Learn NLP: How are chatbots created?

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Chatbot, conversational bot, Artificial Intelligence assistant, intelligent virtual assistant, conversational agent, digital assistant, conversational interface, we find endless names, some more accurate than others, to refer to this technology. Experts do not agree on which one is the best or what subtle differences there are between each one, but what is clear is that they are everywhere.

Conversational assistants answer countless questions and tasks, such as buying a train ticket, knowing the stock of a product in a store, buying movie tickets, ordering food at a restaurant, or checking the weather in your city with the mobile.

It is common to use Machine Learning and Natural Language Processing in Artificial Intelligence to create these chatbots, achieving that, based on examples, they are able to detect what the user needs through text and to maintain a conversation with concrete and coherent answers. With the CIBOP program from Imarticus, get an opportunity to learn more about chatbots and how Natural Language Processing with python can achieve this.  

Types of Chatbots

Although it is clear that these machines have the purpose of making our lives a little easier, there are different types of chatbots depending on the purpose they have:

  • Some assistants have the purpose of maintaining an unstructured conversation, imitating those of the people. A good example of this is BlenderBot, from Facebook, designed to be able to carry on a conversation as if it were a human: with its own personality, showing empathy, knowledge, feelings, etc. 
  • Others are designed for short conversations and are also capable of solving certain specific tasks. For example, Apple's Siri, which is capable of following short dialogues and responding to tasks such as sending a message, setting an alarm, or searching for a song.
  • Another type is chatbots specialized in specific tasks for specific domains. These are tools that provide solutions to limited complex problems, such as booking a flight, ordering food, analyzing health problems, or, for example, buying a train ticket. 

Normally these chatbots use Machine Learning and Natural Language Processing techniques to provide solutions and respond to user needs. 

Within the Natural Language Processing techniques, they need the understanding of natural language (NLU) to understand what the user has said and to be able to respond to it (for this, they use the intentions, entities, and dialogue flows). On the other hand, using natural language generation (NLG) they are able to return answers prefabricated or custom responses through, for example, query databases.

Steps To Create a Chatbot

But the important question that arises here is how do you create a chatbot? There are platforms that help to design a conversational agent, analyze data from conversations, search databases, or train chatbots in a relatively simple way. Some of the many available on the web are Language Understanding (LUIS) of Microsoft, Google Dialogflow, or Watson Assistant IBM.

These tools are usually based on intentions, entities, and flows of dialogue to build conversational agents. By integrating Natural Language Processing with python, chatbots can be specialized in specific tasks depending on the demand. We, at Imarticus, offer Natural Language Processing courses to learn and create chatbots.

Is a Chatbot the Same as a Virtual Assistant?

Some specialists believe that what differentiates a bot from a virtual assistant is the high degree of customization of the latter. In this way, while the chatbot is the face of a company, to whose codes or particularities the user has to adapt to achieve their goal, it is the personal assistant who adapts to the user and not the other way around. 

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