The global artificial intelligence revolution has produced an underappreciated industrial consequence: the complete reengineering of digital infrastructure from software-centric network nodes to physically intensive computational factories. This paper presents a comprehensive, thesis-level analysis of the strategic, technical, economic, and geopolitical dimensions of the density transition sweeping the data center industry from 2022 to the projected horizon of 2035. We examine the emblematic case of the Temple, Texas facility developed by Meta Platforms, in which a partially constructed data center was intentionally demolished and redesigned in 2023 to accommodate next-generation AI infrastructure. This episode serves as a canonical illustration of “stranded asset risk” in the AI era: infrastructure built only a few years earlier under assumptions appropriate for cloud computing suddenly becoming structurally incompatible with the extreme power densities required by large-scale AI training clusters.
Zen Revista (Mon,) studied this question.
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