What are chatbots?
Chatbots are computer programs that allow humans to communicate with modern technology using different input methods like text, voice, touch and gesture, 24 hours a day, seven days a week, 365 days a year. For a couple of years, these bots were usually used in the customer service industry.
Still, it is now being used in different roles within enterprises to help improve customer service experiences and business efficiencies. It is known by different names like conversational Artificial Intelligence bot, Artificial Intelligence assistance, virtual customer assistant, intelligent virtual assistant, virtual assistant, conversational assistant, digital agent, or conversational interface. These chatbots are starting to grow in popularity.
But just like these programs have different names, they also have different degrees of intelligence. A regular chatbot might be a little more than a solution for your company to answer standard Frequently Asked Questions. Programs that are built using bot frameworks that are currently available in the market usually offer more advanced features like filling available slots and other simple transactional features like taking food orders.
But it is only advanced conversational Artificial Intelligence chatbots that have the capabilities and intelligence to deliver the sophisticated experience most companies are looking to utilize. For this article, all kinds of automated conversational interfaces will be referred to as chatbots or CB.
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Why are these programs so popular?
Wearables, smartphones, and IoT or the Internet of Things has changed the technology industry in recent years. Digital artifacts become smaller, but the computing power inside it has become more significant. But data-heavy activities, as well as mobile applications do not go hand-in-hand.
Going through complicated and complex menus is not the seamless and fast user experience companies need to deliver today. Not only that, customers are no longer content, they feel that they are restricted by communication methods that are chosen by a company.
They want to interact with technology across a number of channels. CBs offer a great way to solve these problems by allowing consumers to ask for whatever they want or need across different channels, night or day and wherever they are on the planet.
How do these programs work?
To make the explanation simple, people interact with these programs. If a voice is used, CBs first turns the voice data input into text codes using an Automatic Speech Recognition or ASR technology. Text chatbots like text-based messaging applications skip this step.
These bots then analyze the data, consider the best positive response and deliver that to users. The bot’s reply output can be provided in any way possible like a voice like TTS or Text-To-Speech tools, written text, or by completing the task.
It is worth remembering that, knowing or understanding people is not easy for software or machine. The nuanced and subtle way people communicate is a very complicated task to recreate artificially. That is why CBs uses natural language principles like:
NLP or Natural Language Processing
NLP is used to split the user input into a couple of words and sentences. It also helps standardize the text through a series of methods. For example, converting all texts to lowercase or correcting all spelling mistakes before deciding if the word is a verb or an adjective. It is in this phase where other elements like sentiment are also being considered.
NLU or Natural Language Understanding
NLU helps chatbots comprehend what the users are saying, with the help of both domain and general specific language objects like synonyms, themes and lexicons. These things are used in conjunction with rules or algorithms to construct a dialogue flow that will tell the CBs how to respond appropriately.
NLG or Natural Language Generation
Delivering meaningful and personalized user experiences beyond the pre-scripted responses means using natural language generation. It enables the bots to examine data repositories like third-party databases and integrated back-end systems, and use the information in designing and making a proper client response.
Conversational Artificial Intelligence technology takes Natural Language Understanding and Natural Language Processing to the next level. It allows companies to design and build advanced dialogue systems that use personal preferences, contextual understanding, and memory to deliver an engaging and more realistic natural language interface.
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History of CBs: A brief look at how this program evolved
CBs can be traced a couple of decades ago, but it was not until the usage if the Internet became more prevalent that the program started to be used in different industries like customer support. Here is a breakdown of some of the most critical moments that defined the chatbot history.
Turing test, 1950 – The test asks specific questions like whether the machine can think or not. It was asked in 1950 by Alan Turing in his landmark paper, Computing Machinery and Intelligence.” In his essay, Turing proposed a series of tests where an interrogator needs to determine which player is human and which is a machine using a set of questionnaires. Despite flaws and criticisms, the test is still used regularly today.
ELIZA, 1966 – A computer scientist from MIT named Joseph Weizenbaum started to develop ELIZA in 1966. It would turn out to be the first machine that is capable of speech using natural language processing.
PARRY, 1966 – By the early 70s, a psychiatrist by the name Kenneth Colby takes the principles behind ELIZA a step further. With PARRY, Kenneth Colby adopted a more conversational chatbot strategy compared to ELIZA using a model of a patient with schizophrenia to help increase the believability in responses. In 1973, a simple conversation was set up between PARRY and ELIZA.
Jabberwacky, 1988 – It is a chatbot designed and made by Rollo Carpenter, a British computer programmer. It was considered as one of the earliest attempts to develop Artificial Intelligence through human interaction. It was designed to simulate a natural human chat in an entertaining, humorous and interesting manner.
ALICE, 1995 – Artificial Linguistic Internet Computer Entity or ALICE is also known as Alicebot or Alice, a natural bot that process language, first developed in 1995. ELIZA much inspired the program.
SIRI, 2010 – Siri first came to everyone’s attention in 2010 when Apple launched it as a new iPhone application. The company subsequently bought Siri and integrated the voice assistant into their latest iPhone model at that time, iPhone 4S. It brings voice applications into the mainstream market for good.
Alexa, 2015 – Siri remains the most popular mobile voice assistant on the market until Amazon launched its voice bot, Alexa. Alexa caught their customer’s imagination and launched their smart home speakers.
Bots for Messenger: FB Chatbots, 2016 – With FB’s launch of its messaging platform, they became the leading application for CBs. In 2018, there were at least 300,000 active CBs on Messenger, helping their customers with their inquiries and needs.