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JP
In today’s world, artificial intelligence (AI) is playing a significant role in every aspect of human life, from information retrieval to advanced applications. However, it also brings major challenges in managing the soaring demands for energy and resources.
This is particularly evident in data centers, which are key components in processing large AI systems like ChatGPT, Google Gemini, and Microsoft Copilot. That’s why data center companies like Vantage have decided to build their data centers near energy sources. At the same time, various companies are investing in alternative energy sources and new methods to strengthen the power grid.
Soaring energy demand
There are currently over 8,000 data centers in the world, with roughly half located in the United States. Despite the large number of data centers, it is not enough to keep up with AI’s rapidly increasing energy demands. A single search with ChatGPT consumes up to ten times more energy than a Google search. Additionally, training large AI models produces a significant amount of carbon dioxide, comparable to the lifetime emissions of five gas-powered cars.
According to predictions, data centers could consume up to 16% of the total energy usage in the United States by 2030. It significantly increases from 2.5% in 2022. This alarming rise reflects the rapid growth of the AI industry.
It’s not only electricity demand that is soaring, but water demand is also increasing significantly. It is estimated that global water demand for AI will reach 6.6 million cubic meters by 2027. This is four times the annual water consumption of Denmark. These figures show a significant impact on our natural resources.
The Rapid Rise of AI: Unveiling the Challenges
Supporting increased energy demand: Existing power grids often cannot support the rapidly increasing demand. This drives the need to improve and expand energy infrastructure.
Heat management: Data centers produce large amounts of heat, requiring highly efficient cooling systems. This leads to high water consumption.
Water resource constraints: In Chile, which faces drought issues, water usage by data centers has become a highly contentious topic. It leads to community opposition and the revocation of some licenses.
Environmental Impact: Another challenge that requires attention is the rise in greenhouse gas emissions due to increased energy consumption.
Solutions and innovations
To address these challenges, the data center industry and related companies are developing various solutions, such as:
1. Improving the efficiency of power transmission systems
- Using predictive software to reduce failures at weak points in transformers.
- Developing smarter energy management systems to distribute loads efficiently.
2. Developing an efficient cooling system
- Using liquid cooling directly on the chip instead of air cooling.
- Designing data centers that use less water or no water at all.
3. Enhancing the energy efficiency of equipment
- Using more energy-efficient ARM processors instead of traditional processors.
- Developing low-power storage devices.
4. Developing AI models on hardware devices (On-device AI)
- Reducing reliance on cloud computing by performing some processing on edge devices.
5. Using renewable energy
- Investing in clean energy sources, such as solar and wind power.
- Experimenting with nuclear fusion energy for future data centers.
Challenges in sustainable AI development
The growth of AI brings unprecedented opportunities and challenges. While we are reaping enormous benefits from this technology, we must also be aware of the rapidly increasing resource and environmental costs.
AI has the potential to transform the world. However, its development must come with the responsibility of preserving the environment and using resources sustainably. The data center industry and related companies need to invest in environmentally friendly technologies. They also need to find solutions to support AI’s future growth. This enables the technology to grow sustainably and remain in balance with nature.
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