Over the last decade we have seen the dramatic increase in adoption of Mobile as an engagement channel for consumers and employees within the enterprise. What we are seeing now is the emergence of messaging through channels like FB Messenger, WhatsApp, WeChat, Slack, SMS, as a dominant engagement channel. Over 4.1 Billion users around the world are on instant messaging apps, adopted a rate that was much faster than on social networks. What makes these channels the default choice is the expected instant response if the other person is on or the push notification that triggers the person on the other side to respond immediately. These users that use instant messaging channels to converse with their friends and family want to use the same familiar user experience and channel to instantly communicate with the enterprise. These channels are doing to apps what browsers did to client server apps i.e. these channels are rapidly becoming the next browser. This is leading to the innovations in chatbots powered by artificial intelligence (AI) that is going to help enterprises automate these conversations in scale through these channels.
A chatbot is a computer program designed to simulate conversation with human users, especially over the Internet. So why now? A lot of factors have come together to make this explosion of Intelligent Bots possible. One of them is the fact that people are just plain tired of downloading apps, which I define as “app fatigue.” On the other hand, people have moved into messenger apps — they’re living in chat. So, you could have an app… or you could have a service that lives inside an app they already have. What makes chatbots a viable and preferred choice of interaction is the innovation in artificial intelligence via powerful machine learning algorithms that make it possible for the computer (the chatbot) to hold conversations with the end user without too much human intervention.
Machine learning (ML) is based around the idea that we can create algorithms that can learn from data and then make predictions as they encounter new data. Arthur Samuelson, a pioneer in artificial intelligence, coined the term “Machine Learning” in 1959 and defined it as the field of study that gives computers the ability to learn without being explicitly programmed
Machine learning involves at its core, algorithms that apply advanced statistical and mathematical theory to perform pattern recognition within data. Machine learning is used all around us, and its use will increase substantially in the future. Some examples include: self-driving cars, speech recognition, handwriting recognition, facial recognition, optical character recognition, spam detection, market segmentation, forecasting, astronomy (enabled development of theories about the formation of universe), fraud detection, jet engine failure prediction. And within machine learning, modern neural networks have emerged as a state of the art technique for many applications.
Neural networks were inspired by human intelligence and the brain’s ability to rewire to learn new skills: if we are to model intelligence, why not mimic the human brain, which is capable of learning so many things. Additionally, there exists a theory that our brains may have just a single algorithm that can be trained to learn different skills given different sensory training inputs. Experiments have shown that our auditory cortex, whose primary role is hearing, can be retrained to allow us to see, that our tongues can also be retrained to allow us to see, that we can be trained to echo locate.
As an integral part of Oracle Cloud, we developed a mobile service that has seen excellent adoption with customers, globally and across all industries. Both Gartner and Forrester have named Oracle Mobile Cloud Service (MCS) as a leader given its global customer success and momentum, product capabilities, vision and strategy. Our goal as a leader in providing platform as a service (PaaS) is to enable customers to deliver engaging digital experiences to their internal and external customers. The design goal of MCS is to make it easy to deliver mobile apps across smartphones, tablets, wearables and web pages. Today we have continued to innovate and expanded our cloud platform capabilities by adding Intelligent Bots powered by artificial intelligence.
Oracle Intelligent Bots Builder:
The Oracle Intelligent Bots Platform provides a low-code tool, the Oracle Intelligent Bots Builder that allows customers to develop their chatbots from a web browser. These tools provide the ability for the customers to create a new chatbot, define the intents, entities, the dialog flow, define the custom components and configure the chatbot to connect to one or more channels. The Intelligent Bots Builder provides the ability to test the system in a real time and agile way by entering phrases in the test box and getting results from the NLP engine. Based on the results, the developer can fine tune and re-train the chatbot in real time. In addition, the Intelligent Bots Builder also provides a way for the developer to test the complete conversational interaction by testing that same phrase and testing the end user experience dialog from the dialog flow execution engine.
