IBM, NASA Unveil AI Tool to Map Lunar Surface and Identify Ice Deposits

IBM and NASA have joined forces to create an open-source AI model designed to help scientists analyze decades of lunar observation data. The NASA-IBM Lunar Foundation Model is a publicly available tool that was trained on more than 30 layers of data collected by nine instruments on four NASA missions, including the Lunar Reconnaissance Orbiter.

The model can assist researchers in identifying potential ice deposits on the Moon's permanently shadowed regions and mapping craters to select safe landing sites. It also enables scientists to study volcanic features without relying on lower-resolution machine-learning tools or manually sifting through maps and images.

Benchmark tests have shown that the model accurately identifies key features on the lunar surface up to 23% more effectively than widely used methods, according to NASA and IBM.

The presence of lunar ice is crucial for future space missions as it indicates the availability of water and oxygen resources. These are essential for establishing a human presence on the Moon and producing rocket fuel for missions to Mars, particularly under NASA's Artemis program which aims to return astronauts to the Moon in 2028.