Major technology companies are turning to nuclear energy to power their data centers, driving the demand for AI training. However, experts warn of potential risks and costs associated with this rapid adoption of nuclear power.
Big technology companies are shifting their focus towards nuclear energy to power the data centers essential for training artificial intelligence tools. However, experts are raising concerns that the industry might be moving too rapidly in this direction, given the inherent risks involved. Recent reports reveal that Google plans to purchase power from Kairos Power, a developer of small modular reactors.
Microsoft, on the other hand, signed a deal last year with energy firm Constellation to revive a decommissioned reactor at the Three Mile Island plant in Pennsylvania. This site is infamous for hosting the most severe nuclear meltdown and radiation leak in U.S. history, which occurred back in 1979. Meanwhile, Amazon is collaborating with Dominion Energy to construct a small modular nuclear reactor near one of the company's existing nuclear power stations.These tech giants are attempting to meet the surging demand for generative AI applications, which significantly increase the energy requirements. The International Energy Agency (IEA) projects that electricity consumption from data centers, AI, and the cryptocurrency sector will double from an estimated 460 terawatt-hours (TWh) in 2022 to over 1,000 TWh by 2026. Notably, U.S. data centers alone consumed more than 4% of the nation's electricity just two years ago, and this figure is anticipated to jump to 6% in less than two years. According to the University of Cambridge's Bitcoin Electricity Consumption Index, global Bitcoin mining consumed 121.13 terawatt-hours of electricity in 2023, comparable to the Netherlands' electricity consumption in 2022.Relying on nuclear energy to fulfill these energy demands is not without controversy. Climate activists voice concerns about the hazardous environmental and safety risks associated with nuclear power. Greenpeace, for instance, points out that while nuclear energy doesn't produce carbon dioxide or other greenhouse gases, nuclear waste remains a harmful environmental threat. Furthermore, there are concerns regarding the long-term economic viability of nuclear power compared to investments in AI. Henry Sokolski, the executive director of the Nonproliferation Policy Education Center, questions the wisdom of investing heavily in nuclear energy when the future benefits of AI and the Internet of Things remain uncertain. He argues that if the economy slows down or AI development progresses more slowly than anticipated, the energy demand may not justify the substantial costs of nuclear power plants. These plants often require billions of dollars to construct, and cost overruns are common. Two reactors under construction in Georgia are already projected to cost twice their initial estimates, while a pair of reactors in South Carolina were canceled after costs ballooned from $9.8 billion to $25 billion. Regulatory hurdles and the lengthy construction timelines contribute to these cost escalations.Another challenge lies in the capacity of the U.S. electric grid to handle the substantial energy loads required by data centers. Some regions are experiencing power quality issues, with distorted electricity flows causing damage to appliances and posing a fire hazard. Victor Gilinsky, a physicist and former commissioner on the U.S. Nuclear Regulatory Commission, criticizes the rapid pace at which the industry and policymakers are embracing nuclear energy. He believes that the ADVANCE Act, which aims to accelerate the licensing of advanced reactors, puts undue pressure on the safety review process
Nuclear Energy Artificial Intelligence Data Centers Energy Demand Safety Concerns Cost Overruns Electric Grid
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