// block: Wait for space (unbounded pending queue)
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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首先，Google 去年发布了一个名叫「AppFunctions」的框架，允许开发者公开应用特定的功能和特性入口，以便 AI 助手调用。。91视频对此有专业解读