Core Viewpoint - The article discusses the launch of the upgraded "Dashi" platform by the Shanghai Intelligent Research Institute, Fudan University, and Infinite Light Years, which aims to revolutionize scientific research through advanced AI capabilities, emphasizing the need for a system-level approach rather than isolated tools [4][6][11]. Group 1: AI in Scientific Research - The past few years have seen explosive growth in AI tools for scientific research, yet many scientists feel overwhelmed by the increasing number of fragmented tools, which do not simplify the research process [3][4]. - Scientific research is a complex, highly specialized system that requires a deep understanding of physical constraints and a structured approach to exploration and validation [4][10]. - The "Dashi" platform is designed to address the need for a high-mobility AI that can organize research processes and collaborate with human scientists in deep scientific exploration [8][11]. Group 2: Capabilities of "Dashi" - "Dashi" is defined by four core capabilities: cognition, action, memory, and validation [12][43]. - Cognition involves a true understanding of science rather than merely processing text, which is crucial for effective research [12][18]. - The platform aims to upgrade tools into research-grade skills, allowing for more integrated and adaptive capabilities in scientific workflows [20][22]. Group 3: Memory and Validation - A significant challenge in research is maintaining a comprehensive memory of the entire research process, which is often underestimated in AI applications [28][30]. - "Dashi" employs a multi-branch group memory architecture inspired by software development practices to manage complex research paths effectively [31][33]. - The validation process ensures that AI models are continuously calibrated against physical experiments, creating a reliable feedback loop for scientific inquiry [39][40]. Group 4: Collaboration and Trust - The platform introduces mechanisms for secure collaboration across organizations, ensuring that data remains within its domain while allowing for capability audits and traceability [52][55]. - Trust in AI systems is critical, especially in sensitive research environments, and the platform aims to establish a systematic approach to building trust among collaborators [56][58]. Group 5: Future Implications - The article suggests that the evolution of AI in scientific research may redefine the roles of human scientists, shifting from hands-on execution to problem definition and final decision-making [64][65]. - The ongoing development of "Dashi" signals a deeper transformation in the relationship between AI and scientific research, potentially leading to a new collaborative paradigm [66].