a generator network and a discriminator network. The generator network creates new images, while the discriminator network tries to distinguish between real and generated images. Through this adversarial process, the generator network improves its ability to create realistic images that can fool the discriminator network. Another recent technique is the use of stable diffusion models, which can turn text into images in just a few moments. These models work by gradually refining an initial random image towards the desired output, guided by the input text and a diffusion process that simulates the natural evolution of images. However, it's essential to recognize that even though AI image generators can create impressive results, there's often still a human element involved in the process, such as curating the training data or providing the initial text prompts.