Natural Language Processing (NLP) is a field of AI focused on enabling computers to understand and interact with human language. It involves developing algorithms to process and analyze text and speech data. NLP applications include virtual assistants, language translation, sentiment analysis, and more, transforming how we interact with technology.
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Natural Language Understanding (NLU) is a branch of AI focused on enabling computers to comprehend human language. It involves analyzing text or speech to extract meaning, context, and intent. NLU powers applications like virtual assistants and chatbots, enhancing human-machine interactions.
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Natural Language Generation (NLG) is AI-driven text or speech creation from structured data. It powers automated reports, chatbots, and personalized messaging, enhancing communication across domains. NLG algorithms transform data into coherent language, mimicking human writing styles for effective communication.
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Question Answering (QA) is an AI technique where computers understand and respond to natural language queries. By analyzing data sources, such as documents or databases, QA systems generate accurate answers to user questions. Leveraging natural language processing and information retrieval, QA enhances access to information and facilitates knowledge discovery.
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Problem: Companies face high volumes of customer inquiries, straining support teams.
Solution: NLP-powered chatbots understand and respond to queries, reducing response times and improving customer satisfaction.
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Problem: Businesses need to gauge customer sentiment on social media.
Solution: NLP analyzes social media posts to identify sentiment trends, enabling prompt responses and tailored marketing strategies.
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Problem: Healthcare professionals struggle to extract relevant information from medical literature.
Solution: NLP automatically summarizes medical documents, aiding in quick access to critical information for improved decision-making.
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