10B DISTRIBUTED TRAINING RUN

Summary from the TLDR AI newsletter

Decentralized training of language models is the process of using heterogeneous and non-co-located hardware to train a single model. This is traditionally challenging due to the high cost of memory transfers. This work improves on the state-of-the-art algorithms for highly distributed training.