以人工智能引领科研范式变革（深入学习贯彻习近平新时代中国特色社会主义思想）

Group 1 - Artificial intelligence (AI) is recognized as a strategic technology leading a new round of technological revolution and industrial transformation, emphasizing its strong "leading goose" effect [1] - The development of AI is accelerating, driven by advancements in mobile internet, big data, supercomputing, and brain science, reshaping the fundamental logic and methodology of scientific research [1][2] - AI is transitioning from being an "auxiliary tool" to becoming a "research主体," forming a human-machine collaborative research model that enhances research efficiency [3][4] Group 2 - The historical evolution of research paradigms includes three major transformations: the empirical paradigm, the theoretical paradigm, and the computational paradigm, each emphasizing different methodologies [2] - The emergence of AI large models, such as ChatGPT and DeepSeek, marks a new phase in AI development, with "data-driven" and "computational power-driven" approaches becoming core features of the new research paradigm [3] - AI's ability to mine hidden patterns from vast datasets is revolutionizing scientific innovation, as exemplified by AlphaFold's prediction of nearly 200 million protein structures [3] Group 3 - AI is fostering a shift from "island innovation" to "distributed intelligent networks," transforming traditional research organizations into collaborative networks that enhance knowledge production [5] - The integration of AI with various disciplines is creating a cross-disciplinary innovation ecosystem, improving research efficiency and stimulating new discoveries [3][5] - The development of AI is also pushing for a more open and inclusive research paradigm, enhancing fairness in scientific research through open-source models and collaborative platforms [6][7] Group 4 - China is actively exploring pathways for AI-driven research paradigm transformation, focusing on modular research organization capabilities and dynamic team formations for urgent national strategic tasks [7] - The rich application scenarios in China are being leveraged to enhance AI data augmentation, improving innovation capabilities and model accuracy [7] - The integration of Chinese culture with AI modeling thinking is expanding research horizons and application boundaries, as seen in the digital construction of traditional medical theories [7] Group 5 - The rapid development of AI presents both opportunities and challenges, including data security, ethical considerations, and the need for new evaluation systems for AI-generated research outcomes [8] - Establishing a national research computing power network is essential for supporting AI development, ensuring high-level computing resources are available for research innovation [9][10] - Promoting international collaboration in research through open innovation ecosystems can enhance innovation capabilities and improve the global research environment [11]