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Algorithm

On The Media

Algorithms Understand

Friday, November 07, 2014

Can the algorithms built into social media really understand your emotional well-being? Munmun De Choudhury says yes, and explains how it works. 

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PRI's The World

Reading, math and ... Javascript? Coding is now mandatory in English schools

Thursday, September 25, 2014

This month, England launched one of the most ambitious computer education programs in the world. Every child from 5 to 16 will now learn computer programming, and advocates say it's not only vital but easier than you might think to teach schoolkids how to code.

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On The Media

Google Finally Speaks On the Record About Metafilter

Thursday, June 12, 2014

On TLDR episode #27, we talked to Matt Haughey, the owner of Metafilter, about how his site saw a sudden traffic drop in November, 2012. He attributed the drop to a change in Google’s algorithm, something we essentially couldn’t confirm because Google refused to comment. Danny Sullivan, who also featured in our story, reports that yesterday, Google’s search-swami Matt Cutts confirmed that Metafilter was indeed hit by a change in the algorithm.

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On The Media

Holding Algorithms Accountable

Friday, March 21, 2014

When an earthquake sent tremors through Los Angeles this week, an algorithm called Quakebot allowed the LA Times to release the news faster than any other media outlet. Bob talks with Nick Diakopoulos, a Tow Fellow at Columbia Journalism School, about what reporters should keep in mind as algorithms increasingly play a role in newsrooms.

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New Tech City

Machine Learning + Love

Wednesday, February 12, 2014

As the popularity of online dating sites rises, algorithms are playing a big role in finding Mr. or Mrs. Right. So what will it take to make the machine smarter at finding us love? 

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The Takeaway

A Crack at Algorithms: Bridging the Gap Between Humans and Computers

Tuesday, November 05, 2013

In a world where our lives are increasingly run by computers, algorithms have become the mathematical calculations at the center of how we find what movies to go see, what flights to take and what stocks to buy. This involves mathematical reasoning that can feel beyond the average person's reach. But Kevin Slavin, assistant professor at MIT and founder of the Playful Systems group at the MIT Media Lab, is trying to change that culture.

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Transportation Nation

Algorithm Predicts Red Light Runners

Monday, December 05, 2011

(Courtesy of MIT. Graphic by Christine Daniloff)

MIT has developed an algorithm to predict which vehicles will run a red light. That's useful for a future where cars talk to each other, or traffic signals respond dynamically to traffic.

There are more than 2.3 million accidents a year at U.S. intersections causing 7,000 deaths. About 700 of those fatalities are from red light running. MIT's algorithm aims to reduce that number by giving advanced warning to drivers -- or even just the car's computer braking system -- that another vehicle is approaching that is statistically likely to roll on through an intersection.

The MIT algorithm used sensors capturing vehicle speed, deceleration, and distance from intersection to predict with 85 percent accuracy which cars would run red lights and which wouldn't.

The U.S. Department of Transportation outfitted a Virginia intersection with censors that tracked the behavior of more than 15,000 vehicles, including when they ran a red light. This is part of a larger effort by the DOT to plan for a future where cars talk to each other in numerous ways that improve safety. As we've reported before, once cars can talk to each other, they will need to know what to say that actually improves safety. Early warning of a dangerous approaching vehicle would be near the top of the list.

The new MIT algorithm, with 85 percent accuracy, is an improvement of 15 - 20 percent over previous algorithms. As important as accuracy, the predictions proved early enough to be acted upon. Researchers found a “sweet spot” one to two seconds in advance of a potential collision where the algorithm was most accurate, and while a driver still had time to react if, say, a red danger light on the dashboard began flashing.

According to an MIT News Release, the researchers report their findings in a paper that will appear in the journal IEEE Transactions on Intelligent Transportation Systems.

Hat tip Gizmag.

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