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Image generation by AI is based on "generative models," a type of deep learning technology. Generative models can learn patterns in given data and generate new data similar to that data. There are two types of generative models: discriminative models, which solve problems such as classification and regression through supervised learning, and generative models, which generate new data. Discriminative models extract features from data to perform classifications, etc., while generative models can generate data from random noise. A generative model called a Generative Adversarial Network (GAN) was proposed by Ian Goodfellow in 2014; a GAN can generate realistic images by pitting two neural networks against each other.