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Most of the academic research surrounding deepfakes focuses on the detection of deepfake videos. [172] One approach to deepfake detection is to use algorithms to recognize patterns and pick up subtle inconsistencies that arise in deepfake videos. [172]
According to Deloitte, a leading financial research group, AI-generated content contributed to more than $12 billion in fraud losses last year, and could reach $40 billion in the U.S. by 2027.
Some deepfake techniques include deepfake voice phishing, fabricated private marks, and synthetic social media profiles that contain profiles of fake identities. According to research, [ 1 ] deepfake prevention requires collaboration from key stakeholder such as internal firm employees, industry-wide experts, and multi-stakeholder groups.
Synthetic media (also known as AI-generated media, [1] [2] media produced by generative AI, [3] personalized media, personalized content, [4] and colloquially as deepfakes [5]) is a catch-all term for the artificial production, manipulation, and modification of data and media by automated means, especially through the use of artificial intelligence algorithms, such as for the purpose of ...
And last year, Facebook hosted the Deepfake Detection Challenge, an open, collaborative initiative to encourage the creation of new technologies for detecting deepfakes and other kinds of ...
Hany Farid (born February 10, 1966) [1] is an American university professor who specializes in the analysis of digital images and the detection of digitally manipulated images such as deepfakes. [2] Farid served as Dean and Head of School for the UC Berkeley School of Information . [ 3 ]
Deepfake video and audio have been used to create disinformation and fraud. In 2020, former Google click fraud czar Shuman Ghosemajumder argued that once deepfake videos become perfectly realistic, they would stop appearing remarkable to viewers, potentially leading to uncritical acceptance of false information. [159]
A direct predecessor of the StyleGAN series is the Progressive GAN, published in 2017. [9]In December 2018, Nvidia researchers distributed a preprint with accompanying software introducing StyleGAN, a GAN for producing an unlimited number of (often convincing) portraits of fake human faces.