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For years, we now have talked about cloud-first methods, with the massive hyperscalers competing on compute, storage, databases, and international attain. Generative AI modified the sport. The middle of gravity is shifting from generic infrastructure to AI-native platforms: GPUs, proprietary basis fashions, vector databases, agent frameworks, copilots, and AI-integrated the whole lot.
You possibly can see the shift in how suppliers discuss themselves. Earnings calls now spotlight GPU and AI accelerator spending as the brand new core funding. Homepages and conferences lead with AI platforms, copilots, and agentic AI, whereas conventional IaaS and PaaS take a again seat. Databases, developer instruments, workflow engines, and integration companies are all being refactored or wrapped with AI capabilities which are enabled by default or only a click on away.
At first look, this seems to be progress. You see extra clever search, auto-generated code, anomaly detection, predictive insights, and AI assistants built-in into each console. Nonetheless, behind the scenes, every of those conveniences sometimes depends on proprietary APIs, opinionated information codecs, and a rising assumption that your workloads and information will keep inside that cloud.
