Core Insights - The article discusses the upgrade of Tushen Zhihuo's protein design platform to ProteinNova, which now features AI-driven full-process protein design capabilities [1][5] - The integration of dry and wet lab processes allows for a closed-loop system in AI protein design, enhancing the efficiency of scientific research and product development [2][5] Group 1: AI-Driven Protein Design - The upgraded platform showcases a complete closed-loop process from AI-generated design to experimental validation, emphasizing the importance of real-world testing in scientific research [2] - The platform's capabilities include task management, data tracking, and feedback integration, enabling users to create personalized iterative tasks for rapid prototype validation [2][5] Group 2: Optimization of Decision-Making - The system's reasoning process has been streamlined to enhance clarity and user experience, allowing users to quickly grasp core insights without being distracted by unnecessary steps [3] - A complete logical chain is maintained for users who wish to delve deeper into the AI's reasoning, ensuring transparency while keeping the process efficient [3] Group 3: Reporting Enhancements - The introduction of structured report templates allows AI to extract key information such as design logic and improvement suggestions, improving report readability and usability [4] - The language of the reports has been optimized to balance scientific rigor with accessibility for researchers [4] Group 4: Future Implications - The launch of the dry-wet iteration system marks a significant advancement in AI's role in scientific research, enabling rapid feedback and self-optimization [5] - The platform aims to support a wider range of disciplines and experimental types, moving towards the realization of "automated science" as a foundational tool for research teams [5] Group 5: Company Background - Tushen Zhihuo focuses on accelerating scientific breakthroughs and product innovation through super-intelligent platforms, significantly reducing the cycle time for new product design [6] - The core team comprises experts from prestigious institutions, bringing extensive experience in AI research and commercialization [6]