Two distinct approaches for AI text generation are autoregressive and diffusion. Autoregressive models generate text token by token sequentially, a method used by most current language models. Diffusion models, however, operate more like sculpting, iteratively refining masked positions to generate text and potentially offering greater parallelism and faster generation.
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