NASA Uses AI to Read the Moon Before Humans Return to Its Surface
NASA and IBM Research have launched an open-source artificial intelligence model to extract new insights from nearly two decades of lunar data, aiding future crewed missions to the Moon. Announced Sept. 10, 2026, the NASA-IBM Lunar Foundation Model helps scientists map craters, locate potential ice deposits, and identify geological features. Co-developed with academic institutions, it […]
NASA and IBM Research have unveiled an open-source artificial intelligence model called the NASA-IBM Lunar Foundation Model, designed to extract new insights from nearly two decades of lunar data gathered by the Lunar Reconnaissance Orbiter (LRO). The model, announced on September 10, 2026, aims to help scientists identify craters, locate potential ice deposits, and recognize other lunar features.
Trained on 2 million LRO image tiles, the model leverages observations from various missions, including NASA's GRAIL and Lunar Prospector, and Japan's SELENE (Kaguya). This open-source AI model, available on Hugging Face and GitHub, streamlines access to NASA's extensive lunar archive, enabling researchers to adapt the pre-trained foundation model using smaller, specialized datasets for more efficient exploration and experimentation.
Kevin Murphy, NASA's chief science data officer, highlighted the model's potential to turn large-scale data into discoveries, emphasizing the role of AI in making NASA's petabytes of scientific data more accessible for scientists.
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