Ryan Lowe of McGill University, Montreal has developed a neural network that can differentiate between convincing and unconvincing chatbot responses to human questions, matching the judgement of human evaluators. The system could help teach chatbots to become more "human-like" much more quickly than is currently possible. In his paper, published in Proceedings of the National Academy of Sciences, he describes how this approach works by training an artificial intelligence agent called a Neural Turing Machine (NTM) on thousands of different questions posed
Ryan Lowe of McGill University, Montreal has developed a neural network that can differentiate between convincing and unconvincing chatbot responses to human questions, matching the judgement of human evaluators. The system could help teach chatbots to become more "human-like" much more quickly than is currently possible. Lowe intendeds to open-source his chatbot evaluator, so that it can be used by other researchers.