NASA, IBM Launch New AI Model for Studying the Moon
The model was mostly trained on Lunar Reconnaissance Orbiter data and is meant to speed analysis of NASA’s decades of moon observations.
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6 Articles
Permanently shadowed craters near the Moon’s poles may preserve water ice that future crews could turn into oxygen and hydrogen-based rocket propellant, potentially supporting lunar bases and eventual Mars expeditions. NASA and IBM have now released an AI model trained on roughly two million lunar images spanning more than 30 data layers—and in testing, it outperformed other leading models at mapping where polar ice is most likely to remain stable.
NASA and IBM's open lunar model reduced error by roughly 22 percent on an ice-prospectivity benchmark, while predicting a model-derived stability map rather than measured ice deposits.
NASA and IBM have developed an open-source artificial intelligence that could fundamentally transform lunar mapping. The basic model, created specifically for analyzing the lunar surface, not only shows outstanding accuracy in finding hidden water ice and craters, but also outperformed Microsoft's image analysis system in tests.
NASA and IBM launch an open source lunar AI that maps ice, craters and volcanoes with 17 years of data from Lunar Reconnaissance Orbiter. The NASA and IBM entry train an open source lunar AI with 17 years of data from Lunar Reconnaissance Orbiter aparece primero en Merca2.
The tool identifies features of the moon with greater precision in some tasks and will be available to researchers through Hugging Face. The NASA charge will use AI to study the lunar surface first appeared on Eleven News.
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