While training AI models requires substantial energy, Jensen Huang believes that smarter power grids can distribute electricity more effectively, improving computational efficiency. He stated that “the same work can save 100 or even 1,000 times the energy.” Huang is skeptical of external predictions about significant AI energy consumption, suggesting that “there is likely some redundant computation.”

He considers nuclear energy an outstanding renewable resource, but not the sole option; the data center industry needs a variety of energy sources and must balance availability, cost, and sustainability over time.

As global tech giants invest hundreds of billions in AI infrastructure, the increasing number and scale of data centers are placing unprecedented demands on local power supplies, intensifying electricity supply and demand conflicts.

Under these circumstances, builders must weigh the locations and operations of AI data centers more carefully: some areas cannot support new data centers, certain facilities are sited far from traditional population centers, and some computational infrastructures cannot operate at full capacity.

With the surge in AI applications, energy consumption issues are becoming more prominent. Currently, major global companies are investing billions in what they see as the future of computing infrastructure, making energy consumption a pressing concern. In some regions, power generation is already insufficient to support new data centers. Due to power restrictions, some centers cannot operate at full capacity, and others are built far from population centers.

At the beginning of this year, during the Davos meeting, OpenAI CEO Sam Altman stated that the power consumed by AI technologies would far exceed expectations. A report from the International Energy Agency (IEA) in January estimated that by 2026, the electricity consumption of global data centers, AI, and cryptocurrency industries could double, significantly outpacing the average annual growth rate of 3.4% in global power demand over the next three years. By 2026, total electricity consumption by data centers could exceed 1,000 terawatt-hours (1 terawatt-hour = 1 billion kilowatt-hours).

Recently, Altman considered using electricity from Japanese nuclear power plants and explored the feasibility of offshore wind turbines. Overall, nuclear energy stands out as a viable renewable energy source. This spring, OpenAI held a meeting with Japanese officials in Tokyo, where they proposed a plan to utilize power from decommissioned nuclear plants after the Fukushima disaster in 2011 to support data center construction.

Due to the need for large amounts of clean energy to meet the power demands of its AI data centers, Microsoft signed a 20-year power purchase agreement with Constellation Energy last Friday—known as the Three Mile Island Agreement—which could incentivize the optimization and expansion of the nuclear supply chain, including uranium mining, nuclear fuel processing, and reactor construction and maintenance.

This agreement showcases the enormous potential for clean energy demand. As data centers and other large energy consumers increase their power needs, the demand for nuclear energy, as a stable and low-carbon option, is likely to continue growing.

Huang also mentioned Microsoft’s Three Mile Island Agreement this Friday, calling it “fantastic.” He added that NVIDIA’s next-generation chips consume more power than previous generations but are more efficient, allowing for faster training and operation of AI software while replacing multiple older components.

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