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These aspects are just a part of NLP AI Tech applications, and the actual application domains are extensive and continuously expanding.
Language understanding is a crucial task in NLP, aiming to enable computers to comprehend and interpret the meaning of human language.
Techniques like automatic summarization, article generation, and text fusion can help writers extract and generate key information.
Knowledge question answering involves using natural language to ask questions and retrieve accurate answers from large-scale knowledge bases.
NLP techniques can be used to analyze logical structures, relationships, and meanings expressed in texts for reasoning and inference.
For instance, code generation models can transform natural language descriptions into executable code, assisting developers in quickly generating code. Additionally, automated code commenting and code intent analysis are also areas where NLP finds application in software development.
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