NASA and IBM Open Source Lunar Mapping Tools (huggingface.co)
(Sunday September 13, 2026 @10:34PM (BeauHD)
from the new-discoveries dept.)
- Reference: 0185624496
- News link: https://science.slashdot.org/story/26/09/12/182253/nasa-and-ibm-open-source-lunar-mapping-tools
- Source link: https://huggingface.co/nasa-ibm-ai4science/NASA-IBM-Lunar-Foundation-Model
NASA and IBM have [1]released an open-source AI model [2]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 community can build on," said IBM director of research for Europe, Juan Bernabe-Moreno. The Register reports:
> It is claimed as the first AI model to integrate observations captured in a range of modalities (data formats), and at different viewing angles and spatial scales. Instead of sifting through maps and images by hand or using low resolution machine learning models, scientists can use this to analyze geographic features, the pair say. In particular, NASA and IBM hope researchers will be able to discover previously unidentified lunar ice deposits, analyze volcanic features called Irregular Mare Patches, and identify and classify craters.
>
> Lunar ice indicates the presence of water and oxygen, which may be useful for future manned missions. It is found in permanently shadowed regions, which are among the most difficult areas to observe. The NASA-IBM model combines multimodal and multi-resolution observations to better predict where ice may be present on the lunar surface. Alongside the model, IBM and NASA scientists compiled an open-source lunar dataset from over 30 spatially-aligned layers, using data from nine instruments across four missions. It combines tens of thousands of images and maps showing various geophysical properties of the lunar surface.
[1] https://huggingface.co/nasa-ibm-ai4science/NASA-IBM-Lunar-Foundation-Model
[2] https://www.theregister.com/ai-and-ml/2026/09/10/nasa-and-ibm-open-source-lunar-mapping-tools/5295633
> It is claimed as the first AI model to integrate observations captured in a range of modalities (data formats), and at different viewing angles and spatial scales. Instead of sifting through maps and images by hand or using low resolution machine learning models, scientists can use this to analyze geographic features, the pair say. In particular, NASA and IBM hope researchers will be able to discover previously unidentified lunar ice deposits, analyze volcanic features called Irregular Mare Patches, and identify and classify craters.
>
> Lunar ice indicates the presence of water and oxygen, which may be useful for future manned missions. It is found in permanently shadowed regions, which are among the most difficult areas to observe. The NASA-IBM model combines multimodal and multi-resolution observations to better predict where ice may be present on the lunar surface. Alongside the model, IBM and NASA scientists compiled an open-source lunar dataset from over 30 spatially-aligned layers, using data from nine instruments across four missions. It combines tens of thousands of images and maps showing various geophysical properties of the lunar surface.
[1] https://huggingface.co/nasa-ibm-ai4science/NASA-IBM-Lunar-Foundation-Model
[2] https://www.theregister.com/ai-and-ml/2026/09/10/nasa-and-ibm-open-source-lunar-mapping-tools/5295633
NASA always good with the taxpayer funded (Score:1)
by drnb ( 2434720 )
> NASA and IBM have released an open-source AI mode
NASA has always been pretty good at releasing software developed with taxpayer funding. Adding specialized AI models is a nice addition.
AI Goes to the Moon (Score:4, Insightful)
So we have finally reached the point where we need an AI foundation model to tell us what is hiding in the shadows on the Moon. Somewhere, a crater is now worried about being classified.
Jokes aside, this is actually one of the more sensible applications of these models. The interesting part is not that it is "AI," but that it combines data from multiple instruments and resolutions. Humans are pretty good at looking at one dataset and finding something interesting. We are considerably less good at mentally registering tens of thousands of observations from nine instruments and noticing that three seemingly unrelated measurements line up over the same patch of lunar real estate.
The open dataset may be even more valuable than the model. If researchers can reproduce the results, retrain it, and compare it against conventional geological analysis, we might eventually learn whether the model is actually discovering things or merely becoming extremely good at finding things that look like whatever was in its training data.
And if it helps locate lunar ice deposits, that has some pretty obvious practical value. Water on the Moon is not just something to drink; it potentially means oxygen, hydrogen, fuel, and considerably less stuff that has to be launched from Earth. Finding it before we start digging is probably a worthwhile use of compute.
Of course, the first scientist to publish "AI discovers giant face on Moon" is going to have some explaining to do.
Re: (Score:1)
I prefer [1]the Martian bear [universetoday.com].
[1] https://www.universetoday.com/articles/theres-a-crater-on-mars-that-looks-like-a-bear#more-159775