Imagine looking at a picture of someone you’ve never met before, thinking that this person could be someone you pass by on the street, work with or might even be your neighbor. Only that person doesn’t exist. Or at least they don’t exist in the real world. They were created by a computer algorithm known as GAN, or Generative Adversarial Network. This is the technology behind “This Person Does Not Exist”, a website that generates hyper-realistic faces of people who never existed in the first place.

The Making of “This Person Does Not Exist”

In 2014, researchers at the University of Montreal developed an algorithm that could generate computer images that seemed almost indistinguishable from real ones. The following year, Apple Inc. researchers developed their version of the algorithm that can synthesize images of landscapes, birds, and animals. In 2017, NVIDIA developed GAN, a cutting-edge artificial intelligence algorithm that could create strikingly realistic faces without any pre-existing photos.


The algorithm that powers “This Person Does Not Exist” uses a neural network to synthesize entirely new images from scratch. All it takes is a single picture to generate another photograph of a person who doesn’t exist in reality. The algorithm consists of two neural networks that work together: the generator and the discriminator. The generator creates images, while the discriminator attempts to distinguish between real and fake ones.

Is GAN Technology Going Too Far?

The creation of this website has sparked debate over whether or not AI technology has gone too far. Some argue that the potential of GAN and similar AI algorithms could be utilized positively in areas such as entertainment or art. However, others argue that it might pose a considerable threat to both job security and society at large.

This Person Does Not Exist Image

One possible scenario is that GAN technology could render certain jobs obsolete. For example, imagine a scenario where you apply for a job, and the hiring manager conducts a background check by using pictures of fake people generated by GAN algorithms. This could present discrimination concerns if certain biases are encoded in the dataset used for training the algorithm. Moreover, the use of synthetic images could put traditional photographers or graphic designers out of business.

The Future of GAN Technology

GAN technology is still in its early stages, and its true potential has yet to be seen. While “This Person Does Not Exist” demonstrates the ability of GAN algorithms to generate photorealistic images of people, it’s just the tip of the iceberg. There are many more applications of GAN technology being researched, such as voice synthesis, video, and text. For instance, an AI algorithm could be trained to generate natural-sounding audio, which could revolutionize the field of voiceover and podcasting.

This Person Does Not Exist Image

Despite the potential benefits of GAN technology, there are also potential risks. As the world becomes more dependent upon technology, the line between what is real and what is artificial could become blurred. Deepfake technology, for instance, could be used to manipulate public opinion or to commit identity fraud.


What is GAN technology?

GAN, or Generative Adversarial Network, is an algorithm in the field of deep learning that uses machine learning to generate new data that is similar to pre-existing data. GANs are composed of two deep neural networks – a generator and a discriminator. The generator creates new data instances that are intended to slip past the discriminator, while the discriminator learns to recognize real data from the fake.

How is GAN technology being used outside of “This Person Does Not Exist”?

GAN technology is currently being used in various fields such as entertainment or art. For instance, it can be used to generate new music pieces in a specific style or combine elements of different styles. Another application is to generate computer graphics that would be difficult or even impossible for human designers to create. It is also used in the medical field, such as creating synthetic MRI images to supplement the patient’s data archive.

Video: How “This Person Does Not Exist” Works

In conclusion, as AI advances at a rapid pace, it is essential to consider the benefits of this technology as well as the potential risks and downsides. GAN technology is already being used for positive applications, but it remains to be seen if we can trust artificial intelligence to handle sensitive data and information reliably. For now, “This Person Does Not Exist” is a fascinating example of what GAN technology is capable of, but we have to be cautious about where it should be utilized and where it should not.

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