For the first time, researchers have trained a machine learning model in outer space, on board a satellite.


Copyright: – “Researchers Successfully Train a Machine Learning Model in Outer Space for the First Time”

Featured image: The ION SCV004 satellite, on which the machine learning models were run. The image shows the satellite releasing CubeSats (small satellites) into space. Credit: D-Orbit


This achievement could enable real-time monitoring and decision making for a range of applications, from disaster management to deforestation.

This project has been summarized in a publication, “Fast model inference and training on-board of Satellites,” available on the pre-print server arXiv. The work was also presented at the International Geoscience and Remote Sensing Symposium (IGARSS) conference on 21 July 2023.

Data collected by remote-sensing satellites is fundamental for many key activities, including aerial mapping, weather prediction, and monitoring deforestation. Currently, most satellites can only passively collect data, since they are not equipped to make decisions or detect changes. Instead, data has to be relayed to Earth to be processed, which typically takes several hours or even days. This limits the ability to identify and respond to rapidly emerging events, such as a natural disaster.

To overcome these restrictions, a group of researchers led by DPhil student Vít Růžička (Department of Computer Science, University of Oxford), took on the challenge of training the first machine learning program in outer space.

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During 2022, the team successfully pitched their idea to the Dashing through the Stars mission, which had issued an open call for project proposals to be carried out on board the ION SCV004 satellite, launched in January 2022. During the autumn of 2022, the team uplinked the code for the program to the satellite already in orbit.[…]

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