"AI超级周期启动，智能经济机会无限。" 正当我们讨论 AI浪潮时，一个被忽视的宏大背景正在展开：AI不仅是一个独立的技术赛道，它正站在一个高达10万亿的基础产业之上。这意味着，我们今 天所见的AI趋势，将是下一轮对现有工种和组织形态进行 "彻底改变"的巨大力量。 百度集团执行副总裁、百度智能云事业群总裁沈抖博士在江阴飞马水城带来了《智能，生成无限可能》的分享，从趋势、原理、场景、基建、变革五方面 带领我们透视智能经济的整个面貌，包括 深入浅出的技术解析与 丰富生动 落地实践分享。 此次分享是一份面向未来的生存指南，帮助创业者抓住这波以大模型为核心的技术浪潮，实现企业的高效、变革与增长。 本文仅为部分内容，打开混沌APP，观看完整版课程《智能，生成无限可能》。 AI 的价值会远超互联网 我们正在 AI超级周期的起点，智能经济带来的机会是无限的。 等 AI进一步发展的时候，不但会使得自身的规模变得更大，而且会把整个产业做得更大。所以，尽管今天AI可触达的市场虽然只有200 亿，但它实际上改 造的会是10万亿的市场。——从注册护士、软件开发师到销售、教师，今天的人工智能会彻底地改变每一个工种，包括为其赋能，或者帮 ...

Core Insights - The core focus of Lenovo Ventures is on investing in "Agents" as a key investment direction, marking a shift from previous investments in large models and computing power to intelligent agents that can deliver real commercial value [2][3] Investment Opportunities - The company identifies eight platform-level opportunities in the AI landscape, emphasizing the potential for disruptive innovation in various sectors [4][5][6][7][8] - **Content Generation**: AIGC's capabilities are seen as transformative for content creation, with investments in companies like Liblib AI that aim to democratize content generation [4] - **AI Operating Systems (AIOS)**: The belief is that a universal AIOS will emerge, moving away from traditional operating systems [5] - **Coding Platforms**: The potential for coding to evolve beyond mere tools into a foundational platform for the digital world is recognized [6] - **Model-as-Application**: Companies that can deliver foundational models directly to enterprise clients are viewed favorably, with examples like Palantir [6] - **Reconstruction of Relationships**: AI's ability to enhance productivity and reshape production relationships is highlighted, with Aha Lab as a case study [7] - **AI and Hardware Integration**: The emergence of new hardware as a platform for AIOS is anticipated [7] - **Native AI Applications**: The potential for intelligent agents to redefine social interactions is acknowledged [7] - **Infrastructure for Agents**: A new infrastructure tailored for intelligent agents is expected to develop [8] Characteristics of Successful Founders - Lenovo Ventures emphasizes four key traits in successful Agent entrepreneurs: - **Youthfulness**: A youthful mindset is seen as crucial for innovation [9] - **Experience**: Founders with deep industry knowledge are favored [9] - **Originality**: The ability to innovate from scratch is essential [10] - **Resilience**: The capacity to pivot and adapt is important for success [10] Advice for AI Entrepreneurs - Entrepreneurs are advised to develop their agents to exceed existing model capabilities by at least six months to lead in the market [11][12] - The importance of defining new paradigms in the industry is stressed, with examples of companies like Cursor demonstrating the potential for agents to lead foundational model development [12][13] Market Strategy - The trend of targeting global markets from day one is noted, with a focus on the vast opportunities presented by AI innovations [15][16] - The competitive landscape is characterized by the need for startups to engage directly with large companies, leveraging their unique innovations to capture market attention [13][14]

Core Insights - The article emphasizes that AI agents have the potential to fundamentally transform the future of the travel industry, particularly for travel and hotel companies, marking a critical moment for leveraging this technological change [2] - The penetration of AI in the travel industry is accelerating, with a significant increase in the number of companies mentioning AI in their annual reports, from approximately 4% in 2022 to 35% in 2024 [3] - Despite the enthusiasm for AI, the travel and hotel industry lags behind other sectors in AI maturity, with 11% of executives admitting their organizations have not deployed any AI applications [6][7] AI Potential and Challenges - AI agents can automate tasks and restructure processes, allowing companies to enhance operational models, efficiency, personalization, and risk resilience while creating new revenue streams [2] - The travel industry faces challenges such as data silos and system barriers, which hinder the effectiveness of AI applications [7] - The cautious attitude towards AI in the travel sector stems from its traditional view as a service industry rather than a technology-driven one, leading to insufficient investment in technology [7] Consumer Experience Transformation - AI agents can significantly enhance consumer travel planning and booking experiences by integrating various data types and executing complex tasks autonomously [10][15] - Current consumer acceptance of AI tools for travel planning is increasing, with a growing number of travelers utilizing these technologies [3] Operational Efficiency and Employee Experience - AI agents can improve employee efficiency by automating repetitive tasks, allowing staff to focus on more meaningful customer interactions [19] - The introduction of AI agents can alleviate pressure on frontline employees, particularly in high-stress situations like flight cancellations [19] Hotel and Property Management Innovations - AI agents can optimize hotel operations by automating room assignments, predictive maintenance, and cleaning task management, leading to significant time savings and efficiency improvements [20][21] - The potential for AI agents to enhance menu optimization and revenue management in hotels is also highlighted, with expected profit increases through dynamic adjustments [21][22] Deployment and Integration Strategies - Many travel and hotel companies are beginning to recognize the need for a strategic roadmap for integrating AI agents into their operations, focusing on key business challenges and customer experiences [24][26] - Companies must assess their technological foundations to support the deployment of AI agents, as many still rely on outdated systems [25] Talent Development and Organizational Culture - The integration of AI will necessitate a shift in employee skill requirements, prompting companies to invest in training and development [27] - Organizations should foster a culture that encourages experimentation and adaptability to keep pace with rapid technological advancements [29] Process Reengineering - The article stresses that simply embedding AI into existing processes may not yield significant value; instead, companies should rethink and redesign their workflows to fully leverage AI capabilities [30] - AI agents are seen as a transformative force that can reshape business processes and enhance the overall travel experience [30][31]

中国工程院院士、浙江大学教授谭建荣在主题发言环节，发表题为"大模型与智能体：关键技术与发展趋势"的演讲，系统拆解了人工智能从底层技术到落地 应用的全链路逻辑。 人工智能技术的迅速发展推动了大模型和智能体的融合发展，成为推动产业革新的核心驱动力。12月9日，由中关村科金主办的"超级链接·智见未来"—— EVOLVE 2025大模型与智能体产业创新峰会顺利举办。当日，中关村科金与华为云、阿里云、百度智能云、火山引擎、亚马逊云科技、超聚变、软通动力 等产业领军企业，共同发布 "超级连接" 全球生态伙伴计划。 谭建荣表示，智能体是人工智能的载体，人工智能的核心由数据、算法、算力三大部分构成，而这三者的融合载体便是智能体。智能体作为人工智能的落地 载体，已广泛应用于智能机器人、无人驾驶汽车、无人机等场景。 责任编辑：山上 关键词阅读：智能体 大模型 中关村科金 为什么近年来人工智能火起来了？谭建荣认为，早期专家系统依赖因果关系编程，而如今大模型则依托大数据挖掘关联关系，实现了技术路径的重大突破。 针对未来发展趋势，谭建荣提出大模型与智能体需要实现云、边、端的协同发展，特别是智能体需要云、边、端的协调部署，实现同步协同， ...

其中，得助大模型平台5.0集成六大行业300+企业级智能体，支持 "即取即用"，搭配全链路智能体开发 运维能力，让智能体落地成功率达95%，是IDC认证的智能体开发平台主要厂商。 目前，中关村科金相关产品已服务2000余家行业头部客户，业务遍及 180多个国家和地区，助力金融领 域头部机构降低60%场景创新试错成本，实现工业领域有色金属冶炼能耗下降8%，在汽车营销场景将 到店线索转化提升55%，在海外服务场景将客服效率提升超50%。 12月9日，EVOLVE 2025 大模型与智能体产业创新峰会在北京召开。中关村科金公开企业级智能体落地 路线图，并发布覆盖企业全场景的"3+2+2"智能体产品矩阵，包括得助大模型平台5.0、得助智能客户平 台5.0、得助智能工作应用平台、得助金融智能体平台、得助工业智能体平台等一系列产品和解决方 案，助力企业快速开发智能体，用好智能体。 责任编辑：磐石 关键词阅读：智能体 大模型 中关村科金 ...

统一股份总经理，统一石化CEO 李嘉：我们做润滑油需要很多配方和原材料，一年产生几十万条数 据，我们把这些数据和配方全部放在自主研发的智能体里。这就不用那么多老工程师来做配方的开发。 原来我们开发一个配方可能1年，现在只要3个月就可以把它开发完成。 0:00 ...

10年以后的机器人比人还要多。 "10年以后的机器人比人还要多，未来的Saas和APP都会被智能体取代……"12月10日，清华大学智能产业研究院院长、中国工程院外籍院士张 亚勤在Meet2026智能未来大会上，一口气谈了他对于人工智能未来的多个趋势性洞见。 AI正在从信息世界走向物理世界和生物世界。他将这个过程描述为从大语言模型走向VLA（视觉-语言-动作）模型——不仅要理解文字和图 像，还要在真实世界中行动。其中无人驾驶在今年已到拐点，预计到2030年，约10%的新车将具备无人驾驶能力，那将是自动驾驶 的"DeepSeek时刻"。 机器人是张亚勤眼中"未来最大的赛道"。尽管人形机器人成熟尚需时日，但他认为十年内机器人的数量或将超过人类。但他同时也提醒，AI能 力的快速提升也伴随着风险的急剧增加。 基于对技术架构的前瞻，张亚勤展示了他绘制的演进图。在ChatGPT问世不久后他构想的架构中，基础大模型作为平台，之上支撑着各垂直领 域模型、SaaS服务层，最上层是各类应用APP。而在今年10月的更新中，他明确提出，未来的SaaS服务和终端APP都将被智能体所取代——智 能体即未来的软件与服务形态。这些智能体将涵盖 ...

来源：创投家 时代在向前。2025年被称为"智能体元年"，在年底，突然有一记重拳打来。 而多智能体协同架构带有自学习的专家智能体，比如可以规划行程、预订服务并提供返程提醒，这是智 能的第二阶段。 第三阶段是决策智能体，这个以后再说明白。 说回到这次"豆包手机助手"偷袭，就是在第二阶段的专家智能，是一次"智能体协同领域的一次超前实 验"。 对创业者来说，这意味着要找到新的变量、新的要素，将会涌现新的机会。所有的竞争，有时候不只是 竞争，而是激发大家找到新的方向。 因此，这场看似是"偷袭"，其实意味着一个新的时代机会的到来。或许，你看到的是竞争；但或许，换 个角度看，会让更多的可能性走在这条路上，带来的是良性的竞争。 今天，正在从旧战场，走向新战场。不要迷恋旧战场，一起走向一片看不见的新大陆。就像张一鸣说 的："往前看。" 最近，"豆包手机助手" 在朋友圈刷屏了，它像个藏在手机里的"万能小助理"，你动动嘴，它就能替你 操作不同的APP，把很多复杂的事情搞定。 可没想到，这"小助理"刚想大展身手，就碰了一鼻子灰。微信登录异常，支付宝付不了款，连美团、淘 宝都把它挡在外面——几乎半个互联网都拉响了警报。 这背后，是智 ...

Core Insights - The company "月之暗面" is regaining public attention with recent developments, including the launch of subscription services and preparations for an IPO, as highlighted by its president Zhang Yutong [1][5][11] - The company emphasizes its strategic focus on core technological innovations and productivity tasks, distancing itself from entertainment and homogeneous competition [1][8] Company Developments - Zhang Yutong presented the latest advancements in the Kimi model's performance and product offerings at a Tsinghua University event, marking a significant return to the spotlight after a year of scrutiny [1][5] - The company has launched a subscription model for Kimi For Coding and introduced the Kimi K2Thinking model, which supports real-time tool usage [1][10] - There are indications that the company is preparing for an IPO, with analysts suggesting that the current market conditions may favor such a move [5][11] Market Position and Strategy - 月之暗面 is noted for its low valuation compared to leading U.S. model companies, operating with less than 1% of their resources while still achieving significant technological advancements [2] - The company aims to overcome data limitations rather than computational power, achieving efficiency improvements with the Kimi K2 model [4] - The focus is on niche areas such as complex task management and productivity, rather than competing directly with larger players in the entertainment sector [8][9] User Engagement and Performance - Kimi has approximately 9.67 million monthly active users, ranking fifth among native AI applications, while competitors like Doubao and DeepSeek have significantly higher user bases [7] - The company has shifted its strategy away from user scale competition, focusing instead on its unique strengths in technology and product offerings [8] Commercialization and Partnerships - 月之暗面 is pursuing a direct commercialization strategy for its consumer offerings, particularly in computationally intensive tasks, while maintaining free access for basic interactions [9][10] - The company has secured partnerships with notable platforms, integrating its Kimi K2 model into various applications, indicating a strong position in the B2B market [10]

Core Insights - The "EVOLVE2025" summit highlighted the launch of a comprehensive enterprise-level intelligent agent roadmap by Zhongguancun KJ, featuring a "3+2+2" product matrix that includes three foundational platforms and two application platforms, aimed at accelerating the large-scale implementation of intelligent agents in various industries [1][2] Group 1: Intelligent Agent Development - The development of large models is rooted in the accumulation of smaller models and data modeling, emphasizing the need for data to be transformed into knowledge through the discovery of hidden patterns [1][2] - Intelligent agents integrate core capabilities such as perception, understanding, decision-making, and control, serving as key vehicles for technology implementation [1][2] - The evolution of intelligent agents is supported by foundational algorithms like deep learning and reinforcement learning, with a focus on enhancing efficiency through collaborative deployment across cloud, edge, and endpoint [1][2] Group 2: Industry Trends and Challenges - The need for precision and lightweight models in large model deployment is critical, with techniques like model distillation helping to reduce computational requirements [2] - There are technical risks such as "hallucinations" in natural language understanding, particularly in accurately grasping Chinese semantics, which remain a long-term challenge [2] - The future direction involves transitioning large models and intelligent agents from general-purpose to specialized applications tailored to specific industries and product scenarios [2] Group 3: AI Agent as a Central Hub - AI intelligent agents are seen as the central brain for enterprises, addressing issues like data silos and process fragmentation by connecting key elements such as people, resources, and systems [3] - Each connection made by intelligent agents generates new interaction data, which in turn iterates the model itself, leading to increased intelligence and value creation for enterprises [3] - The evolution from the internet to mobile internet and now to artificial intelligence represents an evolution of connectivity, with intelligent agents acting as super connectors within and outside organizations [2][3]