NASA-IBM AI Model Aids Lunar Exploration with Accurate Ice Detection
IBM and NASA have released an open-source AI model to aid in lunar exploration. The NASA-IBM Lunar Foundation Model is designed to analyze decades of data from four NASA missions, including the Lunar Reconnaissance Orbiter. This tool can help researchers identify potential ice deposits on the Moon's permanently shadowed regions, map craters for safe landing sites, and study volcanic features.
The model has been trained on over 30 layers of data collected by nine instruments, and in benchmark tests, it identified key features up to 23 per cent more accurately than widely used methods. Lunar ice is significant because it indicates the presence of water and oxygen, essential resources for a future Moon base and rocket fuel for Mars missions.
NASA's Artemis programme plans to return astronauts to the Moon in 2028, testing technology for a sustained lunar presence and future Mars missions. The Prithvi family of open foundation models joins this tool, which spans geospatial, weather, and other applications.