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In AI and machine learning, diffusion refers to a technique for generating new data by starting with real data and incrementally adding random noise. A diffusion model is a generative model where a neural network is trained to predict the reverse process, removing noise to recreate data. These models are commonly used to generate new data samples resembling the training set.