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This Person Does Not Exist: What You Need to Know About Fake Faces

It is estimated that by 2024, 60% of data used for analytics projects and the development of AI will be generated synthetically. This means the data created is done so within the digital world instead of being collected from real-world examples. Using synthetic data is one of the most promising techniques in advancing the deep learning that AlgoFace solutions use. The concept of using an artificial intelligence algorithm to create human faces has made a significant impact on a variety of industries.

What Is “This Person Does Not Exist”?

“This Person Does Not Exist” is an AI face generator powered by StyleGAN, which was developed in 2018 by Nvidia. Opening the website produces an image of a random fake face that you can download. If you want to play the “this person does not exist” game and want another image, you simply refresh the page, and the image changes to a completely different fake face.

How Does GAN work?

GAN is a neural network that competes within itself to generate an image and then analyze whether it already exists or is ansynthetic data entirely new image. Once the initial phase succeeds in refining the image to the point that the second phase believes it’s new, the competition is complete, and the image is rendered.

Nvidia designs graphics cards are the engines behind the machine learning used for training algorithms. With access to the most sophisticated GPUs on the market, they were able to develop this cutting-edge technology, which was initially developed to improve AI’s recognition of fake faces and human faces in general.

How Synthetic Data is Generated

Synthetic data is information that is generated by computer simulations or algorithms. Data created synthetically can be produced at a fraction of the cost of an actual image and gives the developer an endless number of options to choose from. The need for datasets to train neural networks requires potentially millions of elements and is immensely time-consuming and expensive. But synthetic data is automatically generated and labeled, conserving both time and money.

This advanced technology can also be used in creating fake human faces as with the “This Person Does Not Exist” site. Also, deep fake technology can use synthetic data to create a face that looks nearly identical to that of a real person. This can be used, for example, to create computer-generated versions of real people that look good enough to fool movie fans—even on a high-definition screen.

Why Use Synthetic Data

synthetic data Synthetic Data is clearly the gold standard in privacy but there are also other advantages to using synthetic data in face AI. For example, synthetic data can be used to teach AI bias avoidance. It can also enhance fairness by assisting in the creation of more representative datasets that maximize diversity and equality. This occurs by adding more difficult to capture scenarios to the training datasets helping the AI model to be more accurate once it has been deployed.

How AlgoFace Uses Face AI

AlgoFace is also using face AI in a way that doesn’t compromise the identities of its users. Instead of using face AI for facial recognition, an application of face AI that AlgoFace never engages in, our technology generates facial landmarks that are overlaid on the image of someone’s face—without taking the extra step of associating the face with someone’s identity. In this way, our engine studies the key features of the face, and uses this data to examine the head position, expressions, the direction of the subject’s eye gaze, and more. Further, our VirtualBeauty application interprets facial landmarks, using the data to enable users to try on different kinds and shades of makeup. Contact AlgoFace today to find out the many ways your company can use our face AI platform to advance your business.