Core Insights - The current era is characterized as the age of artificial intelligence, comparable to the time when the steam engine was invented, marking a significant investment opportunity [3][15] - Technological progress is identified as the fundamental driver of wealth growth and societal advancement, despite economic fluctuations and crises [5][16] - The investment strategy of the company has shifted towards focusing on AI-related companies, similar to past successful investments in technology [9][16] AI Era - The AI era is seen as a transformative period, with potential for significant changes in business models and consumer behavior, such as the use of AI agents for everyday tasks [12][22] - Companies like Nvidia and Google are highlighted as key players in the AI space, with substantial investments in research and development [22][23] Investment Strategy - The company has made strategic decisions to invest heavily in AI technologies, reflecting a belief that the same opportunities that existed in previous technological revolutions are present today [9][16] - The importance of long-term investment perspectives is emphasized, suggesting that successful investments require a multi-decade view [10][19] Market Trends - The Nasdaq index has shown significant growth over the past decades, with historical performance indicating that technology-driven markets tend to outperform others [5][18] - Recent trends show increased investment in companies like Google and Alibaba, indicating a shift in market sentiment towards AI and technology stocks [13][14][23] Competitive Landscape - The competitive environment in AI is described as intense, with major companies like Amazon, Google, and Microsoft investing heavily in AI technologies [22] - The potential for monopolistic structures in the AI industry is noted, with a few companies likely to dominate the market and achieve unprecedented valuations [24]

Core Insights - The rapid development of AIGC technology has led to the generation of highly realistic content with simple prompts, but it also poses significant security risks such as fake news, identity fraud, and copyright infringement [1] - AI-generated image detection has become a fundamental security capability in the AIGC era, yet existing detectors perform well on benchmark datasets but struggle in real-world scenarios [1][3] - Tencent's Youtu Lab, in collaboration with research teams from East China University of Science and Technology and Peking University, has proposed the Dual Data Alignment (DDA) method to systematically suppress biased features and enhance the generalization ability of detectors across different models and data domains [1][18] Problem Identification - The root cause of detection issues lies in the construction of training data, where detectors rely on biased features rather than learning the essential characteristics that distinguish real from fake [3][4] - Systematic differences between real and AI-generated images lead to the learning of "shortcut strategies" by detection models, resulting in high accuracy on specific datasets but poor performance when faced with modified images [4] Proposed Solution - The DDA method aims to eliminate biases in training data through reconstruction and alignment, consisting of three main steps: pixel alignment, frequency alignment, and mixup [7][14] - Pixel alignment uses Variational Autoencoder (VAE) technology to reconstruct real images, ensuring consistency in content and resolution [8] - Frequency alignment addresses the loss of high-frequency information in JPEG-compressed real images, ensuring that the reconstructed images do not introduce new biases [9][12] - The final step involves mixing real and aligned generated images to enhance the alignment of true and false data [13] Experimental Results - The DDA method was evaluated under strict conditions, training a single universal model and testing it across various unknown and cross-domain datasets [15] - In a comprehensive test involving 11 different benchmarks, DDA outperformed in 10 of them, achieving a minimum accuracy (min-ACC) that was 27.5 percentage points higher than the second-best method [18] - The detection accuracy on the challenging "In-the-wild" dataset Chameleon reached 82.4%, demonstrating the model's effectiveness in real-world scenarios [18]

由 文心大模型 生成的文章摘要 腾讯方面表示，此次全球发布的核心宗旨是降低高质量3D模型的制作门槛。依托先进的AI算法，用户 可通过文本描述、参考图像或设计草图等多样化输入方式直接生成3D素材，相较于传统依赖专业软件 的制作方法，能够显著缩短3D资产的生产周期，降低技术门槛与时间成本。 与此同时，混元3D模型应用程序接口（API）已通过腾讯云官方平台正式上线。作为腾讯旗下核心的云 计算服务载体，腾讯云将为全球企业用户提供稳定的技术支撑，助力其将3D生成功能快速集成至自身 业务流程中。据腾讯介绍，该API的应用场景已覆盖游戏开发、电子商务展示、影视特效制作、广告创 意设计、社交媒体内容创作及3D打印建模等多个领域。 在使用权益方面，混元3D创作引擎面向全球个人用户提供每日20次的免费生成额度；通过腾讯云接入 API的企业用户，则可享受每日200个3D资产的免费生成权益，为不同类型用户的初期体验与业务测试 提供支持。 腾讯控股有限公司于本周正式宣布，在全球范围内推出自研的混元3D创作引擎。该引擎是一款以人工 智能技术为核心驱动力的专业创作平台，核心目标在于简化全球创作者及企业用户的3D数字资产生成 流程，推动3D ...

11月28日，由北京师范大学社会治理与公共传播研究中心主办的"协同共建驱动急救变革"主题交流 会在京举行。会议聚焦社会应急救援体系建设，重点研讨了由腾讯公司等社会力量共同推动的"五分钟 社会救援圈"社会创新项目。该项目通过科技赋能与社会协同，有效提升了院外急救效率，为破解我国 院前急救资源紧张、公众参与度不高等难题提供了新思路与新路径，是"科技向善"理念在社会治理领域 的生动实践。 我国院前急救体系长期面临挑战：公众急救技能普及率不足1%，自动体外除颤器（AED）配置密 度相对较低，且急救响应各环节协同效率有待加强。数据显示，心脏骤停患者的抢救成功率与救援时效 密切相关，"黄金4分钟"内的有效干预至关重要。 针对这些痛点，腾讯公司自2020年起，秉持"用户为本，科技向善"的使命愿景，探索构建"五分钟 社会救援圈"。该项目依托企业技术优势，初步形成了"党政引导、企业赋能、社会协同、公众参与"的 多元共建模式。截至2025年10月，项目已累计实施应急救助51511例，其中成功救治心脏骤停患者352 名。 项目核心是打造以"企鹅急救"智能平台为枢纽的数字化急救体系。该平台深度融合微信生态、精准 定位、AI调度算法、 ...

【小鹏汽车捐赠500万港元，支援香港大埔火灾救援】 【喜茶捐赠500万港元，支援香港大埔火灾救援】 【蜜雪冰城捐赠2000万港元，支援香港大埔火灾救援】 【比亚迪捐赠1000万港元，支援香港大埔火灾救援】 【#近130家企业驰援香港大埔火灾#】11月26日下午，香港大埔宏福苑发生严重火灾，导致重大人员伤 亡及财产损失，灾情牵动社会各界。截止目前不完全统计，近130家企业纷纷驰援香港。 详细如下↓ 【腾讯追加2000万港元捐款，累计3000万港元支援香港大埔火灾救援】 | 1 | 行业 | 企业名称 | 捐助金额 | 备注 | | --- | --- | --- | --- | --- | | | | | (万港元) | | | 2 | 互联网 | 阿里巴巴 | 2000 | | | 3 | | 马云公益基金会 | 3000 | | | 4 | | 腾讯公益慈善基金会(香港) | 3000 | 首批捐款1000万+追加2000万 | | 5 | | 字节跳动(香港) | 1000 | | | 6 | | 目度 | 1000 | | | 7 | | 网易 | 1000 | | | 8 | | 微博 | 1000 ...

本文源自：市场资讯 作者：情报员 声明：市场有风险，投资需谨慎。本文为AI基于第三方数据生成，仅供参考，不构成个人投资建议。 国家知识产权局信息显示，腾讯科技（深圳）有限公司申请一项名为"业务系统的测试方法、装置、电 子设备及存储介质"的专利，公开号CN121029577A，申请日期为2024年5月。专利摘要显示，本申请涉 及计算机领域，公开了一种业务系统的测试方法，应用于第一应用的第一应用服务端，方法包括：获取 目标接口的测试配置信息，测试配置信息包括目标接口的生效参数和重放参数；若目标接口的生效参数 指示目标接口在第一业务系统中可被调用，从候选请求集合中获取请求目标接口的目标请求；按照目标 接口的重放参数，向第一业务系统中的目标接口和第二业务系统中的目标接口重放目标请求；获取第一 业务系统响应于目标请求返回的第一响应数据和第二业务系统响应于目标请求返回的第二响应数据；根 据目标接口对应的第一响应数据和对应的第二响应数据，确定第一业务系统的测试结果，实现了以接口 为单位的测试。 天眼查资料显示，腾讯科技（深圳）有限公司，成立于2000年，位于深圳市，是一家以从事软件和信息 技术服务业为主的企业。企业注册资本 ...

深圳 3D 打印赛道的 "内卷"，从资本布局的密集程度可见一斑。作为互联网巨头的腾讯，早已在该领域 埋下 "双保险"—— 公开信息显示，腾讯不仅是创想三维的股东，还曾被传参投拓竹科技新一轮融资 （估值或达 100 亿美元），尽管拓竹创始人陶冶后续回应 "目前没进行中的融资"，但双方此前的合作 已十分紧密：2025 年 7 月，拓竹旗下 3D 模型平台 MakerWorld 全面接入腾讯混元 3D 生成模型，借助 生成式 AI 降低用户建模门槛，为消费级 3D 打印机的市场爆发铺路。 另一边，大疆的入局则带着更强的 "技术协同" 属性。2025 年 11 月，天眼查数据显示大疆持有智能派 5% 股权，大疆相关人士对媒体表示，"投资基于看好消费级 3D 打印技术发展潜力，符合公司对创新科 技的前瞻性布局"。而智能派联合创始人陈波在接受新闻采访时也直言，相较于单纯财务投资，更看重 大疆的技术能力补足，"融资后将对标大疆 All In 产品研发，补齐生态建设"。 2025 年 8 月，深圳 3D 打印企业创想三维正式向港交所递交主板上市申请，冲击 "港股消费级 3D 打印 第一股"；仅 1 个多月后，同为深圳本土企业 ...

Core Insights - The report by Goldman Sachs analyzes the competitive landscape of China's AI industry, focusing on the strategic choices of major players like Alibaba, ByteDance, and Tencent [2][6][18]. Group 1: Alibaba's Strategy - Alibaba is pursuing a "full-stack" approach similar to Google's, with a significant capital expenditure increase of 80% year-on-year, reaching RMB 32 billion [6][7]. - The company aims to build a robust AI infrastructure through vertical integration of "base models + multimodal capabilities," despite challenges in chip supply [6][7]. - Alibaba Cloud's external revenue grew by 29% year-on-year in the September quarter, with AI-related revenue achieving triple-digit growth for nine consecutive quarters [7][8]. Group 2: ByteDance's Approach - ByteDance is leveraging its dominance in consumer applications to enhance its foundational infrastructure, with daily token usage surpassing 30 trillion, approaching Google's 43 trillion [10][14]. - The company's education app Gauth has seen a 394% year-on-year increase in monthly revenue, indicating strong market performance [11]. - ByteDance's Volcano Engine holds a 49.2% market share in the public cloud market for large models, showcasing its competitive edge [14]. Group 3: Tencent's Position - Tencent has adopted a more restrained approach, reducing capital expenditures while focusing on integrating AI capabilities into its extensive social and payment ecosystem [15][17]. - The company has integrated its AI assistant "Yuanbao" into WeChat Pay, enhancing operational efficiency for small and medium-sized businesses [17]. Group 4: US-China AI Competition - The competition between the US and China in AI has entered a "dynamic alternation" phase, with Chinese models expected to rapidly iterate and catch up within 3-6 months following significant advancements in US models [4][19]. - Chinese companies are noted for their resilience and speed, with many leveraging open-source models to enhance their capabilities [19]. Group 5: Valuation Insights - Goldman Sachs indicates that the current state of the Chinese AI sector does not reflect a bubble, with expected P/E ratios for Tencent and Alibaba at 21x and 23x respectively, lower than those of major US tech companies [20].

以往跨境游客购买手信时面临"大包小包"、"携带不便"等痛点，而本次活动的线下门店——"澳门手信微信礼物体验店"汇聚了超20家澳门商家的特 色手信，并创新引入微信礼物功能，游客在店内只需扫描商品"送礼码"下单，即可借助微信蓝包在线上秒送澳门手信给亲朋好友，免去随身携带入境的 麻烦。 港澳地区一直是内地游客出境游首选目的地，今年1月至10月澳门入境旅客超3000万人次，其中超七成为内地游客。为更好服务内地游客赴澳消 费，推动中小商家利用微信生态创新增长，11月28日在澳门经济及科技发展局的支持下，澳门直播协会联合腾讯正式启动微信小店"礼遇澳门"直播电商 好物节，并在澳门最繁华的商业街区——议事厅前地广场附近澳门何老桂巷5号落地首个微信礼物线下体验店，超20家澳门商家的特色手信汇聚线下体 验店，让跨境游客体验"一站式""零负担"买送澳门手信。 中央驻澳门联络办公室、澳门经济及科技发展局、澳门直播协会、腾讯公司等代表为澳门手信微信礼物体验店揭牌 （澳门手信微信礼物线下体验店正式开业） 澳门微信礼物体验店采用在澳门下单、内地发货的"前店后仓"模式，是数字经济和实体经济深度融合发展的生动实践。这一模式可以为商家提升运 营 ...

Core Insights - The report by Goldman Sachs highlights the intense competition in China's AI sector, focusing on the strategic choices of major players like Alibaba, ByteDance, and Tencent, and suggests a new normal of "dynamic alternation" in the US-China AI competition [1][2] Group 1: Alibaba's Strategy - Alibaba is adopting a "full-stack" approach similar to Google's, with a significant increase in capital expenditure, which surged by 80% year-on-year to reach 32 billion RMB in the September quarter [3][4] - The company's cloud revenue grew by 29% year-on-year, with AI-related revenue achieving triple-digit growth for the ninth consecutive quarter, and is expected to accelerate to 38% growth in the December quarter [4][6] Group 2: ByteDance's Approach - ByteDance is leveraging its massive traffic advantage, with a daily token consumption of 30 trillion, approaching Google's 43 trillion, and significantly surpassing competitors like Baidu [9][13] - The company's application "Doubao" leads in domestic AI application activity, while its overseas education app Gauth saw a 394% year-on-year increase in monthly revenue [9][13] Group 3: Tencent's Strategy - Tencent is maintaining a conservative approach, reducing capital expenditure while focusing on seamlessly integrating AI capabilities into its extensive social and payment ecosystem [14][15] - The company has integrated its AI assistant "Yuanbao" into WeChat Pay, enhancing operational efficiency for small and medium-sized businesses [15] Group 4: US-China AI Competition - The report outlines a "dynamic catch-up" cycle in the US-China AI competition, where Chinese models typically follow significant advancements in US models within 3-6 months [16][17] - Chinese companies are noted for their resilience and aggressive cost control, with many leveraging open-source models to enhance their capabilities [17] Group 5: Valuation Insights - Goldman Sachs indicates that the current state of the Chinese AI sector does not reflect a bubble, with projected P/E ratios for Tencent and Alibaba at 21x and 23x respectively, lower than those of major US tech companies [18]