Text generation refers to the ability of artificial intelligence and machine learning systems to produce text automatically. These systems can use advanced language models and algorithms to generate text that is coherent, readable and relevant to a given task.
Text generation is used in a wide variety of applications, such as chatbots, virtual assistants, news summaries, machine translation, product description generation, web content generation and more. It is also used in research tasks, such as generating summaries of scientific articles and synthesising information.
Text generation systems can be based on different approaches, such as supervised learning, unsupervised learning and reinforcement learning. In addition, they can use different natural language processing techniques, such as semantic analysis and natural language generation.
Natural Language Processing or NLP analyzes how machines understand, interpret and process human language.
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