Open-source artificial intelligence model combines diverse lunar datasets to support scientific analysis of the Moon The NASA-IBM model reproduces patterns of lunar ice prospectivity (scaled from blue to yellow), shown at four locations (left) near the Moon’s pole. Top row: reference ice prospectivity map of Mons Mouton near the lunar south pole; middle row: predictions from the ConvNeXt model; bottom row: predictions from the NASA-IBM model. The NASA-IBM model preserves many fine-scale prospectivity patterns in the reference data. Image credit: NASA/IBM Research WASHINGTON, D.C., — September 18, 2026.  Universities Space Research Association (USRA) contributed planetary science expertise, lunar dataset development, and scientific evaluation to the newly released NASA-IBM Lunar Foundation Model, an open-source artificial intelligence (AI) model designed to help researchers analyze the large, diverse datasets collected by lunar missions.…