AI art is generated using machine learning algorithms and artificial intelligence techniques such as deep learning and neural networks. These techniques involve training algorithms on large datasets of images or other types of media to learn patterns and create new works of art based on those patterns.
One common method for generating AI art is through a process called "generative adversarial networks" (GANs). GANs consist of two neural networks: a generator network and a discriminator network. The generator network creates new images by trying to fool the discriminator network into thinking that the images it generates are real, while the discriminator network tries to distinguish between real and generated images.
Another popular method for generating AI art is through style transfer, which involves applying the visual style of one image onto another image. This can be done using convolutional neural networks (CNNs), which can learn to identify and separate the style and content of an image.
Overall, AI art is created through a combination of machine learning algorithms, neural networks, and human input and creativity.