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The growth of generative AI requires huge amounts of water and energy and the US grid is struggling to cope.<\/p>\n
As AI has taken off in the last few years, new data centers are popping up across the country to support the paid acceleration of AI. Learning models need such data centers to provide the vast amount of computing resources required to train and deploy complex machine learning models and algorithms.<\/p>\n
However, data centers also require a huge amount of power to run and maintain them, as well as water to cool the servers inside. Concerns are rising about whether the US power grid can generate enough electricity for the growing number of necessary data centers. While AI has been helping to improve sustainability in some fields<\/a>, if it\u2019s not a sustainable technology in itself, it won\u2019t be doing any good for the planet.<\/p>\n Those working in AI production both on a hardware and software level are working to mitigate these drains on energy and resources, as well as investing in sustainable energy sources<\/a>.<\/p>\n \u201cIf we don\u2019t start thinking about this power problem differently now, we\u2019re never going to see this dream we have,\u201d Dipti Vachani, head of automotive at Arm, told CNBC<\/a>. The chip company\u2019s low-power processors are being used more and more by huge companies like Google, Microsoft, Oracle and Amazon because they can help to reduce power use by up to 15% in data centers.<\/p>\n Work is also being done to reduce how much energy AI models need in the first place. For example, Nvidia\u2019s latest AI chip, Grace Blackwell, incorporates Arm-based CPUs that can supposedly run generative AI models on 25 times less power than the previous generation.<\/p>\n \u201cSaving every last bit of power is going to be a fundamentally different design than when you\u2019re trying to maximize the performance,\u201d Vachani said.<\/p>\n Nonetheless, concerns remain that these measures won\u2019t be enough. After all, one ChatGPT query uses nearly 10 times as much energy as a typical Google search, while generating an AI image can use as much power as charging a smartphone fully.<\/p>\n The effects are being seen most clearly with the larger companies, with Google\u2019s latest environmental report showing greenhouse gas emissions rising nearly 50% between 2019 and 2023, in part because of data center energy consumption. That\u2019s despite claims from Google that data centers are 1.8 times as energy efficient as a typical data center. Similarly, Microsoft\u2019s emissions rose nearly 30% from 2020 to 2024, also due partly to data centers.<\/p>\nWhat can be done to save energy in the AI space?<\/h2>\n