This analysis highlights why we need diverse forecasting approaches. We should be developing projections based on two parallel scenarios:
Scenario 1: Unconstrained AI Demand - Bottom-up modeling based on factors like wafer fabrication, GPU sales volume, token demand, and development-related compute budgets. This shows us where the AI industry wants to go without ceilings.
Scenario 2: Grid-Constrained Reality - Top-down analysis of actual generation capacity additions, interconnection queue timelines, transmission bottlenecks, and regional supply shortfalls. This shows us what's actually possible.
The gap between these scenarios would be incredibly revealing - not just for energy planning, but for understanding which AI development paths are viable versus which are fantasies. Solutions that push the second scenario closer to the first are essential for American leadership in this space.
This analysis highlights why we need diverse forecasting approaches. We should be developing projections based on two parallel scenarios:
Scenario 1: Unconstrained AI Demand - Bottom-up modeling based on factors like wafer fabrication, GPU sales volume, token demand, and development-related compute budgets. This shows us where the AI industry wants to go without ceilings.
Scenario 2: Grid-Constrained Reality - Top-down analysis of actual generation capacity additions, interconnection queue timelines, transmission bottlenecks, and regional supply shortfalls. This shows us what's actually possible.
The gap between these scenarios would be incredibly revealing - not just for energy planning, but for understanding which AI development paths are viable versus which are fantasies. Solutions that push the second scenario closer to the first are essential for American leadership in this space.