What are Generative Adversarial Networks (GANs)?

by andrewthomas on Sep 27th, 2024 06:30 AM

[ltr]Generative Adversarial Networks (GANs) are a class of artificial intelligence algorithms used in machine learning to generate new data samples that resemble existing data. Introduced by Ian Goodfellow in 2014, Generative Adversarial Networks consist of two neural networks: the generator and the discriminator. The generator creates fake data, while the discriminator evaluates its authenticity by distinguishing between real and generated samples. This adversarial process encourages the generator to improve its output, resulting in increasingly realistic data. GANs have applications in various fields, including image and video generation, art creation, and even enhancing image resolution. Their ability to produce high-quality, realistic data makes them a powerful tool in the realm of AI and deep learning.[/ltr]