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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.
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「假設你想要生成一份職缺描述。告訴AI：『我希望你一次問我一個問題，直到你收集到足夠資訊來撰寫一份有吸引力的職缺公告，』」懷特說，「透過一次一個問題的方式，它能根據你的回答進行調整。」