编者按：AI产业的竞争不是比谁跑得更快，而是比谁跑得更稳、更远。2025年，人工智能正以势如破 竹之势重塑未来。从DeepSeek开源大模型的火热"出圈"，到多场人形机器人赛事"极限破圈"，再到"千 问速度"引爆科技圈，AI正以前所未有的速度穿透虚拟与现实、串联技术与产业。站在AI技术革命的拐 点，我们正目睹一场从技术奇迹到实用价值的深刻范式转移，资本市场对人工智能的追逐已从概念炒作 转向价值重估。站在2025年末，新华财经从上游芯片和算力、中游大模型研发、下游端侧应用等角度纵 观这一年的非凡答卷，也以理性视角审视这场浪潮中的真实与泡影，探寻中国人工智能产业升级的关键 路径。 新华财经北京12月29日电（可达） 2025年无论是在资本市场上还是生活中的方方面面，人工智能都占 据着最重要的"风口"。其中，热度最高的无疑就是"大模型"，从"深度求索（DeepSeek）"当选年度国内 词，到"大模型"入选年度十大科普热词，都无一例外地证明了这一点。 这一年，作为大模型发展的关键之年，其发展已然超脱出技术上的范畴，开始成为人们身边的智能助 理，办公室、生产线上的"生产力"工具。智能变革的大幕正徐徐拉开。 而在岁末更替 ...

【环球时报报道 记者 陈子帅 杨沙沙 王冬】 编者的话： 2025年，世界科技舞台的聚光灯频频对准中国，其中人形机器人和大模型的表现尤为亮眼。从 DeepSeek以卓越的实用能力引发全球人工智能（AI）开发者社区热议，到多场人形机器人赛事"极限破圈"，再到年底中国AI开源大模型集体"霸榜"国际榜单 ——2025年的中国经济正以AI高科技为新名片迈出国门。多位受访专家表示，中国高科技应用不仅是单项技术偶发突破，更是来自新型举国体制统筹下的 系统集成能力与集群生态优势。 双线领跑，中国 AI 吸引全球聚光灯 "2025年最大的变化，是具身智能和大模型应用都从好看的技术展示，转向能落地的工程体系和产业模式。其中，具身智能行业真正从'实验室表演'走向'工 厂干活、园区干活'的阶段。赛迪研究院未来产业研究中心人工智能研究室主任钟新龙对《环球时报》记者分析称，这一年，以人形机器人产品为具体表现 的具身智能产业关键突破体现在"产业规模化推进和应用闭环能力的显著增强"。 走出实验室，来到聚光灯下，中国人形机器人在2025年的不同"秀场"亮相——2025年央视春晚，宇树科技的人形机器人以"扭秧歌"形式惊艳登台；4月，北 京亦庄 ...

Core Insights - The report titled "2025 Generative Marketing Industry Research: From AIGC to AIGD" highlights the evolution of generative AI in marketing, transitioning from AIGC (AI-Generated Content) focused on content creation to AIGD (AI-Generated Decision) centered on decision support, indicating a shift from AI as an "efficiency tool" to a "strategic partner" in marketing [2][4]. AIGC: Marketing Supply Explosion - By 2025, generative AI has matured in creating marketing content, including copy, images, videos, and digital personas, significantly enhancing content supply [3]. - The emergence of new models and products like DeepSeek and Manus has lowered technical barriers, evolving AI from a "creative assistant" to an "execution agent" [3]. - However, the explosion of content supply raises challenges for businesses in selecting optimal solutions and ensuring the authenticity and reliability of AI-generated content, as AIGC addresses production issues but not effectiveness [3]. AIGD: Systematic Upgrade in Marketing Decisions - AIGD aims to resolve decision-making challenges from the AIGC era by integrating classic marketing theories with AI tools, creating a complete loop from "insight—generation—validation—decision" [4]. - On the consumer side, over 68% of consumers are influenced by AI recommendations in their purchasing decisions, indicating a shift in decision-making power towards AI [4]. - On the enterprise side, AI is utilized for core marketing tasks such as environmental analysis, brand positioning, and demand exploration, enhancing the scientific and efficient nature of marketing decisions [4]. AI Practices: Deepening Industry Applications - Generative AI has been implemented across various industries: - **Food and Beverage**: Companies like Mengniu and Yili use AI for health models and ad testing [5]. - **Beauty and Personal Care**: L'Oréal optimizes formula development with AI, while Proya builds ROI-driven decision systems [5]. - **Automotive**: AI enhances lead management and user profiling [5]. - **Alcohol Industry**: AI integrates into brewing processes and enhances cultural experiences through digital personas and the metaverse [5]. - **Dining and Retail**: Smart ordering and AI-driven site selection are core to digital transformation [5]. - **Apparel, Home Appliances, and Digital Products**: AI assists in design, sales forecasting, virtual fitting, and customer service [5]. Future Outlook: Human-AI Collaboration with Decision Priority - The future of generative marketing emphasizes human-AI collaboration rather than AI replacing humans, necessitating organizations to build "AI-ready" structures that deeply integrate AI into strategy, operations, and innovation processes [6]. - The transition from AIGC to AIGD represents a shift from "content-driven" to "decision-driven" approaches, where effective use of AI for decision-making will determine market success [6].

Group 1 - China's "5G + Industrial Internet" has achieved systematic breakthroughs in the past five years, with over 20,000 construction projects covering all 41 industrial categories, significantly boosting manufacturing development [1] - The investment scale in "5G + Industrial Internet" has exceeded 50 billion RMB, with over 1,200 5G factories built, leading to notable improvements in product quality, operational costs, and production efficiency [1] - China has established the world's largest and highest-quality mobile broadband network, with China Tower constructing 9.53 million base stations, saving over 210 billion RMB through resource sharing [1] Group 2 - China leads in industrial standard construction, having released the world's first industrial 5G international standard and over 100 national and industry standards [2] - The cost of 5G modules has decreased by 90% compared to the initial commercial phase, facilitating the large-scale application of "5G + Industrial Internet" [2] - AI is driving the transformation of "5G + Industrial Internet," with applications in various industries, such as the "Industrial Brain" project by Kaos, which has empowered 160,000 enterprises [2] Group 3 - In the energy sector, AI has generated direct benefits of 1.9 billion RMB for the National Energy Group, with 40% of new developers focusing on the industrial field [3] - In the automotive sector, generative AI has improved design efficiency by over 8%, with nearly 90% of automotive companies adopting AI assistance [3] - The average efficiency of 5G factories has increased by 19.6%, while operational costs have decreased by 14.5%, leading to significant improvements in quality and efficiency [3]

Core Insights - Singapore is shifting its AI strategy from using US-based Meta's models to adopting China's Alibaba's Qwen model, marking a significant pivot in its national AI initiative [3][5][9] - This transition highlights China's growing influence in the AI sector, particularly in Southeast Asia, as it begins to overshadow US technology [3][10][12] Group 1: Strategic Shift in AI Models - Singapore's national AI program (AISG) has officially announced a major change, opting for Alibaba's Qwen model over Meta's [5][7] - The new project, "Sea-Lion v4," will utilize Alibaba's Qwen3-32B open-source architecture, which is tailored for Southeast Asian languages [5][10] - The collaboration will involve Alibaba providing core model technology and ongoing technical support for the "Sea-Lion" model [7][9] Group 2: Performance Comparison - Meta's Llama series model had significant shortcomings, particularly in Southeast Asian languages, with only 0.5% of training data dedicated to these languages [9][10] - In contrast, Alibaba's Qwen3-32B model covers 119 languages and has over 100 billion tokens of training data specifically for Southeast Asian languages, achieving top rankings in language capability [10][12] Group 3: Investment and Growth in AI - Singapore has invested approximately 7 billion SGD (about 1.5% of its GDP) in AI from 2019 to 2023, making it a global leader in AI investment [19][25] - The country aims to become a leading AI economy by 2030, with plans to expand its AI workforce and enhance its infrastructure [26][30] - The AI sector in Singapore is projected to generate 15 billion SGD in value by 2024, contributing 5.8% to the GDP, reflecting its role as a new economic engine [30][33] Group 4: Global AI Landscape - The rise of Alibaba's Qwen has led to a phenomenon termed "Qwen Panic" among Silicon Valley giants, indicating its competitive edge in the global market [12][17] - Major companies, including Airbnb and Nvidia, have expressed reliance on Qwen for its superior performance and cost-effectiveness compared to other models [14][17] - The collaboration between Singapore and China in AI is seen as a strategic move that could position Singapore as a key player in the Southeast Asian AI market [43][44]

Core Viewpoint - The company, Beixin Source (300352.SZ), has not established direct cooperation with Alibaba or Ant Group in the field of artificial intelligence as of November 26 [2]. Group 1: Company Developments - Beixin Source has developed its own secure communication platform called Xinyuan Mixin, which is capable of integrating with AI-driven intelligent dialogue robots [2]. - The Xinyuan AI capability platform allows for dialogue and secure communication between robots and humans [2]. - The company has already integrated with several domestic AI products, including Baidu's Wenxin Yiyan, Alibaba's Tongyi Qianwen, Zhipu's ChatGLM, Kimi, DeepSeek, and iFLYTEK's Xinghuo large model [2].

Core Insights - The rise of China's four AI giants—Baidu, Alibaba, Tencent, and iFlytek—marks a transition from "technology followers" to "rule makers" in the global AI landscape, highlighting a dual logic of "pragmatism" and "ecosystem reconstruction" in the AI competition [1][6][8] Group 1: Differentiated Technical Paths - Baidu's model is based on search engine data, creating a "open-source ecosystem + scenario closed-loop" approach, with its PaddlePaddle framework attracting over 8 million developers and covering more than 40 scenarios [1][2] - Alibaba integrates AI deeply into its e-commerce ecosystem, with its Tongyi Qianwen model applied in e-commerce recommendations and intelligent customer service, making Alibaba Cloud the only cloud service provider to transition from "selling computing power" to "selling intelligence" [1][2] Group 2: User Experience and Technical Depth - Tencent's Mix Yuan model leverages its vast user data from WeChat to excel in Chinese language processing and multi-modal interaction, enhancing user experience through seamless service integration [2][4] - iFlytek focuses on foundational technologies like voice recognition and natural language processing, achieving a diagnostic accuracy level comparable to chief physicians in top hospitals with its Spark model [2][4] Group 3: Ecosystem Strategies - The ecological strategies of the four giants show a divergence between "open collaboration" and "vertical deepening," with Baidu fostering an AI innovation consortium through its open-source community [3][4] - Alibaba employs a "cloud + AI + industry" integration model, providing end-to-end solutions across various sectors, while Tencent emphasizes "scenario integration" through its super apps [4][5] Group 4: Global Influence and Standard Setting - China's influence in standard-setting is growing, with Baidu's PaddlePaddle becoming the second-largest deep learning framework globally and Alibaba Cloud leading the first international AI cloud service standard adopted by the ITU [5][6] - iFlytek's participation in developing international standards for intelligent voice recognition covers 90% of relevant scenarios, indicating a shift from "technology following" to "rule co-construction" [5][6] Group 5: Market Opportunities and Challenges - Despite significant progress, challenges remain in foundational research, particularly in chip architecture and quantum computing, with existing technologies needing further compatibility and commercial application breakthroughs [5][6] - The Chinese AI market is projected to grow significantly, with Morgan Stanley predicting the core AI industry to exceed 1.2 trillion yuan by 2027, driven by a robust market, complete industrial chain, and supportive policies [6][8] Group 6: Future Directions - The competition in AI is expected to enter a "deep water zone" with breakthroughs in next-generation technologies like quantum computing and neuromorphic computing, necessitating a focus on ecological openness and global collaboration [8][9] - Chinese AI companies are encouraged to shift from "technology monopoly" to "technology symbiosis" and from "traffic harvesting" to "value sharing" to achieve leadership in the global AI race [9]

Core Insights - The State Council has issued the "Implementation Opinions on Accelerating Scene Cultivation and Open Promotion for Large-Scale Application of New Scenes," marking a systematic deployment of scene cultivation at the national level [1] - Recent industry dynamics illustrate a clear path of practice, including the mutual transfer of A-share stakes between China National Petroleum Corporation (CNPC) and China Mobile, and a model exchange event hosted by iFlytek [1][2] - The collaboration between state-owned enterprises (SOEs) and private enterprises is creating a closed-loop ecosystem characterized by capital interlocking, technological collaboration, and scene implementation [2] Scene Supply Side - SOEs are identified as the core carriers and "rich mines" for new scene cultivation, holding significant infrastructure and industry data [2] - SOEs have developed over 800 application scenarios in the "AI + scene" construction, exemplified by the launch of 100 representative application scenarios in the energy and chemical industry alongside the Kunlun model [2] Technical Support Side - Private enterprises like iFlytek provide essential computing power and algorithm support for scene implementation [3] - iFlytek's Spark model is the only general model trained on domestic computing power, enabling efficient construction of industry-specific models [3] - iFlytek has maintained a leading position in public bidding for large models in SOEs, serving over 20 central enterprises [3] Strategic Value of SOE and Private Enterprise Cooperation - The collaboration enhances technological innovation and self-control, reducing reliance on external technologies [4] - It accelerates digital transformation and industrial upgrading, addressing challenges faced by SOEs in digitalization [4] - The partnership optimizes resource allocation and promotes collaborative development across industries, enhancing overall competitiveness [4] - The rapid pace of scene cultivation and opening will lead to diverse applications in areas like "5G+", "AI+", and "Industrial Internet," driving high-quality development in the real economy [4]

Core Insights - Shanghai Lingjing Zhiyuan Technology Co., Ltd. and iFlytek Co., Ltd. signed a strategic cooperation agreement during the 8th World Voice Expo and 2025 iFlytek Global 1024 Developer Festival [1] - The collaboration will focus on multiple dimensions including robot multimodal superhuman interaction, Spark large model foundation, health data services, ecological innovation, and brand promotion [1] - The partnership aims to jointly promote the development and application of domestic embodied intelligence technology [1]

Core Viewpoint - The latest quarterly report from Keda Xunfei shows significant growth in revenue and profit, driven by advancements in AI technology and its industrial application [1][2]. Financial Performance - Keda Xunfei achieved a revenue of 6.078 billion yuan in Q3 2025, representing a year-on-year increase of 10.02% [4]. - The net profit attributable to shareholders reached 172.25 million yuan, a remarkable increase of 202.40% compared to the previous year [4]. - The net profit excluding non-recurring items was 26.24 million yuan, up 76.5% year-on-year [4]. - Operating cash flow showed strong performance with a net amount of 895 million yuan, reflecting a growth of 25.19% [6]. Business Operations - The report indicates that the two core profit indicators demonstrate the company's improved profitability in its main business [5]. - For the first three quarters of 2025, total revenue reached 16.99 billion yuan, a 14.41% increase year-on-year, with a net loss of 0.67 billion yuan, significantly narrowing the loss by 80.6% compared to the previous year [8][9]. AI Technology and Market Position - Keda Xunfei's advancements in AI large models have become a key driver for revenue growth, with significant progress in core technology, product deployment, and ecosystem development [13]. - The "Xunfei Spark" model has undergone critical upgrades, outperforming competitors in various capabilities, including mathematics and translation [14][15]. - The company has secured the highest number and amount of bids for large model projects in the industry, with Q3 bids totaling 545 million yuan, surpassing the combined total of the second to fifth competitors [16]. Research and Development - Keda Xunfei continues to increase its R&D investment, planning to raise up to 4 billion yuan through the issuance of A-shares to fund the development of the Spark education model and computing platform [18][19]. Ecosystem Growth - The AI ecosystem is showing strong growth, with 690,000 new developers added for large models and a total of 1.22 million ecosystem developers [17].