On Friday, the US stock market staged an "AI valuation crisis," with the Nasdaq plunging 1.69% (nearly 400 points). Cloud computing and chip giants like Oracle and Broadcom saw their stock prices dive, and emerging AI infrastructure company Astera Labs temporarily dropped 46% intraday. The entire tech sector gave back most of its gains from December within a single day. This sharp decline instantly woke up market investors who had previously been immersed in AI dividend fantasies.

On the surface, this appears to be a profit-taking and valuation adjustment—after all, the recent gains were indeed excessive. But what is more worth noting is a deeper issue exposed behind this panic: the energy supply supporting the entire AI computing expansion is becoming the hardest constraint.

**"Pressure Signal" in the Texas Power System**

To meet the massive electricity demand from AI data center construction, Texas has received over 220GW of power connection requests by 2030. How crazy is this number? It is more than twice the peak load of the local power grid. Over 70% of this demand comes from the data center industry.

An energy sector expert commented directly: "This looks and smells like a bubble." He even said with some helplessness: "This number is simply too outrageous; we don't have the capacity to build such infrastructure in such a short time." This statement highlights the core contradiction.

**When Tech Genius Meets Reality**

No matter how powerful the chips or how advanced the algorithms are, at the end of the day, they all depend on the most basic energy supply. Data center servers, GPU computations, data storage, cooling systems—each link is energy-intensive.

Building data centers and procuring the latest hardware—activities that seem to involve rapid iteration—become slow processes in the face of energy supply constraints. Upgrading the power grid, constructing new power plants, expanding transmission lines—each is a large-scale project measured in years, involving approval processes, huge capital investments, and long construction cycles—completely different from software development's relatively asset-light iteration approach.

The slow and nonlinear expansion of energy infrastructure directly clashes with the market’s linear optimistic expectations for AI demand.

**Collision of Two Worlds**

The logic in capital markets is straightforward: AI demand continues to explode → computing power companies grow rapidly → stock prices increase linearly. This expectation chain supported the crazy rise of tech stocks in recent months.

But the physical world’s constraint is that the growth rate of electricity supply far lags behind market expectations. Power grid infrastructure development is affected by planning cycles, approval restrictions, resource allocation, technological innovations (such as new energy integration), and other factors, making expansion efficiency inherently low.

When frantic capital spending (the data center arms race) encounters the hard constraints of the physical world (electricity supply limits), the market suddenly realizes: future growth trajectories may not be as "smooth" as before. Concerns over energy bottlenecks constraining growth ultimately overshadowed the enthusiasm for high demand, triggering this round of intense valuation correction.

**What About the A-Share Market?**

The short-term impact will certainly ripple through. As a global investor sentiment indicator, the US tech sector's sharp decline will influence investor psychology. Next week, when trading resumes, A-shares related to AI concepts and computing power sectors are likely to face some pressure.

However, it’s important to note that the A-share market has its own unique logic:

The development stage and policy environment of China’s AI industry differ from those in the US. Most A-share companies are in application layers or hardware manufacturing, rather than core infrastructure, so the impact and magnitude may differ.

China has independent plans and advantages in energy infrastructure, especially with strategic layouts like "East Data West Computing." The specific manifestations of power bottlenecks may vary.

After multiple rounds of adjustment, some stocks already have valuation digestion space.

The subsequent impact will depend on whether the US market can stabilize, how domestic policies are directed, and how quickly market sentiment recovers.