Google’s Gemini Diffusion demo didn’t get much airtime at I/O, but its blazing speed—and potential for coding—has AI insiders speculating about a shift in the model wars.

Diffusion models are widely used in many AI applications, but research on efficient inference-time scalability, particularly for reasoning and planning (known as System 2 abilities) has been lacking.

When a diffusion model trains on this, it learns how to gradually subtract the noise, moving closer, step by step, to a target output piece of media (e.g. a new image).

AMD has officially enabled Stable Diffusion on its latest generation of Ryzen AI processors, bringing local generative AI image creation to systems equipped with XDNA 2 NPUs. The feature arrives ...

To do this, the model is trained, like a diffusion model, to observe the image destruction process, but learns to take an image at any level of obscuration (i.e. with a little information missing ...

Stability AI is out today with a new Stable Diffusion base model that dramatically improves image quality and users’ ability to generate highly detailed images with just a text prompt. Stable ...

TechSpot means tech analysis and advice you can trust. Forward-looking: Stable Diffusion is a deep learning model capable of turning words into eerie, distinctly artificial images.

The custom VAE that Easy Diffusion comes with, vae-ft-mse-840000-ema-pruned, smooths out some of the model's problems with human eyes and hands. Different models may have custom VAEs, but I rarely ...

This model is ideal for professional use cases at 1 megapixel resolution. Stable Diffusion 3.5 Large Turbo: A distilled version of Stable Diffusion 3.5 Large generates high-quality images with ...