The application of artificial intelligence (AI) technology in the field of graduate research is becoming more and more common, which has brought unprecedented opportunities and challenges for the enhancement of graduate research ability. The purpose of this study is to deeply analyze the multiple mechanisms of artificial intelligence promoting the improvement of graduate students' scientific research ability. Firstly, this paper systematically analyzed the theoretical foundation of artificial intelligence in graduate research, covering the application of core algorithms such as machine learning and deep learning in scientific research practice, as well as the mechanism of the integration of artificial intelligence and scientific research, including the potential of interdisciplinary cooperation, the challenges encountered in the integration process and their coping strategies. Then the application examples of artificial intelligence in graduate research practice are expounded, including but not limited to the key links of literature search and analysis, experiment design and data analysis. Then, from the two dimensions of cultivating innovative thinking and improving learning autonomy, how artificial intelligence can help improve graduate students' scientific research ability is discussed. It is believed that artificial intelligence plays an important role in generating new hypotheses, stimulating creativity, breaking through traditional thinking patterns, generating personalized learning resources, and assisting group discussion. In summary, artificial intelligence plays a vital role in improving the scientific research ability of graduate students, and provides strong technical support and innovation motivation for graduate students' scientific research work.
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