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Facebook’s machine learning team taught the program to recognize actions by asking humans to label 130,000 actual Facebook photos.
That machine learning system is behind a number of Facebook’s image-recognition features, from flagging nudity to fighting spam.
Lumos is a machine learning program, which means that the more photos it labels and the more details the team feeds it, the more accurate those photo labels become.
Feeding those descriptions into the machine learning program “taught” the system how to identify actions.
Shutterstock’s app now suggests keywords using AIToday, that system is getting an upgrade with the ability to recognize actions, not just objects.
Facebook Rolling Out New Artificial Intelligence for Photos
First, it’ll make it possible to search Facebook for photos based on what’s in them, rather than just by date taken, tags, or location.
That’s now beginning to change, thanks to new developments in the Menlo Park, Calif.’s artificial intelligence software.
Bloomberg—Bloomberg via Getty ImagesFacebook has long been able to recognize the people in your photos and sort images by where they were taken.
If you’re trying to find a photo of a paella dish you cooked last year, for example, you’ll be able to simply type “paella” in the Facebook search bar.
Services from other technology firms, like Google and Apple , also allow users to search their photos by content.
Facebook Rolling Out “Discover People” Tool to Help You Make New Friends
Facebook is rolling out a new tool to help you make friends with users of its massive social network.
Facebook has confirmed that Discover People just started rolling out and will gradually be available to all iOS and Android users, TechCrunch reports.
The tool is tucked away in the “more” menu navigation tab on the Facebook mobile apps, below “friends,” “events,” “groups,” “nearby places,” and other functions.
Much like the contact and profile suggestions you’d find on the likes of LinkedIn and Twitter, the new “Discover People” feature suggests people you have something in common with.
For example, it could match you with users based on the city you live in, Facebook groups you belong to, events you’ve shown an interest in, and work colleagues.
collected by :Roy Mark