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.
The most obvious trend is continued growth in AI search usage. As more people discover tools like ChatGPT, Claude, and Perplexity, and as these tools improve their interfaces and expand capabilities, the percentage of information-seeking behavior flowing through AI models will increase. This doesn't necessarily mean traditional search engines will disappear, but it does mean the traffic pie is being redivided, with AI search claiming an expanding slice.
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