Scaling AI Sustainably Slides

Abstract: The past 50 years has seen a dramatic increase in the amount of compute per person, in particular, those enabled by AI. Despite the positive societal benefits, AI technologies come with significant environmental implications. I will talk about the carbon footprint of AI computing by examining the model development cycle, spanning data, algorithms, and system hardware. At the same time, we will consider the life cycle of system hardware from the perspective of hardware architectures and manufacturing technologies. The talk will capture the operational and manufacturing carbon emissions of AI computing. Based on the industry experience and lessons learned, I will share key challenges, on what and how at-scale optimization can help reduce the overall carbon footprint of AI and computing. This talk will conclude with important development and research directions to advance the field of computing in an environmentally-responsible and sustainable manner.