Explanation of underlying Chatbot technology

Natural and rich conversational experiences. Mosi Hub Intelligent Assistants provide your customers with a new way of interacting with your products via voice and text-based conversational interfaces powered by Artificial Intelligence. Specifically, Mosi Hub virtual intelligent assistants rely on Natural Language Processing and Machine Learning to engage your customers, where and when they want. Mosi Hub virtual intelligent assistants let you scale to hundreds of millions of users.

Natural Language Processing (NLP)

Natural language processing (NLP) is a branch of artificial intelligence, that enables machines to analyze, understand and derive meaning from human language. Instead of hand-coding large sets of rules, NLP can rely on machine learning to automatically learn these rules by analyzing a set of examples (i.e. a large corpus, like a book, down to a collection of sentences), and making statistical inferences. In general, the more data analyzed, the more accurate the model will be.

Natural Language Processing (NLP)

Natural language processing (NLP) is a branch of artificial intelligence, that enables machines to analyze, understand and derive meaning from human language. Instead of hand-coding large sets of rules, NLP can rely on machine learning to automatically learn these rules by analyzing a set of examples (i.e. a large corpus, like a book, down to a collection of sentences), and making statistical inferences. In general, the more data analyzed, the more accurate the model will be.

Machine learning

Machine learning (ML), a subfield of artificial intelligence (AI), is the study of algorithms and statistical models, which rely on patterns and inference to perform specific tasks without the need for explicit instructions.The machine learning algorithms adjust the parameters of a mathematical model to fit sample data, known as training data. The training data consists of inputs and expected outputs. The algorithm continuously adjusts the model’s parameters (trains the model) until it achieves a good fit with the sample data.

 

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