conversations

Before diving into the ML behind customer-facing chatbots, I’ll first give a quick overview of the system (tl;dr). I will also speak from my experience with Dialogflow, and make the assumption that the approach is similar across other ML-based chatbots.Basically, everything is built around “Intents” and “Entities”.Intents: “When an end-user writes or says something, referred to as an end-user expression, Dialogflow matches the end-user expression to the best intent in your agent. Matching an intent is also known as intent classification.”(definition from Google cloud documentation)Intent diagram from the same documentation as the quote aboveThrough intents, the human creating the chatbot defines the possible topics of conversation. With this context provided, the chatbot can refer to fixed...