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Optimizing AI Infrastructure Management
This chapter explores the complexities of managing a large AI fleet, addressing challenges like system compatibility and the roles of different engineering positions in maintaining reliability. It also discusses the infrastructure strategies at Meta, focusing on on-premise data centers and the transition to more efficient resource management methods to accommodate AI workloads. The conversation highlights innovations in hardware and chip development, emphasizing the need for specialized teams and the integration of advanced technologies for better performance and efficiency.