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AI infrastructure financing is evolving rapidly through creative debt structures and GPU collateralization as capital expenditure is projected to hit $700 billion by 2026.
“The question isn’t who has the best model, but who has the most creative financing to build out AI infrastructure and beyond.”
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Physical bottlenecks including power grid distribution, energy storage, and raw materials like steel have replaced model architecture as the primary constraints on AI scaling.
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Market rotation from software-as-a-service (SaaS) into infrastructure may be overextended as the industry prepares for a major shift from training to inference-optimized workloads.
“The question isn’t who has the best model, but who has the most creative financing to build out AI infrastructure and beyond.”