上周五，阿里的大模型千问狂撒30亿，请全民喝奶茶，只需要一句话"千问，帮我点杯奶 茶"，就能联动千问、淘宝、支付宝、盒马等多个 App，把原本需要多步操作的流程压缩成 一次指令。多家奶茶店接单到手软，被迫临时"歇业"、外卖骑手爆单、千问登顶 App Store 榜一。可以说，让无数大众近距离地真实体验了AI时代的全新生活方式。 而在前不久，另一个现象在开发者社区发生：原本上市一年多、销量平稳的 Mac mini，在短短十 多天里出现显著增量，甚至出现断货与补货讨论。其背后的推手则是一个诞生不到两个月的开源 AI 助手——OpenClaw。它在社区引发了一波"用 Mac mini 部署 AI 助手"的晒图与教程潮，进而 把一台小主机推成了"AI Agent 试验田"。 两件事表面上风马牛不相及，本质却指向同一个趋势： AI Agent（智能体）负载正在崛起。 大模 型时代沉淀的能力，正在通过"智能体化"加速落地——这也意味着，芯片产业的评价体系可能要变 了。 "一只龙虾"，引爆Ma c mini 两个月前，一位已经退休的奥地利软件工程师开发者Peter Steinberger利用周末随手"攒"出了一个 项目。起 ...

中金研究 大模型的演进史，本质上是一部与"遗忘"抗争的历史。 当我们惊叹于模型的推理能力时，往往忽视了一个重要短板： 在缺乏记忆留存的架构下，模型 每一次对历史信息的处理，本质上都是一次昂贵的"重复计算"。 这种以高昂算力对抗遗忘的粗放模式，正面临着显存墙与上下文窗口的物理极限。我 们认为，2026年及之后的AI Infra主战场将增加"模型记忆"这一极。 何为模型记忆？如何理解短期、中期、长期记忆三层记忆系统对应的软硬件需求？ 如何对应模型训练、推理、Agent场景理解记忆分层系统？我们将在本报告中予以解答。 点击小程序查看报告原文 Abstract 摘要 短期记忆构成大模 型单 次推理的"当前视野"。 作为高频读写、对延迟极度敏感的"热数据"，其核心矛盾在于KV Cache对显存容量与带宽的双重挤占。软 件端通过PagedAttention显存虚拟化与PD分离调度进行优化，并探索出无限注意力（Infini-attention）等前沿架构以支撑百万Tokens上下文窗口。这一逻辑 直接锚定了HBM与片上SRAM作为突破"显存墙"与"延迟墙"的重要硬件要素。 中 期记忆保障跨会话的情景连续性，是Agent的基 ...

Core Insights - The article highlights the significant impact of AI in consumer interactions during the 2026 Spring Festival, with a record of 1.2 billion orders processed by AI, marking a milestone in AI's real-world application and commercialization [3][4][9] Group 1: AI Performance and User Engagement - The AI system "Qianwen" achieved 1.2 billion completed orders in just six days, demonstrating a successful execution of AI in real-world tasks [2][3] - Daily active users of Qianwen surged to 73.52 million, nearly matching the industry leader, indicating a strong user engagement [2] - Nearly half of the orders came from county-level cities, and 1.56 million users aged 60 and above experienced ordering through AI for the first time, showcasing a broadening user base [6][8] Group 2: Technological Advancements and Ecosystem Integration - Qianwen successfully integrated the entire process from AI model to ecosystem, payment, and fulfillment, creating a positive feedback loop [5][6] - The underlying technology includes the "Zhenwu 810E" chip and a robust cloud computing infrastructure, enabling efficient handling of high order volumes [8] - Alibaba's extensive experience in e-commerce and logistics supports Qianwen's backend capabilities, enhancing its service offerings in various sectors [8] Group 3: Competitive Landscape and Future Implications - The current AI competition has shifted focus from model parameters to building executable and scalable task-oriented ecosystems, with Qianwen leading this transition [5][9] - The successful implementation of Qianwen during a high-traffic consumer period may redefine user interaction with AI, potentially establishing new habits in AI-assisted shopping and daily life [7][9] - As global competitors like Google test new features, Alibaba's Qianwen has already demonstrated a practical application of AI in consumer markets, positioning China at the forefront of AI model validation [9]

Core Insights - OpenClaw has gained significant traction since its launch in early 2026, achieving high visibility in the global developer community, including over 180,000 stars on GitHub, and leading to the emergence of social experiments like Moltbook, showcasing a new trend in interactive AI agents [3][15] - The creator, Peter Steinberger, emphasizes that the success of OpenClaw is not solely due to technology but rather its community engagement and low entry barriers, allowing users to modify the software easily [6][9] - The project has sparked discussions about the future of AI agents, the redefinition of traditional applications, and the evolution of human-agent interactions, which many entrepreneurs have yet to fully grasp [5][6] Project Origin - The inception of OpenClaw began with Peter's personal need for an AI assistant in April 2024, leading to a series of early experiments that culminated in the project's creation due to frustration over its absence [9][10] - The first working prototype was developed in just one hour, demonstrating the core functionality of interacting with a computer through a chat application [11][12] - The project experienced viral growth after an unexpected feature emerged, showcasing the agent's ability to autonomously handle tasks without prior instruction [12][13] Technical Architecture - OpenClaw's architecture includes several sophisticated components, such as a chat client gateway for decentralized access, a core decision engine, and a skills system for functionality expansion [16][17] - The agent's self-awareness allows it to read and modify its own source code, which is a significant advancement in software engineering [17][18] - The project has faced challenges related to security and brand protection, particularly after its rapid rise in popularity, highlighting the need for integrated security measures [6][27] Community and Social Impact - MoltBook, a social network for AI agents, has emerged as a phenomenon, where agents interact in a Reddit-like environment, leading to discussions that sometimes cause public concern [27][28] - The term "AI psychosis" was coined by Peter to describe the mix of genuine concern and sensationalism surrounding AI developments, reflecting societal fears about AI's role in the digital age [28][29] - OpenClaw represents a balance between freedom and responsibility, as users gain control over their data while also being accountable for its security [30][31] Business Model and Future Outlook - Despite the project's popularity, Peter has chosen to reject significant funding offers, prioritizing the open-source ethos and community engagement over commercial pressures [32][33] - The current financial status shows monthly revenues between $10,000 and $20,000, with ongoing discussions for partnerships with major tech labs, provided the project remains open-source [33][34] - Peter envisions a future where traditional applications may be replaced by AI agents, fundamentally altering the app market landscape [39][40]

Core Viewpoint - The article discusses the transformative impact of AI on creativity and the role of programmers in the AI era, emphasizing the need for collaboration between humans and AI in various fields, particularly in video generation and content creation [1][5]. Group 1: AI and Programming - AI is reshaping the way creativity is approached, leading to questions about the future role of programmers as machines become more capable [1]. - The current state of AI technology is promising, but the commercial applications and business models remain uncertain, with many users still in the "trial" phase [12][13]. - The experience of programmers may become a burden in the AI era, as AI tools can now generate code, shifting the focus from writing code to managing AI outputs [14][18]. Group 2: AI in Content Creation - The video generation sector is highlighted as a key area where AI can democratize content creation, allowing non-experts to produce videos with simple prompts [30]. - AI's ability to generate content is still developing, with a significant gap between current capabilities and the artistic quality expected by professionals [30][41]. - The collaboration between AI and human creators is essential, as AI-generated content often lacks the nuanced artistic judgment that human directors provide [36][50]. Group 3: Market Dynamics and Investment - The investment landscape for AI startups is characterized by uncertainty, with many entrepreneurs and investors feeling anxious about the future direction of AI technology [59][60]. - The article suggests that many investors are following trends rather than establishing a solid understanding of AI's developmental trajectory, which could lead to high risks [60][62]. - The potential for AI to revolutionize the film industry is acknowledged, particularly in reducing production costs and time for animated content, but significant challenges remain for high-quality productions [54][57].

Group 1 - The core event is the launch of "Qianwen's 30 Billion Big Free Order" campaign, which saw users making 4.1 billion requests for assistance and AI completing over 120 million orders within six days, marking a significant milestone in AI's real-world task execution and commercialization [1][2] - The campaign has led to a surge in AI consumption in county areas, with nearly half of the AI orders coming from these regions, and 1.56 million users aged over 60 experiencing food delivery through AI for the first time [1] - Users ordered over 1,000 tons of eggs, more than 2,300 fitness equipment items, and 1,500 books through AI, showcasing a new way of shopping for the New Year [1] Group 2 - The success of Qianwen represents a pivotal moment for users experiencing AI's impact on daily life, indicating a shift in user habits as "Qianwen help me" becomes a new norm in the AI era [2] - The rapid growth of Qianwen is driven by Alibaba's dual approach of leveraging its comprehensive AI technology and ecosystem, combining robust technical foundations with extensive service offerings in e-commerce, travel, and more [2] - The transition from active search in the PC era to AI-driven shopping with a simple request reflects a new paradigm in consumer behavior, heralding the beginning of an AI lifestyle era by 2026 [5]

2026 开年至今，人工智能圈子最火的是一只小龙虾 Clawdbot 。 从 Clawdbot 到 OpenClaw，历经两次改名都无法阻挡大家对它的热情，一种全球性的集体渴望正在浮现 —— 人们迫切希望拥有一个更高级、更通用、更 可靠的超级智能体。 过去的一年里，Agent 层出不穷，2025 年甚至被称为是「AI 智能体元年」。 衡量一款智能体的真正实力，既要看通用场景的综合解决能力，也需要考量 垂直领域的核心专项能力，而 GAIA 通用智能基准榜单和 BrowseComp-Plus 深度研究基准榜单，比任何概念讨论都更加直接。 去年，创业公司 Manus 的智能体爆火，也一并带火了 GAIA 榜单。自此以后似乎每家的智能体都会试着在 GAIA 上刷个榜。而聚焦深度研究与网页浏览 能力的 BrowseComp-Plus 基准测试，也凭借严苛的评测标准，成为智能体检索能力的核心比拼赛场。 最近，我们在翻阅两大榜单时发现，榜首位置均迎来了新突破：基于 openJiuwen 这一新兴开源项目构建的 DeepAgent 和 DeepSearch 双双登顶 GAIA 和 BrowseComp-Plus 榜首。 De ...

Core Viewpoint - The recent release of a top 50 enterprise-level AI Agent applications list highlights a "dual-track" competitive landscape in the AI Agent market, characterized by ecosystem giants like Alibaba, Huawei, and ByteDance, and vertical specialists like Jinzhihui and Maifushi, each following distinct but complementary success strategies [1]. Group 1: Ecosystem Giants - The ecosystem giants focus on "infrastructure" as their core strategy, leveraging their advantages in traffic, computing power, and foundational models to build a universal platform for the AI era [3]. - ByteDance (Kouzi Space) attracts numerous developers with low application development thresholds and a robust plugin ecosystem, enabling non-programmers to quickly create task-oriented agents through graphical representations of complex prompt engineering [3]. - Alibaba (WebSailor) aims to enhance AI's understanding of web execution and browser interaction, addressing automation tasks in publicly available internet information [3]. - Huawei (Hongmeng AI Super Agent) integrates AI agents deeply into hardware, achieving cross-device intent understanding and task continuity through edge-cloud collaboration [3]. - While these giants aim to establish a strategic foothold and provide a universal base, they often struggle to reach the intricate business needs in complex industry sectors [3]. Group 2: Vertical Specialists - Vertical specialists emphasize a deep understanding of industry-specific business logic, integrating AI Agent technology with concrete scenarios to create closed-loop implementation paths [4]. - Maifushi (AI-Agentforce) utilizes a "middle platform + scenario" model in marketing and sales automation, embedding agent technology into CRM and SCRM systems, which allows for rapid scaling in standardized marketing scenarios [4]. - Jinzhihui represents industries with high asset and compliance requirements, such as finance and government, where system security, compliance, and execution accuracy are critical. They propose a "supervised agent" approach that combines the cognitive and planning capabilities of large models with a stable RPA execution engine [6]. - Jinzhihui's approach demonstrates significant application value in scenarios like intelligent risk control and automated operations, enabling financial institutions to transition smoothly from traditional automation to intelligent agents without major system overhauls [6]. - The competitive advantage of vertical specialists lies not only in algorithmic superiority but also in their ability to engineer existing digital assets effectively [6]. Group 3: Market Trends and Future Outlook - The market is witnessing a divergence in solutions addressing the high costs of starting over, with companies like ByteDance and Baidu focusing on providing native cloud-based intelligent agent development environments, while vertical firms like Jinzhihui offer "non-intrusive upgrades" for existing automated processes [7]. - Jinzhihui's "one-click upgrade" path empowers existing processes with LLM capabilities without altering core systems, significantly lowering the barriers for enterprises to adopt AI [7]. - A key measure of vertical specialists' competitiveness is their security governance capability, ensuring that intelligent agents operate within defined boundaries while maintaining data security and compliance [8]. - The future value of AI Agents will increasingly depend on their ability to create "chemical reactions" with business scenarios rather than just technical metrics, shifting the evaluation criteria from what they can communicate to what they can accomplish reliably in complex environments [10]. - For enterprises undergoing digital transformation, 2026 is projected to be a pivotal year for application implementation, necessitating a focus on both efficiency breakthroughs on universal platforms and finding practical solutions that convert intelligent capabilities into stable productivity [10].

盘面上，两市探底回升，芯片设计概念上涨。相关ETF方面，科创芯片设计ETF天弘（589070）标 的指数盘中涨1.76%，成交额达2584.38万元。成分股中，晶晨股份、芯朋微、复旦微电、盛科通信-U涨 超5%，芯原股份、新相微、安路科技等多股跟涨。 新世纪评级指出，中国芯片设计企业在部分领域已达到国际先进水平，但高端通用芯片仍依赖长期 研发投入。行业马太效应明显，投资需聚焦技术突破和核心竞争力提升，以应对国际竞争格局。 每日经济新闻 （责任编辑：张晓波 ） 【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容 的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱： news_center@staff.hexun.com 科创芯片设计ETF天弘（589070）最近十个交易日累计获资金净流入1.38亿元。截至2026年02月11 日，该基金最新规模为6.31亿元。 国产GPU是半导体国产替代的核心赛道，过去三年国产GPU设计企业市场份额从5%提升至12% ， 替代空间广阔。国家大基金三期重点支持高端芯片设计领域，为国产GP ...

周枫总结称，"2025年全年，我们实现了第一个全年经营性现金净流入……展望未来，我们仍然致力于 人工智能原生战略，专注于学习服务和广告。通过推进垂直大型语言模型和扩展人工智能驱动的应用程 序和代理，目标是提供差异化的用户体验，并推动可持续的长期增长。" 网易有道表示，2026年其将从"教育科技"公司正式向"学习与广告AI应用服务提供商"转型，聚焦于学习 +广告双赛道。 周枫认为，2026年将成为AI Agent的关键元年——这种具备复杂任务处理能力、能为用户创造更高价值 的先进AI系统，将成为行业主流。 截至2025年12月31日，网易有道的现金、现金等价物、流动和非流动限制性现金以及短期投资总额为 7.432亿元人民币（1.063亿美元），较2024年年末增长8060万元。该公司的合同负债主要由有道学习服 务产生的递延收入组成，为8.477亿元人民币（1.12亿美元）。网易有道表示，为了支持未来业务，截至 2025年底，网易有道已获得集团财政支持，包括8.78亿元人民币的短期贷款，以及2027年3月31日到期 的1.321亿美元长期贷款。 2月11日，网易旗下智能学习公司有道(NYSE:DAO)发布2025 ...