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For decades, Big Tech has been one of the largest and most innovative proponents of clean energy. Silicon Valley giants have put considerable amounts of money and effort into making their companies greener and supporting renewable energy growth. But in recent years, the conversation around the tech sector’s energy use has changed from one of pride and optimism to a far more anxious conversation colored by an uncertain future. The problem? Artificial Intelligence.
While renewable energy production is on the rise and incentives to expand capacity in the United States are better than ever, that added energy is dwarfed by the rapidly increasing energy consumption of Artificial Intelligence. It’s estimated that the training process for GPT-3, the predecessor of ChatGPT, required around 1,287 megawatt hours of electricity and 10,000 computer chips. That is enough energy to power 121 homes in the United States for an entire year, and produce 550 tonnes of carbon dioxide.
As AI becomes more and more ubiquitous and changes the way we design and work with technologies, the energy and carbon footprints of AI and associated data centers is ballooning exponentially, a trend which will only continue to intensify. Currently, AI alone consumes as much energy in a year as some entire developed nations, and has matched the energy footprint of Bitcoin. Consulting firm Gartner projects that if business continues as usual, the sector will be solely responsible for a stunning 3.5 percent of global electricity consumption by just 2030.
Furthermore, all of that energy consumption is correlated to a significant amount of greenhouse gas emissions. Even though renewable energy represents some of Big Tech’s energy consumption, it has no hope of providing all of the energy that the sector needs. Already, according to figures from the International Energy Agency, data centers and transmission networks are jointly emitting as much carbon dioxide every year as the entire nation of Brazil.
In fact, the projected energy consumption of the tech sector, primarily driven by AI’s breakneck growth, is so large that Big Tech leaders aren’t just worried about having enough clean energy to keep their carbon footprint in check, they’re worried about having enough energy, period. “New data centers can be built faster than new power generation and there is already a supply crunch,” the Wall Street Journal recently reported.
A new data center comes online somewhere in the world every three days according to Bill Vass, vice president of engineering at Amazon Web Services. But that timeline is not sustainable if there’s no energy to power the new centers. Already, construction timelines for many data centers have been pushed back from two to six years due to issues with power supply.
This leaves the tech industry in quite a bind. They want to power their ventures with clean energy, but they also don’t want to have to wait for it. “Tech is not going to wait seven to 10 years to get this infrastructure built,” Toby Rice, CEO of giant U.S. natural-gas producer EQT, was quoted by the Wall Street Journal. “That leaves you with natural gas.”
Other industry insiders, however, are betting big on nuclear energy to meet the tech sector’s massive energy needs without hindering its decarbonization goals. Others are counting on innovation and technological advancements to save the sector from itself. “There’s no way to get there without a breakthrough,” OpenAI chief executive officer Sam Altman said at a Bloomberg event on the sidelines of the World Economic Forum’s annual meeting earlier this year. Altman believes that this breakthrough will come in the form of nuclear fusion.
In 2021, Altman personally provided $375 million in funding to private U.S. nuclear fusion company Helion Energy, which later made a deal to provide energy to Microsoft. Altman is also chairman of the board for nuclear microreactor company Oklo, which may go public this year. “The AI systems of the future will need tremendous amounts of energy and this fission and fusion can help deliver them,” Altman said.
