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From Hype to Hard Assets: 2025 Essays on AI Infrastructure, Power, and Place

From Hype to Hard Assets: 2025 Essays on AI Infrastructure, Power, and Place in Vernon, BC

Current price: $8.69
Original price: $9.99
Buy Online
From Hype to Hard Assets: 2025 Essays on AI Infrastructure, Power, and Place

Coles

From Hype to Hard Assets: 2025 Essays on AI Infrastructure, Power, and Place in Vernon, BC

Current price: $8.69
Original price: $9.99
Loading Inventory...

Size: Kobo eBook

Buy Online
*Product information may vary - to confirm product availability, pricing, shipping and return information please contact Coles
AI did not slow down in 2025. It hit the ground. After years of abstract promises and exponential charts, artificial intelligence became physical. Power plants, substations, land assemblies, water systems, zoning hearings, and permitting timelines replaced chips and models as the real constraints shaping what could actually be built. From Hype to Hard Assets is a field guide to that shift. Drawing on essays originally published throughout 2025, Suhail Y Tayeb traces how AI infrastructure stopped behaving like software and started behaving like real estate. The book examines why capital moved away from pure hyperscale speculation and toward colocation, edge facilities, powered land, and entitlement-ready sites. It shows how grid congestion, water politics, and local resistance are reshaping development economics across the United States and globally. This is not a technology book. It is an infrastructure book. Across four sections, the essays explore the end of frictionless growth, the central role of power in determining geography, the rise of permitting and local politics as financial variables, and the emergence of new execution corridors in places like Texas, the Midwest, and secondary markets long overlooked by institutional capital. Written for investors, developers, policymakers, and anyone trying to understand where AI infrastructure can actually clear, this book focuses on execution rather than prediction. It explains why zoning is now strategy, why entitlement is capital, and why the next decade of AI will be decided not by model weights, but by where power, land, and permission intersect. From Hype to Hard Assets is for readers who want to understand how AI infrastructure is really built, who carries the risk, and where durable value is likely to emerge as the industry enters its constraint phase.
AI did not slow down in 2025. It hit the ground. After years of abstract promises and exponential charts, artificial intelligence became physical. Power plants, substations, land assemblies, water systems, zoning hearings, and permitting timelines replaced chips and models as the real constraints shaping what could actually be built. From Hype to Hard Assets is a field guide to that shift. Drawing on essays originally published throughout 2025, Suhail Y Tayeb traces how AI infrastructure stopped behaving like software and started behaving like real estate. The book examines why capital moved away from pure hyperscale speculation and toward colocation, edge facilities, powered land, and entitlement-ready sites. It shows how grid congestion, water politics, and local resistance are reshaping development economics across the United States and globally. This is not a technology book. It is an infrastructure book. Across four sections, the essays explore the end of frictionless growth, the central role of power in determining geography, the rise of permitting and local politics as financial variables, and the emergence of new execution corridors in places like Texas, the Midwest, and secondary markets long overlooked by institutional capital. Written for investors, developers, policymakers, and anyone trying to understand where AI infrastructure can actually clear, this book focuses on execution rather than prediction. It explains why zoning is now strategy, why entitlement is capital, and why the next decade of AI will be decided not by model weights, but by where power, land, and permission intersect. From Hype to Hard Assets is for readers who want to understand how AI infrastructure is really built, who carries the risk, and where durable value is likely to emerge as the industry enters its constraint phase.

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