What is Diffusion Model?
It is an artificial intelligence method that produces clean and meaningful images from noisy data.
Overview
Diffusion models are generative artificial intelligence systems that can create meaningful images from random noise, i.e. a tingly screen. It learns by cleaning the data step by step and eventually reveals the desired image.
How it works
During training, the model gradually adds noise to the images, making them completely unclear. Then he learns to reverse this process; that is, it reconstructs the original image from a noisy set of points.
Where it is used
DALL-E is used in rendering tools such as Midjourney and Stable Diffusion.
Commonly confused with
It is confused with GAN (Generative Adversarial Networks), but diffusion models produce more stable and high-quality results.
Frequently asked questions
Does it only produce images?
It is primarily visually focused but can also be adapted for audio and video production.
Why does it require so much processing power?
Building the image step by step requires intense processing power as it requires mathematical calculation of millions of pixels.
Related terms
This explanation was written in plain language for TreScout and machine-translated from the Turkish original · the Turkish version prevails. If something looks wrong or missing, write to hello@trescout.com. Read in Turkish →