Tech bosses think nuclear fusion is the solution to AI’s energy demands – here’s what they’re missing
Could nuclear fusion be the answer to AI's energy needs? Tech companies need to consider these factors for the future.
The artificial intelligence boom has already changed how we understand technology and the world. But developing and updating AI programs requires a lot of computing power. This relies heavily on servers in data centres, at a great cost in terms of carbon emissions and resource use.
One particularly energy intensive task is “training”, where generative AI systems are exposed to vast amounts of data so that they improve at what they do.
The development of AI-based systems has been blamed for a 48% increase in Google’s greenhouse gas emissions over five years. This will make it harder for the tech giant to achieve its goal of reaching net zero by 2030.
Some in the industry justify the extra energy expenditure from AI by pointing to benefits the technology could have for environmental sustainability and climate action. Improving the efficiency of solar and wind power through predicting weather patterns, “smart” agriculture and more efficient, electric autonomous vehicles are among the purported benefits of AI for the Earth.
It’s against this background that tech companies have been looking to renewables and nuclear fission to supply electricity to their data centres.
Nuclear fission is the type of nuclear power that’s been in use around the world for decades. It releases energy by splitting a heavy chemical element to form lighter ones. Fission is one thing, but some in Silicon Valley feel a different technology will be needed to plug the gap: nuclear fusion.
Unlike fission, nuclear fusion produces energy by combining two light elements to make a heavier one. But fusion energy is an unproven solution to the sustainability challenge of AI. And the enthusiasm of tech CEOs for this technology as an AI energy supply risks sidelining the potential benefits for the planet.
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