Why Chatbots Cannot Learn Directly From Human Conversations - DZone AI

In the previous article, we presented two ways of categorizing conversational agents -- more widely known as chatbots -- along with their advantages, limitations, and use case scenarios. In this article, we are focused on emphasizing how chatbots infer knowledge from human conversations through a basic rule-based system, machine learning, and natural language processing, which all play a crucial role in facilitating the automation of a request-handling process. A few months ago, we took up the challenge to build a chatbot that could seamlessly integrate into a customer support platform, applicable to various industries. At Tremend, we developed a chatbot prototype for a major telecom client. The primary scope of the project was to create a quality-consistent chatbot that could minimize human labor with respect to tedious or repetitive tasks, usually time-consuming and hard to scale across brief periods of time and on an ad hoc basis.