Generative Adversarial Networks (GANs)

Imagine a world where computers aren’t just learning from data, but are making up new stuff all by themselves – that’s where Generative Adversarial Network comes in. GANs represent a cutting-edge advancement in the field of artificial intelligence. They’re smart systems that learn from data, create new things like images and text, and they keep improving at it, sort of how artists get better with practice. Let’s now understand how a GAN works. Working of GAN GAN works on a principle of competition and collaboration between two neural networks: 1. Generator: The generator network's job is to create new data instances that resemble the training data from machine learning. It starts with generating random noise and gradually learns to transform it into data that looks like the real thing. For example, if it's trained on images of faces, the generator tries to create new faces that are realistic and indistinguishable from real ones. 2. Discriminator: The discriminator network acts ...