AISixteen

DALL·E 2 can create original, realistic images and art from a text description. It can combine concepts, attributes, and styles. DALL·E 2 can can expand images beyond what’s in the original canvas, creating expansive new compositions. DALL·E 2 can make realistic edits to existing images from a natural language caption. It can add and remove elements while taking shadows, reflections, and textures into account. DALL·E 2 has learned the relationship between images and the text used to describe them. It uses a process called “diffusion,” which starts with a pattern of random dots and gradually alters that pattern towards an image when it recognizes specific aspects of that image. Our content policy does not allow users to generate violent, adult, or political content, among other categories. We won’t generate images if our filters identify text prompts and image uploads that may violate our policies. We also have automated and human monitoring systems to guard against misuse.

Karlo stands as a groundbreaking model for generating images based on text prompts. It builds upon OpenAI's remarkable unCLIP architecture but takes a step further by enhancing the standard super-resolution model, allowing it to recover intricate details at a remarkable resolution of 256px, all while minimizing noise through a limited number of denoising steps. To create Karlo, we embarked on an extensive training process. We started from scratch, utilizing a vast dataset of 115 million image-text pairs, which included COYO-100M, CC3M, and CC12M. In the case of the Prior and Decoder components, we harnessed the power of ViT-L/14, a text encoder from OpenAI's CLIP repository. To optimize efficiency, we made a significant modification to the original unCLIP implementation. Instead of employing a trainable transformer in the decoder, we integrated the text encoder from ViT-L/14.