All that you need to know about Chatbots and TensorFlow

All that you need to know about Chatbots and TensorFlow
February 26 2019

A chatbot is a computer program that mimics humans while conversing with website visitors. Chatbots are developed using Artificial Intelligence and Machine Learning  and are essentially used by companies to deliver customer service to their consumers real-time.

Chatbots have been around since 2016 and by 2020, according to Gartner, more than 85% of all businesses will deploy these computer programs. Since 2016, there has been a two-fold growth in the number of chatbots according to the same study.

One major reason why these programs will be used in greater numbers in the years to come is that they can be made by almost everyone having basic coding skills. If you know a little bit of Python and JavaScript, then making a chatbot is super easy. Chatbots shot into prominence after a few platforms like Facebook Messenger started using them.


Developed by Google Brain, TensorFlow is an open-source library that is used for making numerical computations. It being Python friendly, TensorFlow is used extensively by developers in Machine Learning applications.

Machine Learning is indeed difficult to master. However, with Google Brain’s TensorFlow, developers can easily acquire data and training models, serve predictions and even refine results.

This tool bundles together several Artificial Learning and Deep Learning models and algorithms and makes them useful by way of a common metaphor. Deep Learning models are also called Neural Networks and are inspired by the complex neural networks of the human brain.

The architecture of TensorFlow is quite flexible. It is this flexibility that allows developers to deploy chatbots on several CPUs or GPUs like desktops, mobiles and servers. Several Fortune 500 firms like Google and Intel use TensorFlow in various applications.

How do TensorFlow and Chatbots work together?

In their earlier days, chatbots worked in a limited number of ways. However, they could not drive the conversation to a logical conclusion.

These computer programs worked according to the “If/Then” principle which means that the responses of a chatbot depended on a very limited number of options. With TensorFlow, the responses can be numerous. Therefore, when a customer says, “How are you?”, the bot might very well respond, “I am very well” or “I am very well, thank you”.

It is this dynamism of the responses that make these computer programs a very hot property in the years to come.

The Future of Chatbots

Ted Livingston, the founder of Kik, says that in the not-so-distant future, chat apps will be the new browsers while chatbots will function as websites.

He should know much more about these bots than anyone else. After all, he is the founder of Kik, a chat platform that has 240 million users of whom 40% are American teenagers. Most of his subscribers use bots to ask for some product or service, answer reviews and do various stuff. Chatbots can make the job of buying products or services online simpler.

In the normal course of things, people simply head over to a website, choose their product and then load the cart. In the chatbot scenario, the customer fills out a small form on the website and while he is answering those questions, the bot is analysing the answers and within a few seconds is ready with its product recommendation!

Secondly, why chatbots are hot property these days is that they do not compete for your mobile space as the other apps do. Thanks to TensorFlow Deep Learning, bots play out within the messenger apps that you have already downloaded.

Changing landscape

Marketers and technologists agree that the world of marketing  is surely going to change with the new generation of chatbots. People will buy more number of products and services on their messenger platforms in the near future. Customer service will become more human and efficient. In addition, more and more non-technologists will start building their own chatbots.


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