Author: BITWU.ETH

Recently, following Professor Chen Xiaodong's course on "The Social Impact of Disruptive Technologies" at NTU, I reshaped my understanding of nuclear energy.

I used to think that nuclear energy was a typical "national-level project": enormous investment, long cycles, and complex approval processes, making it difficult for ordinary enterprises and capital to truly participate.

However, the emergence of AI data centers may be changing this logic.

The biggest change is not that nuclear technology has suddenly matured, but that nuclear energy has welcomed sufficiently powerful and urgent commercial buyers for the first time.

In the past, nuclear power primarily addressed national energy security issues; now, AI companies like Microsoft, Google, and Amazon are also actively seeking energy solutions that can provide long-term, stable, low-carbon power.

As a result, several changes are occurring simultaneously:

Large nuclear power still belongs to national-level infrastructure; small modular reactors are beginning to enter commercial validation, making them more suitable for the power scale of data centers, industrial parks, and high-energy-consuming enterprises.

At the same time, advancements in passive safety technology, modular manufacturing, and regulatory efficiency are attempting to transform nuclear energy from a "one-off super project" into a replicable industrial product.

The value of nuclear energy is not just in power generation.

Heating, industrial steam, hydrogen production, seawater desalination, and even stable energy supply for high-energy-consuming manufacturing may all become new business scenarios.
This corresponds not only to the nuclear power plants themselves but also includes the entire supply chain of fuel, forgings, instrumentation and control, and high-temperature superconducting magnets.

Of course, nuclear energy is not without risks.

Construction cycles, cost overruns, nuclear waste, fuel supply, regulation, and project financing—any issue in these areas could turn a project from a long-term asset into a stranded asset; true commercialization of fusion still requires time.

Therefore, my current assessment of nuclear energy is:

AI has not made nuclear energy suddenly mature overnight, but it is providing nuclear energy with unprecedented commercial demand, capital support, and realistic orders.

In the next decade, nuclear energy may not be the most attractive narrative in the AI industry, yet it has the potential to become one of the most undervalued infrastructures.

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