Machine learning is nipping at the heels of conventional physical modeling of air quality predictions in more and more places. The latest is Johannesburg, South Africa, where computer engineer Tapiwa M. Chiwewe at the newly opened IBM Research lab is adapting IBM's air quality prediction software to local needs and adding new capabilities. The work is an expansion of the so-called Green Horizons initiative, in which IBM researchers partnered with Chinese government researchers and officials, starting two years ago. Last month, Chiwewe presented some of the Johannesburg lab's first results, involving ground-level ozone level predictions, at the 14th International Conference on Industrial Informatics in Poitiers, France. "You can do a lot of physics to understand how ozone is found in different places," he says, "but what we did is we just collected a lot of data and trained these machines on it and they were able to predict [local ozone levels] without any knowledge of how ozone works in the atmosphere."