Initially, artificial intelligence (AI) didn’t quite live up to the hype that was created by the media, especially by Hollywood movies and sci-fi writers. Many a projects failed because of lofty expectations and underestimation of developmental costs. Despite these initial setbacks, the recent convergence of technologies, such as those in cloud, analytics, big data, hardware capabilities and automation, have rekindled user interest in AI-backed applications.
Many analysts now feel that artificial intelligence is the new electricity, because it is likely to transform almost all the human-machine interfaces that we are familiar with. And if you assume that AI is the new electricity, then data is the grid that it runs on. With the rapidly evolving influence of artificial intelligence over our lives, businesses are grappling with the advances in related technologies and are busy figuring out ways to maximize their value.
Consumers, on the other hand, have already had a taste of artificial intelligence in the form of interactive voice response, text predictors, weather forecast apps, music recommendation bots, and taxi-hailing apps. Gen Z users have been quick to adapt to these solutions and are keen to explore more such offerings that not only improve their experiences but also give them a higher sense of self worth.
The New Language of Chat
People of all age groups love texting these days, to the extent that WhatsApp alone handles 30 billion chat messages globally, each day! Not surprisingly, chat is the most-used feature for smartphone users, with 78% of them wishing they could text a business rather than calling them. And herein lies the genesis of a great opportunity for developing chat-based user engagement software.
The rapid adoption of artificial intelligence has opened the doors to large-scale proliferation of AI chatbots, which are essentially built to simulate a human conversation. Through an internet-enabled device, the user can converse with a computer program that can give “human” answers, by analyzing the text for its intent and seeking relevant responses through big data and cloud.
Which One is Fairest of Them All?
The 5 most prominent chatbot services that are driving value for businesses today are:
Microsoft Azure:
The Azure Bot Service allows you to build, test, deploy and manage intelligent bots in one place, with the use of modular framework. Its SDK allows developers to create bots that convert speech to text, have natural language processing capabilities and can answer user questions. The platform comes with Azure Bot Builder software development kit (SDK) that allows developers to add bots to their sites or applications. These bots get automatically added to the directory of Microsoft Azure. The SDK also supports bots that are coded in Java, Javascript, Python and C#. The Microsoft Azure artificial intelligence service can be embedded with mobile apps, emails, websites, Skype, Slack, GroupMe, Kik and Facebook Messenger. Additional features include: Ability to make logical recommendations, language translation, and machine vision (to recognize users from their pictures).
Google Dialogflow:
The Google Dialogflow incorporates Google’s much–vaunted expertise in machine learning as well as the Speech-to-Text product. Developers can use Dialogflow to create voice and conversational interfaces that work on a wide range of connected devices. The service supports 14+ languages and an array of services tailor made for media, entertainment and hospitality industries. Dialogflow also includes Google analytics tool that can measure several metrics such as usage patterns, latency issues, customer engagement etc. It can be integrated with Kik, Skype, Cisco Spark, Cisco Tropo, Telegram, Twilio, Twitter and Viber.
IBM Watson
Named after IBM’s founder, Thomas J Watson, the Watson supercomputer combines sophisticated analytical software with artificial intelligence. It is designed to provide class-leading performance as a “question answering” machine. The IBM Watson supercomputer, with a processing rate of 80 teraflops, can replicate a human’s ability to answer complex questions that require search through an enormous amount of data.
Its key components include:
Apache UIMA frameworks, infrastructure and other elements for data analysis.
Apache’s Hadoop, a free Java-based programming framework for processing large data sets.
SUSE Enterprise Linux Server 11
Deep QA software with natural language processing & machine learning abilities
Amazon Lex
Amazon Lex allows developers to build conversation bots quickly and easily, by using voice and text recognition. It has advanced functionalities of automatic speech recognition (ASR) and natural language understanding (NLU), which help it in converting speech to text and recognizing the intent of the text. Amazon Lex is an artificial intelligence system that helps you build mobile applications with high levels of engagement and lifelike conversations. Its deep learning technologies and sophisticated algorithms are already powering Amazon Alexa.
Amazon Lex has an easy-to-navigate console that guides you towards creating your own chatbot in a few minutes. You simply have to provide a few example phrases and it will build a natural language model for your specific needs. The user can interact with your application by using voice and text. Amazon Lex has built-in integration with other services on AWS (Amazon Web Services) cloud platform, including Cognito and Dynamo DB.
Facebook Wit
Facebook-owned Wit is an open and extendable natural language processing system for developers. It allows developers to build conversation applications or chat bots in connected devices that can accept a text or voice input. The Wit artificial intelligence platform provides easy-to-use interface and quick-learning APIs that can understand human conversation and parse it into a structured data. The AI can also predict forthcoming events based on accumulated data. The Facebook Wit is a free SaaS platform that allows developers to build a chatbot for their own applications. It makes your task simpler by using samples from past messages and templated responses to common requests. The platform is powerful, efficient, and versatile. Wit-powered chatbots can be built for mobile phones, wearable devices as well as home automation products. An added feature is that it provides a visual preview of conversation flows, context variables and branching logic. For programming and integration, you can use Python client, Ruby client, Node.js client and HTTP API.
Conclusion
The technology to optimize customer service operations and derive value from there is already present and improving everyday. All you need to to is just embrace it and start building your own success story on it.
