The word ‘chatbots’ has become one of the most whispered words in the tech world today. Each and every tech company is putting a lot of effort on researching and developing bot related technologies.
The very first thing that you should keep in your mind is “Bot is not an acronym neither a magic app”. Bot is an application that operates as an agent for a user or another program or simulates a human activity.
I would say, there’s no Artificial intelligence or natural language processing attached with most of the chatbots you see out there. But AI and machine learning have become prominent factors of giving bots more human side.
The evolution of chatting paradigms and the rapid adaptation of millennials for chatting platforms like Facebook messenger, WhatsApp and Viber increased the need of chatbots that can handle business processes.
The same way a website is interacting with a user, bot acts as the interface into the service. Simplicity, increasing productivity, personalized service lines are some of the major benefits that we can achieve with getting chatbots into the play.
Super bots Vs domain specific bots
Probably the very first thought that comes to your mind when it says ‘bots’ might be “Siri, Cortana or Google assistant”. Dominating our pockets with their ability of interacting as a personal assistant, these software utilities can be defined as super bots. They are equipped with speech recognition as well as natural language understanding. Normally there’s a persona specifically designed for these super bots. The backend of these intelligent applications is backed with machine learning and deep learning based technological interventions.
Domain specific bots are easy to find and easy to build (comparatively to the super bots). They are specifically designed aligning to a particular business process. Ordering a pizza from nearest pizza shop, customer service call centers or booking a flight ticket are some example business processes that can be easily adopted to a conversational bot interface. These bots may use machine learning techniques for natural language understanding.
Business bots Vs Consumer bots
Bots are not only mend to be to involve in business process. Fun is mandatory! The consumer bots are specifically designed to maintain human like conversations with the users. Sometimes even for flirting 😉 Mitsuku is known as one of the prominent consumer bots that have built for today.
Text or the voice?
Interacting with a chatbot can be done in several ways. Textual communication is just one thing. Speech recognition enables the user to interact with the chatbots with speech. Some chatbots provide interactive clickable cards for user interaction. Amazon Alexa even has a hardware component that interacts with the user with voice commands.
There are plenty of programming paradigms prevailing today that helps you to build conversational bots. Microsoft Bot Framework is a programmer friendly framework that supports C# or node.js for deploying bots. Integrating chat channels like Skype and messenger can be too done through the framework.
Natural Language understanding provides more human like nature for bot’s conversations. For that, LUIS service by Microsoft, API.AI, wit.ai are some prominent services used today by the programmers. No need to go from the scratch of machine learning algorithms. Just an API call will do the magic for you.
Bots can be given more human like abilities with machine learning based intelligent API services and SDKs. Microsoft Cognitive services is a valuable toolset that you can use to give your chatbot the ability to see, hear and even think!
I guess, codeless bot building services (some are already there in the market, but not so matured) and natural language generation would be the next big things in the conversational bot building industry. Deep learning will come to scene with language generation for sure.
Time to market is a prominent factor in the world of business. Then why not going with the trend and adopt a chatbot for your own business or start building bots as your business? 😉