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

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.

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.

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