值得关注的是，除字节外，自变量在此前的融资中也先后获得了美团、阿里的投资，是国内唯一同时被 这三家互联网大厂投资的具身智能企业。 （文章来源：第一财经） 1月12日，第一财经记者了解到，自变量机器人宣布已完成10亿元A++轮融资。本轮融资由字节跳动、 红杉中国、北京信息产业发展基金、深创投、南山战新投、锡创投等顶级投资机构及多元地方平台联合 投资。据了解，这也是深创投AI基金成立以来的第一笔投资。 ...

Group 1 - Anta Sports-R (82020), Tencent Holdings-R (80700), and Geely Automobile-R (80175) have the highest short-selling ratios at 100.00%, 90.92%, and 80.03% respectively [1][2] - Meituan-W (03690), Alibaba-W (09988), and Tencent Holdings (00700) lead in short-selling amounts, with 1.554 billion, 1.440 billion, and 1.253 billion respectively [1][2] - Tencent Holdings-R (80700), China Wangwang (00151), and Country Garden (02007) have the highest deviation values at 45.18%, 36.17%, and 33.66% respectively [1][2] Group 2 - The top short-selling amounts are led by Meituan-W (03690) at 1.554 billion, followed by Alibaba-W (09988) at 1.440 billion, and Tencent Holdings (00700) at 1.253 billion [2] - The top short-selling ratios include Anta Sports-R (82020) at 100.00%, Tencent Holdings-R (80700) at 90.92%, and Geely Automobile-R (80175) at 80.03% [2] - The highest short-selling deviation values are observed in Tencent Holdings-R (80700) at 45.18%, China Wangwang (00151) at 36.17%, and Country Garden (02007) at 33.66% [2][3]

证券研究报告 传媒 行业定期报告 hyzqdatemark 2026 年 01 月 11 日 证券分析师 陈良栋 SAC：S1350524100003 chenliangdong@huayuanstock.com 陈逸凡 SAC：S1350525040003 chenyifan@huayuanstock.com 周政宇 SAC：S1350525050006 zhouzhengyu@huayuanstock.com 许孟婕 SAC：S1350525120004 xumengjie@huayuanstock.com 魏桢 weizhen@huayuanstock.com 板块表现： AI 应用仍是核心，重视 AI 营销 GEO 模式 投资评级： 看好（维持） ——传媒互联网行业周报（2026.1.5-2026.1.11） 投资要点： 电影/电视剧方向：《飞驰人生 3》正式定档 2026 年春节，或将随着春节档演绎。 我们建议关注相关电影出品/发行方以及院线公司：包括中国电影、猫眼娱乐、大麦 娱乐、上海电影、幸福蓝海、横店影视、金逸影视等。同时，电视剧行业方面，国 家广播电视总局印发实施《进一步丰富电视大屏内容 促 ...

Core Viewpoint - The regulatory authorities in China are taking action against the chaotic competition in the food delivery industry, initiating an investigation into the market competition status of food delivery platforms [1][3]. Group 1: Regulatory Actions - The State Administration for Market Regulation announced that the Office of the State Council Anti-Monopoly and Anti-Unfair Competition Committee will investigate and assess the competitive conditions in the food delivery platform service industry [1][3]. - The investigation aims to address issues such as excessive subsidies, price wars, and traffic control that have been detrimental to the real economy and have intensified "involution" competition within the industry [3]. Group 2: Industry Response - Major food delivery platforms, including Meituan, Taobao Shanguo, and JD, have expressed their support for the investigation and committed to cooperating fully with the regulatory authorities [4]. - Meituan stated that it will use this investigation as an opportunity to work with other platforms to fulfill market responsibilities and promote healthy development in the food delivery service industry [4]. Group 3: Historical Context - This is not the first time regulatory authorities have intervened in the food delivery industry; previous actions included discussions with major platforms in response to the intense competition and subsidy wars that escalated in 2025 [5][6]. - In 2025, significant subsidy investments were made by platforms, including a joint investment of 50 billion yuan by Taobao and Ele.me, and 10 billion yuan by JD [5]. Group 4: Financial Impact - The ongoing price wars have negatively impacted the profitability of major players; for instance, JD's operating profit margin fell to -0.2% in Q2 2025, down from 3.6% in the same period of 2024 [6]. - Meituan reported a net profit of 1.49 billion yuan in Q2, a staggering 89% decrease year-on-year, attributed to industry competition [6].

Core Viewpoint - The article emphasizes the urgent need to address the "involution" in the food delivery industry, as highlighted by the central government's focus on expanding domestic demand, promoting innovation, and combating involution in the economy [5][6]. Group 1: Market Saturation and Competition - The food delivery market in China is nearing saturation, with online food delivery users reaching 592 million by the end of 2024, accounting for 53.4% of the total internet users [8][10]. - The competition in the food delivery sector has shifted to a zero-sum game, where growth is no longer driven by increased demand but rather by existing market share [8][11]. Group 2: Impact on Stakeholders - The ongoing price wars have not benefited any stakeholders in the food delivery ecosystem. Merchants have seen a rise in order volume but a decline in actual revenue, with a reported average decrease of 4% in daily revenue despite a 7% increase in total orders since July 2025 [12][15]. - Delivery riders are also facing increased workloads without corresponding income growth, leading to a significant drop in average monthly earnings [13][15]. Group 3: Regulatory Response - The government has initiated investigations into the chaotic competition in the food delivery market, indicating a serious approach to curbing involution and ensuring fair competition [6][20]. - Previous attempts to regulate the market through discussions with major platforms like Meituan and JD have had limited success, necessitating a more robust regulatory framework [16][18]. Group 4: Long-term Implications - The article argues that the current trajectory of excessive marketing expenditures over long-term capital investments could undermine the long-term value of Chinese internet companies [21][27]. - The call for a shift from price wars to differentiated services and technological innovation is seen as essential for sustainable growth in the industry [27][25]. Group 5: Conclusion - The initiation of market investigations is viewed as a critical step towards meaningful reform in the food delivery sector, signaling the end of unsustainable competition driven by short-term gains [22][27]. - The article concludes that the future of the food delivery industry will depend on platforms' ability to adapt their strategies towards building a healthier ecosystem and enhancing core competitiveness [27][28].

Investment Rating - The report does not explicitly provide an investment rating for the AI industry Core Insights - The AI industry is experiencing significant advancements, with multiple companies releasing innovative products and models, indicating a robust growth trajectory in the sector [1][5][9][14][18] - The Chinese government is actively promoting AI integration in manufacturing, aiming to establish a leading position in AI technology and applications by 2027 [5] - Major companies like Lenovo and Tencent are launching new AI models and platforms, enhancing the capabilities and applications of AI in various fields [8][15][18] Summary by Sections 1. AI Industry Dynamics - The Ministry of Industry and Information Technology and other departments have issued guidelines for the "Artificial Intelligence + Manufacturing" initiative, targeting the development of core AI technologies and industry applications by 2027 [5] - In 2026, over 30 national standards related to data in AI will be introduced, focusing on areas like intelligent agents and embodied intelligence [6] - The Sichuan provincial government has launched a plan to develop a national digital economy innovation zone, aiming to enhance digital infrastructure and promote the growth of digital industries [7] 2. AI Application Insights - LuKe announced the global launch of the "Air Charging AI Smart Lock V7 Max" at CES 2026, featuring technology for continuous power supply [10] - Yushun released training videos for its humanoid robot Unitree H2, showcasing advanced capabilities [11] - DeepTing released the world's first dual-wheeled outdoor companion robot Rovar, designed for various outdoor scenarios [12] - Rokid introduced the "Style" AI glasses at CES 2026, featuring a dual-chip architecture and 4K video capabilities [13] 3. AI Large Model Insights - Alibaba Tongyi has released and open-sourced the Qwen3-VL-Embedding and Qwen3-VL-Reranker models, designed for multimodal information retrieval and understanding [14] - Tencent launched the HY-Motion1.0 model, a significant advancement in 3D character animation generation [15] - Xiaopeng unveiled its second-generation VLA model, marking a shift towards practical applications of physical AI technology [16][17] - Lenovo introduced the Lenovo Qira personal super intelligent agent, emphasizing cross-device functionality and personalized services [18] 4. Technology Frontiers - Alibaba Cloud launched a new multimodal interaction development kit, integrating various foundational models for diverse applications [19] - Tsinghua University published a paper on an AI-driven drug virtual screening platform, significantly improving screening speed and accuracy [20] - Chinese scientists made progress in cancer immunotherapy, developing a protein-targeting degradation technology [21] - A team from the University of Science and Technology of China achieved advancements in heterogeneous quantum communication networks [22]

Core Viewpoint - The article emphasizes the rapid advancement of AI hardware, transitioning from novelty to practical applications, particularly in the realm of "Physical AI" as highlighted at major tech events like CES 2026 and Alibaba's cloud exhibition [1][3][4]. Group 1: AI Hardware Transformation - AI hardware is evolving into intelligent entities capable of perception, understanding, and decision-making, marking a significant shift from mere marketing gimmicks to functional devices [3]. - The demand for AI hardware is increasing, with new applications being rapidly developed, as evidenced by the diverse range of products showcased at the Alibaba cloud exhibition, including over 1,000 smart hardware items from more than 200 brands [8][9]. Group 2: Innovations in AI Hardware - Notable innovations include the Pettichat pet translator, which achieves a 94.6% translation accuracy for pet sounds, demonstrating the potential of AI in everyday applications [6]. - The AI hardware ecosystem is expanding, with various products like smart glasses, AI companions, and training devices becoming mainstream, indicating a robust market for AI-integrated solutions [8]. Group 3: Competitive Landscape - Major players in the AI hardware space, such as Alibaba's Qianwen, are positioning themselves similarly to Android by providing open-source and adaptable solutions that lower barriers for hardware manufacturers [9][14]. - The shift from hardware sales to service-oriented models is becoming prevalent, allowing manufacturers to enhance user experience and establish sustainable profit models [14][15]. Group 4: Future Outlook - The Chinese AI hardware market is projected to exceed 1.1 trillion yuan by 2025, with a year-on-year growth of 13.4%, indicating a strong and ongoing expansion in this sector [16]. - Companies like Alibaba are focused on fostering an ecosystem that encourages innovation and collaboration among hardware manufacturers, aiming to enhance the overall market potential for AI hardware [16].

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The coffee industry remains highly prosperous with brands actively opening new stores, although there is a caution regarding short-term data volatility due to the seasonal downturn [3] - The tea beverage sector is under slight pressure as it enters the off-season, with a trend of subsidy reductions expected despite the government's investigation into delivery platforms [3] - The e-commerce sector continues to face challenges, showing lackluster performance due to the domestic consumption environment [3] - Music streaming platforms are highlighted as valuable internet assets driven by domestic demand, with a recommendation to focus on music subscription platforms [3] - The virtual asset and trading platform market is experiencing limited catalysts, with cryptocurrency prices remaining volatile [3] - The automotive service sector is seeing expansion, with new 4S stores being opened by Zhongsheng Group in various cities [3] - The internet healthcare sector is gaining attention with OpenAI's launch of "ChatGPT Health," suggesting a focus on this area [3] - The AI and cloud sectors are viewed positively, with recommendations to monitor leading tech companies with strong cash flows [3] - The media sector is showing signs of recovery, with new games performing well and user growth in the gaming segment [3] Summary by Sections 1.1 Consumer & Internet - The Hang Seng non-essential consumer index decreased by 0.98%, underperforming the Hang Seng index by 0.57 percentage points [8] - Notable stock performances include: Gu Ming (+8.72%), Ba Wang Tea (+6.99%), and Luckin Coffee (-6.47%) [8][10] 1.2 Platform & Technology 1.2.1 Streaming Platforms - The Hang Seng media index increased by 3.22%, outperforming both the Hang Seng index and the technology index [15] - Key stock performances include: iQIYI (+0.99%) and Tencent Music (-2.86%) [15] 1.2.2 Virtual Assets & Internet Brokers - As of January 9, the global cryptocurrency market cap reached $319.54 billion, up 3.40% [22] - Bitcoin and Ethereum prices were $90,505 and $3,083.14, reflecting changes of +0.6% and -1.2% respectively [22] 1.2.3 Automotive Services - The Hang Seng composite index rose by 0.38%, with notable stock performances including Advance Auto Parts (+12.73%) [31] 1.2.4 O2O - The Hang Seng internet technology index decreased by 0.27%, with key stock performances such as JD Health (+13.31%) and Didi Global (-7.19%) [37] 1.2.5 AI & Cloud - The Nasdaq internet index increased by 1.59%, with Amazon (+9.22%) and Google (+4.26%) showing strong performances [39] 1.3 Media - The Shenwan一级传媒 index increased by 13.14%, with the advertising and marketing sector showing the largest gains [46] - Key stock performances include: Xindong Company (+18.50%) and Tencent Holdings (-1.93%) [46]

Core Insights - The competition in large models has shifted from "Chat" to "Agent," focusing on executing complex tasks in real environments rather than just scoring on leaderboards. The industry anticipates 2026 as the year when commercial value will be realized, with a technological evolution towards verifiable reinforcement learning (RLVR) [2][4][5]. Group 1: Competition Landscape - The engineering challenges of the Chat era have largely been resolved, and future success will depend on the ability to complete complex, long-chain real tasks. The core value of AI is transitioning from "providing information" to "delivering productivity" [4]. - The bottleneck for Agents lies not in cognitive depth but in environmental feedback. Future training paradigms will shift from manual labeling to RLVR, enabling models to self-iterate in systems with clear right or wrong judgments [5][6]. - The industry consensus suggests that while China has a high chance of catching up in the old paradigm (engineering replication, local optimization, toC applications), its probability of leading in new paradigms (underlying architecture innovation, long-term memory) is likely below 20% due to significant differences in computational resource allocation [5][11]. Group 2: Strategic Opportunities - Opportunities for catching up lie in two variables: the global shift towards "intelligent efficiency" as scaling laws encounter diminishing returns, and the potential paradigm shift driven by academia around 2026 as computational conditions improve [5][19]. - The ultimate variable for success is not leaderboard scores but the tolerance for uncertainty. True advancement depends on the willingness to invest resources in uncertain but potentially transformative new paradigms rather than merely chasing scores in the old paradigm [5][10]. Group 3: Perspectives from Industry Leaders - Industry leaders express cautious optimism regarding China's potential to lead, with probabilities of success varying. For instance, Lin Junyang estimates a 20% chance of leading due to structural differences in computational resource allocation and usage [11][12]. - Tang Jie acknowledges the existing gap in enterprise AI lab research but bets on a paradigm shift occurring around 2026, driven by improved academic participation and the emergence of new algorithms and training paradigms [15][19]. - Yang Qiang believes that China may excel in toC applications first, drawing parallels to the internet history, while emphasizing the need for China to develop its own toB solutions to bridge existing gaps [20][24]. Group 4: Technological Innovations - The future of AI will require advancements in multi-modal capabilities, memory structures, and self-reflective abilities, which are essential for achieving higher levels of intelligence and functionality [68][70][73]. - The introduction of new optimization techniques, such as the MUON optimizer, aims to enhance token efficiency and long-context processing, which are critical for the performance of agent-based models [110][116]. - The development of linear attention mechanisms is expected to improve efficiency and performance in long-context tasks, addressing the limitations of traditional attention models [116]. Group 5: Future Directions - The industry is focused on distinguishing between scaling known paths through data and computational increases and exploring unknown paths to discover new paradigms [98][99]. - The potential for AI to participate in scientific research is anticipated to expand significantly, opening new possibilities for innovation and application [101].

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The competition in AI entry points is intensifying, with major companies increasing their investments. China's AI presence globally has significantly improved, with domestic large models continuously iterating. Despite GPT-5.2 and Gemini 3 Pro leading, Chinese models have effectively altered the North American dominance in the competitive landscape. In the global Top 10, three positions are held by Chinese models, and in the Top 15, there are six Chinese companies. By 2025, China's open-source AI model usage is expected to account for over 70% of the global market [2][11][19] - The demand for inference has surged, with the emergence of o1 class inference models unlocking approximately 10 times the potential of traditional models in terms of inference-time compute. The demand for computing power has shifted from being solely "training-driven" to a dual focus on "training + inference" [2][5][37] - The battle for entry points has evolved beyond mobile devices to OS-level intelligent agents and super apps. By December 24, 2025, ByteDance's AI application Doubao announced daily active users (DAU) exceeding 100 million, while Qianwen App reached over 30 million monthly active users within 23 days of public testing, becoming the fastest-growing AI application globally. Doubao bypasses traditional interfaces, creating an "AI operating system" that directly interacts with super apps like WeChat and Alipay, challenging the rules of the traditional app era [2][44][45] Summary by Sections AI Entry Point Competition - China's AI global presence has significantly improved, with domestic large models continuously iterating. In the global Top 10, three positions are held by Chinese models, and in the Top 15, there are six Chinese companies. By 2025, China's open-source AI model usage is expected to account for over 70% of the global market [2][11][19] - The competition for entry points has evolved beyond mobile devices to OS-level intelligent agents and super apps, with significant user engagement reported for new AI applications [2][44][45] Domestic Chip Breakthroughs - The smart computing center in China is expanding, with a projected compound annual growth rate (CAGR) of 57% from 2020 to 2028, reaching 2,781.9 EFLOPS by 2028. Domestic chip technology is steadily improving, with local cloud service providers accelerating the construction of heterogeneous environments [5][50] - Domestic general-purpose GPUs are upgrading from "usable" to "good," with performance metrics approaching those of leading international models. The production capacity of domestic chip manufacturers like SMIC is continuously increasing, providing solid support for domestic AI chip production [5][53][54] Supply and Demand Dynamics - The demand side is characterized by a surge in inference demand as AI applications become more prevalent, while the supply side sees continuous improvements in domestic GPU performance and accelerated adaptation by cloud service providers [5][59] - The AI server market is expected to see a shift towards inference servers becoming the mainstream, with a projected market size of approximately $39.3 billion in 2024, reflecting a year-on-year growth of 49.7% [5][64]