Geoffrey Hinton


'gggg' is the name of the team that won the 2012 Merck Molecular Activity Challenge on Kaggle. The winners consisted of doctoral students and professors from the University of Washington and the University of Toronto, including computer scientist Geoffrey Hinton famous for the back-propagation algorithm used in training neural networks. The objective of the Merck challenge was to develop the best statistical techniques for predicting the biological activities of different molecules towards 15 biologically relevant targets. Using a deep learning model designed for speech recognition, gggg surmounted an industry standard benchmark by 17%, suggesting new computer-aided avenues for pharmaceutical research.