Facebook will one day have a conversational agent with human-like intelligence. Siri, Google Now, and Cortana all currently attempt to do this, but go off script and they fail. That's just one reason why Mark Zuckerberg famously built his own AI for home use in 2016; the existing landscape didn't quite meet his needs. Of course, his company has started to build its AI platform, too--it's called Project M. M will not have human-like intelligence, but it will have intelligence in narrow domains and will learn by observing humans. And M is just one of many research projects and production AI systems being engineered to make AI the next big Facebook platform.
So far, we've had to learn to interact with computers on their terms and limitations. To make as precise online search as possible we are required to know the optimal keywords, and still, we get millions of search results that we have to choose from. However, now with the emergence of conversational search and AI chatbots, things are changing. The demand for more human-like chatbots has resulted to significantly improved natural language processing and machine learning. We are now teaching computers to interact with us on our terms and limitations.
Before building and deploying chatbots, there are some basic practices to follow in separating your chatbot from the others in the market. Fortunately for business owners, launching a quality Chatbot isn't hard, as long as you follow the guidelines below. Before thinking about adopting a chatbot for your business, you should first understand why individuals might want to converse with chatbots rather than a real human being. Whether you are planning to deploy a chatbot for customer support on your website or creating a lead capturing bot, it's time to read the guidelines of Chatbot design and development. The below-compiled guide will help you in building a Chatbot that's engaging and effective enough to drive 4X growth for your business.
The age of conversational AI is here and it's completely redefining how organisations, employees and consumers are communicating with one another. Thanks to its ability to use natural language processing (NLP) to map spoken or written words to intent, conversational AI is no longer just a gimmick. Instead, conversational AI is making an impact across nearly every sector -- in our homes, cars, call centres, banks, online shops, and hospitals--and the use cases are growing. Combining complex NLP, cognitive learning abilities, autonomic task management, and emotional intelligence, conversational AIs can both learn from and respond to text or voice in an engaging, personalised and emotionally cognisant manner. The potential is immense and so it's unsurprising that recent research found that the global conversational AI market is expected to increase from $4.2 billion in 2019 to $15.7 billion by 2024.