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Google rebuilds data center infrastructure to power next-gen autonomous AI agents

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Google is redesigning its global data center architecture to support autonomous AI agents, which require far greater and more sustained computing power than traditional large language models. The company's facilities now process over 3 quadrillion tokens monthly, a sevenfold year-on-year increase, with agentic workloads projected to generate 100 times more inference transactions than conventional AI tasks. To meet this demand, Google introduced two new custom chips: the TPU-8t for training, offering triple the performance of its predecessor, and the TPU-8i for inference, featuring 50 percent more high-bandwidth memory to handle large active data loads. A new Axion N4A CPU was also unveiled to manage orchestration and tool-calling tasks that keep agents running efficiently. The redesigned infrastructure is built for elasticity, regional distribution, and long-term autonomous operation, with Google planning annual hardware platform releases to keep pace with evolving agent requirements.

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Google rebuilds data center infrastructure to power next-gen autonomous AI agents · ShortSingh