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World of Software > Mobile > Intel and Google expand collaboration for AI infrastructure
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Intel and Google expand collaboration for AI infrastructure

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Last updated: 2026/04/10 at 5:38 AM
News Room Published 10 April 2026
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Intel and Google expand collaboration for AI infrastructure
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Intel and Google have announced an expansion of their multi-year collaboration so that Google Cloud continue to use Intel AI infrastructure and continue developing processors together. Google’s cloud platform has been using Intel processors for years and will now use the new Xeon 6 for AI, cloud computing and inference tasks.

The companies will also expand the joint development of customized infrastructure processing units (IPUs), which help accelerate and manage data center tasks by offloading them from CPUs. This chip development collaboration, which began in 2021, will focus on custom ASIC-based integrated processing units (IPUs).

Intel and Google: more CPUs in AI

This expansion comes at a time when the industry Demand for CPUs for artificial intelligence data centers has increased. While GPU accelerators are used to develop and train AI models, CPUs are crucial to running those models and to the overall AI infrastructure, as Intel and NVIDIA’s agreement to combine the two showed.

“AI is transforming the way infrastructure is built and scaled”said Lip-Bu Tan, CEO of Intel, in a company press release. «Scaling AI requires more than accelerators: it requires balanced systems. “CPUs and IPUs are critical to delivering the performance, efficiency, and flexibility that modern AI workloads demand.”.

In recent months, more and more companies have turned their attention to CPUs due to the growing shortage of semiconductors. And not only on the x86 architecture used by Intel and AMD. Last month the Arm AGI was presented to society, a landmark AI CPU with industry-changing potential. The first silicon product from the British foundation – vital in today’s industry for its intellectual property licenses and reference designs – confirms the changes in data centers.

The architectures of the training era assumed that GPUs would dominate all phases of AI. For pure model training and high-performance batch inference, this assumption is valid. But agent workloads have introduced a completely different computing profile and shown the need for more processor equipment. The expansion of the Intel and Google partnership comes to cover these requirements.

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