As the impact of artificial intelligence (AI) continues to proliferate, computer architects must assess and mitigate its environmental impact. This talk will survey strategies for reducing the carbon footprint of AI computation and datacenter infrastructure, drawing on data and experiences from industrial, hyperscale systems. First, we analyze the embodied and operational carbon implications of super-linear AI growth. Second, we re-think datacenter infrastructure and define a solution space for carbon-free computation with renewable energy, utility-scale batteries, and job scheduling. Finally, we develop strategies for datacenter demand response, incentivizing both batch and real-time workloads to modulate power usage in ways that reflect their performance costs. In summary, the talk provides a broad perspective on sustainable computing and outlines the many remaining directions for future work.