DePIN News: MITIGATING THE ENERGY CRISIS BROUGHT BY AI TECHNOLOGIES
Impact of AI on Energy Infrastructures
The challenge is stark. As one of the most energy-intensive modern IT endeavors, AI systems require considerable carbon emissions and electricity. Indeed, the world might not be ready for their demands.
Global Electricity Demand Projections
In 2023, the world became acquainted with the implications of generative AI, and by 2024, its utilization in various sectors magnified. Hence, data centers that power these AI models are becoming massive consumers of electricity.
- Forbes noted that GPT-4 required over 50 gigawatt-hours to train, equivalent to 0.02% of California’s annual electricity production.
- It requires 50 times more energy than its predecessor, GPT-3.
Globally, data centers and their transmission networks now contribute to 3% of global energy consumption, emitting as much carbon dioxide as Brazil. Furthermore, the escalating energy requirements show no signs of abating.
- According to an International Energy Agency (IEA) projection, global electricity demand will surge from 460 terawatt-hours (TWh) in 2022 to 1000 TWh by 2026.
- In the United States alone, the power demand from data centers is expected to increase from 200 TWh in 2022 to 260 TWh by 2026, marking a 6% share of the country’s total power usage.
Amid this backdrop, Ayush Ranjan, CEO of Huddle01, highlighted the urgent need for solutions like DePIN (Decentralized Physical Infrastructure Network) in an interview with BeInCrypto.
This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.