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AI Image Generator such https://www.myimagegpt.com/ typically work by learning patterns and features from a large dataset of images during a training phase. For example, in the case of GANs, there are two neural networks involved: a generator network and a discriminator network. The generator network generates images, while the discriminator network evaluates whether the generated images are realistic or not. Through an adversarial training process, the generator learns to produce images that are increasingly indistinguishable from real ones. In contrast, autoregressive models like ImageGPT generate images pixel by pixel based on contextual information learned from vast amounts of image data.