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

• IBM and NASA released the open-source Lunar Foundation Model to analyse lunar data and support plans for a sustained human presence on the Moon.
• The AI model was trained on data from nine instruments across four NASA missions and improves identification of ice, craters, and volcanic features by 23 per cent over existing methods.
• The model aids in finding lunar ice, crucial for water and oxygen, supporting NASA's Artemis programme aiming to return astronauts to the Moon by 2028.

IBM and NASA on Sept 10 released an open-source AI model designed to help scientists analyse 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 per cent 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 programme plans to return astronauts to the Moon in 2028, testing new technology for a sustained lunar presence and future Mars missions. REUTERS