What does a production-grade large language model look like? While at NDC Sydney, Richard talked with Vaishnavi Gudur from Microsoft about her work scaling LLMs for Teams transcriptions, summaries, and more! Vaishnavi discusses the underlying complexities of operating the Teams LLM infrastructure for a large array of customers across different countries and regulatory regimes. Data sovereignty also plays a large role: different countries have specific rules on where data must reside and how it can be accessed. As the scale increases and the tail gets longer, the rules set gets more complex! Lots of great thinking about what LLMs look like in a production environment.