Language models with billions of possible adjustments and trained on trillions of words are now powering the fastest-growing computing applications in history. Large Language models (LLM) are built using massive amounts of text, usually obtained by pulling data from multiple sources on the internet. Recent advances enable these models to process other kinds of data, including images, graphs and tables. Models with these abilities are known as multimodal LLMs. The best-performing LLMs currently deployed are proprietary, so their parameters, training data, code and documentation are not openly available. Thus, most artificial intelligence (AI) scientists cannot study, experiment directly with, or improve these state-of-the-art models. This project – Open, Multimodal Artificial Intelligence (OMAI) - will provide infrastructure in the form of a suite of powerful, well-documented, up-to-date, open models, and open-source interfaces designed for scientific work. Scientists will be able to access the models, use discipline-specific data and optimize the models. The project empowers researchers, provides documentation to accelerate research and education, and has an active program in early-career training to advance US economic and scientific competitiveness. In addition, opportunities provided through partnerships with a range of institutions and programs will enhance training. The long-term plan is to make the infrastructure available as a low- or zero-cost service to the research