Meta's SAM has become an astronaut
A team of scientists at the University of Aberdeen has developed a new method for detecting planetary craters, which could help to accurately map the surfaces of planets using different types of data. This innovative approach involves using a new universal crater detection algorithm (CDA) that leverages the power of artificial intelligence (AI) to automate the process of identifying craters.
The team of researchers used META AI's Segment Anything Model (SAM), a cutting-edge AI model that can automatically "cut out" any object in an image, to develop the CDA. This allowed the team to automatically map craters, reducing the need for time-consuming manual identification. By using different types of data, the approach also allows for more accurate and flexible surface characterization.
Check out the University of Aberdeen's video below.
Why does crater detection matter and what is SAM's role?
The CDA technique has the potential to be a universal solution for crater detection on various planetary surfaces. It could be used to identify possible landing sites for robotic or human missions, and potentially be used for automatic navigation based on terrain observations. The approach can work with different data and celestial bodies, making it an exciting new possibility for planetary science and exploration missions.
Dr. Iraklis Giannakis, from the University's School of Geosciences, led the research in collaboration with colleagues from the University. He explained that crater detection is a crucial task in planetary science that enables scientists to better understand the geology, history, and evolution of celestial bodies such as Mars, the Moon, and other planets.
With the development of this CDA approach, scientists can study the distribution, size, and morphology of craters to better understand the planetary surface and its evolution over time. This can help in uncovering the geological history, surface processes, and potential habitability of a planet or moon. Craters can also be potential sources of valuable resources, such as water ice on planetary bodies like the Moon or Mars.
By automatically mapping craters, scientists can identify potential locations where resources may be concentrated, which can be important for future human missions and for planning resource utilization strategies in space exploration scenarios.
The preprint of the results has been published on arXiv, and the development of the CDA has created exciting new possibilities for planetary science and future exploration missions.
Many research and development companies, such as META, which continue their research in the field of AI technologies without slowing down, seem to be shaping the world of science too.
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