What Are Deepfakes and How Are They Created?

Yedukrishnan R
3 min readJun 12, 2021

This word comes from a combination of “fake” and “deep learning”. Deep learning is a kind of algorithm called “neural networks” that learns to replicate patterns by going through large data sets. With computing prowess created with machine learning, deepfake can create a convincing fake photo, audio or video.

How deepfakes are created

The main ingredient in deepfakes is machine learning, which has made it possible to produce deepfakes much faster at a lower cost. To make a deepfake video of someone, a creator would first train a neural network on many hours of real video footage of the person to give it a realistic “understanding” of what he or she looks like from many angles and under different lighting. Then they’d combine the trained network with computer-graphics techniques to superimpose a copy of the person onto a different actor.

The first step in establishing a GAN is to identify the desired output and create a training dataset for the generator. Once the generator begins creating an acceptable level of output, video clips can be fed to the discriminator.

As the generator gets better at creating fake video clips, the discriminator gets better at spotting them. Conversely, as the discriminator gets better at spotting fake video, the generator gets better at creating them.

The Benefits

Deepfake technology also has positive uses in many industries, such as movies, entertainment, games, social media, education, digital communications, healthcare, science, and business.

The film industry can benefit from deepfake technology in multiple ways. For example, it can improve amateur videos to professional quality, recreate classic scenes in movies, and create new movies starring long-dead actors. Deepfake technology can also help in making digital voices for actors who lost theirs due to disease.

Malicious deepfakes

Conclution

Although there are some concerns about such technologies, it can have various applications and also show how easy it is nowadays to generate fake stories, raising awareness about it.The understanding of how they work is the first step toward fighting them.

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Yedukrishnan R

Software Engineer , Machine Learning Enthusiast, Mulesoft certified developer