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In text-to-image retrieval, users input descriptive text, and CLIP retrieves images with matching embeddings. In image-to-text retrieval, images are used to find related text content. CLIP’s ability to connect visual and textual data has found applications in multimedia search, content discovery, and recommendation systems. [32] [33]
DALL-E, DALL-E 2, and DALL-E 3 (stylised DALL·E, and pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
The company said the tool correctly identified images created by DALL-E 3 about 98% of the time in internal testing and can handle common modifications such as compression, cropping and saturation ...
AI just took another huge step: Sam Altman debuts OpenAI’s new ‘Sora’ text-to-video tool. Christiaan Hetzner. February 16, 2024 at 5:12 AM. Andrew Caballero-Reynolds—AFP/Getty Images)
Last December, OpenAI said it was testing reasoning AI models, o3 and o3 mini, indicating growing competition with rivals such as Alphabet's Google to create smarter models capable of tackling ...
OpenAI o3 is a reflective generative pre-trained transformer (GPT) model developed by OpenAI as a successor to OpenAI o1. It is designed to devote additional deliberation time when addressing questions that require step-by-step logical reasoning. [1] [2] OpenAI released a smaller model, o3-mini, on January 31st, 2025. [3]
For text-to-image models, textual inversion [54] performs an optimization process to create a new word embedding based on a set of example images. This embedding vector acts as a "pseudo-word" which can be included in a prompt to express the content or style of the examples.