An algorithm used trillions of times a day around the world could run up to 70 per cent faster, thanks to an artificial intelligence created by UK-based firm DeepMind. It has found an improved way for computers to sort data that has been overlooked by human programmers for decades. "We honestly didn't expect to achieve anything better: it's a very short program, these types of programs have been studied for decades," says Daniel Mankowitz at DeepMind. Known as sorting algorithms, they are one of the workhorses of computation, used to organise data by alphabetising words or ranking numbers from smallest to largest. Many different sorting algorithms exist, but innovations are limited as they have been highly optimised over the decades.

The voracious appetite for energy from the world's computers and communications technology presents a clear threat for the globe's warming climate. That was the blunt assessment from presenters in the intensive two-day Climate Implications of Computing and Communications workshop held on March 3 and 4, hosted by MIT's Climate and Sustainability Consortium (MCSC), MIT-IBM Watson AI Lab, and the Schwarzman College of Computing. The virtual event featured rich discussions and highlighted opportunities for collaboration among an interdisciplinary group of MIT faculty and researchers and industry leaders across multiple sectors -- underscoring the power of academia and industry coming together. "If we continue with the existing trajectory of compute energy, by 2040, we are supposed to hit the world's energy production capacity. The increase in compute energy and demand has been increasing at a much faster rate than the world energy production capacity increase," said Bilge Yildiz, the Breene M. Kerr Professor in the MIT departments of Nuclear Science and Engineering and Materials Science and Engineering, one of the workshop's 18 presenters.