IBM and NASA have released an open-source artificial intelligence model designed to help scientists analyze decades of lunar observation data and support plans for a sustained human presence on the Moon.
The Lunar AI model, known as the NASA-IBM Lunar Foundation Model, is publicly available and was developed to study the Moon’s surface. It was trained using more than 30 layers of data collected by nine instruments aboard four NASA missions, including the Lunar Reconnaissance Orbiter.
The model is part of IBM and NASA’s Prithvi family of open foundation models. The series includes models designed for geospatial, weather and other scientific applications.
Researchers can use the new model to identify possible ice deposits in permanently shadowed regions of the Moon. It can also help map craters for safer landing-site selection and analyze volcanic features.
These tasks have traditionally required scientists to examine large numbers of maps and images manually. Earlier machine-learning tools also often relied on lower-resolution data.
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NASA and IBM said benchmark tests showed the model could identify important lunar surface features up to 23% more accurately than widely used existing methods.
Lunar ice remains a major focus for space agencies. Its presence could provide access to water and oxygen, resources that may be essential for future lunar bases. Water could also potentially support the production of rocket fuel for missions to Mars.
NASA’s Artemis program plans to return astronauts to the Moon in 2028. The program aims to test technologies for sustained lunar exploration and help prepare for future human missions to Mars.
