This article is the first part in a series about Chatbots and Machine Learning. Other articles that were published in this series can be found here:
#2: Natural Language Processing and Machine Learning: the core of the modern smart chatbot
By 2020, it’s estimated that around 20 billion ‘connected things’ can be found in an IoT environment. It will be a challenging task to build interfaces that can handle the huge amount of things and data that come with this development. In this article, I will elaborate on the possible role of chatbots within this environment.
What exactly is a chatbot?
There are already well known examples of AI and chatbots, for example Cleverbot, Cortana or Tay. Tay, Microsoft’s first public experiment with a Twitter bot, was so successful that it started mimicking its followers. However, after 16 hours of being “alive” Microsoft had to pull Tay’s plug because it had turned into a feminist bashing racist xenophobe. Even though it was considered a failure, it showed how much the technology around smart chatbots had evolved. Tay could give coherent and meaningful answers to questions and even join a whole conversation.
Chatbots use a dialog system to have a conversation with a human. There are a few steps a chatbot goes through to process human information:
The first step is converting human input into an understandable context for the chatbot. This is done through input recognizers and decoders, which can analyze speech, text and even gestures. The next step is applying Natural Language Processing to analyze the plain text and search for semantics. All the while the input is managed and processed by a dialog manager to ensure a correct flow of information from and to the participant.
The dialog manager also makes sure that questions or issues are assigned to the right task manager and solved. After the tasks are solved the output manager translates the solution into “human like output”. This is done through a natural language generator to mimic human speech. The output rendered will then regulate how the output is communicated, e.g. through audio, voice and in a visual format as well.
Depending on the status of advancement of the natural language processing and its engines for processing the information, the chatbot is thus able to mimic human language and interpret and communicate efficiently. So how can the chatbot be helpful to an IoT environment ?
An interface for an IoT environment?
In an IoT environment, chatbots can function as an interface to make sense of all the data and also make it more accessible.
Facebook Messenger’s chatbot SDK provides companies a platform where they can integrate their own service within the accessibility of the Messenger app. Below, I use the examples of Uber and a shoe retailer to illustrate how the messenger can be used:
An address within a conversation is recognized by Messenger and will be automatically highlighted. With the example of Uber, users are able to get a ride to the specific address within minutes when they click on an address. The show retailer on the other hand, is a great example for illustrating how the chatbot technology can be used when connecting it with an e-commerce solution. Users can initiate a conversation with their chatbot, which will then determine through questioning which kind of shoes they would like.
Another interesting example is Amazon Echo is an example of integrating speech in your chatbot experience, it will allow you to order anything from the Amazon webshop. A new report, states that Amazon has sold near 3 million Amazon Echo smart speakers which supports the belief that chatbots are the future of IoT and retail, and it will be interesting to see what else retailers come up with in the coming years.
