Computers built with analogue circuits promise huge speed and efficiency gains over ordinary computers, but normally at the cost of accuracy. Analogue computers that rapidly solve a key type of equation used in training artificial intelligence models could offer a potential solution to the growing energy consumption in data centres caused by the AI boom. Laptops, smartphones and other familiar devices are known as digital computers, because they store and process data as a series of binary digits, either 0 or 1, and can be programmed to solve a range of problems. In contrast, analogue computers are normally designed to solve just one specific problem. They store and process data using quantities that can vary continuously such as electrical resistance, rather than discrete 0s and 1s.

The 40% energy saving on cooling helped one of Google's data centres to achieve a 15% reduction in power usage efficiency, or PUE. PUE is defined as the ratio of the total building energy usage (pumps, chillers, cooling towers) to the IT energy usage (Google's servers). The lower the PUE, the better.

For Google, the massive network of data centers that powers the web giant's operations run up a similarly massive energy tab. The company has been improving server farm efficiency for years, but it recently adopted a novel technique for trimming usage: letting the robots take control. In particular, Google is giving the reins to an artificial intelligence system developed by its subsidiary DeepMind. The AI overlord succeeded in shaving several percentage points off of data center energy consumption, Bloomberg reported. This led to a 15 percent improvement in power-usage efficiency, the metric of how much power goes to the actual computing as opposed to auxiliary services at the data centers.