Utterances help the engines understand the phrases, but it also means the response to all these utterances will be the same.Įntity: Entity helps identify the intent in detail. I want to place an online order for burgers In our example, there are various ways that the user will ask to place an order, such as: Utterance: It means identifying the different ways in which a user asks their intent. If they ask an AI Chatbot to do so, the bot has recognised the intent that the user wants to place an order. What exactly is the problem statement that the user wants to solve? For example, a user wants to place an order at a Burger Place. Intent Recognition: NLP recognises what the user is trying to get a response for. NLP technology works on deriving context from words. The technique on which these engines rely to understand the human language is called Machine Learning. The ultimate goal of these engines is to decipher and understand the human language in order to generate an accurate response. There are many NLP engines in the market, such as Dialogflow by Google, Watson Assistant by IBM, Lex by Amazon, and Luis by Microsoft. How does an NLP AI Chatbot learn?Īs I mentioned before, NLP is one of the prime differentiation between rule-based and AI Chatbots. To understand how AI Chatbots are different from Rule-Based Chatbots and elements of NLP, check out this article: Difference between Chatbot and Conversational AI. Your AI Chatbot aids a live chat representative’s work, helping them answer complex customer questions and order products and services, among other things, through text-based inputs. It utilises Natural Language Processing (NLP) to understand the intents and respond to those intents. You start by training, helping them identify words and phrases, and with time, the person is capable of speaking the said language independently, without your aid.

Imagine that you’re teaching someone to speak a new language. Rule-based chatbots are built in a flow-chart manner with a decision tree that allows the visitor to choose options.ĪI Chatbots take it up a notch higher, facilitating more advanced conversations on a bot.

A rule-based chatbot doesn’t deviate from the pre-built conversational flow as the questions and answers are already determined. Chatbots are bifurcated into AI Chatbot and Rule-Based Chatbot, and both are vastly different in terms of their complexities and use-cases. Although we use the word chatbot to describe all automated text-based conversations, there are more types to them that encourage these conversations.

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