Microsoft appears to be building a new team to advance its AI plans, hiring a professional who has developed an energy strategy based on Small Modular Reactors (SMR) and microreactor energy.
Microsoft is seeking a chief program manager to lead nuclear technology efforts to support the development of AI models, according to a job posting reported by The Verge.
According to a quote from Microsoft chairman and CEO Satya Nadella in the job description, “The Microsoft Cloud transforms the world's most advanced AI models into a new computing platform, ushering in the next big wave of computing.”
The ideal candidate will have at least six years of experience in the nuclear industry, engineering or energy market. The position will also be responsible for exploring other experimental energy technologies.
Complex machine learning models such as deep learning can consume significant amounts of energy for a variety of reasons, including complex calculations and large data volumes. A study published by MIT Technology Review in 2019 found that training a single AI model could release as much carbon into the atmosphere as five cars over their lifetimes.
A few ways to reduce the energy consumption of AI models include developing more efficient algorithms and hardware and using renewable energy sources such as nuclear power for data centers.
According to the U.S. Office of Nuclear Energy, one of the main advantages of nuclear energy is that it produces zero carbon emissions and does not emit other greenhouse gases. But researchers at Stanford University argue that this energy source is not a solution to environmental problems because it has a long time delay between planning and operation, a large carbon footprint and risks of collapse.
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Microsoft is seeking a chief program manager to lead nuclear technology efforts to support the development of AI models, according to a job posting reported by The Verge.
According to a quote from Microsoft chairman and CEO Satya Nadella in the job description, “The Microsoft Cloud transforms the world's most advanced AI models into a new computing platform, ushering in the next big wave of computing.”
The ideal candidate will have at least six years of experience in the nuclear industry, engineering or energy market. The position will also be responsible for exploring other experimental energy technologies.
Complex machine learning models such as deep learning can consume significant amounts of energy for a variety of reasons, including complex calculations and large data volumes. A study published by MIT Technology Review in 2019 found that training a single AI model could release as much carbon into the atmosphere as five cars over their lifetimes.
A few ways to reduce the energy consumption of AI models include developing more efficient algorithms and hardware and using renewable energy sources such as nuclear power for data centers.
According to the U.S. Office of Nuclear Energy, one of the main advantages of nuclear energy is that it produces zero carbon emissions and does not emit other greenhouse gases. But researchers at Stanford University argue that this energy source is not a solution to environmental problems because it has a long time delay between planning and operation, a large carbon footprint and risks of collapse.
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