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November 29, 2024
Artificial intelligence (AI) is revolutionizing our world at a rapid pace. From medical diagnostics and autonomous driving to personalized advertising, AI is permeating more and more areas of our lives. But this progress comes at a price: AI systems require enormous amounts of energy. The demand for computing power for training and operating complex AI models is increasing exponentially, and with it a growing energy hunger that is increasingly straining the capacities of conventional energy sources. Faced with this challenge, nuclear power is moving into the focus of discussion as a potential solution.
The energy consumption of AI systems is considerable. Estimates suggest that the electricity demand for AI accelerators could account for a significant portion of the total electricity consumption of data centers worldwide in the coming years. Not only the training of AI models, but also the operation and the constantly growing use of AI-based applications contribute to this increase. The increasing use of cloud services and the construction of new data centers further amplify the demand.
To meet the rising energy demand and achieve their climate goals, some tech giants are considering the use of nuclear power. Microsoft, for example, has signed a contract with the operator of the Three Mile Island power plant to restart a decommissioned reactor. Other companies are investing in new concepts such as Small Modular Reactors (SMRs), smaller, modularly manufactured reactors that could potentially be safer and more cost-effective. Google has already signed a contract to purchase electricity from SMRs.
Nuclear power offers the possibility of generating large amounts of CO2-free energy, and could thus contribute to the decarbonization of the energy sector. However, challenges remain regarding safety, the disposal of radioactive waste, and costs. Whether SMRs actually offer the hoped-for advantages remains to be seen in practice. The ambitious schedules for the commissioning of the first SMRs are fraught with uncertainties, and there is a risk of cost increases.
In addition to nuclear power, other solutions are being discussed to meet the energy needs of AI. These include investments in renewable energies such as solar and wind power, the development of more energy-efficient AI models and hardware, and the optimization of data centers. Some companies are relying on hybrid approaches that combine different energy sources. Microsoft, for example, is investing in a data center in Kenya that is entirely powered by geothermal energy.
The question of AI's energy supply is complex and multifaceted. The coming years will show which strategies prove to be effective and sustainable. Whether nuclear power will play a central role or whether alternative approaches will prevail depends on various factors, including technological developments, political decisions, and social acceptance. What is clear is that a sustainable and reliable energy supply is essential to realize the full potential of artificial intelligence while achieving climate goals.
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