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The second approach offers broader feature support, seen in projects like Cloud Hypervisor or QEMU microvm. Built for heavier and more dynamic workloads, it supports hot-plugging memory and CPUs, which is useful for dynamic build runners that need to scale up during compilation. It also supports GPU passthrough, which is essential for AI workloads, while still maintaining the fast boot times of a microVM.
Meanwhile, other tech leaders have warned AI will eventually lead to fewer jobs. Amazon CEO Andy Jassy said last year the company would probably need a smaller headcount as AI started to automate tasks. And Salesforce CEO Marc Benioff said he “needs less heads” after reducing the company’s customer support workforce by 4,000 as AI takes over some work.