Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The rapid development of artificial intelligence (AI) technology is transforming global industrial patterns and driving the fourth industrial revolution, but it also brings multiple security risks related to data, models, infrastructure, and applications [7][8] - The white paper aims to establish a safe, reliable, fair, and trustworthy AI system, focusing on AI security governance, risk analysis, and the development of a governance framework [8][9] - The report emphasizes the need for a comprehensive governance system that includes legal regulations, standards, and management measures to ensure the safe and controllable development of AI technology [20][22] Summary by Sections AI Overview - AI technology has evolved from symbolic rules to machine learning and deep learning, with significant growth in large language models (LLMs) driving technological progress and industrial upgrades [11][12] - Major companies in both domestic and international markets are expanding the application of large models across various industries, enhancing AI technology's development and industrial intelligence [12][13] AI Security Governance Risk Analysis and Challenges - AI security governance risks include vulnerabilities inherent to AI and external threats faced during application, categorized into infrastructure, data, model algorithm, and application security risks [29][30] - Specific risks include hardware device security, cloud security, model-as-a-service platform security, and computational network security [31][32][33][37] AI Security Governance System - The governance system consists of a four-part supervisory and management framework, focusing on infrastructure, model, data, and application security [20][22] - The report outlines the importance of addressing security at all levels to build a truly secure AI ecosystem [22] AI Security Technology Solutions - The report discusses various technical solutions and case studies across AI infrastructure, data, models, and applications to enhance security governance [8][9] AI Security Development Recommendations - Recommendations include establishing a legal framework, building a standard system, exploring cutting-edge technologies, and fostering talent through industry-academia collaboration [8][9]

Key Points - The report from CITIC Securities highlights two critical time points in the year: the first is the external risk landing in early April, which is expected to create trading opportunities, and the second is the synchronization of the economic and policy cycles between China and the U.S. around mid-year, which will provide allocation opportunities for core assets [1][2][3] Group 1: Key Time Points - The first key time point is the external risk landing in early April, including the results of the U.S. trade policy memo and the clarity on "reciprocal tariffs." This is expected to lead to trading opportunities in the technology sector due to its weak macroeconomic correlation and strong industrial catalysts [2][3] - The second key time point is the synchronization of the economic and policy cycles between China and the U.S. in mid-year, which may lead to the fourth round of economic stimulus in China since 2013, as the U.S. faces economic weakening and increased tariff pressures [2][8] Group 2: Trading Opportunities - Following the external risk landing in early April, the technology sector is anticipated to experience new trading opportunities, particularly in the context of the U.S. trade policy developments and the expected adjustments in the macroeconomic environment [3][4] - The report emphasizes that edge AI is likely to be a significant catalyst for market movements, with upcoming product launches, particularly from companies like Xiaomi, expected to boost market sentiment [4][10] Group 3: Investment Focus - The report suggests focusing on core assets in both A-shares and Hong Kong stocks, particularly in sectors such as domestic computing power, edge AI, lithium batteries, military industry, and innovative pharmaceuticals in Hong Kong [10] - Additionally, it recommends paying attention to sectors that may experience potential earnings surprises in Q1, including wind power components, engineering machinery, automotive electronics, and service consumption [10]

沈思越 连一席 遥远 本轮春季躁动当中投资者有两大烦恼：一是港股走牛、A股震荡，两地市场的分化造成机构产品 业绩分化；二是国内宏观波动在降低，市场从三年宏观大年步入宏观小年，但不少原有应对剧烈 宏观波动的杠铃型策略很难在市场快速上涨时完成调仓。从市场分化的角度来看，本轮以新经济 为主线的春季躁动当中，互联网、硬科技、智能车和创新药当中最优质的核心资产聚集在港股， 这是港股走牛而A股仍在震荡的本质原因。约6 0%的公募资管产品不具备港股通权限，即使具备 权限，测算港股可投比例距离基金合同上限平均还有约2 6 . 5%的上升空间，业绩分化和赛马机制 在驱动配置型持仓加速从A股转向港股，加剧两地市场走势分化。从策略范式的角度来看，过去 三年是宏观大年，宏观波动和政策应对是驱动市场的主要变量，杠铃策略成为应对频繁宏观扰动 的方式；反观今年，政策方向和目标清晰，国内宏观波动在降低，市场在向宏观小年过渡，宏观 和政策的边际变化很难再成为驱动市场方向和结构的因素，产业景气驱动的思路在接棒杠铃策 略。从应对而言，端侧AI和高能量密度电池是A股相对具有独占性的产业主题，且我们预计二季 度将会迎来密集催化；A股传统核心资产出清在 ...