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By Space Force
The first cycle of the Space Force Generation model is currently underway, poised to manage the battle rhythm of assigned forces and maintain the highest possible level of overall readiness for the service.
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By NASA
2 min read
Geospatial AI Foundation Model Team Receives NASA Marshall Group Achievement Award
Rahul Ramachandran of NASA IMPACT, left, Elizabeth Fancher of NASA IMPACT, Ankur Kumar of the University of Alabama in Huntsville (UAH), Sujit Roy of UAH, Raghu Ganti of IBM Research, David McKenzie of NASA, Muthukumaran Ramasubramanian of UAH, Iksha Gurung of UAH, and Manil Maskey of NASA IMPACT, right, accept the NASA Marshall Space Flight Center Group Achievement Award on Thursday, August 15, 2024 at NASA Marshall. NASA NASA’s science efforts aim to empower scientists with the tools to perform research into our planet and universe. To this end, a collaborative effort between NASA and IBM created an AI geospatial foundation model, which was released as an open-source application in 2024.
Trained on vast amounts of NASA Earth science data, the foundation model can be adapted for Earth science applications such as flood, burn scar, and cropland studies. Tailoring the model for a specific task takes far less data than the original training set, providing an easy path for researchers to perform AI-powered studies.
For their groundbreaking work on this project, the development team behind the foundation model has received the NASA Marshall Space Flight Center Group Achievement Award. Their success with the model showcases their commitment to advancing AI and scientific research and will inspire progress in this field for years to come.
The team members from NASA’s Marshall Space Fight Center /IMPACT (Interagency Implementation and Advanced Concepts Team) are:
Rahul Ramachandran Manil Maskey Elizabeth Fancher The team members from the University of Alabama in Huntsville (UAH) are:
Sujit Roy Ankur Kumar Christopher Phillips Iksha Gurung Muthukumaran Ramasubramanian The team members from IBM are:
Ranjini Bangalore Juan Bernabe-Moreno Dario Augusto Borges Oliveira Linsong Chu Blair Edwards Paolo Fraccaro Carlos Gomes Raghu Ganti Adnan Hoque Johannes Jakubik Levente Klein Devyani Lambhate Gabby Nyirjesy Naomi Simumba Johannes Schmude Mudhakar Srivatsa Harini Srinivasan Daniela Szwarcman Rob Parkin Kommy Weldemariam Campbell Watson Bianca Zadrozny The team members from Clark University are:
Hamed Alemohammad Michael Cecil Steve Li Sam Khallaghi Denys Godwin Maryam Ahmadi Fatemeh Kordi To learn more about the NASA projects improving accessible science discovery for the benefit of all, visit the Open Science at NASA page.
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Last Updated Aug 15, 2024 Related Terms
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By NASA
Phil Kaaret (ST12) is lead author on the paper which describes Chandra X-ray Observatory observations of the galaxy NGC 2366. Escape of Lyman continuum (LyC) emission from galaxies found in the early universe was essential for the reionization of the universe when the intergalactic medium (IGM) changed from being neutral gas to the ionized IGM that we observe today. Compact emission-line galaxies (LCGs) are the most abundant class of confirmed Lyman continuum (LyC) emitters and provide (relatively) nearby analogs of the galaxies found in the early universe. An optical integral field study of NGC 2366 revealed an outflow originating at a star cluster known as “knot B” that is thought to clear a channel via mechanical feedback that enables LyC escape. We observed NGC 2366 with the Chandra and detected X-ray emission from a point source coincident with the apex of the outflow at knot B. The pointlike nature and variability of the X-ray emission suggests accretion onto a compact object in an X-ray binary. The accretion could produce sufficient kinetic energy to power the outflow. Thus, outflows from X-ray binaries may be important in enabling LyC emission from galaxies.
Read more at: https://arxiv.org/abs/2405.13192.
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By NASA
Rahul Ramachandran and Maskey (ST11/IMPACT) participated in IBM Think, where their IBM collaborators showcased two innovative AI applications for weather and climate modeling. The first application focuses on climate downscaling, enhancing the resolution of climate models for more accurate local predictions. The second application aims to optimize wind farm predictions, improving renewable energy forecasts. During the event, Ramachandran and Maskey were interviewed, highlighting the ongoing fruitful collaboration with IBM Research and its potential to advance climate science and renewable energy forecasting.
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