architectures

Diffusion Model

A generative model that learns to create data by reversing a gradual noising process. During training, noise is progressively added to data; the model learns to denoise step by step. At generation time, it starts from pure noise and iteratively refines it into coherent output.

In practice

Stable Diffusion and DALL-E 3 use diffusion models to generate images from text descriptions.

Stable Diffusion
An open-source text-to-image diffusion model developed by Stability AI that generates detailed images from text prompts. It operates in a compressed latent space for efficiency and has spawned a large ecosystem of community extensions and fine-tuned variants.
Text-to-Image
AI technology that generates images from natural language descriptions, translating text prompts into visual content. Text-to-image models have advanced rapidly from simple compositions to photorealistic and artistically sophisticated outputs.
GAN
Generative Adversarial Network, an architecture consisting of two neural networks: a generator that creates synthetic data and a discriminator that tries to distinguish real from generated data. The two networks train adversarially, pushing each other to improve.

In the index

Tools that mention Diffusion Model

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