Hardware faults can have a significant impact on AI training and inference. Silent data corruptions (SDCs), undetected data errors caused by hardware, can be particularly harmful for AI systems that rely on accurate data for training as well as providing useful outputs. We are sharing methodologies we deploy at various scales for detecting SDC across [...] Read More... The post How Meta keeps its AI hardware reliable appeared first on Engineering at Meta.
