Tech giants are quietly changing the way data centers operate. Recently, Alphabet, Google's parent company, was reported to be acquiring the power storage company Intersect. Behind this lies a crucial logic that has been overlooked by the industry — the energy supply model of traditional data centers can no longer keep up with the pace of the AI era.

How serious is the problem? Current AI model training and inference require an astonishing amount of electrical resources, and this demand is continuous and cannot be interrupted. Unfortunately, the power grid infrastructure in most regions is still stuck in the last era, already stretched thin, and now it has to support the energy demands of dozens of ultra-large-scale data centers, which is bound to cause problems sooner or later. This is the core contradiction that Intersect aims to solve.

The "power-first" data center development model they proposed simply changes the traditional construction logic. Instead of first selecting a location to build the machine room and then praying that the local power grid can support it, it is better to reverse the process—first ensure energy self-sufficiency, and then plan the machine room around the energy infrastructure.

How exactly is this done? Imagine a large data center's energy system being transformed into a complete autonomous operating system: the roof covered with solar panels providing clean electricity, complemented by natural gas generators as peak-shaving measures, along with a super-large capacity battery storage system as a buffer. What is the result? Most of the electricity demand of this data center can be self-sufficient, only treating the public power grid as an emergency backup. In this way, it does not rely on the expansion cycle of the public power grid and significantly reduces the impact on traditional energy infrastructure.

This architecture has several advantages. First, it solves the "electricity shortage" issue in the AI era—no longer do we have to worry that centralized data centers will overwhelm the local power grid; the bottleneck of computing power deployment has shifted from electricity to capital and technology itself. Second, the energy structure is more elegant—relying solely on solar or wind energy for power generation is definitely not feasible; what do we do at midnight or on cloudy days? However, with a combination of "solar energy + natural gas peak shaving + battery storage," we can achieve a high proportion of clean energy usage while ensuring stable electricity supply 24/7.

There are also considerations of speed and cost. The construction of new transmission lines involves a complex approval process, taking as few as several years and as many as ten years. However, Intersect's co-location model ties data centers and energy facilities together, significantly shortening the approval and construction cycle, allowing AI companies to expand their computing power more quickly. In the long run, although the initial investment in a self-owned power generation system is high, the stable generation costs may be more economical than traditional electricity prices.

This acquisition move by Google is actually sending a signal - the future competition in data centers will not only be about computing power density and chip performance, but also about whose energy solutions are more advanced and independent. It is expected that a wave of tech giants will follow suit, and the boundaries between data center operators and energy companies may gradually blur, even leading to deep binding or capital mergers.

However, this path is not completely smooth. Grid connection approval, technical operation and maintenance of hybrid energy systems, and competitive resistance from traditional energy companies—these are all real challenges that Intersect and companies adopting this model must face. But from a broader perspective, as the demand for AI computing power continues to explode, this "power first" mindset will gradually become the industry standard.