The International Business Machines (IBM) and National Aeronautics and Space Administration (Nasa) on Thursday 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 program plans to ⁠return ​astronauts to the Moon in 2028, ​testing new technology for a sustained lunar presence and future Mars ​missions.