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AI energy demands create global concerns as DePIN offers a solution

AI energy demands create global concerns as DePIN offers a solution

GrafaGrafa2024/09/13 05:35
By:Liezl Gambe

The rapid growth of artificial intelligence (AI) and generative AI technologies has significantly increased global energy consumption, posing a threat to energy stability worldwide. 

While these technologies have become an integral part of everyday life, from smart alarms to personalised news apps, their rising energy demands highlight the urgent need for sustainable solutions. 

Decentralised Physical Infrastructure Networks (DePIN) are emerging as a promising response to this growing challenge.

AI systems are among the most energy-intensive modern technologies, requiring substantial electricity and contributing significantly to carbon emissions. 

The world is facing a surge in energy demands driven by the widespread adoption of AI. 

In 2023, the implications of generative AI became evident, and by 2024, its use across various sectors intensified, leading to a substantial increase in electricity consumption by data centers. 

Forbes reported that training the GPT-4 model required over 50 gigawatt-hours, equivalent to 0.02% of California’s annual electricity production, and 50 times more energy than GPT-3. 

Currently, data centers and transmission networks account for 3% of global energy consumption, emitting as much carbon dioxide as an entire country like Brazil.

The International Energy Agency (IEA) projects that global electricity demand could rise from 460 terawatt-hours (TWh) in 2022 to 1000 TWh by 2026, with U.S. data center demand expected to increase from 200 TWh to 260 TWh by 2026. 

Addressing this issue, Ayush Ranjan, CEO of Huddle01, emphasised the need for solutions like DePIN to manage AI’s escalating energy requirements. 

“AI data centers require a substantial amount of electricity for computation and cooling. If AI applications continue to grow at the current rate, we will see a significant strain on both local and global energy grids that will prove unsustainable. This burden will continue to increase as AI systems get more and more complex with time. This will again lead to higher emissions and grid instability,” he warned.

DePIN aims to distribute computational tasks more efficiently by leveraging underutilised hardware resources. 

By decentralising energy consumption and employing edge computing, DePIN networks can alleviate the burden on energy grids and reduce the strain on centralised data centers. 

Ranjan explained, “This reduces the workload on servers and spreads energy consumption more evenly across regions, easing the burden on energy grids.” 

This approach minimises energy-intensive, long-distance data transfers, particularly since 84% of data centers are concentrated in the U.S., Europe, and China.

Through decentralised solutions like DePIN, the growing energy demands of AI can be managed more sustainably. 

Ranjan affirmed, “Splitting the energy consumption across multiple devices and regions, reducing the load on data centers and energy grids by leveraging existing devices or resources to build the network will prove critical in solving this issue.” 

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Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.

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