Investment Rating - The report does not explicitly state an investment rating for the industry. Core Insights - The software ecosystem faces significant challenges regarding autonomy, security, and trustworthiness, primarily due to reliance on foreign software and the risks associated with supply chain vulnerabilities [8][9][18]. - The introduction of Machine Language Models (MLM) is proposed as a solution to enhance software analysis, security, and performance optimization, thereby addressing the existing gaps in understanding binary programs [35][60][82]. Summary by Sections Background - The software is identified as the cornerstone of cyberspace, with a growing need for self-controllable and secure software solutions [6][7]. - The current software ecosystem is dominated by foreign entities, leading to risks of supply chain disruptions and intellectual property concerns [8]. Key Issues - The report highlights two main challenges: the difficulty in achieving software autonomy and the increasing security risks associated with software vulnerabilities [9][22]. - The analysis of closed-source software is particularly challenging, complicating the identification of security issues [18][22]. Intelligent Solutions - The report discusses the potential of large language models to provide intelligent solutions for software analysis, emphasizing the need for advanced tools to understand binary code [35][60]. - Key technological breakthroughs include the integration of domain knowledge into model design and the use of contrastive learning for semantic understanding [51][54]. Typical Applications - The MLM can be applied in various scenarios, including software reverse engineering, ecosystem migration, and supply chain analysis, enabling fine-grained and high-speed binary code comparison [66][87]. - The model aims to facilitate software consistency checks, vulnerability discovery, and copyright protection analysis [67][87]. Conclusion - The report concludes that the MLM represents a significant advancement in software analysis capabilities, surpassing traditional methods and providing a comprehensive solution for modern software challenges [60][82].