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DARPA’s new “Spectrum Collaboration Challenge” with a $2million prize for who can motivate a machine learning approach to dynamically sharing the RF Spectrum.


WASHINGTON, March 28, 2016 /PRNewswire-iReach/ — On March 23rd, 2016 DARPA announced its next Grand Challenge at the International Wireless Conference Expo in Las Vegas, Nevada. Program Manager, Paul Tilghman of DARPA’s Microsystems Technology Office (MTO), made the announcement to industry leaders following the conferences Dynamic Spectrum Sharing Summit. The challenge will motivate a machine learning approach to dynamically sharing the RF Spectrum and has been named the “Spectrum Collaboration Challenge.” A top prize of $2million dollars has been announced.

While mostly transparent to the typical cell phone or Wi-Fi user, the problem of spectrum congestion has been a long standing issue for both the commercial sector and Department of Defense. The insatiable appetite for wireless connectivity over the last 30 years has grown at such a hurried pace that within the RF community the term spectrum scarcity has been coined. RF bandwidth, the number of frequencies available to communicate information over, is a relatively fixed resource, and advanced communication systems like LTE and military communications systems consume a lot of it. As spectrum planners prepare for the next big wave of connected devices, dubbed the Internet of Things, they wonder where they will find the spectrum bandwidth they need to support these billions of new devices. Equally challenging, is the military’s desire to connect every soldier on the battlefield, while using these very same frequencies.

DARPA has chosen Barone Consulting to help develop the Spectrum Collaboration Challenge to address these critical infrastructure and military operation needs. In the tradition of other DARPA Grand Challenges, the Spectrum Collaboration Challenge provides an opportunity for experts across a wide variety of disciplines to devise groundbreaking strategies and systems and compete in open competition to win prizes, while advancing the state-of-the-art and seeding new technology communities. For the Spectrum Collaboration Challenge, the tasks are to combine distributed sensing techniques, innovative RF transmit and receive technologies, and cutting edge machine learning algorithms to create radio networks capable of learning to collaborate with other unknown radio networks, in real time.

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Clarius Mobile Health, a firm based outside of Vancouver, Canada, is unveiling a wireless ultrasound transducer that uses your Android or Apple iPhone as the display and control system. There aren’t many details provided by Clarius about the product, but the company expects these ultrasounds to be used for procedures such as nerve blocks and for helping to deliver needle injections. The device has yet to receive clearance from the world’s regulatory bodies.

Check out the preview video for the Clarius mobile ultrasound:

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And Steve Jobs was not yet back at Apple when he gave a remarkably prescient interview to Wired’s website the same year. Although the iMac, iPod, and iPhone were still years away, and Jobs was working at NeXT, he clearly saw where the computing industry was headed.

And although his later work at Apple clearly influenced the way things turned out, he still offered a slew of predictions that are shockingly accurate today.

Here’s what Jobs got right:

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POSTECH has created a solid oxide fuel cell (SOFC) that not only adds life to drones but can also replace lithium-ion batteries in smartphones.

Battery life. Two words that can turn anyone who owns an electronic device into a total wreck. But scientists at POSTECH may have found the solution to prevent you from having a panic attack each time you see your device almost out of juice.

Prof. Gyeong Man Choi and his Ph.D. student Kun Joong Kim have developed a miniaturized solid oxide fuel cell (SOFC) powerful enough to extend the flying time of drones to more than an hour. And that’s just the start.

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Researchers in Finland have figured out a way to reliably make quantum computers — technology that’s tipped to revolutionise computing in the coming years — even more powerful. And all they had to do was throw common sense out the window.

You’re almost certainly reading this article on a classical computer — which includes all phones, laptops, and tablets — meaning that your computer can only ever do one thing at a time. It reads one bit, then the next bit, then the next bit, and so on. The reading is lightning fast and combines millions or billions or trillions of bits to give you what you want, but the bits are always read and used in order.

So if your computer searches for the solution to a problem, it tries one answer (a particular batch of ones and zeros), checks how far the result is from the goal, tries another answer (a different batch), and repeats. For complicated problems, that process can take an incredibly long time. Sometimes, that’s good. Very clever multiplication secures your bank account, and faster or more efficient equation-solvers put that in jeopardy.

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Now, we’re hitting Terminator mode with this.


If you’re worried that artificial intelligence will take over the world now that computers are powerful enough to outsmart humans at incredibly complex games, then you’re not going to like the idea that someday computers will be able to simply build their own chips without any help from humans. That’s not the case just yet, but researchers did come up with a way to grow metal wires at a molecular level.

At the same time, this is a remarkable innovation that paves the way for a future where computers are able to create high-end chip solutions just as a plant would grow leaves, rather than having humans develop computer chips using complicated nanoengineering techniques.

DON’T MISS: iPhone 7: Everything we know so far

Researchers from IBM’s T.J. Watson Researcher Center are working to create wires that would simply assemble themselves in chips. The scientists use a flat substrate loaded with particles that encourage growth, and then add the materials they wish to grow the wire from.

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You may have never heard of AMD, but you’ve almost certainly used products powered by the company’s technologies.

AMD, or Advanced Micro Devices, is one of the biggest chipmakers in the world. The 46-year-old California company makes computer chips and all the related tech needed to power applications on PCs, smartphones, tablets, and more.

On Monday, AMD surprised everyone with its newest initiative: The Sulon Q, built out of a partnership with Ontario-based Sulon Technologies.

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https://youtube.com/watch?v=hX0UELNRR1I

A few weeks ago DJI unveiled its newest drone, the Phantom 4, the first craft to offer robust obstacle avoidance at a price the average consumer can afford. It relied on computer vision to power its autonomous flight, and since DJI had shown off this kind of tech before, we assumed that all the hardware on the Phantom 4 was homegrown, or backed by a giant like Intel. But today the chipmaker Movidius announced that its latest offer, the Myriad 2, was at the center of the onboard processor powering the Phantom 4’s incredible new abilities.

As it turns out this isn’t the first time Movidius has partnered with a big name to develop cutting edge technology. Back in 2014 its first chip, the Myriad 1, was revealed as the brains inside of Google’s first generation of Project Tango tablets. After a decade toiling in relative obscurity, the small 125 person company is suddenly poised to emerge as a leader at the intersection of several major markets — from drones to phones to virtual reality — which are looking for ways to enable cheap, power-efficient computer vision.

“The company was founded in late 2005, so we’ve had a long gestation,” says CEO Remi El-Ouazzane with a laugh. In its early years it found some business converting old movies into 3D, helping to shore up content offerings for the 3D TV market that never took off. In 2010 its chips were put to use as an engine for 3D rendering, but it was competing with plenty of established chip makers in that market. It wasn’t until 2013, and its partnership with Tango, that the company realized how widespread the application of computer vision could be, and focused in on optimizing for what it believed would be the next wave of devices.

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