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29 May 2026
Training a large language model is not just about writing good code and pressing run. These models are spread across hundreds or thousands of processors – such as Google's Tensor Processing Units (TPUs), specialised accelerators designed to train and serve large-scale machine learning models – that must learn to work in lockstep: exchanging data, splitting tasks, staying synchronised. When something goes wrong, the whole system slows down, and expensive hardware sits idle.
