The computational budgets used for machine learning research have increased dramatically in recent years. Machine learning systems are also used in production more than ever before, impacting many people around the world. In this interview we will discuss the implications of this increase in computational cost in research and production, touching on the environmental impact of AI and how unequal access to computational resources impacts our communities. The observed trends have shown no sign of slowing down, and thus we will discuss an overarching theme of much work in modern AI: efficiency is more important than ever.
