From The Chinese University of Hong Kong: A New Algorithm That Recognizes Faces Better Than People CanPosted: April 24, 2014
It’s already a little eerie when Facebook suggests tags for who it recognizes in your photo, especially for faces that are small, blurry, or otherwise difficult to distinguish. What if Facebook were even better–better at recognizing people in pictures than you are?
Two computer scientists are announcing they’ve made a program that is better at matching photos than people are, the Physics arXiv Blog reports. This is the first time a program has performed better than people at recognizing people.
To be sure, the new algorithm, developed at the Chinese University of Hong Kong, outperforms people in a very specific task with a very specific set of photos. The Hong Kong researchers asked the algorithm to tell whether two faces are the same, drawing from a set of 13,000 photos of 600 public figures. Humans get the right answer 97.53 percent of the time, on this test. The Chinese University of Hong Kong algorithm is right 98.52 percent of the time. (You can try some sample matches at the Physics arXiv Blog!)
For The Washington Times, Douglas Ernst reports: The Pentagon’s research agency tasked with developing breakthrough technologies for national security has come up with a plan for dealing with shrinking budgets: robotic flight crews..
The Defense Advanced Research Projects Agency (DARPA) is currently working on technology that will be able to replace up to five crew members on military aircraft, in effect making the lone human operator a “mission supervisor,” tech magazine Wired reported.
The Aircrew Labor In-Cockpit Automation System (ALIAS) would offer the military a “tailorable, drop-in, removable kit that would enable the addition of high levels of automation into existing aircraft to enable operation with reduced onboard crew,” DARPA said….(read more)
Note: Some good stuff can be found in IMDB’s Trivia page
Robot Space Trooper
I’ve been a black aircraft enthusiast all my life (and that goes back to the days when the SR-71 was still “secret”). Sweetman is one of the best aerospace/defense/mil-tech journalists around, although he’s been accused of being willing to run with a story a little too soon. I personally feel like he does sometimes report on rumors and informed speculation, but is careful to identify them as such.
At least as far as the available information on this one goes, I feel like this is a solid lead. The photos do not look photoshopped at all (there is a history of shopped pics among back plane chasers), and the aircraft does fit into a niche that many have wondered about — the US lacks a large, high-altitude, stealthy ISR platform and, as Sweetman points out, sat photos of Groom Lake (Area 51) show way more capability than can be accounted for with known programs.
So I put this one in the “definitely possible, maybe even probable” category.
Scientists in Japan are trying to create a computer program smart enough to pass the University of Tokyo‘s entrance exam, it appears.
The project, led by Noriko Arai at Japan’s National Institute of Informatics, is trying to see how fast artificial intelligence might replace the human brain so that people can start training in completely new areas. “If society as a whole can see a possible change coming in the future, we can get prepared now,” she tells the Kyodo news agency.
But there’s also another purpose behind the Can A Robot Get Into The University of Tokyo? project, which began in 2011. If machines cannot replace human beings, then “we need to clarify what is missing and move to develop the technology,” says Noriko Arai.
The Singularity is Coming and it’s Going To Be Awesome: ‘Robots Will Be Smarter Than Us All by 2029′Posted: February 23, 2014
Adam Withnall writes: By 2029, computers will be able to understand our language, learn from experience and outsmart even the most intelligent humans, according to Google’s director of engineering Ray Kurzweil.
“Today, I’m pretty much at the median of what AI experts think and the public is kind of with them…”
One of the world’s leading futurologists and artificial intelligence (AI) developers, 66-year-old Kurzweil has previous form in making accurate predictions about the way technology is heading.
[Ray Kurzweil's pioneering book The Singularity Is Near: When Humans Transcend Biology is available at Amazon]
When the internet was still a tiny network used by a small collection of academics, Kurzweil anticipated it would soon make it possible to link up the whole world.
Frances Martel reports: 2013 was a banner year for uncalled for expansion of China’s borders, from the Senkaku Islands Air Identification Defense Zone to a state TV show claiming the entirety of the Philippines for China. But on the economic front, China plans an expansion of a completely different kind: the use of robots to make manufacturing even cheaper.
Canada’s Globe and Mail has a feature out this week on China’s increased push to replace human labor with automated work. While China boasts some of the cheapest labor in the world–hence their domination of the manufacture of many simple to make items–salaries are, by necessity, increasing. This, argues author Scott Barlow, is pressuring the Chinese government to stay competitive economically with other nations by suppressing the growing wages. And to do that, he continues, businesses need to hire fewer people.
Klint Finley writes: Nothing beats a movie recommendation from a friend who knows your tastes. At least not yet. Netflix wants to change that, aiming to build an online recommendation engine that outperforms even your closest friends.
The online movie and TV outfit once sponsored what it called the Netflix Prize, asking the world’s data scientists to build new algorithms that could better predict what movies and shows you want to see. And though this certainly advanced the state of the art, Netflix is now exploring yet another leap forward. In an effort to further hone its recommendation engine, the company is delving into “deep learning,” a branch of artificial intelligence that seeks to solve particularly hard problems using computer systems that mimic the structure and behavior of the human brain. The company details these efforts in a recent blog post.
Netflix is following in the footsteps of web giants like Google and Facebook, who have hired top deep-learning researchers in an effort to improve everything from voice recognition to image tagging.
With the project, Netflix is following in the footsteps of web giants like Google and Facebook, who have hired top deep-learning researchers in an effort to improve everything from voice recognition to image tagging. But Netflix is taking a slightly different tack. The company plans to run its deep learning algorithms on Amazon’s cloud service, rather than building their own hardware infrastructure a la Google and Facebook. This shows that, thanks to rise of the cloud, smaller web companies can now compete with the big boys — at least in some ways.
I came across this last night:
In mid-2015, the asteroid probe Dawn is scheduled to establish orbit around Ceres, the only dwarf planet in the inner Solar System, as well as the largest asteroid, to begin roughly six months of close-up observation. The level of interest in this mission has significantly increased with the detection by the ESA’s Herschel space observatory of plumes of water vapor being exuded from Ceres’ surface from a pair of local sources.
It turns out that Ceres may have more water than all the fresh water on Earth. If that’s true, it may well be the the best place to actually create a robust human presence off Earth (after a real foothold is established on Earth’s moon). Some people might think that water would be useful on Mars, but why put it at the bottom of a gravity well one-third as deep as Earth’s?
Now the only question is: Who’s going to grab this uniquely valuable spot?
David Rotman writes: Given his calm and reasoned academic demeanor, it is easy to miss just how provocative Erik Brynjolfsson’s contention really is. Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator and coauthor Andrew McAfee have been arguing for the last year and a half that impressive advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years. Even more ominous for workers, the MIT academics foresee dismal prospects for many types of jobs as these powerful new technologies are increasingly adopted not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine.
Economic theory and government policy will have to be rethought if technology is indeed destroying jobs faster than it is creating new ones.
That robots, automation, and software can replace people might seem obvious to anyone who’s worked in automotive manufacturing or as a travel agent. But Brynjolfsson and McAfee’s claim is more troubling and controversial. They believe that rapid technological change has been destroying jobs faster than it is creating them, contributing to the stagnation of median income and the growth of inequality in the United States. And, they suspect, something similar is happening in other technologically advanced countries.
If self-replicating machines are the next stage of human evolution, should we start worrying?
George Zarkadakis writes: When René Descartes went to work as tutor of young Queen Christina of Sweden, his formidable student allegedly asked him what could be said of the human body. Descartes answered that it could be regarded as a machine; whereby the queen pointed to a clock on the wall, ordering him to “see to it that it produces offspring”. A joke, perhaps, in the 17th century, but now many computer scientists think the age of the self-replicating, evolving machine may be upon us.
It is an idea that has been around for a while – in fiction. Stanislaw Lem in his 1964 novel The Invincible told the story of a spaceship landing on a distant planet to find a mechanical life form, the product of millions of years of mechanical evolution. It was an idea that would resurface many decades later in the Matrix trilogy of movies, as well as in software labs.
In fact, self-replicating machines have a much longer, and more nuanced, past. They were indirectly proposed in 1802, when William Paley formulated the first teleological argument of machines producing other machines.