At ~$100B in AI funding, the question isn’t capital—it’s physical constraints. Data centers need power (H100s are ~700W each), and recent capacity additions we

At ~$100B in AI funding, the question isn’t capital—it’s physical constraints. Data centers need power (H100s are ~700W each), and recent capacity additions were mostly pre-allocated. Chip supply is also constrained by CoWoS packaging, not fab capacity, and expansions take years. If power, packaging, and GPUs are fixed in the near term, does $100B mostly drive inflation in AI infrastructure prices rather than materially more deployed compute? Are we seeing the real cost of a usable GPU cluster rise faster than actual capacity? Has anyone modeled what $100B actually buys in deployable compute over the next 2–3 years given these constraints—and whether that figure is shrinking as more capital piles in?