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Wit.ai, Inc
Wit.ai, Inc
https://wit.ai/
Information Technology
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Wit.AI Inc. is a company that provides natural language solutions. The Company enables developers to add a natural language interface to their applications or devices.
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Wit.ai, Inc
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Chatbot Development
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Wit.ai
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Wit.ai, Inc
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Chatbot Development
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Chatbots can be classified into usage categories such as conversational commerce (e-commerce via chat), analytics, communication, customer support, design, developer tools, education, entertainment, finance, food, games, health, HR, marketing, news, personal, productivity, shopping, social, sports, travel and utilities.\r\nBeyond chatbots, Conversational AI refers to the use of messaging apps, speech-based assistants and chatbots to automate communication and create personalized customer experiences at scale.\r\nThe process of building, testing and deploying chatbots can be done on cloud-based chatbot development platforms offered by cloud Platform as a Service (PaaS) providers such as Oracle Cloud Platform SnatchBot and IBM Watson. 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In banking, chatbots and virtual assistants are some of the industry’s newest tools designed to simplify the interaction between humans and computers.\r\n<span style=\"font-weight: bold;\">What is a chatbot?</span>\r\nA chatbot is artificial intelligence (AI) software that can simulate a conversation (or a chat) with a user in natural language through messaging applications, websites, mobile apps or through the telephone.\r\n<span style=\"font-weight: bold;\">Why are chatbots important?</span>\r\nA chatbot is often described as one of the most advanced and promising expressions of interaction between humans and machines. However, from a technological point of view, a chatbot only represents the natural evolution of a Question-Answering system leveraging Natural Language Processing (NLP). 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It analyzes the user’s request to identify the user intent and to extract relevant entities.\r\nThe ability to identify the user’s intent and extract data and relevant entities contained in the user’s request is the first condition and the most relevant step at the core of a chatbot: If you are not able to correctly understand the user’s request, you won’t be able to provide the correct answer.\r\nReturning the response: once the user’s intent has been identified, the chatbot must provide the most appropriate response for the user’s request. The answer may be:\r\n<ul><li>a generic and predefined text;</li><li>a text retrieved from a knowledge base that contains different answers;</li><li>a contextualized piece of information based on data the user has provided;</li><li>data stored in enterprise systems;</li><li>the result of an action that the chatbot performed by interacting with one or more backend application;</li><li>a disambiguating question that helps the chatbot to correctly understand the user’s request.</li></ul>\r\n<span style=\"font-weight: bold;\">In what is the benefit of chatbots?</span>\r\nChatbot applications streamline interactions between people and services, enhancing the customer experience. At the same time, they offer companies new opportunities to improve the customer's engagement process and operational efficiency by reducing the typical cost of customer service.\r\nTo be successful, a chatbot solution should be able to effectively perform both of these tasks. 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Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, although as of 2019, they are far short of being able to pass the Turing test. Chatbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. Some chatbots use sophisticated natural language processing systems, but many simpler ones scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database.\r\nThe term "ChatterBot" was originally coined by Michael Mauldin (creator of the first Verbot, Julia) in 1994 to describe these conversational programs. Today, most chatbots are accessed via virtual assistants such as Google Assistant and Amazon Alexa, via messaging apps such as Facebook Messenger or WeChat, or via individual organizations' apps and websites. Chatbots can be classified into usage categories such as conversational commerce (e-commerce via chat), analytics, communication, customer support, design, developer tools, education, entertainment, finance, food, games, health, HR, marketing, news, personal, productivity, shopping, social, sports, travel and utilities.\r\nBeyond chatbots, Conversational AI refers to the use of messaging apps, speech-based assistants and chatbots to automate communication and create personalized customer experiences at scale.\r\nThe process of building, testing and deploying chatbots can be done on cloud-based chatbot development platforms offered by cloud Platform as a Service (PaaS) providers such as Oracle Cloud Platform SnatchBot and IBM Watson. 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In banking, chatbots and virtual assistants are some of the industry’s newest tools designed to simplify the interaction between humans and computers.\r\n<span style=\"font-weight: bold;\">What is a chatbot?</span>\r\nA chatbot is artificial intelligence (AI) software that can simulate a conversation (or a chat) with a user in natural language through messaging applications, websites, mobile apps or through the telephone.\r\n<span style=\"font-weight: bold;\">Why are chatbots important?</span>\r\nA chatbot is often described as one of the most advanced and promising expressions of interaction between humans and machines. However, from a technological point of view, a chatbot only represents the natural evolution of a Question-Answering system leveraging Natural Language Processing (NLP). Formulating responses to questions in natural language is one of the most typical examples of Natural Language Processing applied in various enterprises’ end-use applications.\r\n<span style=\"font-weight: bold;\">How does a chatbot work?</span>\r\nThere are two different tasks at the core of a chatbot:\r\n<ol><li>user request analysis</li><li>returning the response</li></ol>\r\nUser request analysis: this is the first task that a chatbot performs. It analyzes the user’s request to identify the user intent and to extract relevant entities.\r\nThe ability to identify the user’s intent and extract data and relevant entities contained in the user’s request is the first condition and the most relevant step at the core of a chatbot: If you are not able to correctly understand the user’s request, you won’t be able to provide the correct answer.\r\nReturning the response: once the user’s intent has been identified, the chatbot must provide the most appropriate response for the user’s request. 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