IBM, NASA launch AI model to help map ice, craters on Moon

NASA-IBM Lunar Foundation Model is a public AI tool trained on data from nine instruments on four NASA missions

IBM and NASA on Thursday released an open-source AI model designed to help scientists analyze decades ​of lunar observation data and support plans for ‌a sustained human presence on the Moon.

The NASA-IBM Lunar Foundation Model is a publicly available AI tool designed to study the ​Moon. It was trained on more than ​30 layers of data collected by nine instruments ⁠on four NASA missions, including the Lunar Reconnaissance Orbiter.

The ​model joins IBM and NASA's Prithvi family of open ​foundation models, which span geospatial, weather and other applications.

It can help researchers identify potential ice deposits on the Moon's permanently shadowed ​regions, map craters to select safe landing sites and ​study volcanic features — tasks that have traditionally required scientists to sift ‌through ⁠maps and images manually or rely on lower-resolution machine-learning tools.

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In benchmark tests, the model identified key features on the lunar surface up to 23% more accurately than ​widely used ​methods, NASA and ⁠IBM said.

Lunar ice is of particular interest to space agencies because it indicates ​the presence of water and oxygen, resources ​considered essential ⁠for a future Moon base and for producing rocket fuel for missions to Mars.

ASA's Artemis program plans to ⁠return ​astronauts to the Moon in 2028, ​testing new technology for a sustained lunar presence and future Mars ​missions.