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Today at Google Cloud Next 25, we\u2019re introducing Ironwood, our seventh-generation Tensor Processing Unit (TPU) \u2014 our most performant and scalable custom AI accelerator to date, and the first designed specifically for inference. For more than a decade, TPUs have powered Google\u2019s most demanding AI training and serving workloads, and have enabled our Cloud customers to do the same. Ironwood is our most powerful, capable and energy efficient TPU yet. And it’s purpose-built to power thinking, inferential AI models at scale.<\/p>\n
Ironwood represents a significant shift in the development of AI and the infrastructure that powers its progress. It\u2019s a move from responsive<\/i> AI models that provide real-time information for people to interpret, to models that provide the proactive<\/i> generation of insights and interpretation. This is what we call the \u201cage of inference\u201d where AI agents will proactively retrieve and generate data to collaboratively deliver insights and answers, not just data.<\/p>\n
Ironwood is built to support this next phase of generative AI and its tremendous computational and communication requirements. It scales up to 9,216 liquid cooled chips linked with breakthrough Inter-Chip Interconnect (ICI) networking spanning nearly 10 MW. It is one of several new components of Google Cloud AI Hypercomputer architecture, which optimizes hardware and software together for the most demanding AI workloads. With Ironwood, developers can also leverage Google\u2019s own Pathways software stack to reliably and easily harness the combined computing power of tens of thousands of Ironwood TPUs.<\/p>\n
Here\u2019s a closer look at how these innovations work together to take on the most demanding training and serving workloads with unparalleled performance, cost and power efficiency.<\/p>\n<\/div>\n