chatbot environment
Question-Answering Chatbot Development using XLnet transformer model for Digital/Smart Learning
Society is becoming more "mobile-first" as a result of digitization (Oracle, n.d.). As messaging apps grow increasingly common, chatbots are becoming more important in this mobility-driven revolution (Oracle, n.d.). Intelligent conversational chatbots are increasingly being utilized as interfaces for mobile applications, and they're changing the way businesses and customers communicate (Oracle, n.d.). Chatbots enable businesses to communicate with consumers on a personal level without incurring the costs of hiring human representatives (Oracle, n.d.). Chatbots are nothing more than a program that engages in conversation with the user and responds to their questions (Oracle, n.d.).
Updated: A Comparison Of Eight Chatbot Environments
I have built prototypes with most of the commercial cloud and opensource Conversational UI & AI platforms currently available. I have found that environments are generally very similar in their approach to tools available for crafting a conversational interface. Considering what's available, chatbot development environments can still be segmented into 4 distinct groups. The leading commercial cloud environments attract customers and users to them purely for their natural language processing prowess and presence. Among these I would count IBM Watson Assistant, Microsoft Bot Framework / Composer / LUIS / Virtual Agents, Google Dialog Flow etc. Established companies gravitate to these environments, at significant cost of course.