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    AI's Massive Energy Demands Prompt Search For Efficiency Solutions

    4 hours ago
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    It's 2024: artificial intelligence is becoming more common and part of our everyday lives. Every day, a new AI model is being launched, but at what cost? This innovative development is causing massive strains on energy grids, pushing industry players to think of alternative solutions to power these models. Today, startups cannot cope with the cost of running data centers and often rely on large players to upscale their computing capability to run their models.

    AI Models Need More Energy

    Unlike traditional Internet, AI is an advanced type of computing that requires an increased amount of electricity and energy to develop and operate seamlessly. Why does AI require more energy than the Internet and other types of computing? Any artificial intelligence model requires advanced algorithms always operating on the back end, a setup different than those used for Internet functions like search engines. These applications usually require more than 100 times more data exchange than traditional services to run and thus demand more resources and energy to sustain their functionality.

    Microsoft Copilot's Energy Consumption

    Microsoft’s 2024 Environmental Sustainability Report revealed that their energy consumption increased from 18 million megawatts in 2022 to over 24 million megawatts in 2023. This surge in consumption is attributable to the demands of running the company's generative artificial intelligence model, Microsoft Copilot. According to the report, the tech giant does source 98.2% of the energy it uses to run its operations, including Copilot, from renewable sources like electricity, chilled water, and hot water.

    AI Race

    As these innovative models grow, the more computational power they will require and the more energy they will consume. Tech giants like Google, Meta, and Microsoft have not relented in their race to have the top AI models; however, there should also be more efforts to seek alternative energy sources to reduce emissions.

    Furthermore, the data centers are collectively consuming millions to billions of gallons of water, which can potentially lead to water scarcity in their local communities. Both state and federal governments should intervene to push the industry players to adopt efficient energy sources. Without stricter regulations on energy consumption, these companies will continue to use millions of gallons of water and electricity and strain local resources to unsustainable levels.

    Final Thoughts

    Even though AI has permeated every part of our lives, it will continue to invade our lives more as the energy and water needed to run these models are likely to double by 2030. There is a need for an aggressive push for companies to shift their operations from non-renewable sources of energy to renewable.

    Industry players have been adopting more investments in carbon offsets, but this is not adequate. Significant investments in renewable sources of energy and initiatives to replenish water sources should take precedence to avoid a crisis in the future. The search for alternative energy sources should progress full steam to avoid future disruptions of technological advancement.

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    Article originally written by John Muthui.


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