"SatNad argued that corporate AI sovereignty hinges on control over models trained on proprietary knowledge, not the physcial infrastructure location. "If you're not able to embed the tacit knowledge of the firm in a set of weights in a model that you control, by definition you have no sovereignty. That means you're leaking enterprise value to some model somewhere." He added: "In fact, the datacenter, where it runs, is the least important thing.""
"The reframing follows Microsoft's struggles with traditional data sovereignty. The software and cloud biz's EU data boundary - intended to assuage European customers' concerns over dependency on a US-owned entity - cannot guarantee protection against US government access demands. So is it better to advance the conversation to sovereignty in the AI era, where - according to Nadella - datacenter location is the least of an enterprise's worries. He said encryption would address sovereignty concerns with only the speed of light constraining datacenters placements."
Corporate AI sovereignty depends on firms controlling models trained on their proprietary knowledge and embedding tacit organizational knowledge into model weights. Without such control, firms effectively leak enterprise value to externally managed models. Datacenter location is characterized as the least important factor for sovereignty, with encryption presented as a mitigating technology and the speed of light as the main constraint on datacenter placement. Traditional data sovereignty measures, such as geographic EU data boundaries, cannot fully guarantee protection from foreign government access demands. AI sovereignty can be framed as operational control over models rather than physical infrastructure.
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