A TELUS AI agent approached sustainability like a chess game

Everything in this small, nondescript datacentre comes in singles. There's one server, one cooling unit, and one cardinal rule: stay within thermal guidelines. It's into this setting that TELUS released an AI agent tasked with cooling the room as efficiently as possible, and gave it virtual carte blanche to figure out how. This was the first real-world test in TELUS' Energy Optimization System Project (EOS), a pilot in which a reinforcement learning agent took control of a real physical system in order to teach itself how to best operate it. Two months prior, that same agent had showed it could increase energy efficiency by 2%-15% in a simulator, thanks in large part to a series of its own ingenious innovations.