AI's next constraint is the infrastructure around the model

Reported by at least two different outlets.

Power, data-center capacity, specialized chips, and networking are becoming as consequential as model capability.

Key points

• The bottleneck is shifting from model access toward power and computing capacity.
• Organizations need to prioritize workloads by measurable value, not model size.
• Energy planning is becoming part of AI strategy rather than a separate facilities question.

Why it matters

The teams that connect computing spend to specific outcomes will have more room to scale than teams treating capacity as unlimited.

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