Group 1 - The core viewpoint of the article emphasizes the transformation of traditional luxury automotive brands like Mercedes into software-centric companies, reflecting the broader changes in the semiconductor industry driven by AI and software [1][4][6] - Siemens EDA's annual technology summit highlighted the industry's challenges, including project delays and declining first-pass success rates, while projecting semiconductor industry revenue to reach $1 trillion to $1.2 trillion by 2030, with transistor counts exceeding 1 trillion [4][6] - The introduction of "software-defined, AI-empowered, chip-enabled" strategies by Siemens EDA signifies a profound insight into industry trends, with a notable emphasis on the increasing importance of AI in Electronic Design Automation (EDA) [4][7] Group 2 - The concept of "software-defined" in the semiconductor industry indicates a shift from hardware-centric approaches to software-driven differentiation, necessitating a change in design methodologies to incorporate software considerations early in the design process [6][9] - AI's role in EDA is characterized by its industrial-grade applications, focusing on five key features: verifiability, usability, universality, robustness, and accuracy, which are essential for ensuring reliable chip design [7][8] - Siemens EDA's development of a comprehensive digital twin system aims to support the entire digital ecosystem, integrating various design and verification processes across multiple domains, thereby enhancing the overall design and production lifecycle [9][10]