NASA and IBM's Open Source Lunar Model Turns 17 Years of Orbiter Data Into a Foundation for Lunar Science
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NASA‑IBM Lunar Foundation Model: A Multimodal Lunar AI Backbone For Research, Not Navigation » Saipien
NASA and IBM turned 17 years of lunar data into a reusable AI backbone, usable for research, not for navigation NASA and IBM Research, with academic partners, released the NASA‑IBM Lunar Foundation Model (LFM). It’s a publicly available, pretrained multimodal foundation model built on SomBench, which the teams call the largest co‑registered lunar corpus to […]
NASA and IBM's open source lunar model turns 17 years of orbiter data into a foundation for lunar science
NASA and IBM have released the Lunar Foundation Model, one of the first open-source AI models for lunar science. Trained on nearly 2 million tile bundles, mostly from 17 years of Lunar Reconnaissance Orbiter data, it cuts the error in predicting polar ice deposits by up to 22 percent compared to the strongest model it was tested against. The article NASA and IBM's open source lunar model turns 17 years of orbiter data into a foundation for lunar…
NASA and IBM presented one of the first open source AI models for lunar research with the Lunar Foundation Model. Trained on nearly two million tiled bundles from 17 years of orbiter data, it predicts ice deposits in Poland up to 22 percent more accurately than previous comparative models. The article New Foundation Model by NASA and IBM is intended to accelerate water ice search on the moon first appeared on The Decoder.
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