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Facebook’s Deepfake Detection Challenge, Announced the Winner

Facebook Deepfake detection challenge Deepfakes are synthetic media, in which a person in a video or image replaced by another face. 
Deepfakes have garnered widespread attention for their unethical use in celebrity pornographic videos, revenge porn, financial fraud and fake news.

So the detection of deepfakes are necessary in any platform to keep an eye on them.Doing so was the object of Facebook’s “Deepfake Detection Challenge”, which was launched last year.

Facebook wants to use AI to help fight back against AI generated fakes. To train AIs to spot manipulated videos, it is releasing the largest as about more than 100000 clips of deepfakes produced using 3,426 actors and a range of existing face-swapping techniques.

Facebook has also announced the winner of its Deepfake Detection Challenge, in which 2,114 participants submitted around 35,000 models trained on its data set. The best model, developed by Selim Seferbekov, a machine-learning engineer at mapping firm Mapbox, was able to detect whether a video was a deepfake with 65% accuracy when tested on a set of 10,000 previously unseen clips, including a mix of new videos generated by Facebook and existing ones taken from the internet.

“Deepfakes are currently not a big issue,” says Facebook’s CTO, Mike Schroepfer. “But the lesson I learned the hard way over last couple years is not to be caught flat-footed. I want to be really prepared for a lot of bad stuff that never happens rather than the other way around.”

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