Before investing in AI infrastructure, it helps to pause and look at how the balance of data, compute and intelligence is shifting. In working with companies just starting their AI journey, we’ve seen clear patterns in what separates early success from later struggle. The location of data, the pace of expansion to the edge and the diversity of models and partners all shape what “doing AI right” really means. It starts with building a foundation for distributed AI. Edge use cases are on a meteoric rise. As models become smaller, smarter and more domain-specific, inference is increasingly happening closer to…

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