Can AI solve its own environmental crisis?

Can AI solve its own environmental crisis before it’s too late?

What you probably already know: If left unchecked, demand for power to support artificial intelligence could drive up global emissions by 80%, according to Climate Action Against Disinformation, a global coalition of 50 climate and anti-disinformation organizations. These systems use enormous amounts of energy and water, and the report estimates AI demand for these resources could double in the next two years. Some data centers already use more power than a small city. Now, though, some are suggesting AI could solve its own problem.

Why? One AI chip maker recently suggested AI data centers could consume up to 25% of America’s power by 2030, compared to 4% today, and called on tech leaders to use their own innovations to solve the crisis. AI chips are already getting more efficient, and experts are suggesting that will continue to happen like it has for all computer technology: The only way to improve performance is by getting more efficient, which means the systems naturally use less power over time.

What it means: Nvidia’s newest generation of AI chips are 250 to 30 times more efficient than the previous generation, and the company has said its chips have gotten 45,000 times more efficient over the last eight years. Companies also need to narrow the use of AI and give it more specific tasks, which make it more efficient, something the experts are calling “lightweight” AI models.

What happens now? Companies are also calling for AI data centers to be built and expanded in areas where power resources are more abundant and sustainable, like in Canada and Norway, whose grids are highly reliant on hydropower. There are also companies like Crusoe Energy Systems, which is building modular data centers designed to run on excess natural gas produced at oil wells. The company’s systems have the added benefit of almost eliminating the release of methane into the atmosphere at these same wells.

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