Summary of Machine Learning in Space: Surveying the Robustness Of On-board Ml Models to Radiation, by Kevin Lange et al.
Machine Learning in Space: Surveying the Robustness of on-board ML models to Radiation
by Kevin Lange, Federico Fontana, Francesco Rossi, Mattia Varile, Giovanni Apruzzese
First submitted to arxiv on: 4 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper investigates the impact of radiation on machine learning (ML) models used in spacecraft. Despite the growing reliance on ML in modern spacecraft, there is a lack of understanding about how radiation affects ML models designed for space applications. The authors conduct a reflective analysis of the current state of the art and provide evidence that prior work did not adequately examine the effects of natural hazards on ML models meant for spacecraft. They then perform simple experiments to demonstrate how to assess the robustness of practical ML models against radiation-induced faults using current frameworks. The evaluation reveals that not all faults are as devastating as claimed by some prior work, providing a foundation for developing space-tolerant ML models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about making sure machine learning (ML) models used in spacecraft can withstand the effects of radiation. Radiation can damage computer equipment and affect how well ML models work. The authors looked at what’s already been done to study this problem and found that it hasn’t been studied enough. They then did some simple experiments to show how current frameworks can be used to test the strength of ML models against radiation-induced faults. Their results showed that not all flaws are as bad as previously thought, which is a step forward in developing more reliable ML models for space applications. |
Keywords
» Artificial intelligence » Machine learning
