Core Insights - The article emphasizes the importance of continuous innovation in transforming technological potential into real productivity, particularly through the integration of "physical feedback learning" mechanisms in large model training [1] - The research team aims to address real-world challenges in laboratory automation and precision manufacturing by focusing on soft-hard coupling structures and long-sequence task planning [1] - The goal is to create a "testing ground" for new technologies and products, which will serve as an accelerator for the development of emerging industries and promote large-scale industrial application of new technologies [1] Summary by Categories - **Innovation and Technology** - The introduction of "physical feedback learning" in large model training is seen as a crucial step for future applications in various fields [1] - The focus on real-world verification of technologies ensures they meet performance requirements and can adapt to large-scale applications [1] - **Market and Industry Development** - The initiative aims to bridge the gap between laboratory innovations and market needs, fostering the development of new technologies and products [1] - By accelerating the industrialization of new technologies, the initiative is expected to stimulate innovation and drive high-quality economic development [1]