"四奇安信 Coremail CACTER 中国企业邮箱安全性 研究报告 THE REPO 2025年3月出品 00000 00000 编写组 组长 林延中 裴智勇 主要编写人员 朱腾蛟 江嘉杰 黄楚斯 《中国企业邮箱安全性研究报告》由广东盈世计算机科技有限公 司与奇安信集团联合为您提供，本联合报告的编撰获得了 Coremail 邮件安全人工智能实验室、Coremail 邮件安全大数据中心以及奇安 信行业安全研究中心相关专家的悉心指导和宝贵建议，在此表示感谢。 主要观点 不论是从企业邮箱注册域名数、活跃用户数、还是邮件收发量等方面来看，国内企业级 电子邮箱应用市场，都呈现出持续、稳定发展的态势。尽管垃圾邮件、钓鱼邮件的总量 也有小幅增长，但带毒邮件数量已经呈现出逐年下降的趋势。这主要得益于邮件安全技 术，特别是邮件反病毒技术的持续进步。 邮箱盗号问题仍然十分严重。2024 年，全国被盗企业邮箱账户多达 1074 万个，占全年 活跃企业邮箱账号总量的 5.37%。由被盗企业邮箱账号发出的垃圾邮件多达 822.5 亿封。 特别值得关注的是，邮箱盗号问题已经成为商业机密泄露、商业邮件诈骗等高危安全风 险事件频发的重 ...

Investment Rating - The report maintains a "Buy" rating for Baidu with a target price of $146.70, representing a potential upside of 61.7% from the current price of $90.74 [2][3]. Core Insights - Baidu is actively promoting its business transformation by integrating more generative AI-related search results to enhance user experience and engagement. Although the monetization of these search results has not yet begun, it is expected to start by the end of Q2, which should help boost advertising revenue growth and operating profit margins [9]. - The company has introduced several AI applications, including the Wenxin large model 4.5 Turbo and X1 Turbo, which feature multi-modal capabilities, strong reasoning, and reduced costs. The input price for the 4.5 Turbo model is only 0.8 RMB per million tokens, and the output price is 3.2 RMB, marking an 80% price reduction compared to its predecessor [1]. - Baidu's cloud business is anticipated to maintain strong revenue growth driven by increasing demand for digitalization and AI solutions, supporting overall revenue growth for the group [9]. Financial Summary - The financial forecast for Baidu shows expected sales revenue of 137,622 million RMB in FY25, with a projected growth rate of 3.4%. The adjusted net profit is estimated at 26,943.5 million RMB, reflecting a slight decrease of 0.2% [10]. - The company’s sales revenue for FY23A was 134,598 million RMB, with a year-on-year growth of 8.8%. However, FY24A is projected to see a decline of 1.1% in sales revenue [11]. - The adjusted net profit margin is expected to stabilize around 19.6% by FY27E, with a return on equity projected at 7.6% [12].

在这个大多数人都可能借助生成式AI优化职业发展的时代，关键的差异和优势并非来自AI的自动化功能，而是你与AI互动的能力优于竞争对 手。所以，最重要的建议是尝试并花时间与不同工具和平台互动。通过使用精心设计的提示语并提供详细背景信息，你能最大限度地发挥其效 能，满怀信心地开启职业之旅。 无论你是刚毕业的学生、寻求转型的职场中年人，还是希望提升领导技能的高管，职业导师都是宝贵的资源。2021年哈里斯民意调查对1535名成年人展开 调研，结果显示，尽管当时仅有12%的在职成年人正在接受职业咨询服务，但近三分之二的人都认同，就未来职业发展与专业人士交流能带来帮助。这一 差距或许源于传统职业指导既昂贵又耗时，2023年职业导师的平均时薪高达272美元。 随着ChatGPT、Perplexity、DeepSeek和Claude等生成式人工智能平台的兴起，许多求职者开始将AI视为传统职业导师的替代选择，认为它便捷、高效且能 提供个性化指导，即便有些人已经有幸拥有优秀的人类职业导师。要确切量化目前人们使用生成式AI进行职业指导的具体程度颇具难度。不过，一些调 查表明，多达65%的求职者在求职过程的某个阶段会借助AI寻求帮助。 ...

• 临床试验进展缓慢： 尽管AI技术在分子设计、靶点发现起到提升效率和优化设计作用，但药物研发仍 需经过湿实验及较长的临床周期验证，产品进展存在不确定性。 本期Banglink从创业邦独家企业数据库睿兽分析精选11家AI药物研发领域优秀企业，覆盖多组学数据整 合、蛋白质结构预测、分子模拟优化、自动化实验平台、成药性智能评估等多个技术领域。如对精选项 目感兴趣，欢迎扫码进行委托联系！ AI药物研发是以数据驱动、算法赋能为核心，通过机器学习、生成式AI等技术重塑药物发现、优化及 临床试验全流程的创新领域。随着全球医药产业对效率提升的迫切需求，AI正从辅助工具升级为核心 驱动力 —— 据BCG报告，AI设计的药物分子在Ⅰ期临床试验成功率达80%-90%，远超传统方法的 40%-65%；部分企业已将药物发现周期从5-6年压缩至2-3年，研发成本降低30%-50%。 政策与资本双重加持下，行业进入爆发期：各国纷纷将AI制药纳入战略规划，国内《卫生健康行业人工 智能应用场景参考指引》明确84种应用场景，资本加速布局，2024年全球AI制药融资超50亿美元，晶泰 科技、英矽智能等企业管线快速推进，多款AI设计药物进入Ⅱ/Ⅲ ...

Core Insights - 福立旺 reported a revenue of 1.285 billion yuan for 2024, a year-on-year increase of 29.60%, while net profit attributable to shareholders decreased by 38.38% to 54.526 million yuan [1] Group 1: Business Performance - The 3C precision metal components business generated revenue of 793 million yuan, up 40.26% year-on-year, with strong performance in wearable components such as headphone metal headbands and charging cases [2] - The automotive precision metal components segment achieved revenue of 223 million yuan, reflecting a year-on-year growth of 21.12%, focusing on key applications in various automotive systems [2] - The electric tools precision metal components business saw revenue of 194 million yuan, a significant increase of 68.71% year-on-year, entering the qualified supplier system of large multinational electric tool companies [3] Group 2: R&D and Future Plans - R&D expenses for the period reached 122.426 million yuan, a 24.22% increase from the previous year, with 149 new R&D personnel added, marking a 42.33% growth [3] - 福立旺's 2025 business plan highlights a focus on the humanoid robot dexterous hand sector, with the global market expected to reach 1.706 billion USD in 2024 and exceed 3 billion USD by 2030 [4] - The company is investing 1 billion yuan in a new project for manufacturing components for humanoid robots, with construction expected to start in mid-2025 [4]

底层半导体资本和运营成本动态 近年来，全球多国通过战略政策推动半导体制造和供应链的本土化。例如，美国推出《两党基础设 施法案》、《芯片与科学法案》、《通胀削减法案》及各州激励措施，试图吸引企业在本土建厂。 类似的激励措施也在欧洲、印度、日本、中国大陆、东南亚、韩国与中国台湾陆续推出，从而带动 全球晶圆厂建设热潮。 如果您希望可以时常见面，欢迎标星收藏哦~ 到2030年，全球半导体公司计划在新晶圆厂（fabs）建设上投资约1万亿美元，行业年收入也有望 突破1万亿美元。这一数字尚未包括生成式AI（gen AI）在中等乐观情境下可能带来的额外增长潜 力。除了满足日益增长的市场需求，这些投资也将增强各地区在半导体价值链上的供应弹性。 然而，尽管这场全球范围的大规模投资有望显著扩展半导体的产能版图，实现其预期效益的道路却 并不平坦。除了已公布的建设项目本身执行难度大之外，至少还有五大结构性障碍，特别在北美和 欧洲市场可能长期制约新增投资带来的实质进展：包括资本与运营成本结构、材料需求增长、关键 原材料及封装环节的离岸集中、物流与处理瓶颈，以及人才短缺等问题。若行业希望实现投资的长 期价值，就必须正视并逐一应对这些挑战。 ...

" 更低成本的真实数据需求，更快迭代智驾系统。 " 作者丨田哲 编辑丨林觉民 4月23日，第二十一届上海国际车展上，商汤绝影发布了包括生成式智驾R-UniAD、4D世界模型"绝影开 悟2.0"、AI内核"绝影千机"在内的多个核心技术。 统观绝影发布的技术，一句话概括为：不是做"功能模型"，而是做"系统AI"。 过去几年，端到端技术被认为是智能驾驶实现路径中的"终极形态"，但大多数方案都卡在数据、性能、安 全三道门槛前。R-UniAD的思路，是在这三道门槛外，再造一层AI基础设施。 据介绍，R-UniAD结合世界模型和强化学习，以VLAR（视觉、语言、行动、强化学习）技术架构为核 心，支持仿真环境中进行闭环训练，让模型能在虚拟世界里"试错—强化—泛化"，最终形成系统策略能 力。 以车展现场展示的"施工占道场景"为例，R-UniAD先通过"绝影开悟"世界模型构建4D动态环境，再让模 型反复在这个世界里强化训练不同策略。最终结果是，模型不仅能精准避让，还能泛化到其它类似场景 中。 这种能力的意义在于，它不仅降低了数据成本，更提高了模型上限——在少数据场景里跑出更强泛化能 力，是当前行业少见的尝试。 如果说R-Uni ...

Group 1: Financial Performance - The company achieved an annual revenue of 14.08 billion yuan and an operating profit of 1.742 billion yuan in 2024, indicating steady operational progress and improved quality and efficiency [1] - The core membership segment saw significant growth, with the number of effective members reaching 73.31 million and membership revenue exceeding 5 billion yuan, a year-on-year increase of 19.3% [1] - The company expects to benefit from a tax exemption policy from 2024 to 2027, which will enhance profits by allowing a full refund of previously paid corporate income tax amounting to 260 million yuan [2] Group 2: Membership and International Expansion - The company focused on enhancing membership value, achieving a dual increase in membership scale and revenue through improved operational efficiency and innovative strategies [3] - The international app downloads surged from 130 million in 2023 to 261 million in 2024, with overseas revenue growing from 62 million yuan to 141 million yuan, exceeding the target of doubling [3] Group 3: Content and Innovation - The company made significant investments in original and customized series, with over 60% of its content being self-produced, leading to a notable increase in viewership [4] - The company has developed over 70 scenarios for generative AI applications, significantly reducing production costs and enhancing creative capabilities [4]

IDC总裁德尔普雷特在接受日本经济新闻（中文版：日经中文网）的独家采访时透露，2025年全 球IT支出增长率将从同比增长10％降至同比增长5％。2025年半导体市场的增长率也可能从原本 预计的11％降至9％左右…… IDC总裁克劳福德・德尔普雷特（Crawford Del Prete）在接受日本经济新闻（中文版：日经中文 网）的独家采访时透露了上述内容。此前，IDC预计2025年的IT支出规模为4.1万亿美元，同比增 长10％。德尔普雷特表示，由于美国启动关税政策，"被认为会出现增长率降至5％的情况"。 版权声明：日本经济新闻社版权所有，未经授权不得转载或部分复制，违者必究。 IT支出不仅包括智能手机和服务器等硬件，还涵盖云服务等软件产品。预计硬件和软件都将因特 朗普关税而导致成本增加，并转嫁到价格上。德尔普雷特预测称："价格上涨会让消费者难以购买 产品和服务，自2025年下半年起，IT支出将减速"。 除了IT支出外，IDC还汇总了半导体市场动向。包括特朗普政府正在考虑引进的半导体关税政 策，IDC还在研究2025年半导体市场的增长率从原本预计的11％降至9％左右的可能性。 半导体的设计、生产、制造设备、零部 ...

Core Insights - The emergence of open-source large models, such as DeepSeek-R1, has sparked a revolution in the AI industry, challenging the debate over the merits of open-source versus closed-source models [2][3] - Open-source AI is still in its early stages, with significant potential for industry transformation, but challenges related to security and commercialization remain [2][11] Group 1: Open-Source AI Impact - Open-source models are reshaping global industry dynamics, enabling lower-cost access to advanced AI capabilities for small and medium enterprises [3][4] - The cost of using DeepSeek-R1 for inference is only 1/30 of OpenAI's model, allowing developers to create applications at a fraction of the cost, such as a legal document generation tool that saw a 90% cost reduction [4] - The rise of "Model as a Service" (MaaS) is changing the service model of traditional cloud providers, making it easier for startups to deploy AI applications without building their own infrastructure [4][5] Group 2: Security Challenges - Security has become a major concern with the rise of open-source AI, with 57% of IT decision-makers citing privacy and data security as top issues [6][9] - High-profile security incidents, such as unauthorized access to Hugging Face's platform, highlight the vulnerabilities associated with open-source models [6][7] - DeepSeek has faced significant security threats, including DDoS attacks and data breaches, indicating the challenges that open-source platforms must address [7][8] Group 3: Future Considerations - The demand for computational power remains high, even with reduced costs, necessitating better observability and security measures from cloud service providers [5][9] - The integration of edge computing with AI is creating new security challenges, requiring companies to develop more complex security frameworks [10] - As data becomes a critical asset, ensuring data privacy and security in AI deployments is essential for companies [10][11]