#spacetech #computing #neuromorphic-computing Created at 041023 # [Anonymous feedback](https://www.admonymous.co/louis030195) # [[Epistemic status]] #shower-thought Last modified date: 041023 Commit: 0 # Related # neuromorphic computing in space Neuromorphic computing offers several advantages in space applications due to its unique characteristics inspired by the human brain. Some of the key benefits include: 1. **Low power consumption**: Neuromorphic computing systems are ultra-low power, which is crucial for space missions where energy efficiency is a top priority[2]. 2. **High-performance processing**: Neuromorphic computers can potentially perform complex calculations faster than traditional architectures, making them suitable for real-time data analysis and decision-making in space applications[1]. 3. **Fault tolerance**: Neuromorphic architectures are inherently fault-tolerant, which is essential for reliable operation in the harsh environment of space[1]. 4. **Radiation tolerance**: Some hardware implementations of neuromorphic computing have high radiation tolerance, making them suitable for space missions where radiation exposure is a concern[1]. 5. **Real-time machine learning**: Neuromorphic computing can efficiently implement real-time machine learning algorithms, which can be useful for solving emerging problems in space applications, such as autonomous data analysis and decision-making[1]. Future applications of neuromorphic computing in space may include autonomous on-board data analysis, enabling quicker response times and more efficient processing of information from multiple sources[1]. The Air Force Research Laboratory's Neuromorphic Computing Intelligence Systems+ (NICS+) program is working on integrating advanced neuromorphic technologies into space and airborne experiments for on-system learning, with projects like FALCONSAT-X (FSX) aiming to demonstrate the first Neuromorphic AI/ML Intelligent Computing in Space[2]. Citations: [1] https://csps.aerospace.org/sites/default/files/2021-08/Bersuker_NeuromorphicComputing_12132018.pdf [2] https://afresearchlab.com/technology/nics [3] https://arxiv.org/abs/2212.05236 [4] https://www.nature.com/articles/s43588-021-00184-y [5] https://www.frontiersin.org/articles/10.3389/fnins.2019.00260 [6] https://www.humanbrainproject.eu/en/science-development/focus-areas/neuromorphic-computing/