New fully open source vision encoder OpenVision arrives to improve on OpenAI’s Clip, Google’s SigLIP

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The University of California, Santa Cruz has announced the release of OpenVision, a family of vision encoders that aim to provide a new alternative to models including OpenAI’s four-year-old CLIP and last year’s Google’s SigLIP. A vision encoder is a type of AI model that transforms visual material and files — typically still images uploaded by a model’s creators — into numerical data that can be understood by other, non-visual AI models such as large language models (LLMs). A vision encoder is a necessary component for allowing many leading LLMs to be able to work with images uploaded by users, making it possible for an LLM to identify different image subjects, colors, locations, and more features within an image. OpenVision, then, with its permissive Apache 2.0 license and family of 26 (!) different models spanning between 5.9 million parameters to 632.1 m ... Read full article.