Snippet: Mercury matches the performance of GPT-4.1 Nano and Claude 3.5 Haiku, running over seven times faster. Inception ...

A common denominator among all generative AI architectures is the use of a method known as the diffusion model, which takes inspiration from the physical process of gas molecule diffusion, where ...

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).

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.

The Stable Diffusion model is a state-of-the-art text-to-image machine learning model trained on a large imageset. It is expensive to train, costing around $660,000.

New research shows that threat actors can easily implant backdoors in diffusion models used in DALL-E 2 and open-source text-to-image models.

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 ...

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.