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[TECHNOLOGY] · United States, Japan · 2 sources

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Part of situation: NASA-IBM lunar exploration AI model release (2 clusters)

NASA and IBM release open-source lunar foundation model

lunar foundation model machine learning moon science open-source AI lunar data

NASA and IBM Research have released an open-source lunar foundation model designed to advance lunar science through machine learning. The model was trained from scratch using SomBench, described as the largest co-registered multimodal lunar corpus to date, containing nearly 2 million tile bundles across 11 modalities.

The dataset integrates 17 years of observations from NASA’s Lunar Reconnaissance Orbiter (LRO), alongside data from the GRAIL mission, Lunar Prospector, and JAXA’s Kaguya/SELENE probe. This collection includes over 30 spatially aligned data layers from nine instruments and four missions.

Unlike task-specific algorithms, this foundation model can be adapted to various scientific tasks with minimal labeled examples. Key applications include crater detection, the segmentation of Irregular Mare Patches, and predicting potential ice deposits at the lunar poles, where the model shows particular strength.

Entities

IBM Research · JAXA · Lunar Reconnaissance Orbiter · NASA

Sources

Lunar Foundation Model Advances Moon Science [stratnewsglobal.com]
NASA and IBM's open source lunar model turns 17 years of orbiter data into a foundation for lunar science [the-decoder.com]