NASA and IBM Open Source Lunar Mapping Tools
NASA and IBM have released an open-source AI model trained on a large collection of lunar observations to help scientists analyze the Moon at scale. "The NASA-IBM Lunar Foundation Model gives scientists a foundation to explore the Moon at scale, connecting observations across instruments, revealing patterns that are difficult to see in isolation, and providing an open platform the global research…
NASA and IBM have collaborated to release an open-source AI model trained on extensive lunar observations. The NASA-IBM Lunar Foundation Model enables scientists to analyze the Moon more effectively by integrating data from various instruments, revealing hidden patterns, and providing a platform for the global research community to build upon.
According to IBM's director of research for Europe, Juan Bernabe-Moreno, this marks the first AI model to incorporate observations in different formats, angles, and spatial scales. The primary goals are to identify previously unknown lunar ice deposits, analyze volcanic features known as Irregular Mare Patches, and classify and locate craters.
Lunar ice, if found, could be beneficial for future manned missions as it indicates the presence of water and oxygen. The AI model combines multimodal and multi-resolution observations to more accurately predict where ice may exist on the lunar surface. In addition to the model, IBM and NASA have compiled an open-source lunar dataset consisting of over 30 spatially-aligned layers, which includes tens of thousands of images and maps presenting various geophysical properties of the Moon's surface.
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