THE ROLE OF THE PRINCIPLES OF OPERATION OF GENERATIVE ADVERSARIAL NETWORKS IN SOCIETY

Аннотация

В статье анализируются принципы работы технологии Generative Adversarial Networks и ее роль в обществе. GAN — это модель искусственного интеллекта, основанная на конкуренции между нейронными сетями генератора и дискриминатора. Эта технология позволяет создавать новые, реалистичные данные, такие как изображения, видео, музыка и другой креативный контент. Технология GAN также поднимает этические и социальные вопросы, такие как вредное воздействие технологии deepfake. В статье рассматриваются положительные и отрицательные эффекты GAN в различных областях, их влияние на общество и перспективы будущего развития. Ключевые слова: технология Generative Adversarial Networks, генератор, дискриминатор, нейронные сети, искусственный интеллект, модель, данные, Выпуск журнала №-26 Часть–6_ Май –2025 320 MODERN EDUCATION AND DEVELOPMENT изображения, видео, музыка, другой креативный контент, этика, технология deepfake. Generative Adversarial Networks (GANs) are one of the most revolutionary technologies in the field of artificial intelligence and machine learning. GANs are an artificial intelligence model consisting of two neural networks: one is a generator and the other is a discriminator. This network is able to create new information and identify existing information by working against each other. GANs technology was first proposed by Ian Goodfellow in 2014 and is currently successfully used in many areas such as image, video, music and even text generation. Studying the role of GANs in society and their impact in various fields helps to understand its social and economic aspects in a deeper way. How Generative Adversarial Networks (GANs) work. GANs consist of two main components: Generator: This neural network tries to create new information from random noise. The information it generates should be as close as possible to the real information available in the network itself. Discriminator: This neural network tries to determine whether the information generated by the generator is real or fake. The discriminator tries to distinguish between real data and data generated by the generator. These two neural networks work against each other: the generator network tries to fool the discriminator, and the discriminator tries not to fool the generator. This process trains the generator over time to produce more realistic and accurate data. As a result, GANs can create new data that has never been seen before, such as realistic images, videos, and music. Role and impact in society. Creative industries. The biggest impact of GANs technology has been on the creative industries, including art, fashion, film, and music. For example, GANs can be used to create artwork and manipulate images. Artists and designers are using GANs to create new and innovative images, logos, and digital artwork. With apps like DeepArt, users can turn their photos into images in the style of famous artists. Выпуск журнала №-26 Часть–6_ Май –2025 321 MODERN EDUCATION AND DEVELOPMENT In the fashion industry, GANs have made it possible to create new clothes and designs, analyze the market, and develop new collections based on customer demand. This technology has also made it easier to create virtual clothes and accessories and develop appropriate marketing strategies for them. Medicine and medical imaging. GANs are also making revolutionary advances in medicine. They can improve the processing and diagnosis of medical images. For example, in the field of radiology, GANs can be used to create medical images and images, detect diseases, and speed up diagnosis. GANs are also being used in genomic analysis and the development of new drugs. GANs technology can be used to work with genetic data, create new drug models and develop models to test their effectiveness. This will create innovations in the field of healthcare and help develop effective treatments for patients. Advertising and marketing. GANs technology has also found its place in the field of advertising and marketing. With the help of artificial neural networks, it is possible to create individual and personalized advertising content. For example, GANs can be used to create customized video ads and banners for users. Advertising agencies and companies are using the technology to create more creative and impactful ads using GANs. GANs also create the opportunity to create new designs and visual content for brands. Through these ads, companies can more effectively influence their target audience. Media and social networks. GANs technology is also widely used in media and social networks. One of the most famous examples of this is the "deepfake" technology. With the help of deepfake, it is possible to change people's faces, voices and even movements in images and videos. This technology is used in social networks, advertising, films and games. However, the social impact of deepfake technology can be unpleasant. If used for the wrong purposes, it can harm people's privacy, lead to information manipulation