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NASA and IBM Unveil Open-Source Lunar AI Model
The open-source system can identify ice deposits and classify craters with 23% fewer errors than a Microsoft baseline, NASA and IBM said.
- On Thursday, NASA and IBM released the NASA-IBM Lunar Foundation Model, an open-source AI system available on Hugging Face for analyzing decades of lunar observation data.
- Researchers previously struggled to analyze disjointed, multi-mission lunar data, as manual reviews or low-resolution tools lacked the accuracy needed to identify geographic features across vast archives.
- The model outperforms widely used methods by up to 23% in identifying key geographic features, including potential ice deposits, craters, and volcanic formations called Irregular Mare Patches.
- IBM and NASA scientists also released a unified dataset containing over 2 million data points, providing a standardized framework for the global research community to build future models.
- These tools support NASA's Artemis program by providing essential mapping for safe landing sites and identifying water and oxygen resources critical for a sustained human presence on the Moon.
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NASA and IBM Open-Source Lunar AI Model to Map Ice, Craters and Volcanic Secrets
NASA and IBM released an open-source AI foundation model trained on lunar data from multiple missions. It improves ice detection by up to 23%, aids crater mapping and volcanic analysis with less compute. The unified dataset and adaptable model promise to accelerate lunar science ahead of Artemis missions.
IBM and NASA have unveiled an open source artificial intelligence model designed to help researchers analyze decades of data from lunar observations.
·Tehran, Iran (Islamic Republic of)
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Total News Sources59
Leaning Left4Leaning Right3Center13Last UpdatedBias Distribution65% Center
Bias Distribution
- 65% of the sources are Center
65% Center
L 20%
C 65%
15%
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