Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The report highlights significant advancements in China's large language model (LLM) sector since the launch of ChatGPT, with over 80 different pre-trained language models emerging in the region, involving top academic institutions and tech companies [6][52] - The report emphasizes the transformative impact of LLMs on industry research capabilities, enhancing report writing efficiency and quality through advanced natural language processing techniques [5][54] - The evaluation of 12 major LLMs was conducted to assess their capabilities in industry research, focusing on report writing, foundational model abilities, and industry understanding [48][54] Summary by Sections Industry Overview - Large language models are defined as deep learning-based natural language processing technologies that learn from vast text datasets, achieving human-like content generation capabilities [19][20] - The evolution of LLMs has transitioned from rule-based systems to statistical machine learning, and now to self-supervised learning, marking a significant leap in human-computer interaction [26][29] Research Objectives - The report aims to understand the current development status of China's LLM industry, analyze its historical progression, explore its industrial value, and assess its application in industry research [9][10] Evaluation Methodology - The evaluation covered over 1,800 questions assessed by a team of 20 senior research analysts through a double-blind process, focusing on report writing ability, foundational model capabilities, and industry understanding [54][68] - The assessment framework includes a comprehensive 8-D methodology for evaluating industry research report writing logic and capabilities [68][71] Industry Understanding - The report includes insights from over 5,000 industry reports across 14 major sectors, evaluating the models' understanding and output capabilities in specific industry contexts [78][80] - The evaluation process involved detailed questions related to industry definitions, classifications, characteristics, and market dynamics [54][75] Challenges in Traditional Research - Traditional industry research faces significant challenges, including outdated tools, difficulties in knowledge transfer, and complex information sourcing, which hinder efficiency and innovation [41][45] - The report advocates for digital industry research solutions that leverage LLMs to overcome these challenges and enhance research quality and efficiency [35][41]

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Investment Rating - The report does not explicitly provide an investment rating for the industry or companies involved Core Insights - The evaluation of large language models in report writing highlights the top performers: 商汤商量, 讯飞星火, and 文心一言 3.5, which excel in various assessment dimensions [8][9][21] - The report emphasizes the importance of foundational capabilities in industry research, with models like 商汤商量, GPT3.5, and 文心一言 3.5 demonstrating strong performance in logical reasoning, text generation, and intent understanding [24][28][32] Summary by Sections Report Writing Capability Assessment - 商汤商量, 讯飞星火, and 文心一言 3.5 ranked highest in report writing capabilities, with 商汤商量 showing consistent performance across all evaluation modules [10][12][21] - The assessment identified significant differences in performance among various platforms, with GPT3.5 and 百川 losing points due to outdated information and completeness issues [12][21] - The evaluation of low-difficulty writing modules showed no significant differences among the 12 models, although some models lost points due to inability to answer specific questions [8][17] Foundational Research Capability Assessment - 商汤商量, GPT3.5, and 文心一言 3.5 lead in foundational research capabilities, showcasing strengths in logical reasoning, text generation, and intent understanding [24][28][32] - The report indicates that models like 智谱清言 and 百川 excel in specific areas, such as intent understanding, despite lower overall scores [26][28] - The foundational capability assessment revealed that 商汤商量 excels in context switching and knowledge retention, while 讯飞星火 leads in logical reasoning and text generation [27][29]

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Investment Rating - The report does not explicitly state an investment rating for the open source software industry in China. Core Insights - The open source software industry in China is experiencing steady growth, particularly in foundational software, which accounts for approximately 10% of the overall software revenue and shows a stable growth trend [2][20]. - The cessation of CentOS has accelerated the development of domestic open source operating systems, with OpenEuler's market share increasing from 15.1% in 2021 to 25.7% in 2022 [3][26]. - China's open source database projects have entered an internationalization phase, with open source databases comprising 54.2% of the global database market as of December 2023 [4][31]. - The open source AI framework sector is exploring new technological features such as full-scenario and large models, with leading frameworks like PyTorch and TensorFlow dominating the market [4][34]. Summary by Sections Industry Overview - The open source software industry in China has undergone four major development stages since its inception in 1991, with leading companies now actively innovating through open source models [2][13]. - The software and information technology service industry in China is stable, with software business revenue reaching CNY 231.77 billion in the first ten months of 2023, a year-on-year increase of 13.7% [8][10]. Open Source Software Development - In 2022, China ranked second globally in the number of new open source developers, contributing to 12.5% of global open source projects [18][19]. - The open source software licensing framework is crucial for ensuring compliance and fostering a healthy ecosystem [16][17]. Foundational Software Analysis - The foundational software sector, which includes operating systems and databases, is a key area of growth, with a stable revenue contribution of about 10% to the overall software industry [20][22]. - The domestic open source operating system community has formed four major communities, enhancing collaboration and innovation [27]. Open Source Database and AI Frameworks - Notable open source database projects like TiDB and OceanBase are leading the charge in China's database internationalization efforts [4][31]. - The open source AI framework sector is rapidly evolving, with platforms like Baidu's PaddlePaddle gaining traction in the market [35].