Core Insights - The integration of artificial intelligence (AI) is driving rapid advancements in scientific research, becoming a consensus in the scientific community [1][3] - The Chinese government has outlined six key actions to accelerate the implementation of "AI+" in science and technology, highlighting the importance of AI in various fields such as life sciences, mathematics, and materials science [1][4] Group 1: AI's Role in Scientific Research - AI helps researchers overcome cognitive limitations, formulate better questions, and identify valuable research directions [1][3] - AI optimizes existing research tools and can autonomously create new tools or innovative combinations [1][3] - AI enables researchers to comprehensively examine research subjects, uncovering overlooked potential connections [1][3] Group 2: Challenges and Opportunities - The complexity of scientific discovery has increased, making significant breakthroughs more challenging, often limited by researchers' cognitive levels and knowledge dissemination [2] - The transition from serendipitous discoveries to systematic ones is a critical issue that AI-driven research must address [2] - The emergence of large models in AI has improved generalization capabilities but has also highlighted the need for specialized depth, making "integration of general and specialized knowledge" essential for scientific discovery [2] Group 3: Practical Applications and Innovations - AI can generate cross-disciplinary ideas, assess the value of research hypotheses, and enhance cognitive levels for better scientific questioning [3] - The Shanghai AI Laboratory has developed and open-sourced the "Shusheng" multimodal scientific model, which integrates various scientific data types and has shown promising results in quantum computing and drug development [3] - The platform based on the "Shusheng" model has made advancements in quantum computing, drug research, and polymer chemistry [3] Group 4: Future Implications - AI is expected to play a crucial role in technological innovation and will serve as a significant engine for breakthroughs across disciplines and fields [4] - Accelerating the exploration of AI-driven research paradigms and building application-oriented scientific models will enhance AI's role in achieving high-level scientific breakthroughs [4]