I am a marketing intern at Valuefirst Digital Media. I write blogs on AI, Machine Learning, Chatbots, Automation etc for House of Bots. ...

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I am a marketing intern at Valuefirst Digital Media. I write blogs on AI, Machine Learning, Chatbots, Automation etc for House of Bots.

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Challenges of building intelligent chat bots

By shiwaneeg |Email | Feb 21, 2018 | 15552 Views

Chatbots are the new front line for customer service. It reduces the impact on human agents. Also, it helps businesses save significant money in the process. Building an intelligent chat bot is a challenging task. From making the chat bot context-aware to building the personality of the chat bot, there are challenges involved in making the chat bot intelligent: 

i. Context integration
Sensible responses are the major requisite of the chatbots. Integrating meaningful context into the chat bot is the first challenge while building a chat bot. 

There must be integration of both the physical as well as linguistic context to produce sensible responses. For incorporating linguistic context, conversations are immersed into a force, which becomes a challenging objective to achieve. While integrating contextual data, location, time, date or details about users and other such data must be integrated with the chat bot.

ii. Meaningful responses
Achieving logical responses is another challenge to overcome while building a chat bot. The chat bot must be well-equipped to answer consistently to inputs that are similar in linguistic terms. 

An intelligent chat bot must provide the same answer to queries which are similar in meaning. Though it looks straight forward but incorporating logic and sense into the model is a challenging task. The remedy to this challenge is to train the chat bot to produce consistent logical answers.

iii. Human intelligence
If we want to make chat bots seem more human-like, we have a good resource, ourselves. The technologies are capable enough because of the programmers who build them. There is a large trend that digital players are shifting their focus from traditional engineers to machine-learning experts. Rather than teaching humans to understand machines, we're now teaching machines to understand us.

iv. Natural language processing (NLP)
Right now, chatbots require us to improvise them precisely. If we ask them 'What's the weather?' we will get proper answer. But, if we ask 'Could you check the weather?' we might not get a proper answer for it. To solve these types of problem, NLP will help to enable bots to understand all the ways we say something, and how context changes what we mean. 

Lastly, chatbots has many advantages and has proven to be a boon for the organizations. But there are some challenges, which if dealt well, could actually flourish many businesses.

Source: HOB