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Generative artificial intelligence tools have developed significantly, transforming from mere language models for producing text into reliable tools for scientific research. They are now used for summarizing scientific papers, analyzing data, and detecting patterns, all supported by strict technical foundations to ensure accuracy. However, issues such as AI "hallucinations" have emerged, where the technology can generate incorrect information or fabricated references, highlighting the necessity of scientific verification and human review to ensure the validity of results. The optimal use of AI in scientific research involves relying on it as an assistant rather than as an ultimate source, with careful verification of local references and precise operation to enhance reliability and reduce errors.
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