软件ETF（515230）跟踪的是软件指数（H30202），该指数从市场中选取涉及软件开发、销售和服务等 业务的上市公司证券作为指数样本，覆盖操作系统、应用软件、网络安全等领域的代表性企业，以反映 软件行业相关上市公司证券的整体表现。该指数具有显著的成长性和技术导向性，能够较好地体现软件 行业的市场趋势和发展动态。 长江证券指出，豆包手机助手作为首个豆包与手机厂商在操作系统层面合作的手机AI助手，实现了通 过系统语音、侧边AI键及智能耳机唤醒等功能，直接读取屏幕内容并跨应用调用服务。此举推动手机 操作系统交互逻辑从"图标点击"向"意图识别"转变。终端设备可能是AI落地的重要方向，而全栈AI或将 是未来模型厂商的发展趋势。可关注国产大模型厂商、AI基础设施提供商、AIAgent相关公司以及中国 推理算力产业链。 （文章来源：每日经济新闻） ...

曦华科技成立于2018年8月，是国家级重点"小巨人"企业，主要提供智能显示芯片、智能感控芯片及解决方案，已应用于智能汽车、手机、可穿戴设备和 机器人等市场。其自主研发芯片累计出货量超过1亿颗。 曦华科技部分产品线布局（图源：曦华科技官网） 该公司的智能显示芯片及解决方案包括核心图像处理芯片AI Scaler及智能显示驱动芯片STDI芯片。曦华科技研发了全球首款ASIC架构的Scaler，在视觉 无损压缩、画质增强及高速接口传输方面掌握关键技术。 12月3日，深圳端侧AI芯片与解决方案提供商曦华科技正式递表港交所。 沙利文数据显示，2024年，全球Scaler市场中前五大供应商合计市场份额达70.8%，曦华科技凭借3700万颗的出货量排名全球第二，市场份额为18.8%。根 据批注估计，公司A为莱迪思半导体、公司B为京微齐力、公司C为安路科技、公司D为荣晶电子。 且曦华科技在AI Scaler细分赛道占据55%的市场份额，排名全球第一，其来自AI Scaler的收入自2022年以来连续3年位列中国榜首。 | 排名 | 公司名稱 | 出意量 | 市場份額 | | --- | --- | --- | --- | | ...

Core Insights - The global tech industry is experiencing a shift from cloud-based AI to edge AI, driven by the limitations of cloud dependency and the need for real-time processing in critical applications [1][4][18] - The current trend emphasizes the development of smaller, more efficient AI models that can operate independently on edge devices, rather than relying on large cloud models [16][18] Group 1: Challenges of Cloud Dependency - Cloud-based AI systems face significant latency issues, which can be detrimental in time-sensitive applications like autonomous driving [2][4] - Privacy concerns arise from the need to transmit sensitive data to cloud servers, making edge computing a more attractive option for users [2][4] Group 2: The Shift to Edge AI - The industry is moving towards a "cloud-edge-end" architecture, where complex tasks are handled by cloud models while real-time tasks are managed by edge devices [7][18] - Edge AI must overcome the "impossible triangle" of high intelligence, low latency, and low power consumption, necessitating innovative solutions [7][8] Group 3: Techniques for Edge AI Implementation - Knowledge distillation is a key technique that allows smaller models to retain the intelligence of larger models by learning essential features and reasoning paths [8][10] - Extreme quantization reduces model size and increases speed by compressing model weights, allowing for efficient processing on edge devices [10][11] - Structural pruning eliminates redundant connections in neural networks, further optimizing performance for edge applications [10][11] Group 4: Hardware Innovations - The "memory wall" issue in traditional architectures leads to inefficiencies, prompting the development of specialized architectures that integrate storage and computation [11][13] - Companies are exploring dedicated chip designs that optimize performance for specific AI tasks, enhancing efficiency in edge computing [13][14] Group 5: Industry Evolution - The focus is shifting from general-purpose AI models to specialized models that excel in specific applications, improving reliability and performance [15][16] - The Chinese AI industry is collectively recognizing the importance of practical applications over sheer model size, leading to a more grounded approach to AI development [16][18]

然而，产品发布后随即遭遇多个软件平台的使用限制，首批用户反馈在作微信时触发登录环境异常导致 封号;多家银行App及阿里系应用识别出非人工作风险，拒绝执行支付、验证码等敏感指令或直接提 示"设备异常"。面对广泛的业内抵制和使用限制，豆包团队被迫于12月3日及5日紧急下线微信及金融类 应用的作能力，并对游戏代玩、点击激励广告等使用场景对使用AI助手进行了限制。 中银国际发布研报称，明年将是AI手机助手开始广泛发展的一年，未来几个季度市场也将陆续发布带 有AI手机助手功能的产品。该行认为豆包手机助手的发布将显著强化手机厂商的FOMO心态，从而带来 对端侧AI相关的功能性硬件的提前投入和升级，如SoC、存储、续航、散热和传感器等。 中银国际指，邀请手机智能助手的业内资深专家参与了讨论，并一致认为手机AI助手正在逐步走向应 用的拐点，基本的底层技术栈的设计已经比较成熟，而目前所面对的主要困境更多来自互联网服务商、 手机硬件厂商以及监管之间不同利益所带来的摩擦。 报道称，12月1日，字节跳动联合中兴手机发布搭载豆包手机助手预览版的工程样机，其核心卖点在于 通过语音指令实现跨应用的自动化AI Agent作能力。豆包手机广告 ...

2025年 12 月 12-13 日，由 GAIR 研究院与雷峰网联合主办的「第八届 GAIR 全球人工智能与机器人大 会」，将在深圳南山·博林天瑞喜来登酒店举办。点击文末"阅读原文"，即可报名参会。 今年大会，将开设三个主题论坛，聚焦大模型、算力变革、世界模型等多个议题，智算论坛将汇聚来自 AI 芯片、智算中心、云计算、基础设施与资本领域的建设者与思考者，共同探讨算力革命的现实逻辑与趋势 走向。 科创板上市的AI芯片公司严抓品控，落地数个千卡集群 登陆科创板的AI芯片公司，正严格把控算力服务器生产质量，已安排专人驻点合作服务器厂商，确保机器 制造品质。 据悉，该公司面向集群客户的最新一代旗舰产品，单卡算力约0.5P，包含组网、交换机等全模块的价格为 25万元；上一代旗舰产品的8卡一体机售价则在60-65万元。目前，公司已与运营商等合作方合作落地数 个千卡级别集群项目。 2026年将是国产芯片发展的重要时间节点，各家AI芯片厂商的订单量如何？技术迭代有何方向？欢迎添加 微信 YONGGANLL6662 交流更多信息。 国产头部AI芯片公司近期频中大单，向互联网大厂承诺「不限量供应」 头部AI芯片公司近期订单表 ...

接下来市场应重点关注发布会是否披露具体硬件合作伙伴、开发者支持细则、以及首批商品化机型与量 产时间表，这些细节将直接影响产业链的投资与备货节奏。 （校对/秋贤） 技术路线方面，谷歌预告重点在于将AI能力向端侧设备下沉，实现端侧推理与情境感知，从而减少对 云端的依赖并提升响应速度与隐私保护。端侧AI在计算、能耗与算法适配上有较高门槛；若Android XR将Gemini的轻量化或分层推理能力部署到可穿戴端，将推动芯片、传感、低功耗神经网络引擎及系 统级调度等环节的协同发展。产业链人士指出，端侧AI的实际落地还需要软硬件与生态（包括开发者 工具、算法模型微调和功耗管理）三方面配合。 回看进程，谷歌在今年 Google I/O 2025 已展示Gemini 2.5系列及Android XR相关技术框架，本次特别发 布会被市场视为从愿景展示向产品化落地的检验窗口。若发布会带来可量产的参考实现或开放性开发套 件（SDK/Platform），将大幅降低厂商与应用开发者的接入成本，推动AI眼镜、AR/VR一体机进入更快 的商业化轨道。谷歌生态的开放策略也可能促成芯片厂商与ODM加速针对XR优化的产品路线。 行业机构与券商研 ...

Investment Rating - The industry investment rating is maintained at "Overweight" [1] Core Views - The report highlights the potential investment opportunities in edge AI, particularly with the release of the "Doubao Mobile Assistant" by ByteDance, which showcases the capabilities of AI in mobile applications [5][6] - The electronic industry has shown a recovery trend in consumer electronics, with continuous releases of foldable smartphones and sustained high demand for AI infrastructure [19] Market Performance - The electronic industry index rose by 1.09% during the week of December 1 to December 5, 2025, closing at 6300.64 points [3][10] - The semiconductor sector reported a slight increase of 0.88%, while consumer electronics saw a rise of 1.61% [3] - Year-to-date, the electronic industry index has increased by 42.15%, outperforming the CSI 300 by 25.65 percentage points [10] Valuation Metrics - The electronic sector's Price-to-Earnings (PE) ratio (TTM, excluding negative values) is 57.70X, which is at the 39.97th percentile of the past 10 years [4][11] - The Price-to-Book (PB) ratio is 4.81X, positioned at the 57.57th percentile historically [4][11] Industry Dynamics - The report emphasizes the collaboration between Doubao and smartphone manufacturers to integrate AI capabilities into mobile operating systems, enhancing user experience through complex task automation [5][6] - The ongoing advancements in AI technology are expected to drive demand for edge hardware upgrades, particularly in sectors like SOC and thermal materials [19] Investment Recommendations - The report suggests focusing on investment opportunities in AI infrastructure, edge SOC, the supply chain for foldable smartphones, and the storage industry [19] - Specific companies to watch in the AI infrastructure sector include Cambricon, Chipone, and Aowei Technology, while in the edge SOC sector, companies like Rockchip, Hengxuan Technology, and Espressif Systems are recommended [19]

12月伊始，豆包手机助手凭借系统级AI功能迅速走红的同时，也卷入了些许隐私争议。 有质疑声称，其使用的"INJECT_EVENTS权限"属于敏感权限，存在隐私相关风险。对此，豆包团队12月3日回应称，该权限是行业实现跨应用操作的常规 需求，需用户主动授权且全程透明可控，不会替代敏感操作；12月5日，团队再度发文，宣布限制AI在刷分、金融类应用及部分游戏场景的使用，进一步回 应市场关切。 技术本体背后，AI部署路径相关话题再度升温：当云端处理的数据隐私风险仍存不确定性，端侧本地算力成为兼顾体验与安全的可行方向之一。联想集团 副总裁、联想中国技术管理委员会执行主席阿不力克木·阿不力米提曾在某次论坛期间向北京商报等媒体记者表示，个人大模型的落地，离不开终端强大的 本地智能算力与可信的数据安全存储能力。 有些巧合的是，在行业讨论聚焦端侧之际，国内端侧AI芯片龙头曦华科技于12月初正式递表港交所，拟通过特专科技通道冲刺IPO——2022—2025年前9个 月间，曦华科技累计录得净亏损约4.26亿元，但公司年收入复合增速高达67.8%，属于典型的潜力选手。 公司招股书披露，曦华科技专注于端侧AI芯片与解决方案，产品基于M ...

Core Viewpoint - The article emphasizes the rapid shift of AI applications from cloud to edge devices, highlighting the increasing investment by tech giants in edge AI hardware, which is reshaping the consumer electronics landscape [1][3]. Group 1: Edge AI Market Dynamics - Major tech companies are actively launching edge AI products, such as AI glasses and smartphones, indicating a strong market interest [3]. - According to Frost & Sullivan, the Chinese edge AI market is projected to reach 307.7 billion yuan by 2029, with a compound annual growth rate of 39.9% [4]. - The profitability of edge AI is driven by the demand for AI servers and smart hardware components, benefiting Chinese supply chain companies [4]. Group 2: Edge AI Characteristics - Edge AI operates on local devices, ensuring faster response times and better privacy protection compared to cloud AI, which relies on remote servers [4]. - Edge AI models are generally smaller and designed for lightweight tasks, focusing on hardware compatibility and low power consumption [4][5]. Group 3: Primary Device for Edge AI - Smartphones are currently viewed as the primary device for edge AI due to their mature hardware and extensive user base, making them the most logical application scenario [6][7]. - While smart glasses show potential, they may require a longer adoption period and are likely to complement rather than replace smartphones [7][8]. Group 4: Investment Opportunities - Investment in edge AI should focus on innovative supply chain companies, assembly manufacturers, and key components like cooling, storage, and system interaction technologies [10][11]. - Companies with strong brand capabilities and ecosystems are expected to gain a first-mover advantage in the edge AI market [10][11]. Group 5: Valuation and Market Sentiment - Despite rising valuations in the edge AI sector, concerns about market "bubbles" are seen as a lack of patience regarding industry development [13]. - The ongoing investments by major players like Apple, Samsung, and Google in edge AI products indicate a long-term commitment to building competitive advantages [13][14].

Core Viewpoint - The article discusses the rapid shift of AI applications from cloud to edge devices, highlighting the increasing investment by tech giants in edge AI hardware, which is reshaping the consumer electronics landscape [1][2]. Group 1: Edge AI Market Growth - The edge AI market in China is projected to reach 307.7 billion yuan by 2029, with a compound annual growth rate (CAGR) of 39.9% [3]. - The profitability of edge AI is driven by the demand for AI servers and smart hardware components, benefiting Chinese supply chain companies [3]. Group 2: Technology and Product Development - Major tech companies are actively launching products in the edge AI space, including AI glasses and smart terminals, indicating a competitive landscape [2]. - Edge AI models operate locally on devices, enhancing response speed and privacy compared to cloud-based models, which focus on complex tasks [3][4]. Group 3: Mobile Devices as Primary Edge AI Carrier - Mobile phones are identified as the primary carrier for edge AI due to their mature hardware, extensive user base, and strong payment willingness [5][6]. - While AI glasses show potential, they may require a longer adoption period compared to mobile phones, which have established usage habits [6][7]. Group 4: Investment Opportunities - Investment in edge AI should focus on innovative supply chain companies, assembly manufacturers, and key components like cooling and storage solutions [8]. - Companies with strong brand capabilities and ecosystems are likely to gain a first-mover advantage in the edge AI market [8][9]. Group 5: Valuation and Market Sentiment - Despite rising valuations in the edge AI sector, concerns about market "bubbles" are noted, with a call for patience regarding the industry's long-term potential [10][11]. - Companies with strong traditional business foundations that integrate edge AI may present lower risk of overvaluation compared to those with weaker fundamentals [11].