Facebook News Update 2014: Facebook has the technology to match almost all the faces within it. Given that it owns the world's largest photo library.
According to Huff Post, 'Facebook announced last week that it has developed a program called "DeepFace," which researchers say can determine whether two photographed faces are of the same person with 97.25 percent accuracy.
According to Facebook, humans put to the same test answer correctly 97.53 percent of the time -- only a quarter of a percent better than Facebook's software.
Facebook has essentially caught up to humans when it comes to remembering a face. The program was developed by three in-house Facebook researchers and a professor at Tel Aviv University.'
DeepFace, the developers show an example in a paper on the program, can successfully recognize a photo of Sylvester Stallone.
When you upload a photo in Facebook, its facial recognition software is able to suggest friends to tag using information like the distance between eyes, nose and eyes in profile pictures and already tagged photos. 'But those results are much more inaccurate than DeepFace, which uses techniques from deep learning, a field of artificial intelligence specializing in understanding irregular types of data.' Report from the Huff Post said.
The program which was first reported on by the MIT Technology Review, is only a research project for now and will not affect the 1.23 billion people who use Facebook regularly.
However, Mark Zuckerberg, Facebook CEO, has expressed deep interest in building Facebook's artificial intelligence capabilities.
Zuckerberg described to analysts and investors on the call, "The goal really is just to try to understand how everything on Facebook is connected by understanding what the posts that people write mean and the content that's in the photos and videos that people are sharing. The real value will be if we can understand the meaning of all the content that people are sharing, we can provide much more relevant experiences in everything we do."
His ambition actually is to interpret mood and context not just facial recognition. He looks forward to analysing the text of status updates and comments to link it to some related sites. As an example, Huff Post stated, 'imagine a deep learning-enhanced Facebook as a jealous ex who stalks and overanalyzes your every online move. Instead of merely knowing you'd shared a photo, Facebook might be able to figure out that the snapshot showed a beach, along with a picture of your ex-boyfriend and that you two were smiling. When, a few days later, you post a status update, Facebook could perhaps analyze your phrasing to guess that you're lonely and depressed. And before long, you might be seeing ads for dating sites, antidepressants and funny films.'
'There's a business purpose behind all this intellectual enthusiasm: Understanding all the information we post on the social network is central to Facebook's business model, which leverages data to personalize ads so you'll be more likely to click on them,' Huff Post reported.
