Stable Diffusion is a latent diffusion model that generates AI images from text. Instead of operating in the high-dimensional image space, it first compresses the image into the latent space.
Stable Diffusion belongs to a class of deep learning models called diffusion models. They are generative models, meaning they are designed to generate new data similar to what they have seen in training. In the case of Stable Diffusion, the data are images.
Why is it called the diffusion model? Because its math looks very much like diffusion in physics. Let’s go through the idea.
The illustration below highlights the algorithms most frequently utilized in our everyday activities: They play a key role in everything we do from online shopping recommendations, navigation apps, social media, email spam filters and even smart home devices.
🔹 𝗦𝗼𝗿𝘁𝗶𝗻𝗴 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 – Organize data for efficiency. ➜ Example: Sorting email threads or search results.
🔹 𝗗𝗶𝗷𝗸𝘀𝘁𝗿𝗮’𝘀 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 – Finds the shortest path in networks. ➜ Example: Google Maps driving routes.
🔹 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 – AI models that understand context and meaning. ➜ Example: ChatGPT, Claude and other LLMs.
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