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Natural language generation (NLG) is the sub-category of artificial intelligence (AI) that uses machine learning (ML) algorithms to analyze a collection of discrete digital inputs and summarize them by producing text that appears to be written by a human.
NLG algorithms rely on computational linguistics, natural language processing (NLP) and natural language understanding (NLU) to autonomously transform structured data into human-readable text. The goal of NLG is to programmatically produce narratives that are capable of passing a Turing test.
Traditional NLG use cases include mail merge, report generation and templated content creation. When used in conjunction with NLP and the internet of things (IoT), natural language generation can provide end users with personalized — and hopefully correct — responses to chatbot and virtual assistant queries.
Techopedia Explains Natural Language Generation
Natural language generation is actually one of the frontiers of artificial intelligence. It is the idea that computers and technologies can take non-language sources — for example, Excel spreadsheets, videos, metadata and other sources — and create natural language outputs that seem human.
NLG and GPT-3
GPT-3 (Generative Pre-trained Transformer 3) is software designed by the OpenAI group to generate content copy. In contrast to many other artificial intelligence models, Generative Pre-trained Transformer models are able to perform well with very limited training data.
