Source: SiliconANGLE
As production AI models demand consistent, high-bandwidth infrastructure that public clouds struggle to provision reliably at scale, enterprises are reconsidering private cloud deployments—shifting the calculus that drove cloud migration over the past decade. Broadcom is positioning itself as the infrastructure backbone for this shift, recognizing that companies building real AI applications need predictable performance and cost models that shared public cloud resources can't guarantee. This reflects a practical constraint, not nostalgia: AI's resource intensity and latency requirements have created a new class of workload that behaves more like traditional capital-intensive infrastructure than the elastic, pay-as-you-go services that defined cloud's promise.