HOW META TRAINS LARGE LANGUAGE MODELS AT SCALE

Summary from the TLDR Web Dev newsletter

Meta is facing challenges in training large language models due to the amount of computational power required. This has led to the company rethinking its infrastructure in terms of hardware reliability, failure recovery, efficient training state preservation, and optimal GPU connectivity. Meta is innovating across the infrastructure stack by developing new training software and scheduling algorithms, modifying hardware like the Grand Teton platform, optimizing data center deployments, and exploring new fabrics for network infra.