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By NASA
2 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Multinational corporations are using the M2M Intelligence platform in data centers and other settings. The system offers automated, secure communications on a ground-based global 5G network. Getty Images Artificial intelligence (AI) is advancing rapidly, as intelligent software proves capable of various tasks. The technology usually requires a “human in the loop” to train it and ensure accuracy. But long before the arrival of today’s generative artificial intelligence, a different kind of AI was born with the help of NASA’s Ames Research Center in California’s Silicon Valley — one that only exists between machines, running without any human intervention.
In 2006, Geoffrey Barnard founded Machine-to-Machine Intelligence Corp. (M2Mi) at Ames’ NASA Research Park, envisioning an automated, satellite-based communication network. NASA Ames established a Space Act Agreement with the company to develop artificial intelligence that would automate communications, privacy, security, and resiliency between satellites and ground-based computers.
Central to the technology was automating a problem-solving approach known as root cause analysis, which NASA has honed over decades. This methodology seeks to identify not only the immediate cause of a problem but also all the factors that contributed to the cause. This would allow a network to identify its own issues and fix itself.
NASA Ames’ director of nanotechnology at the time wanted to develop a communications network based on small, low-powered satellites, so Ames supported M2Mi in developing the necessary technology.
Barnard, now CEO and chief technology officer of Tiburon, California-based branch of M2Mi, said NASA’s support laid the foundation for his company, which employs the same technology in a ground-based network.
The company’s M2M Intelligence software performs secure, resilient, automated communications on a system that runs across hundreds of networks, connecting thousands of devices, many of which were not built to communicate with each other. The M2Mi company worked with Vodafone of Berkshire, England, to build a worldwide network across more than 500 smaller networks in over 190 countries. The companies M2M Wireless and TriGlobal have begun using M2M Intelligence for transportation logistics.
With NASA’s help, emerging industries are getting the boost they need to rapidly develop technologies to enhance our lives.
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Last Updated Apr 29, 2025 Related Terms
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2 min read NASA Engineering Sparks Innovative New Battery
Nickel-hydrogen technology is safe, durable, and long-lasting – now it’s affordable too.
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NASA is creating artificial intelligence tools to help researchers use NASA’s science data more effectively.
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By Space Force
Senior leaders discuss Global Integration, during the Air and Space Force Association Warfare Symposium in Aurora, Colorado, March 4.
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By European Space Agency
Video: 00:09:01 Proba-3 is such an ambitious mission that it needs more than one single spacecraft to succeed. In order for Proba-3’s Coronagraph spacecraft to observe the Sun’s faint surrounding atmosphere, its disk-bearing Occulter spacecraft must block out the fiery solar disk. This means Proba-3’s Occulter ends up facing the Sun continuously, making it a valuable platform for science in its own right.
Proba-3 is scheduled for launch on a PSLV-XL rocket from Satish Dhawan Space Centre in Sriharikota, India, on Wednesday, 4 December, at 11:38 CET (10:38 GMT, 16:08 local time).
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By NASA
1 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Callista PuchmeyerCredit: NASA Cleveland State University (CSU) inducted Callista Puchmeyer, chief counsel at NASA’s Glenn Research Center in Cleveland, into the CSU College of Law Hall of Fame during a ceremony on Nov. 1.
Puchmeyer provides expert legal advice to NASA Glenn’s center director and other senior leaders. She also manages Glenn’s Office of the General Counsel, a diverse legal staff that advises Glenn clients on a broad spectrum of federal matters.
Established in 2017, CSU’s Law Hall of Fame honors the outstanding contributions of its distinguished alumni, faculty, staff, friends, and community leaders.
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By NASA
The NASA Science Mission Directorate (SMD) instituted the Entrepreneurs Challenge to identify innovative ideas and technologies from small business start-ups with the potential to advance the agency’s science goals. Geolabe—a prize winner in the latest Entrepreneurs Challenge—has developed a way to use artificial intelligence to identify global methane emissions. Methane is a greenhouse gas that significantly contributes to global warming, and this promising new technology could provide data to help decision makers develop strategies to mitigate climate change.
SMD sponsored Entrepreneurs Challenge events in 2020, 2021, and 2023. Challenge winners were awarded prize money—in 2023 the total Entrepreneurs Challenge prize value was $1M. To help leverage external funding sources for the development of innovative technologies of interest to NASA, SMD involved the venture capital community in Entrepreneurs Challenge events. Numerous challenge winners have subsequently received funding from both NASA and external sources (e.g., other government agencies or the venture capital community) to further develop their technologies.
Each Entrepreneurs Challenge solicited submissions in specific focus areas such as mass spectrometry technology, quantum sensors, metamaterials-based sensor technologies, and more. The focus areas of the latest 2023 challenge included lunar surface payloads and climate science.
A recent Entrepreneurs Challenge success story involves 2023 challenge winner Geolabe—a startup founded by Dr. Claudia Hulbert and Dr. Bertrand Rouet-Leduc in 2020 in Los Alamos, New Mexico. The Geolabe team developed a method that uses artificial intelligence (AI) to automatically detect methane emissions on a global scale.
This image taken from a NASA visualization shows the complex patterns of methane emissions around the globe in 2018, based on data from satellites, inventories of human activities, and NASA global computer models. Credit: NASA’s Scientific Visualization Studio As global temperatures rise to record highs, the pressure to curb greenhouse gas emissions has intensified. Limiting methane emissions is particularly important since methane is the second largest contributor to global warming, and is estimated to account for approximately a third of global warming to date. Moreover, because methane stays in the atmosphere for a shorter amount of time compared to CO2, curbing methane emissions is widely considered to be one of the fastest ways to slow down the rate of global warming.
However, monitoring methane emissions and determining their quantities has been challenging due to the limitations of existing detection methods. Methane plumes are invisible and odorless, so they are typically detected with specialized equipment such as infrared cameras. The difficulty in finding these leaks from space is akin to finding a needle in a haystack. Leaks are distributed around the globe, and most of the methane plumes are relatively small, making them easy to miss in satellite data.
Multispectral satellite imagery has emerged as a viable methane detection tool in recent years, enabling routine measurements of methane plumes at a global scale every few days. However, with respect to methane, these measurements suffer from very poor signal to noise ratio, which has thus far allowed detection of only very large emissions (2-3 tons/hour) using manual methods.
This landscape of “mountains” and “valleys” speckled with glittering stars is actually the edge of a nearby, young, star-forming region called NGC 3324 in the Carina Nebula. Captured in infrared light by NASA’s new James Webb Space Telescope, this image reveals for the first time previously invisible areas of star birth. Credit: NASA, ESA, CSA, and STScI The Geolabe team has developed a deep learning architecture that automatically identifies methane signatures in existing open-source spectral satellite data and deconvolves the signal from the noise. This AI method enables automatic detection of methane leaks at 200kg/hour and above, which account for over 85% of the methane emissions in well-studied, large oil and gas basins. Information gained using this new technique could help inform efforts to mitigate methane emissions on Earth and automatically validate their effects. This Geolabe project was featured in Nature Communications on May 14, 2024.
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Last Updated Aug 20, 2024 Related Terms
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