Didi currently processes over 11 million trips, plans over 9 billion routes, and collects over 50TB of data per day. Machine learning strategies are vital to the company's success, and with growth comes the need to constantly improve on core algorithms, especially those that impact supply-demand forecasting. The competition is a challenge to machine learning and big data students around the world to improve how the company ensures riders always get a car when and where they need it, and drivers know where to be even before a ride is hailed. Didi has just published the competition data set, and registration closes on June 17 when the first round submission is due. The Top 10 teams will be invited to Didi in July to compete for the top prize.