At its core, the Llama 3.2 vision models (available in 11B and 90B parameters) leverage a pre-trained image encoder to process visual inputs, which are then passed through the language model.

Researchers at the University of Pennsylvania and the Allen Institute for Artificial Intelligence have developed a groundbreaking tool that allows open-source AI systems to match or surpass the visual ...

Machines are rapidly gaining the ability to perceive, interpret and interact with the visual world in ways that were once ...

In the race to develop AI that understands complex images like financial forecasts, medical diagrams and nutrition labels—essential for AI to operate independently in everyday settings—closed-source ...

It employs a vision transformer encoder alongside a large language model (LLM). The vision encoder converts images into tokens, which an attention-based extractor then aligns with the LLM.

"Windows 11 is the home for AI," it adds, "offering the most expansive and capable AI experiences for consumers today on ...

A new Apple study introduces ILuvUI: a model that understands mobile app interfaces from screenshots and from natural language conversations.

Available via Hugging Face, the open-source model builds on the company’s previous OpenHermes-2.5-Mistral-7B model. It brings vision capabilities, including the ability to prompt with images and ...

Google DeepMind released PaliGemma 2, a family of vision-language models (VLM). PaliGemma 2 is available in three different sizes and three input image resolutions and achieves state-of-the-art perfor ...

Hugging Face Inc. today open-sourced SmolVLM-256M, a new vision language model with the lowest parameter count in its category.The algorithm’s small footprint allows it to run on devices such as ...