分析师 1: 好的。各位投资的朋友，大家晚上好，我是方安策略首席袁道宇。我们这个整个策论中关 第一期，我们是很荣幸的邀请到我们这个传媒和互联网首席焦娟来给大家讲一讲这个，聊 一聊 AI 应用，因为我们看到，其实从年初以来。整个 AI 应用板块表现还是挺好的，包括 像一些细分的像传媒在今年应该是领涨的，在所有一级行业领涨的。那么这个 AI 应用这 块，包括可能涉及到港股，包括港股互联网，还有这个 A 股的一些具体的一些细分板块的 这个催化也好，包括后面这个行情的节奏，包括排序这块我们今天都会聊到。 那我们现在就这个正式开始，就是我先，就是请教那个焦老师第一个问题，因为我是，就 是从策略角度来说，我注意到就可能从 23 年 ChatGPT 出现以来，其实 AI 应用基本上好 像每年春节前后都会有一波行情。这个包括今年也不例外，就是这个背后的原因。主要是 有哪些？那个姜老师 分析师 2: 好的，我这边的话总结了三个比较深刻的原因，正好借着袁老师的这个场子，跟大家汇报 一下。确实，我自己非常长足的进步，也是从 2023 年，尤其是 23 年 ChatGPT 出来之后， 我自己这边基本上把这个研究架构都搭得差不多。然后 ...

Consumer Sector - Major companies are accelerating their C-end AI initiatives, with significant marketing investments exceeding 4.5 billion CNY from Tencent, ByteDance, and Baidu for the Spring Festival[4] - The top three AI applications have achieved over 100 million monthly active users (MAU): Doubao (approximately 320 million), Deepseek (approximately 150 million), and Qianwen (approximately 100 million) as of January 2026[7] High-end Manufacturing - Elon Musk announced plans to build 200 GW of solar capacity in the U.S. within three years, focusing on space-based solar energy, but the short-term impact on the photovoltaic industry remains limited[14] - Major photovoltaic companies are projected to incur significant losses in 2025, with Longi Green Energy, Tongwei Co., and TCL Zhonghuan each expected to lose over 6 billion CNY[17] Hard Technology - The electronic supply chain is experiencing a divergence in performance, with upstream companies like Western Digital and Seagate reporting better-than-expected earnings due to AI-driven demand, while downstream sectors face cost pressures[19] - Global smartphone SoC shipments are expected to decline by 7% in 2026, with low-end models under the most pressure[22] Health Sector - The CXO and research upstream sectors are showing signs of recovery, with notable profit growth expected for leading companies: WuXi AppTec's net profit is projected to increase by 102.65% to 19.15 billion CNY in 2025[26] - Global biopharmaceutical financing data is expected to show a 2.7% increase in 2025, with China's growth rate at 6.4%[28]

●于海斌 现代人工智能是先进计算的产物，也是赋能千行百业的技术。从早期符号主义在有限算力下的踯躅前 行，到神经网络思想历经沉浮，直至大数据与图形处理器（GPU）的邂逅，引爆了深度学习的革命，使 复杂模式识别与认知成为可能；再到今天，支撑起超大规模模型训练的已是千亿乃至万亿参数级别的并 行计算集群和高速互联网络。正是这样一场波澜壮阔的计算进化，将人工智能从实验室推向了产业应 用，成为一股赋能千行百业、重塑社会的颠覆性力量。 对智能的向往从未停止 人类对于智能的向往并非源自现代，而是深植于数千年的文明积淀之中。当远古的先民发出第一个有意 义的音节，创造出能够指代事物、表达意图、传递复杂信息的符号系统，存在于个人大脑中的思维便获 得了在群体间流通的载体，语言成为人类智能的第一次伟大迸发。结绳记事、刻画符号，直至体系化的 文字出现，人类首次突破了大脑记忆的时空限制，将思想、律法、天文观测、生产工艺等宝贵信息固化 于泥土、金石与竹简之上，树起了一座人类"智能存储"的里程碑。从打磨第一件石器开始，人类就走上 了一条通过创造"智能实体"来放大自身能力之路，随着车轮、指南针、火药、蒸汽机等的发明，人类始 终渴望通过制造工具和 ...

Summary of Kimi K 2.5 Model Conference Call Company and Industry Overview - The conference call discusses the Kimi K 2.5 model, a significant advancement in the field of Artificial General Intelligence (AGI) in China, which is considered to be on par with international leaders like Google's Gemini 3 [1][2][3][7]. Key Points and Arguments Model Features and Performance - Kimi K 2.5 is described as the most comprehensive and powerful version to date, featuring multi-modal input and output capabilities, front-end generation, and an intelligent agent collaboration system [1][3][4]. - The model's multi-modal capabilities allow it to process and integrate various types of data, which is a standout feature compared to competitors [5][9]. - Despite its strengths, Kimi K 2.5 has limitations in speed and precision, particularly in complex 3D library and hardware control tasks, where it lags behind Gemini 3 [11][12][14]. Market Reception - The release of Kimi K 2.5 has garnered significant attention from market professionals and investors, being hailed as a "national treasure" in the AGI field for 2026 [2]. Comparison with Competitors - Kimi K 2.5's performance in front-end generation is slower than Gemini 3, taking approximately 7.5 minutes for tasks that Gemini can complete in about 10 minutes [11]. - In terms of data processing, Deepseek provides transparency in data sources but lacks the depth and professionalism of reports generated by Gemini 3 [10]. Development and Training - The model utilizes end-to-end training to achieve its multi-modal capabilities, which are superior to other models and are open-source, enhancing transparency and replicability [4][16]. - Kimi K 2.5 has refined its product settings to better understand user intent and improve task completion rates by differentiating between various task types [8]. Challenges and Limitations - The intelligent agent collaboration system, while powerful, incurs high costs due to resource usage, making it more of a technical showcase than a practical productivity tool [6][18]. - Kimi faces challenges in promoting products directly to end-users, lacking offerings comparable to consumer-focused products from major companies like Microsoft [19]. Future Considerations - There is potential for cost reduction in multi-agent systems through optimization of fixed processes, which could enhance efficiency and lower overall costs for users [21][22]. Additional Important Insights - The domestic AGI development is only about two months behind international leaders, indicating a competitive landscape [7]. - Kimi K 2.5's ability to handle large files and multiple inputs simultaneously is a significant advantage, allowing for more complex and user-aligned outputs [13]. - The model's interaction capabilities are still in the early stages compared to Gemini 3, which has explored more advanced interaction methods [17]. - The perceived decrease in text processing capabilities is attributed to an increase in video data weight, rather than an actual decline in text processing ability [20].

Core Insights - Hangzhou aims to become the leading city in artificial intelligence innovation by 2026, with a focus on differentiated development and unique characteristics in AI [2][3] - The city has made significant progress in AI elements such as computing power, data, and models, establishing a strong foundation for future growth [3][5] - Hangzhou's government is committed to transforming its economy from a platform-based model to an AI-driven model during the 14th Five-Year Plan period [5][7] Group 1: Development Goals - The city plans to support the iteration and upgrade of major AI models like Alibaba's Qianwen and DeepSeek, and aims to create an international first-class open-source community [5][7] - By 2030, Hangzhou targets to cultivate over three internationally top-level open-source foundational models and achieve over 600 billion yuan in revenue from the core AI industry [7] Group 2: Legislative and Institutional Support - Hangzhou has introduced local regulations to promote the development of embodied intelligent robots, marking a significant step in institutional innovation for AI [3][5] - The government emphasizes the importance of creating systems for data governance, legal frameworks, and international cooperation to support AI development [3] Group 3: Community and Ecosystem Engagement - The city is actively engaging with enterprises by providing support for research and development through initiatives like computing power vouchers and legislative guarantees for embodied intelligence [5][8] - Hangzhou is also focusing on enhancing educational opportunities in AI for the elderly, reflecting its commitment to inclusive growth and community engagement [8]

Core Insights - The year 2025 marked a significant surge in China's artificial intelligence (AI) industry, with over 6,000 AI companies expected and a core industry scale projected to exceed 1.2 trillion yuan [2][10] - The Ministry of Industry and Information Technology (MIIT) emphasized the integration of technological and industrial innovation, positioning AI as a strong driver for industrial economic growth [2][10] Industry Development - The MIIT plans to accelerate high-quality development in the AI sector, focusing on technological innovation, application integration, enterprise cultivation, ecosystem construction, and safety governance [11] - The AI chip industry is experiencing a boom, with several stocks reaching their daily limit up as of January 21 [11] AI in Manufacturing - The Chinese government aims to achieve deep integration of AI with six key sectors by 2027, with a target application penetration rate of over 70% for new-generation smart terminals and intelligent agents [12] - By 2025, the smart computing power in the industry reached 1,590 EFLOPS, and over 178 million AI glasses were shipped in the first three quarters of 2025, with nearly 80% being AI glasses [12] Smart Manufacturing - China has cultivated 15 leading smart factories, with AI penetrating over 70% of their business scenarios, leading to the development of over 6,000 vertical models and the application of more than 1,700 key smart manufacturing equipment and industrial software [13] - The MIIT plans to continue implementing smart manufacturing projects and support leading enterprises in exploring future manufacturing models [13] Humanoid Robots - The humanoid robot sector is experiencing rapid growth, with a market expected to reach 100 billion yuan by 2030, and over 140 companies producing humanoid robots with more than 330 products launched in 2025 [14] - The year 2025 is recognized as the year of mass production for humanoid robots, with advancements in technology and product quality being prioritized [14] Employment Concerns - The MIIT acknowledges that technological advancements may lead to job restructuring but emphasizes that this does not equate to job loss, advocating for the development of a workforce skilled in both AI and manufacturing [15][16]

中新网杭州1月21日电(记者 王逸飞)21日的杭州市十四届人大六次会议上，杭州市市长姚高员作政府工 作报告时介绍，"十四五"时期杭州累计引进35周岁以下大学生超200万名。 人才是城市发展的重要资源。刚刚过去的2025年，杭州实现全职引进诺贝尔奖获得者"零"的突破，新引 进35周岁以下大学生42.9万名，连续15年入选"外籍人才眼中最具吸引力的中国城市"。 一"青荷驿站"。富阳区融媒体中心供图 在营商环境方面，杭州"无事不扰、有求必应"营商环境品牌持续擦亮，经营主体数量突破200万户。在 人才服务环境方面，去年，该市"企业认定、政府认账"累计授权企业2752家、认定人才4.3万名；新 增"青荷驿站"房源964套(间)，为外地年轻人来杭就业提供免费短期住宿。 聚焦"十五五"，杭州市政府工作报告提出，将推进青年发展型城市建设，实施更加积极开放的人才政 策，让杭州成为中外人才眼中最具吸引力的城市。 作为新一线城市的杭州被誉为"创新活力之城"。数字经济的底蕴、活力，以及人工智能等未来产业的先 发优势，是该市能够持续汇聚年轻人才的重要原因。 去年，杭州GDP达到23011亿元，数字经济核心产业增加值增长9%以上。在人工 ...

Summary of AI-Driven Drug Development Conference Call Industry Overview - The conference call focuses on the application of Artificial Intelligence (AI) in the pharmaceutical industry, particularly in drug discovery and development processes [1][2][3]. Core Insights and Arguments - **AI Enhancements in Drug Development**: AI significantly improves the efficiency and success rates of drug development processes, traditionally characterized by lengthy and costly stages [2][3]. For instance, AlphaFold enhances protein structure prediction speed and accuracy, accelerating target discovery [2]. - **AI vs. Traditional Methods**: Unlike traditional Computer-Aided Drug Design (CADD), which relies on physical rules, AI-driven drug discovery (AIDD) utilizes vast datasets for direct predictions, bypassing complex physical computations [3][4]. - **Evaluation of AI Capabilities**: To assess a company's AI capabilities in drug development, it is crucial to examine the use of advanced algorithms like deep learning, the quality of data, successful case studies, and ongoing innovation [5][6]. - **Specific Applications of AI**: AI applications in pharmaceuticals include generating drug structures, gene diagnostics, and automating tasks like report writing through large models (e.g., ChatGPT) and smaller, specialized models [7][8]. Important but Overlooked Content - **Graph Neural Networks (GNN)**: GNNs are effective for small molecule structure data but struggle with complex molecules due to increased computational demands [9][13]. The need for new encoders to represent complex small molecules is emphasized [14]. - **Multimodal Learning**: This approach integrates various data types (images, text, fingerprints) to enhance drug development efficiency, as demonstrated in KRAS target research [15]. - **Market Trends**: Current AIDD companies exhibit diverse technical characteristics, with some focusing on generative adversarial networks (GANs) and others on traditional CADD while incorporating deep learning [16]. The future of AI in pharmaceuticals is expected to involve more complex small molecule designs and stricter confidentiality to protect technological advantages [17]. - **Agent Applications**: The use of intelligent agents in workflow design is emerging, allowing for autonomous process design and execution, which can significantly enhance efficiency [20]. Future Trends - The pharmaceutical industry is likely to see a rise in the complexity of small molecule designs, the mainstreaming of multimodal fusion technologies, and the emergence of new encoders and deep learning algorithms to meet evolving demands [17][18].

文 任泽平 2026 年 1 月初，我和泽平宏观商学的企业家游学美国，逛了两天 CES ，人山人海，听了黄仁勋、苏姿丰、杨元庆的开幕式演讲，参访了特斯拉、英伟 达、谷歌、斯坦福以及美国创投机构。 如果用一个词来形容，就是震撼！ AI 正在快速改变世界，奇点时刻到来！ 整好赶上马斯克的三小时访谈刷屏： 我们正处于奇点之中，这是一场超音速海啸， 2026 年 AI 智力超越最聪明的人类个体。 巴菲特在 2025 年 5 月的访谈中提到：" AI 的危险不亚于核武器"， AI" 既有巨大的潜力造福人类，也有巨大的潜力造成危 害 " 。随后股神抛售了苹果， 大手笔买入谷歌。 在火爆的CES和硅谷，我看到了未来的AI世界。 一、 AI 的进步太快了，快速改变世界：她来了！她来了！她真的来了！ 在 CES 展，毫无疑问只有一个主题，就是 AI ， CES 展完全变成了 AI 展 ，太火爆了。最火爆的赛道都与 AI 有关，机器人、自动驾驶的展位人山人海。 我们看到机器人进步神速，翻跟斗，打拳击，端盘子，折纸， 360 度自动旋转身体。马斯克放出豪言， 3 年内 Optimus 机器人手术水平超越全球顶尖医 生。据内部见过 ...

Core Insights - The article discusses the evolving perception of human creativity in the age of AI, where human creators increasingly face skepticism about the authenticity of their work, often being accused of producing AI-generated content [1][2][4] - It highlights a shift from a default assumption that creative works are human-generated to a presumption of guilt, where creators must prove their humanity and originality [1][4][5] Group 1: The Impact of AI on Human Creativity - The emergence of AI has led to a situation where human creators are frequently questioned about the authenticity of their work, with accusations often stemming from overly structured or polished content [1][2] - This skepticism reflects a broader societal issue where trust in content has eroded, leading to a "guilty until proven innocent" mentality regarding authorship [2][4] - The article emphasizes that accusations of AI authorship can undermine a creator's time, subjectivity, and presence, reducing their work to mere noise rather than a personal expression [4][5] Group 2: The Dual Standards in Content Creation - The article points out a double standard where high-quality AI-generated content is often overlooked, while well-crafted human work is scrutinized for AI-like qualities [5][6] - It notes that the proliferation of low-quality AI content has created a public perception that AI outputs are either poor or overly polished, leaving little room for human creativity [5][6] Group 3: The Concept of Authenticity in Creation - The discussion raises questions about the relevance of "authenticity" in creative work, suggesting that as AI becomes more adept at mimicking human imperfections, the notion of what constitutes genuine creativity may need reevaluation [6][7] - The article argues that the focus should shift from who created the work to the real-world issues the work addresses, emphasizing the importance of the relationship between the creator and the audience [10][11] Group 4: The Economic Implications of AI in Creative Fields - The article discusses the concept of "humanity tax," where creators who rely on AI face increased pressure to produce more content at a higher quality, often at the expense of their creative integrity [16][18] - It highlights that the introduction of AI in creative processes has led to a new set of expectations and standards, pushing creators to adapt or risk obsolescence [18][20] Group 5: Redefining the Role of Creators - The article proposes a redefinition of the creator's role in the AI era, suggesting a shift towards recognizing "mixed subjects" that combine human and AI contributions [21][22] - It emphasizes the need for a new understanding of creativity that values the questions posed by creators rather than just the execution of content [22][23] - The article calls for a cultural shift away from questioning authorship towards evaluating the problem-solving capacity of creative works [22][25]