International Business MachinesIBM and NASA open-sourced the Lunar Foundation Model, an R&D/product release that outperforms existing methods in identifying lunar features.

IBM and NASA announced the open-source release of the NASA-IBM Lunar Foundation Model, one of the first publicly available foundation models for scientific exploration of the Moon. The model exceeds widely used methods by up to 23% in identifying key geographic features on the Moon's surface, including potential ice deposits, craters and volcanic formations. A NASA-IBM authored technical paper shows the model reduced error in identifying areas with high potential for lunar ice by up to 22% compared to the SwinV2-B (ImageNet) model, and at context-scale resolution of roughly 100 meters it outperforms SwinV2-B by nearly 19% using just half the training data. Alongside the model, IBM and NASA scientists built the first open-source lunar dataset of its kind, aggregating over 30 spatially-aligned layers from nine instruments across four missions, including data from NASA's Lunar Reconnaissance Orbiter and GRAIL mission and complementary data from the Japanese Aerospace Exploration Agency's SELENE/Kaguya. The release extends the IBM and NASA collaboration and joins the Prithvi family of open foundation models spanning geospatial, weather, heliophysics and now the Moon.
International Business MachinesIBM and NASA open-sourced the Lunar Foundation Model, an R&D/product release that outperforms existing methods in identifying lunar features.