Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.
Bias in AI refers to systematic errors or prejudices that can occur within AI systems due to biased training data, faulty algorithms, or human…