NVIDIA: Could AI Solve its Own Sustainability Issues

As the capabilities of AI continue to expand, so too does its market size, with an overwhelming majority of companies across various industries exploring and implementing AI solutions.
However, this rapid growth raises important questions about the environmental impact of the technology, particularly in terms of energy consumption.
At the heart of the AI revolution lie data centres, the powerhouses of modern computing.
These facilities can house tens of thousands of devices and run 24/7 to meet the constant demand for services.
These services include data storage, cloud computing, media streaming and AI processing.
The sheer scale of these operations translates into significant energy requirements, both for powering the machines and keeping them cool.
Jensen Huang, CEO and Co-Founder of NVIDIA, explains: "Data centres are already about 1-2% of global electricity consumption and that consumption is expected to continue to grow.
“This continued growth is not sustainable, neither for operating budgets nor for our planet."
NVIDIA's approach to sustainable AI
Chip-maker NVIDIA has become one of the largest American companies by market cap.
The company invented graphics processing units (GPUs) in the 1990s and has become a dominant supplier of AI hardware and software.
Headquartered in California, USA, NVIDIA has more than 26,000 employees and had revenue of US$60.9bn in 2023.
In March 2024 it became only the third company in the history of the US to close with a market capitalization in excess of US$2tn.
NVIDIA is optimistic about AI’s ability to solve sustainability problems including the energy consumption of data centres.
Joshua Parker, Senior Director of Corporate Sustainability at NVIDIA, says: "AI, I firmly believe, is going to be the best tool that we've ever seen to help us achieve more sustainability and more sustainable outcomes."
NVIDIA's approach centres on the concept of accelerated computing, which combines GPUs and CPUs to handle complex computations quickly and efficiently.
The company says these systems can be up to 20 times more energy efficient than traditional CPU-only systems for AI inference and training.
Joshua explains: "If you compare the energy efficiency for AI inference from eight years ago until today, it's 45,000 times more energy efficient."
Cooling solutions for data centres
Beyond processor efficiency, NVIDIA is also exploring innovative cooling solutions to further reduce energy consumption in data centres.
The company is advocating for direct-to-chip liquid cooling, which offers significantly higher efficiency compared to traditional air conditioning methods.
"Our recommended design for the data centres for our new B200 chip is focused all on direct-to-chip liquid cooling," Joshua explains.
This approach not only reduces energy consumption but also allows for higher computing densities, potentially reducing the overall footprint of data centres.
How AI can help to address climate change
While optimising energy consumption in data centres is crucial, AI's potential to address climate change extends far beyond this single application.
NVIDIA and other industry leaders are exploring various ways in which AI can contribute to sustainability efforts across different sectors.
AI can have a big impact on weather forecasting by enhancing the accuracy of weather predictions.
This can enable better preparation for climate-related weather events, potentially saving lives and resources.
Another promising AI application is the use of digital twins – virtual replicas of physical systems or processes.
These AI-powered simulations allow companies to optimise energy consumption without making costly and potentially risky changes in the real world.
Joshua says: "AI and accelerated computing in general are game-changers when it comes to weather and climate modelling and simulation."
AI is also helping to improve the efficiency of electric vehicle batteries and enhance the performance of solar panels.
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