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ZDNET's key takeaways
AI investment is driving up energy demands and impacting local grids.
AI energy use must be considered relative to tech's energy demands overall.
Businesses and individuals have several options for managing their AI footprint.
AI feels inescapable. It's everywhere: Your smartphone, Google, even your work tools. AI features promise to make life easier and more productive, but what does all this new tech mean for the environment?
As AI investment grows -- as does user adoption -- so do the technology's energy costs. Made up of high-compute systems, AI requires a lot of data, which needs to be stored on large networks of computers known as data centers. Just like your personal computer, those gigantic centers need electricity -- as does the process of training an AI model, which relies on more compute than traditional computer functions.
Also: Google reveals how much energy a Gemini query uses - in industry first
But in the context of the energy we already use every day, from office lights and laptops to social media, how does that consumption actually compare? Can the technology's resource needs change or be improved over time? Is the time it supposedly saves worth the extra emissions? And what should you know about your personal AI footprint?
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