Deep Learning Achievements Over the Past Year – Stats and Bots

Almost a year ago, Google announced the launch of a new model for Google Translate. The company described in detail the network architecture -- Recurrent Neural Network (RNN). The key outcome: closing down the gap with humans in accuracy of the translation by 55–85% (estimated by people on a 6-point scale). It is difficult to reproduce good results with this model without the huge dataset that Google has. You probably heard the silly news that Facebook turned off its chatbot, which went out of control and made up its own language. This chatbot was created by the company for negotiations. Its purpose is to conduct text negotiations with another agent and reach a deal: how to divide items (books, hats, etc.) by two. Each agent has his own goal in the negotiations that the other does not know about.