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AI Accelerators and Distributed Systems
This chapter explores the dynamics of AI accelerators, emphasizing the importance of large-scale distributed systems for managing millions of users. It discusses innovations like the Maddox chip design and the necessity of integrating training and inference processes to minimize latency. The conversation also highlights the challenges and opportunities within distributed AI training, examining the balance between local agents and hyperscaler dominance in the market.