NASA and IBM launch open-source AI for lunar mapping

NASA and IBM have released the NASA-IBM Lunar Foundation Model, an open-source artificial intelligence tool designed to accelerate lunar research and exploration. The model was trained on 17 years of data from NASA’s Lunar Reconnaissance Orbiter (LRO), including 2 million image tiles, as well as data from the GRAIL mission, Lunar Prospector, and Japan’s Selenological and Engineering Explorer.

The AI is capable of mapping craters, identifying volcanic features, and estimating the stability of ice in permanently shadowed regions. In comparative tests, the model demonstrated a 23% reduction in errors compared to Microsoft’s SwinV2-B system and outperformed it by 19% in crater recognition using only half the training data. The model also successfully identified a new impact crater created by a SpaceX Falcon 9 collision.

To support the scientific community, the codebase is available on GitHub, and the model is hosted on Hugging Face for public use.