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Ana Paula Pereira7 hours agoMicrosoft to form nuclear power team to support AI: ReportMicrosoft is forming a new team of professionals to advance its artificial intelligence plans with Small Modular Reactors and microreactors.2884 Total views15 Total sharesListen to article 0:00NewsJoin us on social networksTech giant Microsoft is apparently forming a new team to advance its artificial intelligence plans by hiring a professional to develop an energy strategy based on Small Modular Reactors (SMRs) and microreactor energy.


According to a job postreported by The Verge, Microsoft is looking for a principal program manager who will lead its nuclear technology efforts to support the development of AI models.


“The next major wave of computing is being born, as the Microsoft Cloud turns the world’s most advanced AI models into a new computing platform,” according to a quote from Microsoft’s chairman and CEO Satya Nadellaavailable in the job description.


The ideal candidate must have at least six years of experience in the nuclear industry, engineering, or energy market, reads the post, which is currently closed to applications. The position will also be responsible for exploring other experimental energy technologies.


Complex machine learning models, like deep learning, can consume a significant amount of energy for several reasons, including complex computations and large volumes of data. A studypublished in 2019 by the MIT Technology Review found that training a single AI model can emit as much carbon in the atmosphere as five cars in their lifetimes.The estimated cost of training AI models. Source: MIT Technology Review


A few ways to reduce the energy consumption of AI models involve developing more efficient algorithms and hardware, as well as using renewable energy sources for data centers, such as nuclear power.


According to the U.S. Office of Nuclear Energy, one of the main advantages of nuclear power is that it produces zero carbon emissions and doesn’t emit other greenhouse gases. However, researchers at Stanford Universityargue that this energy source isn’t a solution to environmental problems, since it has a long-time lag between planning and operation, a large carbon footprint, and meltdown risks.


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