A thin sliver of Earth’s edge is brightly illuminated against the vast darkness of space in this April 3, 2026, image taken during the Artemis II mission. Artemis II was the first crewed flight in a series of missions to test NASA’s human deep space capabilities, paving the way for future lunar surface missions.
See more imagery from the Artemis II mission.
Image credit: NASA
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HQ Web Team
Through NASA, a university-designed small spacecraft is paving the way to studying particles, known as neutrinos, that move through the universe at near-light speeds. The Solar Neutrino Astro-Particle PhYsics CubeSat, known as SNAPPY, launched at 12 a.m. PDT on Sunday aboard a SpaceX Falcon 9 rocket from Space Launch Complex 4 East at Vandenberg Space Force Base in California and was deployed via launch integraor Exolaunch.
The SNAPPY project will test a prototype solar neutrino detector in low Earth polar orbit. Weighing approximately half a pound, the prototype detector consists of four crystals and is encased in a shielding block made of epoxy loaded with tungsten dust to match the density of steel. The detector and a dedicated electronics stack for power and readout purposes are housed inside a CubeSat platform from Kongsberg NanoAvionics.
The idea behind SNAPPY was sparked by interest in NASA’s Parker Solar Probe mission. As the probe prepared to become the first spacecraft to fly through the Sun’s corona, Nick Solomey, a professor of mathematics, statistics, and physics at Wichita State University, was inspired knowing the spacecraft would pass an area where the solar neutrino flux, the rate of particles passing through a specific area, is nearly 1,000 times stronger than what reaches Earth.
“All life on Earth – past, present, and future – relies on the Sun,” remarked Solomey, whose career is centered on elementary particle physics. “We must work to understand this ball of energy to the best of our abilities because it’s what makes life on Earth possible.”
Neutrinos are believed to be the second most abundant fundamental particles in the universe and could help us better understand the structure of the universe, the origin of mass, and the core of the Sun itself. On Earth, neutrino detectors must be buried deep underground to isolate their extremely faint signals. Using what we learn from SNAPPY, a future mission may one day place a detector closer to the Sun, allowing scientists to observe and study solar neutrinos in a completely new way.
Before such a mission is possible, researchers must understand how a neutrino detector performs in space, and SNAPPY is designed to take the critical first step. This includes proving it can operate reliably in orbit and eliminating signatures from other activities, such as energy interactions, that could mimic a true neutrino interaction in space. These measurements will help scientists determine whether a future large detector positioned closer to the Sun is feasible.
Through NASA’s Innovative Advanced Concepts program, within the Space Technology Mission Directorate, SNAPPY was selected for a Phase I award in 2018, followed by a Phase II award in 2019, and a Phase III award in 2021, helping mature the project from its early studies through flight demonstration.
NASA’s Marshall Space Flight Center in Huntsville, Alabama, designed and built the dedicated electronic readout cards for the SNAPPY detector, and Wichita State University graduate students programmed the payload computer to interact with the electronics.
To date, 36 graduate and undergraduate students have had the opportunity to work on the SNAPPY project. This achievement reflects the dedication of experts across agency and academia, including NASA Marshall, NASA’s Jet Propulsion Laboratory in Southern California, the University of Minnesota, the University of Michigan, and South Dakota State University.
To learn more, visit:
https://www.nasa.gov/about-niac/
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Loura Hall
4 min read
A team of researchers from Adelaide University and the SmartSat Cooperative Research Center in South Australia has successfully uploaded and demonstrated NASA and IBM’s open-source Prithvi Geospatial artificial intelligence (AI) foundation model aboard two in-orbit platforms, making it the first geospatial foundation model to be deployed in orbit. Trained on 13 years’ worth of data, Prithvi can facilitate a wide variety of Earth observation tasks.
By uploading a compressed version of Prithvi to the South Australian government’s Kanyini satellite and to the Thales Alenia Space IMAGIN-e (ISS Mounted Accessible Global Imaging Nod-e) payload aboard the International Space Station, the researchers tested the model’s flood and cloud detection performance across two different orbiting platforms and computing environments.
The team chose Prithvi for their research because of its strong generalization across Earth observation tasks, and because of its availability as an open-source model.
“If Prithvi weren’t open source, I would have to train my own foundation model,” said Dr. Andrew Du, the project’s lead researcher, who is a postdoctoral researcher at Adelaide University and an AI engineer at the SmartSat Cooperative Research Center. “Having that model openly available saved a lot of time and effort.”
A foundation model is an AI model trained on an enormous amount of unlabeled data, which allows the model to begin detecting patterns in the data that humans wouldn’t notice on their own. The model can then be fine-tuned for specific applications using much smaller amounts of labeled data.
“Prithvi is the first model of its kind to be deployed in orbit, and that demonstrates exactly why we make our AI models open source,” said Kevin Murphy, chief science data officer at NASA Headquarters in Washington, whose office led the collaboration that created Prithvi. “By sharing these tools with anyone who wants to use them, we accelerate scientific and technological development into the future.”
Developed by a team of data scientists from IBM and NASA’s IMPACT team within the Office of Data Science and Informatics at NASA’s Marshall Space Flight Center in Huntsville, Alabama, the Prithvi Geospatial model was trained on the Harmonized Landsat and Sentinel-2 dataset. This dataset compiles over a decade of global geospatial data from NASA’s Landsat and ESA (European Space Agency) Sentinel-2 satellites. Prithvi can be adapted for tasks such as mapping flood plains, monitoring disasters, and predicting crop yields.
Kevin Murphy
NASA Chief Science Data Officer and Acting Chief Data Officer/Chief AI Officer
Earth-observing satellites collect enormous amounts of data about our planet. Processing and analyzing the data in orbit before the satellite sends it back to Earth can help researchers gain insights more quickly. However, active satellites often can’t accept large software updates because of bandwidth limits, so the AI models they carry for data analysis tend to be lightweight and highly specialized.
Researchers can use the flexibility of a foundation model to facilitate a wide range of Earth observation tasks in one software architecture. If they want the model to take on a new task once the satellite is in orbit, they only need to upload a small extra decoder package – using far less bandwidth than uploading a whole new model to the satellite.
Sending Prithvi to orbit is an early demonstration of how foundation models could transform Earth observation. In addition to data analysis, foundation models could eventually help scientists interact with the instruments collecting the data.
“A large language model is also a type of foundation model,” Du said. “In the future, this could allow operators to interact with satellites in natural language, asking questions about onboard data or system status and receiving responses in a conversational way.”
The NASA team behind Prithvi continues to work on open-source foundation models trained on NASA data. A heliophysics model, Surya, was released in 2025, and the team intends to create foundation models for planetary science, astrophysics, and biological and physical sciences as well.
The Prithvi Geospatial foundation model is funded by the Office of the Chief Science Data Officer within NASA’s Science Mission Directorate at NASA Headquarters in Washington. The Office of the Chief Science Data Officer advances scientific discovery through innovative applications and partnerships in data science, advanced analytics, and artificial intelligence. To learn more about NASA’s AI foundation models and other AI tools for science, visit:
https://science.nasa.gov/artificial-intelligence-science
By Lauren Leese
Web Content Strategist for the Office of the Chief Science Data Officer
Powered by WPeMatico
Through NASA, a university-designed small spacecraft is paving the way to studying particles, known as neutrinos, that move through the universe at near-light speeds. The Solar Neutrino Astro-Particle PhYsics CubeSat, known as SNAPPY, launched at 12 a.m. PDT on Sunday aboard a SpaceX Falcon 9 rocket from Space Launch Complex 4 East at Vandenberg Space Force Base in California and was deployed via launch integraor Exolaunch.
The SNAPPY project will test a prototype solar neutrino detector in low Earth polar orbit. Weighing approximately half a pound, the prototype detector consists of four crystals and is encased in a shielding block made of epoxy loaded with tungsten dust to match the density of steel. The detector and a dedicated electronics stack for power and readout purposes are housed inside a CubeSat platform from Kongsberg NanoAvionics.
The idea behind SNAPPY was sparked by interest in NASA’s Parker Solar Probe mission. As the probe prepared to become the first spacecraft to fly through the Sun’s corona, Nick Solomey, a professor of mathematics, statistics, and physics at Wichita State University, was inspired knowing the spacecraft would pass an area where the solar neutrino flux, the rate of particles passing through a specific area, is nearly 1,000 times stronger than what reaches Earth.
“All life on Earth – past, present, and future – relies on the Sun,” remarked Solomey, whose career is centered on elementary particle physics. “We must work to understand this ball of energy to the best of our abilities because it’s what makes life on Earth possible.”
Neutrinos are believed to be the second most abundant fundamental particles in the universe and could help us better understand the structure of the universe, the origin of mass, and the core of the Sun itself. On Earth, neutrino detectors must be buried deep underground to isolate their extremely faint signals. Using what we learn from SNAPPY, a future mission may one day place a detector closer to the Sun, allowing scientists to observe and study solar neutrinos in a completely new way.
Before such a mission is possible, researchers must understand how a neutrino detector performs in space, and SNAPPY is designed to take the critical first step. This includes proving it can operate reliably in orbit and eliminating signatures from other activities, such as energy interactions, that could mimic a true neutrino interaction in space. These measurements will help scientists determine whether a future large detector positioned closer to the Sun is feasible.
Through NASA’s Innovative Advanced Concepts program, within the Space Technology Mission Directorate, SNAPPY was selected for a Phase I award in 2018, followed by a Phase II award in 2019, and a Phase III award in 2021, helping mature the project from its early studies through flight demonstration.
NASA’s Marshall Space Flight Center in Huntsville, Alabama, designed and built the dedicated electronic readout cards for the SNAPPY detector, and Wichita State University graduate students programmed the payload computer to interact with the electronics.
To date, 36 graduate and undergraduate students have had the opportunity to work on the SNAPPY project. This achievement reflects the dedication of experts across agency and academia, including NASA Marshall, NASA’s Jet Propulsion Laboratory in Southern California, the University of Minnesota, the University of Michigan, and South Dakota State University.
To learn more, visit:
https://www.nasa.gov/about-niac/
Powered by WPeMatico
Get The Details…
Loura Hall
4 min read
A team of researchers from Adelaide University and the SmartSat Cooperative Research Center in South Australia has successfully uploaded and demonstrated NASA and IBM’s open-source Prithvi Geospatial artificial intelligence (AI) foundation model aboard two in-orbit platforms, making it the first geospatial foundation model to be deployed in orbit. Trained on 13 years’ worth of data, Prithvi can facilitate a wide variety of Earth observation tasks.
By uploading a compressed version of Prithvi to the South Australian government’s Kanyini satellite and to the Thales Alenia Space IMAGIN-e (ISS Mounted Accessible Global Imaging Nod-e) payload aboard the International Space Station, the researchers tested the model’s flood and cloud detection performance across two different orbiting platforms and computing environments.
The team chose Prithvi for their research because of its strong generalization across Earth observation tasks, and because of its availability as an open-source model.
“If Prithvi weren’t open source, I would have to train my own foundation model,” said Dr. Andrew Du, the project’s lead researcher, who is a postdoctoral researcher at Adelaide University and an AI engineer at the SmartSat Cooperative Research Center. “Having that model openly available saved a lot of time and effort.”
A foundation model is an AI model trained on an enormous amount of unlabeled data, which allows the model to begin detecting patterns in the data that humans wouldn’t notice on their own. The model can then be fine-tuned for specific applications using much smaller amounts of labeled data.
“Prithvi is the first model of its kind to be deployed in orbit, and that demonstrates exactly why we make our AI models open source,” said Kevin Murphy, chief science data officer at NASA Headquarters in Washington, whose office led the collaboration that created Prithvi. “By sharing these tools with anyone who wants to use them, we accelerate scientific and technological development into the future.”
Developed by a team of data scientists from IBM and NASA’s IMPACT team within the Office of Data Science and Informatics at NASA’s Marshall Space Flight Center in Huntsville, Alabama, the Prithvi Geospatial model was trained on the Harmonized Landsat and Sentinel-2 dataset. This dataset compiles over a decade of global geospatial data from NASA’s Landsat and ESA (European Space Agency) Sentinel-2 satellites. Prithvi can be adapted for tasks such as mapping flood plains, monitoring disasters, and predicting crop yields.
Kevin Murphy
NASA Chief Science Data Officer and Acting Chief Data Officer/Chief AI Officer
Earth-observing satellites collect enormous amounts of data about our planet. Processing and analyzing the data in orbit before the satellite sends it back to Earth can help researchers gain insights more quickly. However, active satellites often can’t accept large software updates because of bandwidth limits, so the AI models they carry for data analysis tend to be lightweight and highly specialized.
Researchers can use the flexibility of a foundation model to facilitate a wide range of Earth observation tasks in one software architecture. If they want the model to take on a new task once the satellite is in orbit, they only need to upload a small extra decoder package – using far less bandwidth than uploading a whole new model to the satellite.
Sending Prithvi to orbit is an early demonstration of how foundation models could transform Earth observation. In addition to data analysis, foundation models could eventually help scientists interact with the instruments collecting the data.
“A large language model is also a type of foundation model,” Du said. “In the future, this could allow operators to interact with satellites in natural language, asking questions about onboard data or system status and receiving responses in a conversational way.”
The NASA team behind Prithvi continues to work on open-source foundation models trained on NASA data. A heliophysics model, Surya, was released in 2025, and the team intends to create foundation models for planetary science, astrophysics, and biological and physical sciences as well.
The Prithvi Geospatial foundation model is funded by the Office of the Chief Science Data Officer within NASA’s Science Mission Directorate at NASA Headquarters in Washington. The Office of the Chief Science Data Officer advances scientific discovery through innovative applications and partnerships in data science, advanced analytics, and artificial intelligence. To learn more about NASA’s AI foundation models and other AI tools for science, visit:
https://science.nasa.gov/artificial-intelligence-science
By Lauren Leese
Web Content Strategist for the Office of the Chief Science Data Officer
Powered by WPeMatico
