Navigating AI’s Influence on Climate Change: How SUSE AI Can Play a Positive Role

Artificial intelligence (AI) is already on the path to revolutionizing industries, driving new commercial opportunities and impacting society at a scale similar to the introduction of web 2.0. However, the nature of how AI works coupled with its rapid development and mass adoption raise concerns about its energy demands and subsequent impact on the environment. The 2015 Paris Agreement increased regulation and forced companies into action to limit the increase in the global average temperature to below 2°C. Many organizations that set public targets aligned with the Paris Agreement will find it challenging to meet their commitments if AI development fails to consider its energy requirements across the entire IT ecosystem.

This article explores those concerns,the opportunities AI presents and the role SUSE AI can play.

What’s the Outlook?

The forecasted energy demands of AI in the near term are noteworthy.

The International Energy Agency (IEA) predicts that global electricity usage by data centers, which power AI systems, could double from 2022 to 2026. This surge is equivalent to adding the energy consumption of a large country like Germany to the global grid(1).
AI processes are energy-intensive, with a single ChatGPT query reportedly consuming ten times more electricity than a standard Google search (2).
As AI becomes more prevalent in our daily lives and in business, this exponential increase in energy consumption poses a significant challenge to global efforts to reduce carbon emissions.

The potential environmental impact of AI’s energy hunger is evident. If this increased demand is met primarily through traditional fossil fuels, it could severely undermine global efforts to combat climate change. In light of this forecast, major technology infrastructure suppliers such as Amazon, Microsoft and Google are investing in nuclear power. According to the New York Times, “Microsoft, Google and Amazon have recently struck deals with operators and developers of nuclear power plants to fuel the boom in data centers, which provide computing services to businesses large and small. The demand has accelerated because of the big investments these and other tech companies have made in A.I., which requires far more power than more conventional technology businesses like social media, video streaming and web searches” (3).

AI Innovates at Scale

AI, however, can help to address some of the climate challenges we face today by:

Improving climate modeling and predictions. AI can process complex climate data to provide more accurate and detailed climate patterns and forecast change.
Optimizing renewable energy systems. AI algorithms can predict energy demand, optimize grid operations, and integrate renewable energy sources. This improves the efficiency and reliability of renewable energy systems, reducing emissions.
Reducing carbon footprints across industries. AI helps design improved energy-efficient buildings, plan low-emission transportation routes, assist in carbon capture technologies, and identify energy reduction opportunities.

By prioritizing energy efficiency in our software, AI developers can ensure that the benefits of AI do not come at the cost of our climate goals. At COP29, leaders emphasized the need to reduce tech manufacturing’s carbon footprint while recognizing digital technologies’ role in climate change solutions.

SUSE AI – A Catalyst for Sustainable Technology

As an AI platform provider, SUSE can play a role in helping combat climate challenges. SUSE AI is a trusted, proven platform for enterprises to securely deploy and run Generative AI (GenAI) solutions. It’s vendor-agnostic, allowing customers to deploy any Large Language Model (LLM) and flexibly manage data augmentation. Observability and security features enable GenAI solutions to safely be developed and safely run. SUSE AI helps enterprises operate more sustainably in two key facets:

Scalability

SUSE AI maximizes efficiency by enabling you to deploy the right size hardware footprint. As workload requirements increase, the SUSE AI platform will empower you to scale your AI applications and underlying infrastructure to meet those requirements.

Resource Optimization

SUSE AI provides observability into the stack to load balance to maximize efficiency. For example, load balancing between underutilized vs overutilized nodes. The observability functionality can perform hardware monitoring to identify underutilized, expensive GPUs. SUSE AI monitors applications and underlying hardware to identify inefficient and rebalance loads for maximum efficiency. By focusing on developing more energy-efficient software and supporting the transition to renewable energy sources for data centers, we can contribute significantly to making AI more sustainable.

By taking these different factors into consideration, SUSE is committed to enabling this crucial transition.

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