Google Cloud and Intel expanded their multi-year partnership Thursday, deepening their collaboration on custom infrastructure processing units (IPUs) and committing to Intel's latest Xeon 6 processors for AI inference workloads. The deal, which builds on a chip development partnership that started in 2021, focuses on custom ASIC-based IPUs designed to offload data center tasks from CPUs — addressing what Intel CEO Lip-Bu Tan calls the need for "balanced systems" beyond just accelerators.

This move highlights a strategic shift happening across the industry. While GPU shortages dominate headlines, the real infrastructure crunch is emerging around CPUs needed for AI inference at scale. Training gets the attention, but inference is where the actual business happens — and that's CPU-heavy work. SoftBank's Arm Holdings just announced its first self-produced AGI CPU amid this "worldwide crunch," signaling that chip companies see the CPU shortage as the next major bottleneck.

What's telling is how this partnership fits into Google's broader infrastructure strategy. Recent deals show Google Cloud aggressively courting enterprise customers with AI partnerships — from Adobe's creative AI integration to Liberty Global's five-year European telecom transformation. These aren't just cloud contracts; they're bets that whoever controls the inference infrastructure will control AI deployment at enterprise scale.

For developers, this points to a practical reality: start planning for CPU constraints in your AI applications. The GPU shortage taught us to optimize for training efficiency, but the coming CPU crunch means rethinking inference architecture. Custom IPUs and specialized processors aren't just enterprise luxuries anymore — they're becoming necessary infrastructure for any serious AI deployment.