sensors that detect wing icing. Most notable are pencil-stub-size spectrometers that shoot an infrared beam across a small, open-air gap and measure the signal returning from a reflector. Opaque rime ice blocks the beam, cutting off the return signal. Clear ice acts like a spliced-in chunk of optical fiber, reducing the beam’s dissipation and strengthens the return. The sensor reports either deviation.

Ezzat G. Bakhoum, leader of the UWF team, calls these solutions quick and reliable, but they have a common draw-back: These sensors are not embedded in the lifting surfaces, but are mounted separately. They detect icing in the sensor itself, not icing on the airframe. With graduate student Kevin Van Landingham and WVU’s Marvin H. M. Cheng, Bakhoum devised a system that responds to the amount of ice actually building up on the wing.

As they report in IEEE Transactions on Instrumentation and Measurement, the group turned to alpha particles, the bundles of two protons and two neutrons emitted by some radioactive isotopes as they decay. Alpha emitters include Americium 241, the element often used in household smoke detectors. Americium shoots out alpha particles, which have relatively high energies ( 5500 kiloelectronvolts, compared to the 100 keV or so of a medical x-ray photon) but high mass, low speeds, and little penetrating power. Indeed, a sheet of paper, the topmost layer of your skin, or a 50-micrometer-thick sheet of water or ice will block the beam.

With two protons and no electrons, alpha particles carry a positive charge, which is the key to their usefulness in sensors. To build their ice detector, the UWF researchers affixed a thin wafer of Americium (a chunk they describe as just slightly larger than used in smoke detectors) to the forward surface of a test plane’s wing, and mounted an aluminum electrode a few centimeters above it. If there is no ice or water on the wing, the stream of alpha particles pours into the electrode, transferring their charges to it. If even 100 micrometers of water coats the wing over the Americium wafer, it cuts off the alpha stream. By connecting the electrode to the gate of an n-channel MOSFET transistor, they can continuously monitor the electrode’s charge, and so instantly know how much of the alpha-particle stream is getting through. If the electrode charge drops to zero, the device flips a switch and sends a “wet” signal, indicating water or ice is blocking the beam.

That’s not enough to sound a klaxon in the cockpit, of course. Additional data and analysis have to be built into the instrument. The device’s output voltage fluctuates—and fluctuates more as airspeed increases.  In rain, the output fluctuates widely around “Gee, I’m wet,”  for example, while an ice-covered wing produces a steadier signal. With some built in signal-analysis logic and an attached thermometer, the ice sensor can reliably distinguish among a variety of environmental conditions.

Bakhoum and colleagues wind-tunnel tested the detector under seven different sets of conditions—clean dry air, very humid air, clouds, rain, ice crystals, dust, and lightning—at airspeeds of 0 to 900 kilometers per hour. Tests with dry, humid, cloudy air, and even dusty air, produced outputs that oscillated just above the 0-voltage “dry” reading.  Simulated rain produced output that jumped and spiked just below the 6-volt “wet” value. Only ice produced the steady “wet” value, seconded by the thermometer, and prompted  an icing alarm. (As for lightning: the artificial bolts confirmed that protective components did indeed keep the circuit from frying.)

Bakhoum calls the device “very robust and reliable” compared to optical detectors, and he expects that the device will be commercialized in the near future.

Images: Photo: Nicholas Eveleigh/Getty; E.G. Bakhoum/UWF

Another Transit System Tests Inductive-Charging Buses

A city known for its Gordian roundabouts and pedestrian-defeating roads is testing a clean new form of public transit: electric buses charged via induction. The borough of Milton Keynes, in the UK, will begin testing eight electric buses whose batteries get a charge from underground induction coils located at the start and end of their 25-kilometer route.

Inductive charging occurs when an electric current run through a coil, creates a magnetic field, which, in turn, induces current in any nearby conducting loops. When a bus stops at either of the charging stations, its on-board induction loops, lowered to 4 centimeters above ground, enter the magnetic field. The resulting current tops up its batteries enough to ensure it has enough energy to make it to the other end of the route and its next charge up. This scheme means the electric buses require less onboard energy storage, making them lighter and less challenging to produce from a design standpoint.

Milton Keynes will pioneer the UK's use of wireless vehicle charging, but other cities in Europe, such as Turin and Genoa, both in Italy, have been testing the technology since 2002. A German trial of a 200-kilowatt inductive-charging system began in September as part of a wider test. In 2010, IEEE Spectrum explored reasons why the technology is not in wider use. Among other reasons is the technology's low efficiency and the health effects of strong electromagnetic fields. That's why the bus's loop needs to get so close to the underground loop.

A Korean research team has taken the idea one step further and installed charging strips under an entire tram route, so vehicles on it won't need to stop to recharge, they wrote earlier this year in Spectrum. The Spanish city of Málaga is building a 5-km stretch of road for a setup like the on-the-go charging system fielded by the Korean researchers. Mass transit is a good place to start exploring electric induction for propulsion, since the locations of the vehicles are more predictable than those of private cars, but that isn't stopping major car and component makers from giving it a whirl.

Photo: Arriva

IBM Invests $1 Billion to Grow Watson Supercomputer's Struggling Business

IBM faces a puzzle that might give even the world's greatest detective pause: How to grow its "Jeopardy"-conquering Watson supercomputer into a $10-billion business within a decade. The company hopes to boost Watson's profit-making possibilities with a $100 million venture-capital fund aimed at spurring new apps based on the computer's problem-solving capabilities.

Watson achieved fame by beating human "Jeopardy" champions in several 2011 matches that showcased the computer software's learning capabilities. But an Oct. 2013 conference-call transcript (reviewed by The Wall Street Journal) reveals that Watson has struggled to translate its "Jeopardy" sleuthing into real-life problem-solving.

The IBM Watson business unit has generated less than $100 million so far. But the slow start has not stopped IBM from aggressively investing in Watson as a cornerstone of its future business. The company recently announced it is investing more than $1 billion in its Watson business unit and setting up a $100-million venture capital fund to encourage apps built on Watson's technology.

During the Oct. 2013 conference call, IBM CEO Virginia Rometty set forth the target of having Watson generate $10 billion in annual revenue within 10 years. She based her goal on the projection that Watson would earn $1 billion in revenue per year by 2018.

Watson's first customers hope to leverage the supercomputer's learning capabilities. In one case, Watson is working on recommending potential cancer treatments for specific medical cases based on a confidence percentage. The supercomputer learns from its mistakes when human physicians correct its errors during training.

But translating individual customers' business technicalities into usable software for Watson to process has been rough sledding for IBM engineers. That has led to delays in one of Watson's biggest client projects—an effort, involving the University of Texas M.D. Anderson Cancer Center, to make a version of Watson capable of recommending leukemia treatments by sifting through medical journals and books.

A similar healthcare application is in the works in conjunction with the Memorial-Sloan Kettering Cancer Center in New York City, where Watson would also serve as an adviser on cancer diagnoses and treatments. Watson has also found work with Wellpoint, the U.S. largest health insurer.

Turning Watson's "Jeopardy" smarts into huge business profits may seem anything but elementary for IBM at this point. But to the company's credit, it has continued to back Watson despite the early difficulties and has enlisted AI researchers to continue improving the supercomputer's capabilities as it reaches out to more potential customers.

Photo: IBM

Postmortem on Last Year's Predictions

One way to win the predictions game is to make a lot of guesses and remember just the winners. Here at IEEE Spectrum, we play a harder game. We told you what to expect in 2013, and now we are 'fessing up to our misses, as well as bragging about our hits. 

Truth be told, we're a bit proud of the misses as well. After all, it's not our fault if reality fails to meet our high standards!

Hit: We said that Google Glass would be big, that it would spawn a lot of associated business, and maybe even some copycatting. We were right on all counts. Woo-hoo! Japan's Telepathy One is bringing out a kind of augmented-reality visor; Epson just announced at CES it was doing the same. Innovega is going even further with a contact-lens and glasses combo.

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Innovega Delivers the Wearable Displays that Science Fiction Promised

Video: Celia Gorman
Photo: Innovega

There's a simple reason why we don't have immersive augmented reality displays in the form of sunglasses yet: it's impossible. Our eyes are not designed to focus on things that are as close to them as sunglasses are, and if you put a display at that distance, it'll be blurry.

Typically, the way to deal with this is to insert a bunch of clunky optics in between your eye and a display to allow your eye to deal with something that close, which is what a system like Google Glass does. But as you increase the display size and field of view (a requirement of truly immersive augmented reality), the amount of optics required to make it work increases geometrically, and eventually you'll end up with something very immersive but very gigantic like the Oculus Rift. Realistically, the widest field of view you'll be able to get in a compact wearable display is probably 25 or 30 degrees; Google Glass is just 13 degrees, and the much more chunky Epson Moverio only manages 23 degrees.

These compromises are not the future that we've been promised by science fiction and Google Glass concept videos—glasses with integrated wraparound high-resolution transparent displays that makes AR seamless and effortless. Fortunately, there's a way to solve everything to make immersive AR in a pair of glasses work, and it's easy: modify the eyeballs.

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Gordon Moore Giving Big to Big Data Scientists

Moore’s new law is that big data will lead to big science. The Gordon and Betty Moore Foundation plans to give US$1.5 million grants (in $200 000 to $300 000 yearly installments) to 15 worthy interdisciplinary scientists who can develop and use new algorithms, machine learning techniques, and other data-intensive science tricks to turn huge volumes of data into amazing scientific discoveries. According to the foundation, this is “likely the largest private investment in individuals who are pushing the frontiers of a new kind of data-driven science—inherently multidisciplinary, combining natural sciences with methods from statistics and computer science.”

Moore’s foundation seems to think that there’s already enough data out there or being generated for big discoveries to take place. The new money can’t be used for a big piece of equipment or experiments to obtain new data sets, only to analyze them in a new way.

The foundation may be right. Big projects like the BRAIN Initiative and big instruments like the Large Hadron Collider are already generating more data than scientists can use. One of the best examples of how science is drowning in data is in genetics where the cost of sequencing a genome has fallen so far and so fast that the analysis is falling behind.

The seeds of the data deluge problem were already apparent more than a decade ago, when networks pioneer John Hopfield told IEEE Spectrum he was already feeling as though scientists were taking the easy way out by going after new data instead of trying to squeeze insight out of what they’d already gathered. He challenged neural networks nerds to figure out the inner workings of a virtual mouse—really a collection of simulated neurons he and a colleague had strung together—using just a small set of data. Though the contest was won, it probably did little to abate the allure of just gathering more data.

Certainly new and interesting sources of scientific data are both needed and wanted. And it’s happening even without sophisticated new instruments. So called citizen science—where we ordinary folk act as environmental, geospatial, or medical sensors or gain access to remote scientific equipment and the resulting data—has been on the rise for years. It’s already produced great things like post-Fukushima radiation maps of Japan.

But Moore is probably right to lavish some cash on those who can find a way to make that data produce even more than its gatherers could have hoped for. Data-intensive science is here to stay. Also, data scientists are sexy, according to the Harvard Business Review. So the winners will be sexy and rich.

CES 2014 Trends: The 3-D Printing Industry Is Poised to Explode

The 2014 CES will be remembered as the year when 3-D printing arrived. Sure, there were plenty of grizzled veterans around who were willing to point out, as 3-D SystemsAvi Reichental did, that “3-D printing is an overnight success 30 years in the making.”

But on the other hand, there was poster-boy Bre Pettis observing that five years ago, “MakerBot was the only 3-D printing company at CES.” This year, CEA opened a zone of show floor dedicated to 3-D printing for the first time—it promptly sold out, had more space added, and then sold out again. (MakerBot itself announced no less than three new printer models at the show.)

However, many technologies have had notable arrivals at CES following years of patient nurturing, only to fall by the wayside—3-D TV, HD DVD, and the MiniDisc are just a few examples that spring to mind. So what are 3-D printing’s prospects like outside the CES bubble?

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