What is deepfake video technology and how does it work?


Deepfake technology use artificial intelligence to replace the likeness of one person in video and other digital media with that of another.
Computers have steadily improving their ability to simulate reality. In place of the genuine settings and props that were once popular, modern film depends significantly on computer-generated sets, scenery, and characters, and most of the time these scenes are largely indistinguishable from reality.

What exactly is a deepfake and how does it function?
The name “deepfake” is derived from the underlying technology “deep learning,” which is a type of artificial intelligence. Deep learning algorithms are used to swap faces in video and digital information to create realistic-looking false media. Deep learning algorithms train themselves how to solve issues when given vast volumes of data.

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Deepfakes can be created in a variety of ways, but the most frequent is to use deep neural networks with autoencoders that use a face-swapping methodology. You’ll need a target video to utilize as the deepfake’s foundation, as well as a collection of video clips of the individual you wish to place in the target.

The videos can be completely unrelated; for example, the target could be a clip from a Hollywood film, while the films of the person you wish to include in the film could be random YouTube clips.

The autoencoder is a deep learning AI software tasked with analyzing video clips to determine how a person appears from various angles and environments, and then mapping that person onto the individual in the target video using common traits.

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Another type of machine learning, known as Generative Adversarial Networks (GANs), is added to the mix, which finds and improves any errors in the deepfake over numerous rounds, making it more difficult for deepfake detectors to decode it.

What are deepfakes and how do they work?
While the capacity to swap faces automatically to create credible and realistic-looking synthetic video has some interesting benign applications (such as in film and gaming), it is clearly a dangerous technology with some problematic applications. Synthetic pornography was one of the first applications of deepfakes in the real world.

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In 2017, a Reddit user known as “deepfakes” constructed a pornographic forum using face-swapped actors. Since then, pornography (especially revenge pornography) has repeatedly made headlines, wreaking havoc on the reputations of celebrities and public figures. Pornography accounted for 96 percent of deepfake videos discovered online in 2019, according to a Deeptrace analysis.

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