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But despite the tremendous development of chatbots and their ability to execute intelligent behavior not displayed by humans, chatbots still do not have the accuracy to understand the context of questions in every situation each time.Chatbots currently operate through a number of channels, including web, within apps, and on messaging platforms.An indicator of just how human-like these machines can be was actually developed in the 1950s by British scientist Alan Turing.His Turing Test checks the presence of mind, thought, or intelligence in a machine and if it can fool a human to believe that it is a human as well, then it passes the test.Machine learning can be applied in different fields to create various chatbot algorithms, while NLP has the ability to pick up conversational cadences and mimic human conversation.The chatbot is trained to translate the input data into a desired output value.

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Chatbot technology will continue to improve in the coming years.The predictive analytics within bots uses statistics, modeling, data mining and more to generate information proactively, rather than in response to a prompt.The sentiment analysis in machine learning uses language analytics to determine the attitude or emotional state of whom they are speaking to in any given situation.This machine learning algorithm, known as neural networks, consists of different layers for analyzing and learning data.Inspired by the human brain, each layer is consists of its own artificial neurons that are interconnected and responsive to one another.

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