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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chunks.push(chunk);
这相当于让AI学会了“团队作战”，杨植麟表示，“高质量数据的增长速度赶不上算力增长，Agent Swarm可以被视为测试时扩展的一种形式，同时也提供了训练时扩展的方式。”