Hardware Error

Hardware errors pose a significant threat to the reliability of increasingly complex computing systems, particularly those employing deep learning models and high-performance computing architectures. Current research focuses on developing mitigation strategies, including reinforcement learning algorithms for adaptive error correction and novel hardware designs optimized for resilience against faults, such as specialized accelerators for spiking neural networks. These efforts are crucial for ensuring the dependable operation of AI systems in safety-critical applications and for maximizing the efficiency of large-scale computing infrastructures.