A Neural Conversational Model

This paper introduces a neural network approach to building conversational agents. It uses a sequence-to-sequence model to predict the next utterance in a conversation, given the previous utterances. The model is trained on a large dataset of conversations and can generate coherent and relevant responses, demonstrating the potential of neural networks for creating more natural and engaging conversational AI.