The problem compounds because AI search is still in its explosive growth phase. Usage is doubling and tripling year over year as more people discover these tools and integrate them into their daily workflows. The traffic opportunity today is significant, but it's tiny compared to what it will become in the next few years as AI search becomes default behavior for entire demographics.
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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Фото: Артем Геодакян / РИА Новости
00:30, 28 февраля 2026Россия