Posts Tagged ‘Algorithm’

We Robot 2013 | Do Robots Dream of Electric Laws? An Experiment in Laws as Algorithm.

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On April 8, 2013, Stanford’s Program in Law, Science & Technology and Stanford’s Center for Internet and Society hosted the second annual robotics and law co…
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Google updates Santa tracking algorithm, reopens North Pole privacy debate

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Old Saint Nick may be full of mystery and magic most of the year, but as soon as December 24th rolls around, all eyes are on the jolly fat man, especially in this era of always-on social media. Sure, it’s not the first to track Santa, but Google’s been in on the sled following game since 2004. Naturally, the company has refined its approach a bit over the years, and for 2012, Google’s offering up a new algorithm to track Mr. Kringle and his eight tiny reindeer’s route. The site counting down to the start of the Google Earth tracking is now live and you can also get in on the fun via a new Chrome Extension. As to whether you’ve been naughty or nice, you’ll just have to consult the traditional social media channels.

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Via: Google Maps Blog, Google+

Source: Santa Tracker, Google Chrome Store

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Can an algorithm take down terror cells?

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Paulo Shakarian, a teacher at West Point’s Network Science Center, has established an algorithm intended at shutting down decentralized terrorist organizations like al Qaeda. Wired takes an appearance at the paper, which proposes utilizing social-network analysis to tactically oblige the organization to become more centralized, rather than merely targeting leaders like Osama bin Laden or Abu Mussab al-Zarqawi. This method is inefficient, states Shakarian, because these amorphous teams “regenerate their leadership.” For more on Shakarian’s theory and algorithm, examine out the complete article at the source link below.

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MIT-created algorithm predicts likelihood of running red lights, places blame where appropriate

The bad news: Math will always judge you. The good news: It’ll still be there to judge everyone else. In a recent article published in the IEEE Transactions on Intelligent Transportation Systems, MIT‘s Professor Jonathan How and three colleagues announced they’ve created an algorithm that can predict whether an oncoming car is about to run a red light one or two seconds before a possible collision. The algorithm can compute the likelihood of a vehicle running a red light based on its rate of deceleration as it is approaching the intersection with a level of precision down to mere milliseconds. The team, which applied the algorithm to more than 15,000 vehicles during the study, used instruments that monitored vehicle speeds and locations as well as when the lights turned red. When the results were tallied, they found that they were able to correctly predict who would run a red light 85 percent of the time. In other news, MIT is working on a much simpler algorithm capable of predicting when your significant other will break up with you, the formula factoring in at least four behavioral elements from the last season of “Jersey Shore.”

MIT-created algorithm predicts likelihood of running red lights, places blame where appropriate originally appeared on Engadget on Fri, 02 Dec 2011 05:01:00 EDT. Please see our terms for use of feeds.

Permalink Los Angeles Times  |  sourceIEEE  | Email this | Comments

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Zdenek Kalal’s object tracking algorithm learns on the fly, likely to make next 007 flick (video)

Microsoft’s own OneVision Video Recognizer may be novel, but if the folks in Redmond are seriously looking to take things next-level, they should probably cast their gaze across the pond. Zdenek Kalal, a researcher at the University of Surrey, has just created what may be the most sophisticated vision system known to the civilian world. In essence, it takes the mundane task of tracking objects to an entirely new platform, enabling users to select an object on the fly and have the algorithm immediately start tracking something new. Within seconds, it’s able to maintain a lock even if your object twists, turns, or leaves / returns. Furthermore, these “objects” could be used as air mice if you force it to track your digits, and if you teach it what your staff looks like, you’ll have a fully automated security scanner that can recognize faces and grant / deny access based on its database of white-listed individuals. Frankly, we’d rather you see it for yourself than listen to us extolling its virtues — vid’s after the break, per usual.

Continue reading Zdenek Kalal’s object tracking algorithm learns on the fly, likely to make next 007 flick (video)

Zdenek Kalal’s object tracking algorithm learns on the fly, likely to make next 007 flick (video) originally appeared on Engadget on Thu, 31 Mar 2011 23:40:00 EDT. Please see our terms for use of feeds.

Permalink   |  sourceUniversity of Surrey (1), (2)  | Email this | Comments

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Google Helps Find Simplest Solution to Rubik’s Cube

No matter how mixed-up it is, the Rubik’s Cube can be solved in 20 moves or less, say a team of researchers who used computer time donated by Google to run complex algorithms to prove it.

That means all the 43,252,003,274,489,856,000 positions of the Cube require no more than 20 steps to get the Cube in shape.

“It took 15 years after the introduction of the Cube to find the first position that provably requires 20 moves to solve,” says the team on their webpage. “It is appropriate that 15 years after that, we prove that 20 moves suffice for all positions.”

The Rubik’s Cube, a 3-D puzzle, was invented in 1974 by a Hungarian sculptor and professor Erno Rubik. Rubik licensed it to be sold as a toy and since then it has turned into the world’s top-selling puzzle. As of January 2009, at least 350 million cubes have sold worldwide.

Solving the Rubik’s Cube can take anywhere from seconds to hours. The official championship record for 2008 is 7.08 seconds.

The shortest sequence of moves that the most efficient algorithm takes to solve the Cube is known as “God’s number.” In 1981, it was thought a maximum of 52 moves was required. By August 2008, it had been reduced to 22.

To get their number, the group — comprising math teachers, a Google engineer and a programmer — broke the larger problem of solving the Rubik’s Cube into 2,217,093,120 smaller problems. Each of these smaller problems had 19,508,428,800 different positions.

The subproblems were small enough to fit in the memory of a modern PC. But it would take an Intel four-core, 2.8-GHz Nehalem chip-based desktop computer 1.1 billion seconds, or about 35 years, to perform the calculation. So the team turned to the impressive computing power that Google has to solve the problem. (Google won’t disclose exactly what kind of computing resources it offered to the group.)

If you’d like to geek out further on the math of solving the Rubik’s Cube efficiently, the Cube 20 site has all the details.

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Photo: (Marc Brakels/Flickr)

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Google Helps Find Simplest Solution to Rubik’s Cube

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Microsoft algorithm uses six-axis motion sensors to fix blurry snapshots, inadvertantly pimping your ride

Trying to snap a shot of your cherry red Mazda, but can’t keep your hands still? You’ll find all the tech you need to smooth things out in an iPhone 4 or (MotionPlus-equipped) Nintendo Wiimote. Experimenting with 6DOF inertial measurement sensor packages, scientists at Microsoft Research have developed a software algorithm that literally records your exposure-destroying shake via accelerometer and gyroscope, then magically removes the blur by canceling it out. While the technique still isn’t perfect — spot ghostly line above some of those background cars — the Microsoft researchers compared their results to other in-progress algorithms, and we think you’ll agree this new solution presents the best results by far. It’s a shame Microsoft doesn’t say when we’ll see the tech in a spiffy DSLR attachment, or better yet a cameraphone. See before and after animated GIFs after the break, and find high-res comparison images and much more at our source link.

Continue reading Microsoft algorithm uses six-axis motion sensors to fix blurry snapshots, inadvertantly pimping your ride

Microsoft algorithm uses six-axis motion sensors to fix blurry snapshots, inadvertantly pimping your ride originally appeared on Engadget on Mon, 02 Aug 2010 12:44:00 EDT. Please see our terms for use of feeds.

Permalink Slashdot  |  sourceMicrosoft Research  | Email this | Comments

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Google Changes Search Algorithm To Include Site Speed As A Ranking Factor

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Google has kept a promise it made last year: Site speed is now a ranking factor in Google’s algorithm, and is already in place for U.S. searchers.

But Google also cautions web site owners not to sacrifice relevance in the name of faster web pages, and even says this new ranking factor will impact very few queries.

Keep reading at Search Engine Land >

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See Also:

  • MARCH SEARCH SHARE: Get This — Bing And Yahoo Up, Google DOWN
  • Google Wants To Hire 500 Ad People Right Now
  • Google Makes Gmail Easier



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Dung Beetle Inspired Algorithm Enhances Video Shot in Almost Pitch Black Environments [Cameras]

Click here to read Dung Beetle Inspired Algorithm Enhances Video Shot in Almost Pitch Black Environments

Swedish startup Nocturnal Vision thinks their new dung beetle inspired algorithm can be integrated into cellphone cameras to allow people to capture high-quality video in low-light environments. They’ve already got Toyota investing in the algorithm for automobile night vision systems. More »







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