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The underlying logic of this AI boom isn't that complicated: big internet companies spend money to buy NVDA graphics cards, which provide computing power, then break down that computing power into tokens to sell externally. Basically, it's a retail business of selling computing power.
Following this line, a few very sobering conclusions can be drawn.
**The stronger the computing power, the cheaper the tokens, but the demand actually increases**
Chip performance improves year after year, and the cost per token will definitely decrease. But there's a catch: pricing power is not in your hands at all; it’s in the hands of the model developers.
As long as programmers still need to write code, analysts need to perform data analysis, product managers want to improve efficiency, and enterprises pursue automation, token consumption will not stop. Instead, it will become more and more intense.
There are also a bunch of other players now: API wrapper startups, AI middlemen, micro-innovation SaaS, various "AI+" tools... The brokerage software you use, office tools, video apps, design platforms—all are adding AI features. The token consumption of upper-layer applications will ultimately impact the lower layers—the demand for hardware computing power.
**The US's computing power shortage is a systemic issue, not a short-term fluctuation**
Many underestimate the difficulty of building data centers in the US. Land approval, power infrastructure, rack installation, cooling systems, union costs... each of these steps is a trap in the US.