Diffusion Models: The Unsung Heroes of AI Image Generation

Unlike transformer-based language models, diffusion models generate images by progressively removing noise from a noisy image. Training involves teaching the model to identify added noise, eventually allowing it to generate images from pure noise. This is akin to sculpting, gradually refining a rough block of stone into a masterpiece. While still nascent for text, diffusion models show great promise in image and video generation, as seen in OpenAI's Sora and Google's VEO. The core lies in how it models the relationship between noise and data, a stark contrast to transformers' focus on language structure.