How Meta trains large language models at scale

This article likely discusses the infrastructure, techniques, and challenges involved in training large language models (LLMs) at Meta. It would probably cover topics like data preparation, model architecture, distributed training, and resource management. The 'at scale' aspect suggests a focus on efficiency, cost-effectiveness, and the ability to handle massive datasets and model sizes.