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AIQuiet 10d · day 14

IBM and NASA open-source lunar AI model to map Moon for Artemis missions

The NASA-IBM Lunar Foundation Model integrates decades of multi-sensor data to help astronauts navigate terrain, find water ice, and prepare for long-term lunar habitation.

What to know

  • IBM and NASA have released the NASA-IBM Lunar Foundation Model, a multi-modal AI system that consolidates decades of lunar data to create the most comprehensive Moon map to date.
  • The model addresses longstanding challenges in handling high-volume, multi-sensor data at varying scales, integrating observations from missions like GRAIL and the Lunar Reconnaissance Orbiter.
  • NASA prioritizes three applications: mapping uncatalogued craters, investigating volcanic history, and locating water ice at the lunar poles to support Artemis missions and eventual Mars exploration.
  • The model uses a version of TerraMind architecture to handle sharp lunar lighting contrasts and terrain obstacles that would complicate human astronaut navigation.

IBM AI model developer and co-creatorNASA Space agency partner and Artemis program leadJuan Bernabé-Moreno Director of IBM Research Europe for Ireland and UKEuropean Space Agency (ESA) Co-developer of TerraMind, the underlying architecture

How it unfolded 1 development · click the chart to see its coverage articlesposts

Peak 7 pieces in 3h at Sep 15, 6 AM; 20 pieces over 14 days (1 article · 6 posts · 13 comments) Sep 14, 9 AM — 2 pieces · 1 article · 1 post — Hacker News 1, Newswires 1Sep 14, 12 PM — quietSep 14, 3 PM — quietSep 14, 6 PM — quietSep 14, 9 PM — quietSep 15, 12 AM — quietSep 15, 3 AM — quietSep 15, 6 AM — 7 pieces · 3 posts · 4 comments — Hacker News 4, Mastodon 2, Reddit 1Sep 15, 9 AM — 6 pieces · 1 post · 5 comments — Hacker News 5, Mastodon 1Sep 15, 12 PM — 1 piece · 1 comment — Hacker News 1Sep 15, 3 PM — 1 piece · 1 comment — Hacker News 1Sep 15, 6 PM — quietSep 15, 9 PM — quietSep 16, 12 AM — quietSep 16, 3 AM — quietSep 16, 6 AM — 1 piece · 1 comment — Hacker News 1Sep 16, 9 AM — quietSep 16, 12 PM — quietSep 16, 3 PM — 1 piece · 1 post — Mastodon 1Sep 16, 6 PM — quietSep 16, 9 PM — quietSep 17, 12 AM — quietSep 17, 3 AM — quietSep 17, 6 AM — quietSep 17, 9 AM — quietSep 17, 12 PM — quietSep 17, 3 PM — quietSep 17, 6 PM — quietSep 17, 9 PM — quietSep 18, 12 AM — quietSep 18, 3 AM — quietSep 18, 6 AM — quietSep 18, 9 AM — 1 piece · 1 comment — Hacker News 1Sep 18, 12 PM — quietSep 18, 3 PM — quietSep 18, 6 PM — quietSep 18, 9 PM — quietSep 19, 12 AM — quietSep 19, 3 AM — quietSep 19, 6 AM — quietSep 19, 9 AM — quietSep 19, 12 PM — quietSep 19, 3 PM — quietSep 19, 6 PM — quietSep 19, 9 PM — quietSep 20, 12 AM — quietSep 20, 3 AM — quietSep 20, 6 AM — quietSep 20, 9 AM — quietSep 20, 12 PM — quietSep 20, 3 PM — quietSep 20, 6 PM — quietSep 20, 9 PM — quietSep 21, 12 AM — quietSep 21, 3 AM — quietSep 21, 6 AM — quietSep 21, 9 AM — quietSep 21, 12 PM — quietSep 21, 3 PM — quietSep 21, 6 PM — quietSep 21, 9 PM — quietSep 22, 12 AM — quietSep 22, 3 AM — quietSep 22, 6 AM — quietSep 22, 9 AM — quietSep 22, 12 PM — quietSep 22, 3 PM — quietSep 22, 6 PM — quietSep 22, 9 PM — quietSep 23, 12 AM — quietSep 23, 3 AM — quietSep 23, 6 AM — quietSep 23, 9 AM — quietSep 23, 12 PM — quietSep 23, 3 PM — quietSep 23, 6 PM — quietSep 23, 9 PM — quietSep 24, 12 AM — quietSep 24, 3 AM — quietSep 24, 6 AM — quietSep 24, 9 AM — quietSep 24, 12 PM — quietSep 24, 3 PM — quietSep 24, 6 PM — quietSep 24, 9 PM — quietSep 25, 12 AM — quietSep 25, 3 AM — quietSep 25, 6 AM — quietSep 25, 9 AM — quietSep 25, 12 PM — quietSep 25, 3 PM — quietSep 25, 6 PM — quietSep 25, 9 PM — quietSep 26, 12 AM — quietSep 26, 3 AM — quietSep 26, 6 AM — quietSep 26, 9 AM — quietSep 26, 12 PM — quietSep 26, 3 PM — quietSep 26, 6 PM — quietSep 26, 9 PM — quietYesterday, 12 AM — quietYesterday, 3 AM — quietYesterday, 6 AM — quietYesterday, 9 AM — quietYesterday, 12 PM — quietYesterday, 3 PM — quietYesterday, 6 PM — quietYesterday, 9 PM — quietToday, 12 AM — quiet 1
Sep 15Sep 16Sep 17Sep 18Sep 19Sep 20Sep 21Sep 22Sep 23Sep 24Sep 25Sep 26now · 2:34 AM ET
  1. 1

    NASA prioritizes three applications: crater mapping, volcanic analysis, and ice prospecting

    NASA identifies three initial use cases for the Lunar Foundation Model: mapping smaller uncatalogued craters on the Moon's surface, investigating the Moon's volcanic history, and locating ice deposits in polar craters that could provide drinking water, oxygen, and fuel for future astronaut missions.

    “We hope that our AI model can help the science community explore the lunar landscape and help the next generation of astronauts find their way around before heading into space.”
    — Juan Bernabé-Moreno, Director of IBM Research Europe · source
    • Will roughly crash landing scrap on the moon cause nearby cave systems to collapse, and where are the caves to shelter from meteorite bursts in?"Removing these 50 objects from orbit would cut danger from space junk in half" https://news.ycombinator.com/item?id=45469259 :> When will it be safe and cost-efficient to - instead of deorbiting toward…

      westurnerHacker News9d agoview on Hacker News ↗
    2 more of the top 3 · 14 posts in this stretch
    • darkuncle@infosec.exchange

      This was pretty cool -- IBM and NASA have a new "multi-modal lunar model" that is a major improvement in our understanding of mapping the lunar surface, which will help significantly in future missions. Oh, and it's open sourced. :) https:// research.ibm.com/blog/nasa-ibm -lunar-foundation-model # space # AIforGood # AI

      darkuncle@infosec.exchangeMastodon11d agoview on Mastodon ↗
    • did not know we have -246°c to play with, which means the potential for the whole set of usefull volitiles is there, not just water/O²/H², and given that there is also the potential for +121°c very close to cold deposits, gives most of the basics for refining a whole host of molecules and compounds. Non of that changing the fact that bieng on the…

      metalmanHacker News12d agoview on Hacker News ↗
    all of them →
  2. background

    IBM and NASA open-source NASA-IBM Lunar Foundation Model — IBM and NASA publicly release a multi-modal AI model designed to map the Moon by consolidating and harmonizing decades of data from US and Japanese missions. The model is the first to integrate observations captured in multiple modalities at different viewing angles and spatial scales, built on a version of TerraMind, IBM's Earth-observation model developed with the European Space Agency.

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