It’s well documented that AI is a power-hungry technology. But there has been far less reporting on the extent of that hunger, how much its appetite is set to grow in the coming years, where that power will come from, and who will pay for it. For the past six months, MIT Technology Review’s team of reporters and editors have worked to answer those questions. The result is an unprecedented look at the state of AI’s energy and resource usage, where it is now, where it is headed in the years to come, and why we have to get it right.
At the centerpiece of this package is an entirely novel line of reporting into the demands of inference—the way human beings interact with AI when we make text queries or ask AI to come up with new images or create videos. Experts say inference is set to eclipse the already massive amount of energy required to train new AI models. We were so startled by what we learned reporting this story that we also put together a brief on everything you need to know about estimating AI’s energy and emissions burden.
