Intelligent question answering (QA) is a technology that uses artificial intelligence to enable computers to automatically answer natural language questions based on given information or knowledge bases. This task involves multiple fields such as natural language understanding, information retrieval, knowledge representation, and text generation. The goal is to enable machines not only to match keywords but also to understand the semantics of questions and generate effective answers from relevant information.

The development of intelligent question answering is built upon long-term research in natural language processing, information retrieval, and machine reading comprehension. Early question answering systems primarily relied on rule matching, knowledge base queries, and information retrieval methods, which had limited ability to handle complex open-domain problems. With the development of deep learning, researchers began to utilize neural networks to improve machines' ability to understand text semantics and contextual relationships. In 2016, Stanford University researchers published a paper... SQuAD: 100,000+ Questions for Machine Comprehension of Text The work proposed the SQuAD dataset, which built a large-scale human-annotated reading comprehension benchmark, promoted the development of machine reading comprehension (MRC) and extractive question answering research, and became one of the important representative studies in the field of intelligent question answering.

Modern intelligent question-answering systems typically combine information retrieval, pre-trained language models (such as BERT), large language models (LLM), and retrieval augmentation generation (RAG) technologies to extract relevant information from text, databases, or knowledge bases and generate answers that meet user needs. This technology has been widely applied in scenarios such as intelligent customer service, search engines, educational assistance, enterprise knowledge bases, and scientific research information retrieval, providing important technical support for human-computer natural language interaction.