Stanford's Marin project aims to redefine openness in AI by providing complete transparency throughout the foundation model development process, including sharing code, datasets, and training methodologies. Utilizing JAX and a new framework called Levanter, the project addresses key engineering challenges to ensure reproducibility and efficiency in training large-scale models. By fostering collaboration and trust, the Marin project invites researchers to participate in advancing foundation model research.