PROJECT SUMMARY As the NIDDK Information Network (dkNET) Coordinating Unit we must develop strategies to ensure that dkNET continuously evolves to meet community needs. As the use of a wide-array of methods that generate large amounts of complex data become more common in biomedical research, there is a growing need to develop an interdisciplinary workforce that can use and further refine computational and statistical approaches to interrogate this high-content data. Within this phase of dkNET, a new Computational Core has been introduced whose aim is to bring powerful new AI/ML techniques and cloud computing resources to the NIDDK research community to fully leverage data assets cataloged by dkNET to explore and develop hypotheses. Here we plan to continue the dkNET bioinformatics pilot program with a focus on AI to Accelerate Diabetes Research, to capitalize on the timely opportunity offered by recent AI advances. Specifically, this pilot program will: (1) develop AI foundation models for T2D; (2) validate the models with top research questions in T2D heterogeneity; (3) disseminate the models and engage the community for further development, validation and application; and (4) develop use cases that demonstrate the models’ potential in accelerating the tempo of research.