Recent advances in AI-based Image Generation spearheaded by Diffusion models such as Glide, Dalle-2, Imagen, and Stable Diffusion have taken the world of “AI Art generation” by storm. Generating high-quality images from text descriptions is a challenging task. It requires a deep understanding of the underlying meaning of the text and the ability to generate an image consistent with that meaning. In recent years, Diffusion models have emerged as a powerful tool for addressing this problem.

Diffusion models can be interpreted as stochastic encoder/decoder architectures, which are built around a residual architecture that successively applies a learned transformation.

By making the problem into a game and then utilising the machine-learning techniques that another of the company's AIs used to defeat human players in games like Go and chess, researchers at DeepMind in London have demonstrated that artificial intelligence (AI) can find shortcuts in a basic type of mathematical calculation.