Is AI the next big climate-change threat? We haven’t a clue
At a recent conference in San Francisco, Gary Dickerson took the stage and made a bold prediction. The chief executive of Applied Materials, which is a big supplier to the semiconductor industry, warned that in the absence of significant innovation in materials, chip manufacturing and design, data centers’ AI workloads could account for a tenth of the world’s electricity usage by 2025.
Today, the millions of data centers around the world soak up a little less than 2%—and that statistic encompasses all kinds of workloads handled on their vast arrays of servers. Applied Materials estimates that servers running AI currently account for just 0.1% of global electricity consumption.
Other tech executives are sounding an alarm too. Anders Andrae of Huawei thinks data centers could end up consuming a tenth of the globe’s electricity by 2025, though his estimate covers all their uses, not just AI.
Jonathan Koomey, special advisor to the senior scientist of Rocky Mountain Institute, is more sanguine. He expects data center energy consumption to remain relatively flat over the next few years, in spite of a spike in AI-related activity.
These widely diverging predictions highlight the uncertainty around AI’s impact on the future of large-scale computing and the ultimate implications for energy demand.
AI is certainly power hungry. Training and running things like deep-learning models involves crunching vast amounts of data, which taxes memory and processors. A study by research group OpenAI says that the amount of computing power needed to drive large AI models is already doubling every three and a half months.
Applied Materials’ forecast is, by its own admission, a worst-case scenario designed to highlight what could happen in the absence of new thinking in hardware and software. Sundeep Bajikar, the company’s head of corporate strategy and market intelligence, says it assumes there will be a shift over time in the mix of information being used to train AI models, with videos and other images making up a rising percentage of the total relative to text and audio information. Visual data is more computationally intensive and therefore requires more energy.
There will also be more information for models to crunch thanks to the rise of things like autonomous vehicles and sensors embedded in other smart devices. And the spread of super-fast 5G wireless connectivity will make it even easier to shuttle data to and from data centers.
