Artificial Intelligence (AI) has emerged as a transformative tool for establishing connections between data and acting as a tool that empowers humans to solve a wide variety of problems for which there were no easy solutions.  In heliophysics, AI has been applied to a wide variety of problems including space weather forecast, data calibration and homogenization, computer vision (i.e. segmentation), coronal field extrapolation, etc.  

However, compared to other communities, the scientific community is nearly a decade behind in terms of taking advantage of AI.  There are many factors behind this lag, including (but not limited to) access to computational resources, lack of expertise, lack of explainability, difficulty validating results, etc. The aim of this mini-workshop is to get feedback for the construction of HelioFM: a multi-purpose large AI foundation model, built with an extensive subset of SDO data and a complementary infrastructure to make it usable and useful to the heliophysics community.