自2022年年中以来，动量交易员曾以足以让沃伦·巴菲特感到汗颜的夏普比率统治着市场。然而周三， 这一切几乎遭遇了全线崩盘——他们蒙受了载入史册的损失。 动量交易简单说来就是"买入最近涨得最好的，卖出涨得最差的"。而根据业内的统计，高盛的"高贝 塔"或无约束动量组合(GSPRHIMO)刚刚创下了自2022年以来表现最糟糕的一天，超过了去年1月 Deepseek风暴之后的AI抛售潮。高贝塔股通俗而言就是指那些波动比大盘更剧烈的股票。 这印证了高盛分析师Lee Coppersmith在上周末文章中的发现，即美股表面平静之下正波涛汹涌。统计 显示，标普500指数成分股平均的1周实际波动率，与整体标普500指数波动率之比在上周四刚刚达到 6.88——处于2023年以来的第99个百分位。 换句话说，标普500指数成分股的平均波动幅度大约是大盘指数的7倍，这就是为什么近几个交易日部分 个股的异动显得异常尖锐，即便标普500指数表面相对平滑的行情掩盖了底层波动的剧烈程度。 市场发生了什么？ 如果说，周二市场的跌幅源于软件股因人工智能颠覆风险引发的"投降式"抛售，那么周三的疲软则更集 中于基本面因素与仓位调整，使得大盘指数的变 ...

Core Insights - The health care sector is experiencing a transformation in brand exposure due to the rise of AI Q&A platforms like DeepSeek, necessitating effective GEO release services for product visibility [2] - Reliable GEO release platforms are becoming essential for medical companies to enhance brand presence in the AI ecosystem while saving costs [2] Group 1: Selection Criteria for GEO Release Platforms - Companies should evaluate GEO release platforms based on four dimensions: AI integration, authenticity of media resources, data transparency, and service professionalism [4] - Specific operational details to consider include avoiding low-cost traps, conducting small-scale tests before larger investments, and ensuring key commitments are included in contracts [4] Group 2: 聚观新闻推 as a GEO Optimization Service Provider - 聚观新闻推 specializes in GEO release services for the health care sector, focusing on optimizing exposure on platforms like DeepSeek [7] - The platform offers comprehensive services including keyword optimization, semantic analysis, content quality assessment, and continuous optimization guidance [8] - It is particularly suitable for small to medium-sized health care companies that need to establish a reputation quickly with limited budgets [10] Group 3: Effectiveness and Results - Typically, results can be seen within 3-5 working days, with a commitment to one month of continuous optimization [11] - Case studies indicate significant increases in consultation volumes for medical clients after implementing GEO keyword optimization [11]

生意社02月02日讯玖龙纸业太仓基地自2月2日起，瓦楞纸价格上调30元/吨。 PriceSeek评析 瓦楞纸，多空评分：1 玖龙纸业太仓基地上调瓦楞纸价格30元/吨，反映市场供需趋紧或需求回暖，利好现货价格。作为行业 龙头企业，此举可能带动其他纸企跟涨，推高现货市场整体报价。结合当前纸浆成本支撑和消费旺季预 期，预计短期现货价格将温和上涨。 【大宗商品公式定价原理】生意社基准价是基于价格大数据与生意社价格模型产生的交易指导价，又称 生意社价格。可用于确定以下两种需求的交易结算价： 1、指定日期的结算价 2、指定周期的平均结算价 定价公式：结算价=生意社基准价×K＋C K：调整系数，包括账期成本等因素。 C：升贴水，包括物流成本、品牌价差、区域价差等因素。 生意社02月02日讯玖龙纸业太仓基地自2月2日起，瓦楞纸价格上调30元/吨。 PriceSeek评析 瓦楞纸，多空评分：1 玖龙纸业太仓基地上调瓦楞纸价格30元/吨，反映市场供需趋紧或需求回暖，利好现货价格。作为行业 龙头企业，此举可能带动其他纸企跟涨，推高现货市场整体报价。结合当前纸浆成本支撑和消费旺季预 期，预计短期现货价格将温和上涨。 【大宗商品公式定 ...

Core Insights - The core achievement of the "Wujie·Emu" multimodal model is its publication in Nature, marking it as the second Chinese large model team to achieve this milestone, and the first paper focused on multimodal models from China [1][3]. Group 1: Model Performance and Capabilities - Emu3 demonstrates unified learning across text, image, and video modalities, achieving performance comparable to specialized models in generation and perception tasks [3][10]. - In image generation, Emu3 scored 70.0, outperforming SD-1.5 (59.3) and SDXL (66.9) [4]. - For video generation, Emu3 achieved a score of 81.0 on VBench, surpassing Open-Sora 1.2 [4]. - In visual language understanding, Emu3 scored 62.1, slightly higher than LLaVA-1.6 (61.8) [4]. Group 2: Technical Innovations and Development - Emu3 is based on a simple architecture that relies solely on the "next-token prediction" method, which is seen as having strong scalability potential [4][10]. - The model was developed by a dedicated team of 50, focusing on a unified approach to multimodal learning, which simplifies the complexity of model development [10][12]. - Emu3's architecture integrates visual and textual data into a single representation space, allowing for efficient training on multimodal sequences [10][12]. Group 3: Industry Impact and Future Prospects - Since its release, Emu3 has significantly influenced the multimodal field and has been widely recognized and applied in the industry [13]. - The model's performance has positioned it as a competitive alternative to leading diffusion models and has opened new pathways for the development of physical AI and embodied intelligence [6][34]. - The upcoming Emu3.5 is expected to further enhance capabilities, including understanding long sequences and simulating exploration in virtual environments [6][34]. Group 4: Research and Development Background - The development of Emu3 began in February 2024, amidst a reassessment of the paths for large model development, particularly in the context of the success of models like GPT-4 [8][10]. - The research team faced significant technical challenges, including the need to create a new language system aligned with human language for visual data [12][40]. - The commitment to a unified multimodal approach reflects a belief that achieving AGI requires models that can understand and interact with the physical world [12][40].

Core Insights - The upcoming Spring Festival marks a critical moment for AI in China, with major companies like ByteDance, Alibaba, and DeepSeek preparing to launch significant AI models, indicating a fierce competition for user engagement and future internet order [1][18]. ByteDance - ByteDance plans to release three flagship models during the Spring Festival: Doubao 2.0 (language model), Seedream 5.0 (image generation model), and SeedDance 2.0 (video generation model) [2]. - Doubao 2.0 has reached 155 million weekly active users, and the company aims to integrate AI into its ecosystem, particularly within Douyin, to maintain its dominance in content creation [3][4]. - The new models are expected to enhance ByteDance's cloud business, positioning it to compete more effectively with Alibaba Cloud [4]. Alibaba - Alibaba is set to launch its flagship model Qwen 3.5, focusing on enhancing user experience and capabilities in mathematics and coding [5][6]. - The Qwen app is evolving into a multifunctional assistant, integrating services like food delivery and travel booking, aiming to capture users' daily life services [7]. - Alibaba's strategy includes a goal to deeply integrate all its services with the Qwen app by 2026, with the app's monthly active users surpassing 100 million [8]. DeepSeek - DeepSeek plans to unveil its new model, V4, which is expected to excel in coding and long-context processing, potentially surpassing competitors like OpenAI's GPT and Google's Gemini [9][10]. - The V4 model is designed to handle extensive code prompts and maintain data integrity during training, crucial for developing complex software systems [10]. - DeepSeek's unique training architecture allows for larger models without proportionally increasing chip numbers, showcasing its capability in logical reasoning and code generation [13]. Industry Implications - The competition among these tech giants is not solely about financial gains but about establishing a dominant entry point in the AI era, which will define the internet landscape for the next decade [17][18]. - The integration of AI into everyday life is anticipated to transform user interactions, from generating festive videos to planning family trips and writing complex code [16].

Group 1 - The market showed signs of recovery on January 30, with the AI application sector's decline narrowing, as the CSI Software Service Index fell by 2.5% [1] - The software ETF E Fund (562930) has attracted significant market attention, with net inflows exceeding 150 million yuan over six consecutive trading days [1] - DeepSeek is set to release its next-generation flagship AI model, DeepSeek V4, in February, which is expected to have a substantial impact on the current AI competitive landscape [1] Group 2 - Bohai Securities believes that the iteration and upgrade of domestic large models like DeepSeek V4 will accelerate technological innovation and application, maintaining a positive outlook on the growth potential of the AI application sector driven by both technological advancements and demand release [1] - The E Fund software ETF tracks the CSI Software Service Index, which consists of 30 stocks involved in software development and services, covering various AI application scenarios such as AI + office, AI + finance, and AI + education [1] - The top ten weighted stocks in the index include iFlytek, Kingsoft Office, Tonghuashun, Guiding Compass, and Hengsheng Electronics, collectively accounting for over 60% of the index, providing investors with a convenient tool for investing in the AI application sector [1]

Group 1 - The A-share market is undergoing a correction, with the CSI Software Service Index down by 3.06% as of the midday close, led by declines in companies such as Deepin Technology and others [1] - DeepSeek is set to release its V4 model, which is expected to surpass the capabilities of closed-source models like Claude and GPT series, achieving significant advancements in coding ability, long-context understanding, and training stability [1] - The new mHC architecture and Engram conditional memory module in V4 are anticipated to reduce training costs and alleviate GPU memory bottlenecks, potentially improving the domestic AI chip situation and accelerating the development of the domestic computing power ecosystem [1] Group 2 - The demand for CPUs is being driven by the explosion of agent applications, with IDC projecting the number of active agents to soar from 28.6 million in 2025 to 2.216 billion by 2030, reflecting a compound annual growth rate of 139% [1] - The server CPU market is entering a tight balance due to the expansion of AIDC and advanced process capacity shifts, with domestic leaders expected to penetrate the incremental market through customization capabilities [1] - As of December 31, 2025, the top ten weighted stocks in the CSI Software Service Index account for 60.89% of the index, including companies like iFlytek and Kingsoft [2] - Investors can access AI software investment opportunities through the Software ETF (159852), which tracks the CSI Software Service Index [2][3]

Core Viewpoint - Recent updates from multiple domestic large model manufacturers indicate a shift from merely competing on parameters and dialogue performance to a deeper focus on engineering and system-level capabilities, aiming to transition large models from "research achievements" to "industrial products" [1] Group 1: Model Updates - Alibaba released the Qwen3-Max-Thinking flagship reasoning model, while DeepSeek and Kimi updated their models with DeepSeek-OCR 2 and Kimi K2.5 respectively [1] - MiniMax launched the Music2.5 music generation model, addressing two major AI music technology challenges, which significantly boosted stock prices in the Hong Kong market, with MiniMax's stock rising over 20% and Zhiyu's stock increasing over 10% [1] Group 2: Challenges in Engineering Phase - The first challenge is balancing cost and efficiency, as high-parameter models incur substantial training and inference costs, making it financially burdensome for most companies to adopt top models for full-scale business operations [2] - The second challenge involves meeting industrial-grade requirements for stability and interpretability, as current models still exhibit issues like "hallucinations" and output variability, which could pose significant risks in critical applications such as financial risk control and medical diagnosis [2] - The third challenge is the integration with existing systems, which requires complex API connections, data format conversions, workflow restructuring, and adaptation of security frameworks, yet many models remain at the "chat demonstration" level without deep integration capabilities [2] Group 3: Path to Overcoming Challenges - Breakthroughs in each challenge are technically demanding, necessitating a shift from "pursuing extreme parameters" to "optimizing unit computational efficiency" to ensure affordability and usability for enterprises [3] - Companies are increasingly seeking stable problem-solving capabilities rather than just technical specifications, prompting a shift from merely providing models to offering comprehensive services and solutions [3] - Implementing techniques like prompt engineering and retrieval-augmented generation can help build safeguards for key application scenarios, effectively controlling hallucinations and enhancing result reliability and interpretability [3]

Core Insights - 360 has launched the first industrial-grade AI comic production platform, "Nano Comic Production Line," aimed at enhancing efficiency and quality in the comic industry [1][5]. Industry Overview - The domestic AI comic market is experiencing rapid growth, with an annual launch volume increase exceeding 80%, and the market size projected to surpass 20 billion yuan by 2025 [5]. - The industry faces challenges in balancing mass production and quality, leading to issues such as low success rates in content generation and the emergence of professional "card pullers," resulting in significant resource waste [5]. Platform Features - The Nano Comic Production Line integrates script analysis, asset generation, storyboard creation, and dynamic synthesis into a streamlined workflow, allowing creators to maintain control over the creative process [5][6]. - The platform boasts a production speed over three times faster than mainstream tools, with single episode production time reduced to 30 minutes to 1 hour, and a material generation success rate exceeding 90% [5][6]. - It features a proprietary "video world model" that enhances creative freedom by ensuring consistency in style and narrative throughout the production process [6]. - The platform supports film-level storyboard design and dynamic storytelling, ensuring 100% control over the creative process while allowing for unique visual styles through private AI integration [6]. Collaborations and Future Prospects - The Nano Comic Production Line has partnered with leading film and comic companies, including Poly Film, Huashi Entertainment, and others, to explore new production models that enhance content quality and capacity [9]. - Some collaborative projects have already been completed and are set to be released soon, including the second season of the award-winning AI live-action drama "Mecha Bureau" [9]. - The platform is positioned as a productivity tool and a means for 360 to establish industry standards in AI comic production, emphasizing the principle of "empowering creativity through technology" [9].

Core Insights - Two prominent domestic AI startups, DeepSeek and Kimi, have released significant open-source updates to their models, DeepSeek-OCR 2 and K2.5, respectively, marking a pivotal moment in AI development [1][4] - DeepSeek-OCR 2 focuses on enhancing the model's ability to "read" information through a new visual encoding mechanism, aiming to improve efficiency and reliability in processing complex documents [1][10] - Kimi K2.5 aims to evolve AI from merely answering questions to executing complex tasks, emphasizing long memory, multi-modal understanding, and task execution capabilities [4][12] Group 1: DeepSeek-OCR 2 - DeepSeek-OCR 2 introduces a new approach to document processing, allowing the model to learn human-like visual logic and compress lengthy text inputs into higher-density "visual semantics" [1][10] - The model shifts from a mechanical text processing method to understanding document structure, enabling it to identify titles, tables, and related information more effectively [8][10] - This upgrade addresses long-standing issues in AI document handling, such as high costs and inefficiencies associated with traditional text input methods [10][11] Group 2: Kimi K2.5 - Kimi K2.5 emphasizes the transition from a question-answering model to a more capable digital assistant, capable of handling complex tasks and multi-modal inputs [4][12] - The model's long memory feature allows it to retain context over extended interactions, reducing the need for repeated explanations [12][17] - Kimi K2.5's focus on task execution and intelligent agent capabilities positions it as a more versatile tool for real-world applications, moving beyond simple advisory roles [12][22] Group 3: Industry Trends - The recent upgrades in AI models reflect a broader industry shift towards practical applications, prioritizing usability and integration into real-world workflows over mere parameter scaling [15][16] - Key areas of focus include enhancing memory retention, improving visual comprehension, and redefining AI's role from advisor to executor [17][22] - The emphasis on engineering and deployment capabilities highlights the industry's commitment to making AI tools more accessible and effective in business environments [22][23]