Group 1 - The integration of artificial intelligence (AI) in biomanufacturing is driving a paradigm shift in the industry, showcasing new value creation models and transforming traditional practices [1][2][3] - AI technologies are addressing challenges in biomanufacturing, such as long cycles, low efficiency, and high costs, by enabling data-driven decision-making and algorithm optimization [1][2] - The typical applications of AI in biomanufacturing include areas like biobreeding, fermentation engineering, and intelligent detection, highlighting the dual nature of biological systems and engineering frameworks [1] Group 2 - AI is facilitating a shift from experience-driven to data-driven research and development, allowing researchers to focus on innovative strategy design rather than repetitive experiments [2][3] - The emergence of flexible manufacturing systems combined with AI scheduling algorithms enables rapid product line switching, enhancing production efficiency [2][3] - The integration of AI in biomanufacturing is reshaping the valuation metrics for pharmaceutical companies, moving from pipeline quantity to AI technology barriers, data assets, and intelligent production capabilities [3]