https://www.techtarget.com/whatis/definition/deepfake

Deepfake technology is a type of artificial intelligence used to create convincing fake images, videos and audio recordings. The term describes both the technology and the resulting bogus content and is a portmanteau of deep learning and fake.

Deepfakes often transform existing source content where one person is swapped for another. They also create entirely original content where someone is represented doing or saying something they didn’t do or say.

Deepfakes aren’t edited or photoshopped videos or images. In fact, they’re created using specialized algorithms that blend existing and new footage. For example, subtle facial features of people in images are analyzed through machine learning (ML) to manipulate them within the context of other videos.

Deepfakes uses two algorithms — a generator and a discriminator — to create and refine fake content. The generator builds a training data set based on the desired output, creating the initial fake digital content, while the discriminator analyzes how realistic or fake the initial version of the content is. This process is repeated, enabling the generator to improve at creating realistic content and the discriminator to become more skilled at spotting flaws for the generator to correct.

The combination of the generator and discriminator algorithms creates a generative adversarial network.

A GAN uses deep learning to recognize patterns in real images and then uses those patterns to create the fakes.

When creating a deepfake photograph, a GAN system views photographs of the target from an array of angles to capture all the details and perspectives.
When creating a deepfake video, the GAN views the video from various angles and analyzes behavior, movement and speech patterns.
This information is then run through the discriminator multiple times to fine-tune the realism of the final image or video.