Powering artificial intelligence models takes a lot of energy. A new analysis demonstrates just how big the problem could become
Every online interaction relies on a scaffolding of information stored in remote servers—and those machines, stacked together in data centers worldwide, require a lot of energy. Around the globe, data centers currently account for about 1 to 1.5 percent of global electricity use, according to the International Energy Agency. And the world’s still-exploding boom in artificial intelligence could drive that number up a lot—and fast.
Now, it’s not going to happen like that because Google would also have to invest $100 billion in hardware to make that possible. And even if had the money to invest, the supply chain couldn’t deliver all those servers right away. But I still think it’s useful to illustrate that if you’re going to be using generative AI in applications , that has the potential to make every online interaction much more resource-heavy.
What type of hardware you’re using also matters. The latest servers are more efficient than older ones. What you’re going to be using the AI technology for matters, too. The more complicated a request, and the longer the servers are working to fulfill it, the more power is consumed.
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