The Next AI Power Bottleneck Will Be Inside Cities

Over the past few years, and counting, the AI infrastructure market has spent a great amount of time and money (close to $7 trillion of data-centre investment by 2030, by McKinsey’s estimate) learning how to build large data centres wherever power is available. “Wherever” being the key word because the location wasn’t very important. A training cluster simply needs access to sufficient power.

But location is starting to become increasingly relevant nowadays as AI’s usage grows beyond chat interfaces to machines, voice systems, video, and applications interacting with the physical world. Such operations require computing power to be closer to the urban centres where those interactions happen to keep latency down. While tools like chatbots can tolerate a half-second delay, automated service applications like remotely supervised delivery robots, live voice assistants or automated fulfillment systems may need to react within milliseconds.

This is the new challenge on the block for AI companies. How to find smaller blocks of reliable power in and around large metropolitan areas? And even after locations have been scouted, how to deal with the backlash that…