Extreme Learning Machines (ELM) provide efficient unified solutions to generalized feedforward networks including but not limited to (both single‐hidden‐layer and multi‐ hidden‐layer) feedforward neural networks, RBF networks, and kernel learning. ELM possesses unique features to deal with regression and (multi‐class) classification tasks. Consequently, ELM offers significant advantages such as fast learning speed, ease of implementation, and minimal human intervention. ELM has good potential as a viable alternative technique for large‐scale computing and artificial intelligence. Organized by Tsinghua University, Northeastern University and Nanyang Technological University, ELM2013 will be held in Beijing, the capital of China. This conference will provide a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique, as well as participating in a competition on a data‐centric application problem. Details of ELM2013 competition will be announced by March 15, 2013.