AI Glossary · Generative AI
Diffusion Model
A generative approach (used in Stable Diffusion, Imagen, Sora) that produces images or video by iteratively denoising random noise.
Definition
What is Diffusion Model?
Diffusion Model is a generative approach (used in Stable Diffusion, Imagen, Sora) that produces images or video by iteratively denoising random noise.
- Category
- Generative AI
- Glossary set
- 10 related terms
- Audience
- Enterprise AI leaders
Why does Diffusion Model matter in enterprise AI?
Diffusion Model matters in enterprise AI programs because it helps business and technology leaders align vocabulary, scope, ownership, and measurable outcomes.
Related terms in Generative AI
- Few-Shot Learning
- Guiding a model with a handful of examples in the prompt to shape output format or reasoning — no retraining required.
- Generative AI
- AI that creates new artifacts — text, code, images, audio, video — as opposed to only classifying or predicting.
- Image Generation
- Synthesizing images from text prompts (Midjourney, DALL·E, Imagen, Flux). Enterprise use: marketing, product design, synthetic training data.
- Latent Space
- The compressed internal representation where generative models operate; navigating it enables controllable generation and style transfer.
- One-Shot Learning
- Guiding a model with a single example — a common pattern for structured extraction and consistent formatting.
- Speech Synthesis (TTS)
- AI-generated speech from text, increasingly indistinguishable from human voices; the audio half of voice AI.