Group 1 - The core viewpoint of the articles is that the synthetic chemistry field is undergoing a significant paradigm shift from traditional "experience-driven" methods to "data-driven" and "intelligent-driven" approaches, primarily through the integration of robotics and artificial intelligence (AI) [1][2][4] - The introduction of high-throughput technology platforms allows researchers to systematically design thousands of different catalyst formulations and quickly identify patterns that would take traditional methods a significant amount of manpower to uncover, leading to the successful development of advanced materials [2][3] - The development of deep learning technologies has dramatically increased research efficiency, exemplified by Dow Chemical's use of Microsoft Azure AI, which reduced a 4-6 month workload to just 30 seconds, achieving a 200,000-fold increase in efficiency [3] Group 2 - Current advancements in AI models and automation technologies have significantly transformed the operational aspects of synthetic chemistry research, enabling high-precision, high-throughput, and safer chemical operations [4][5] - The first AI chemical robot, which autonomously completed 688 experiments in just 8 days, highlights the potential of AI in assisting rather than replacing chemists in experimental design [6][7] - Challenges such as data scarcity and the complexity of reactions remain in the application of AI in synthetic chemistry, necessitating a problem-driven approach that combines limited automation with human cognition for intelligent molecular creation [7][8]

Group 1 - The core viewpoint of the article emphasizes the transformation in the field of synthetic chemistry, shifting from traditional experience-driven methods to data-driven and intelligent-driven approaches, primarily through the integration of robotics and AI [2][5][6] - The "Synthesis Chemistry Research New Paradigm - Robotics and AI Symposium" held in Shanghai aims to promote the intersection of chemistry, artificial intelligence, and automation technology, fostering academic innovation and accelerating industrial application [2][4] Group 2 - The keynote speeches highlighted the necessity of evolving the research paradigm in synthetic chemistry, with a focus on enhancing research efficiency through advanced methods beyond traditional techniques [5][6] - Various experts presented their findings on how AI and automation are revolutionizing the development of catalytic materials, significantly reducing research timelines by over 50% [12] - The integration of AI with robotics is being explored to create intelligent autonomous experimental platforms, which aim to accelerate the discovery of new materials and enhance research capabilities across various industries [14][40] Group 3 - The symposium featured discussions on the challenges faced in applying AI in synthetic chemistry, such as data scarcity and the complexity of reactions, while emphasizing the need for a collaborative approach to build a comprehensive synthetic chemistry database [23] - A consensus was reached among participants on the importance of creating an open data ecosystem to overcome interdisciplinary barriers and enhance the synergy between academia and industry [49] - The closing remarks underscored the progress made in Chinese academic conferences and the collective commitment to embrace intelligent technologies for substantial contributions to global chemistry [56]