2025-12-15 16:50发布于北京腾讯新闻《深网》栏目官方账号 此次再出发，李笛集结了昔日核心班底：Nextie的联合创始人包括小冰原联合创始人、前微软首席研发总监曾敏，以及小冰大模型与算 法负责人、前英特尔架构师王文斓。公司已获得奇绩创坛的初始投资。 深网 文丨薛芳 编辑丨张睿 出品丨深网·腾讯新闻小满工作室 2025年12月7日，北京中关村国际创新中心内，奇绩创坛秋季创业营路演日正在进行。室外冬日的寒风已经开始变得凛冽，室内年轻的 AI创业者们热情似火。 在每个项目两分钟的展示环节里：有清华在读博士的"AI饭搭子"，有关注心理健康的"AI学习伴侣"，也有前微信AI产品经理自主研发 的"AI视频创作智能体平台"……演示精彩处，台下不时爆发出笑声与掌声。 下午四点半，微软"小冰之父"李笛作为压轴嘉宾登台。此刻，他的身份是"创业营54号项目——"明日新程"（英文名：Nextie，寓意下一 程）"的创始人。当日路演的53个项目中，有3个项目由李笛指导，实际是驻场企业家。 李笛站在舞台中央，他将Nextie定义为"一个基于群体智能与认知模型的多智能体框架"。这是自今年4月他离开自己创立的小冰公司后， 首次以 ...

根据蘑星AI的最新研究报告，2023年至2025年，AI软件应用将全面进入"L3认知型智能体"时代。这一阶段的智能体不再是简单的自动化脚本或对话程序， 而是融合了大规模预训练模型与深厚领域知识的"数字专家"，正在深刻重塑各行各业的竞争力格局。 Midjourney为代表的内容创作工具，已使超50%的年轻职场人将AI作为日常生产力倍增器。 报告分析认为，这一转变意味着企业间的竞争维度正被重新定义。拥有领先的AI认知能力，即能够更高效地训练和利用专属"数字专家"的企业，将在产品创 新、客户服务、运营效率等方面建立新的壁垒。能否成功跨越到L3阶段，并实现智能体与组织、业务流程的深度融合，已成为区分行业领导者与跟随者的 关键标尺。未来两年，将是各行业构建自身"认知智能"护城河的黄金窗口期。 在企业运营层面，认知型智能体已渗透至核心价值链。例如，腾讯云智能体平台能够辅助开发者，将代码编写效率提升高达40%；京东的供应链智能体可进 行动态优化决策；360安全智能体将威胁检测的准确率提升了20%。这些"数字员工"正将AI从后台支持角色推向业务前线。在个人应用领域，以Notion AI、 ...

在信息爆炸与消费者偏好瞬息万变的商业环境中，供应链选品正面临着前所未有的复杂性挑战。传统选品依赖人工经验，易受主观局限且效率低下；纯算法 驱动的AI选品虽能处理海量数据，却可能陷入"数据黑箱"，错失新兴趋势与人文洞察。朗尊电商（Legendshop）创新性地将 P2S2C双层漏斗模型 与 AI人工 推荐 深度融合，打造了一种兼具科学性、精准性与人性化的 专利选品模式。该模式并非简单的"人机分工"，而是构建了一个"算法洞察+专家判断+市场反 馈"的 双脑协同智能选品系统，其核心在于通过 双重筛选机制，从海量商品中实现与细分市场需求的精确匹配。本文旨在深度解析这一创新模式如何重构供 应链选品流程，如何将"人找货"升维为"货找人+人慧选"的 供需双向精准匹配 闭环，从而在私域电商、企业福利等场景中创造独特的竞争优势与客户价值。 一、选品困局：从经验依赖到数据迷失的演进与突围 经验主义的"窄巷"与数据主义的"迷雾" 传统选品模式根植于采购经理或买手的个人经验与市场直觉。他们凭借对行业的深度理解、人脉网络和过往成功案 例进行决策，这种模式在面对熟悉的、稳定的市场时可能高效。然而，其弊端日益凸显：选品范围受限于个人视野， ...

Core Insights - The integration of intelligent driving technology is reshaping lifestyles at an unprecedented pace, driven by advancements in artificial intelligence and a unique market environment in China [1][3] - The Chinese intelligent driving industry is transitioning from a phase of rapid growth to one of high-quality development, with regulatory frameworks being strengthened alongside pilot programs for higher-level autonomous driving [3][4] - The rapid adoption of electric vehicles is providing an optimal platform for intelligent driving technologies, creating a virtuous cycle between electrification and intelligence [4][6] Industry Trends - The emergence of cognitive intelligence technologies is transforming intelligent driving from a rule-based tool to a cognitive-driven entity, with new architectures like end-to-end and VLA opening new possibilities for high-level autonomous driving [3][5] - The intelligent driving sector is witnessing a clear focus on L4-level scenario-based applications, with significant investments directed towards areas like unmanned delivery and logistics [6][7] - Key components of the supply chain, such as sensor manufacturers and chip companies, are receiving substantial funding, highlighting their foundational role in the development of autonomous driving [7] Regulatory Environment - The regulatory landscape is evolving, with policies being introduced to facilitate the testing and commercialization of L3-level and above autonomous driving technologies in multiple cities [3][4] - The dual approach of relaxing pilot programs while simultaneously enhancing regulatory frameworks is creating clearer competitive advantages for companies with core competencies [3][4] Investment Landscape - Investment activities in the intelligent driving sector are increasingly concentrated in later-stage financing, indicating a shift from technology validation to large-scale commercial applications [7] - Traditional automotive companies are actively participating in investments to address technological gaps, while collaborations within the supply chain are emerging to build ecological advantages [7] Future Outlook - The competition in intelligent driving is entering a new phase where success will depend on the ability to integrate technology, compliance, and commercialization effectively [9] - The industry is at a historical turning point, with the potential for new industry giants to emerge from the convergence of technology, policy, and market dynamics [8][9]

Core Insights - The establishment of Jiadu Technology Group's headquarters in Changsha's Dazeh Lake Overseas Returnee Town marks a significant step in the company's strategy to enhance its presence in the central region of China and respond to national development strategies [2][3] - Jiadu Technology aims to leverage its new headquarters to foster innovation in cognitive intelligence and other advanced technologies, contributing to the digital economy and smart city initiatives in Hunan province [2][3] Group 1: Company Development - Jiadu Technology Group is setting up "one headquarters and three centers" in Dazeh Lake, which includes the South Central Regional Headquarters, a second R&D center, a regional delivery center, and a digital transformation operation center [1] - The company has already established a research team of over 100 personnel dedicated to cognitive intelligence and other cutting-edge fields [2] Group 2: Strategic Importance - The location in Dazeh Lake is chosen for its advantageous geographical conditions, complete industrial ecosystem, and excellent business environment, which are crucial for attracting high-end talent and fostering partnerships with local educational and research institutions [2] - Jiadu Technology's collaboration with local partners, such as the Changsha Rail Transit Group, has led to the successful implementation of smart metro lines, showcasing the company's leadership in the smart rail transit sector [1] Group 3: Innovation and Technology - The company showcased its technological achievements in areas such as smart rail transit, smart city governance, and AI large models during the innovation results exhibition [3] - Jiadu Technology is committed to increasing R&D investment and scaling the application of innovative technologies in smart transportation and city governance, aiming to support the intelligent upgrade of regional industries [3]

Core Viewpoint - The article discusses the launch of three key products by Lingxin, integrating AI with psychological services aimed at students and teachers, marking a significant step towards promoting mental health education in schools [2][3][9]. Product Overview - Lingxin has introduced the AI Psychological Assessment System, AI Dual-Teacher Interactive Psychology Course, and Lingxin Mental Health Space, along with an upgrade to the Emohaa psychological model [2][3]. - The AI Psychological Assessment System utilizes a "gentle" dialogue approach to conduct multi-modal assessments of personality, emotions, and behaviors, addressing traditional assessment challenges [2]. - The AI Dual-Teacher Interactive Psychology Course is designed for middle and primary school students, featuring an AI teacher and real-time content analysis to enhance classroom experiences [3]. - Lingxin Mental Health Space has been implemented in over a hundred schools across China, providing emotional support and real-time analysis for teachers and parents [3]. Technological Support - The Emohaa model, developed by Lingxin, has been upgraded to include features such as emotional companionship and light intervention, covering various psychological topics [5][6]. - Emohaa has achieved high ratings in emotional understanding and support compared to leading global models, indicating its effectiveness in psychological counseling [6]. Market Context - The article highlights the growing need for mental health services in China, with approximately 170 million people suffering from mental illnesses and a significant shortage of psychological professionals [11]. - The market for AI in mental health is expected to grow significantly, driven by demographic changes and technological advancements, despite current challenges in service standardization and stigma [11][14]. AI's Role in Mental Health - AI is poised to transform traditional psychological counseling and psychiatric treatment, promoting equity in mental health services [9][14]. - The development of large models in emotional intelligence is seen as a key opportunity for enhancing accessibility to psychological support, especially in underserved areas [14]. Challenges and Future Directions - The application of AI in psychology faces challenges due to the complexity and individuality of mental health issues, necessitating a comprehensive understanding of various factors [18]. - Lingxin aims to provide accessible mental health services through AI, including 24/7 online consultations and personalized support systems [18].

Core Insights - Shanghai Pudong New Area is focusing on three leading industries, with artificial intelligence (AI) being one of them, projected to account for approximately 40% of Shanghai's AI industry by 2024, amounting to 163.7 billion yuan [1][3] Industry Development - The AI industry in Pudong is accelerating its "empowerment applications," establishing the first national-local co-built humanoid robot innovation center, and gathering over 200 upstream and downstream companies in key parks like Zhangjiang Robot Valley [3][4] - Zhangjiang has developed an "AI Town," which includes the AI Island, aiming to create a highland for the AI industry, featuring the first "5G+AI" commercial demonstration park in China [4][6] Ecosystem and Collaboration - The AI Island has attracted major multinational corporations such as Infineon and IBM, as well as leading AI companies like Alibaba and Baidu, creating a best practice area that integrates production, education, research, and application [6][7] - By 2025, the park aims to continue attracting leading enterprises and key players in AI, enhancing industry clustering effects and promoting deep applications of AI technology across various fields [7][9] Application and Innovation - Pudong has over 1,500 industrial enterprises, 800 integrated circuit companies, and 3,900 biomedical firms, providing a vast landscape for vertical model applications and technology validation [9][12] - The establishment of the MoLi Community has attracted nearly 200 related companies, fostering a unique ecosystem where entrepreneurs support each other [7][9] Investment and Funding - The L Hub in Zhangjiang has introduced 15 leading investment institutions and funds, focusing on integrated circuits, biomedicine, and AI, highlighting a distinctive characteristic of industry investment aggregation [8][9] Case Studies and Success Stories - HuaYuan Computing, a key player in AI algorithm technology, has developed a cognitive intelligence engine platform with over 60,000 models and capabilities to support 700 billion parameter pre-training [12] - LianRen Health has successfully reduced prescription error rates by 40% through the application of AI in 30 hospitals, showcasing the practical impact of AI technology in healthcare [12]

Group 1 - Shanghai is positioned as a major hub for artificial intelligence development, emphasizing the integration of AI with traditional and emerging industries [1] - The World Artificial Intelligence Conference (WAIC2025) highlighted the strategic commitment of Shanghai to expand AI application scenarios [1] - The Cognitive Intelligence Innovation Forum focused on three core areas: cognitive reasoning, autonomous decision-making, and causal learning, providing diverse perspectives for technological breakthroughs [1] Group 2 - Professor Dong Bin from Peking University identified the bottleneck in mathematical research as theoretical verification and theorem proving, suggesting AI tools can offer innovative solutions [2] - A proposed research path includes the development of customized large language models for mathematics and the digitalization of key reasoning steps to enhance collaboration between humans and AI [2] - Professor Yang Hongxia from Hong Kong Polytechnic University discussed the challenges of deploying large models in vertical industries and the trend towards decentralized AI development [2][3] Group 3 - The ultimate goal of generative AI is to achieve deep integration with robotics, requiring over a decade of data accumulation and technological development [3] - The focus of current industry development is on democratizing technology to lower barriers and encourage expert participation in building vertical models [3] - The founder of Huayuan Computing, Xuan Xiaohua, stated that AI technology is transitioning from laboratory research to industrial application, emphasizing the importance of independent innovation [3] Group 4 - The Huayuan Intelligent Agent Platform features three core characteristics: orchestration planning, tool invocation, and short/long-term memory [4] - The platform allows users to create intelligent assistants and automated processes through a visual orchestration system, significantly lowering the technical barrier for AI usage [4][5] - This platform addresses the challenges of long development cycles and high technical barriers in traditional AI systems, facilitating rapid digital transformation across industries [5]

Core Viewpoint - Intelligent automotive technology is a key solution for traffic safety, which remains a perpetual theme in the development of smart vehicles [1] Group 1: Current State of Intelligent Vehicles - Low-level intelligent vehicles have achieved a high market penetration rate, but accidents still occur as the industry transitions to higher levels of autonomous driving [1] - There are significant challenges in safety technology that need to be addressed in the context of complex long-tail scenarios [1] Group 2: Technological Approaches - The early development of intelligent vehicles relied on rule-driven approaches, while current mainstream autonomous driving methods include data-driven techniques [4] - Rule-driven systems are observable and interpretable but are inflexible in complex environments, whereas data-driven systems utilize deep learning but suffer from a "black box" nature that obscures decision-making processes [4] - A proposed third route, "cognitive-driven," aims to combine the interpretability of rule-driven systems with the learning capabilities of data-driven systems, enhancing adaptability and transparency [4][5] Group 3: Cognitive-Driven Architecture - The cognitive-driven approach is based on a deep understanding of the interactions between humans, vehicles, and roads, leading to accurate modeling and digital representation of system characteristics [5] - The architecture consists of three layers: perception, cognition, and decision-making, integrating physical state estimation, semantic understanding, and human-like adaptive decision generation [5][6] Group 4: Future Trends and Goals - The evolution of autonomous driving is shifting from rule-driven and data-driven methods to cognitive-driven systems, focusing on human-like cognition, learning, and evolution [5] - A new paradigm of "self-learning + prior knowledge" is necessary to enhance environmental understanding and reasoning capabilities, improving safety and generalization in long-tail scenarios [5] - The ultimate goal is to develop a high-level intelligent driving system that possesses self-learning, self-reflection, and adaptive capabilities, ensuring safety and verifiability [6]

Investment Rating - The investment rating for Kingsoft Office (688111.SH) is maintained at "Buy" [1] Core Views - The company's performance exceeded expectations, leading to an upward adjustment in the net profit forecast for 2024-2026 to 1.645 billion, 2.064 billion, and 2.542 billion yuan respectively, with corresponding EPS of 3.56, 4.46, and 5.50 yuan per share [4][5] - The growth is attributed to the robust performance of core business revenues, improved operational efficiency, and increased investment income [5] - The integration of WPS AI with Deepseek marks a shift from "assistive tools" to "cognitive partners" in smart office tools, enhancing user engagement and conversion rates [6] Financial Summary and Valuation Metrics - The company is expected to achieve a total revenue of 5.121 billion yuan in 2024, representing a year-on-year growth of 12.4% [5] - The projected net profit for 2024 is 1.645 billion yuan, with a year-on-year increase of 24.8% [5] - The gross margin is expected to remain stable around 85%, while the net margin is projected to increase to 32.1% in 2024 [8] - The P/E ratios for 2024, 2025, and 2026 are forecasted at 97.3, 77.6, and 63.0 respectively [8]