NASA and IBM's open source lunar model turns 17 years of orbiter data into a foundation for lunar science

NASA and IBM have released the Lunar Foundation Model, an open-source AI trained on 17 years of data from the Lunar Reconnaissance Orbiter. By analyzing nearly 2 million image bundles, the model improves the accuracy of polar ice deposit predictions by up to 22 percent. This development provides researchers with a specialized tool for lunar mapping and resource identification, lowering the barrier to entry for analyzing planetary data.