The era of Machine Learning Chatbots will bring about a wave of productivity amplification
Smart Chatbots are about using machine learning approaches to bring about a widening area of applications - Here's an exploration on how it's getting smarter and more relevant for today's business functions.
Spoken to Siri, Alexa or Hey Google before? Asking them to set up timers, reminders or even to call a contact? But why has it been so tough in asking them generic or philosophical topics? Because these Bots are built with a goal-oriented dialogue system to begin with. Hence the struggle to hold a conversation that is generic in nature is not a pre-programmed feature of these bots. Of course, with the advancement and development of technology, we may see the re-introduction of Microsoft's TAY Bot which is built for generic dialogue with its audience.
Building Chatbots are not just about programming a reply towards a question, there's greater intelligence built into delivering a really impactful Chatbot. It's A.I. that's driving the evolution of Chatbots. The baseline of proper communication technology for Chatbot is fueled by the natural language processing (NLP) capabilities (Dialogue system) and ideally, we make the technology become indistinguishable from Humans. Although the goal has not been reached yet, humans are now ready to talk with Bots due to maturity of NLP technologies (Successfully developed since the 1960s)
3 Basic level of requirements for an effective bot requires,
1.) Small talk - Your Hello's, Goodbye's and how are you's.
2.) FAQs - The knowledge depository where it knows how to deliver the right answer at the right time.
3.) Conversations - The processes, the outcomes and the logic behind it.
However, these are just really scratching the surface of what goes behind the technology. Conversational modeling is an important task in natural language understanding and machine intelligence. What we do at Su-Ette is building up bespoke Chatbots for businesses which perform effectively at Entity Extraction, Intent Detection and Machine learning via a convolutional neural net.
However, in comparing the deployment of such dialogue systems, the reality is that the success comes from a closed-domain rather than an open domain. Hence, the successful deployment of Chatbots in customer service, sales processing, Human Resource processes, etc are highly impactful and effective in today's development.
Behind it all, embarking on a hybrid conversational model to conceive several sentences of dialogue context and predict the answer for this context through our Bots happens during bespoke development efforts in Su-Ette.
What it means for businesses is the way we evaluate neural conversational models which will best correlate with the human judgment of appropriateness of the reply for a given context.
That's what goes behind the scene's while we continue to bring your market leading Bot technologies. Signing off with a short video on how we bring Bots in the space of handling customer service... Enjoy!
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