Report Summary 1. Report Industry Investment Rating - The report recommends a long position for all four major stock index futures contracts (IH, IF, IM, IC) and suggests buying out - of - the - money long - term call options on stock indices [1][2][3]. 2. Report's Core View - The market is expected to evolve into a trending upward market. The governance of low - price and disorderly competition among enterprises is likely to boost the performance of listed companies, and international funds are expected to flow into A - shares due to the "de - Americanization" of global financial asset reallocation. Although the Shanghai Composite Index had a short - term pullback, the medium - and long - term outlook is optimistic [2]. 3. Summary by Relevant Catalogs **Market Review** - On Wednesday, the major stock indices in the two markets were strong first and then weak. The Shanghai Composite Index fluctuated above 3500 points and declined after 14:00. The innovative drug sector led the gains. The total trading volume of the two markets was 1.50 trillion yuan, with little change. The CSI 1000 Index closed at 6390 points, down 17 points or - 0.27%; the CSI 500 Index closed at 5953 points, down 24 points or - 0.41%; the SSE 50 Index closed at 2739 points, down 7 points or - 0.26%; the SSE 300 Index closed at 3991 points, down 7 points or - 0.18%. The CSI 1000, CSI 500, SSE 300, and SSE 50 index futures saw net outflows of 80, 37, 31, and 4 billion yuan in settled funds respectively [1]. **Important Information** - The Economic Daily stated that breaking "involution" means returning the market to fair competition. When enterprises shift from low - price competition to competing in technology, user understanding, and market creation, they can move up the value chain [1]. - National Development and Reform Commission Director Zheng Shanjie said that during the "14th Five - Year Plan" period, China's GDP continuously exceeded 110, 120, and 130 trillion yuan, and this year's economic volume is expected to reach about 140 trillion yuan [1]. - In June, the consumer price index (CPI) increased by 0.1% year - on - year, up from a decline in the previous month, and decreased by 0.1% month - on - month, with a narrower decline than the previous month [1]. - The A - H premium converged, and the Hong Kong stock market showed a valuation premium. Foreign investors still have a large demand for Chinese core assets. As of June 30, the A - H premium in the Shanghai - Shenzhen - Hong Kong market fell below 130%, similar to the level in early 2021 [1]. - Goldman Sachs pointed out that the Chinese software market continued the strong development momentum of AI - native applications in Q2 2025, with intelligent agents, multi - modal AI models, and model deployment as the three core growth engines [1]. - JD Takeaway launched the "Double - Hundred Plan", investing over 10 billion yuan to support more brand products to achieve sales of over one million [1]. - US Commerce Secretary Luttner is expected to meet with Chinese officials in early August to discuss trade issues [1]. - OPEC+ unexpectedly increased production, but oil prices did not fall, indicating that the global oil supply - demand balance is more tense than the surface data shows [2]. - Tether Holdings SA, the world's largest stablecoin issuer, stores about $8 billion worth of gold in a Swiss vault, making it the largest gold holder outside banks and national institutions [2]. - The US Treasury plans to increase the cash reserve in the general account from about $313 billion on July 3 to $500 billion by the end of July and to $85 billion by September [2]. - US President Trump announced a 50% tariff on copper imports, causing the US copper futures price to soar 13% to a record high [2]. - The spread between US junk bonds and Treasury bonds has dropped to a record low of about 2.88 percentage points, indicating strong investor confidence in the economic outlook [2]. **Market Logic** - The major stock indices in the two markets were strong first and then weak on Wednesday. China's economic volume is expected to reach about 140 trillion yuan this year. The A - H premium converged, and foreign investors have a large demand for Chinese core assets. The US imposing tariffs on Japan, South Korea, and Southeast Asia benefits China's exports. Goldman Sachs expects Chinese listed companies to pay a total of 3 trillion yuan in dividends by the end of 2025 [2]. **Outlook for the Future Market** - The market is expected to evolve into a trending upward market. The "de - Americanization" of global financial asset reallocation may accelerate international funds flowing into A - shares. The central government's measures to promote a unified national market and regulate low - price competition are expected to boost the performance of listed companies. The short - term pullback of the Shanghai Composite Index does not affect the medium - and long - term optimism [2]. **Trading Strategies** - For stock index futures directional trading, given the expected improvement in listed company performance and the potential for a trending upward market, it is recommended to be bullish on the four major stock index futures contracts [2]. - For stock index option trading, as the market is expected to turn into a trending upward market, it is recommended to buy long - term out - of - the - money call options on stock indices [3].

Core Insights - The Shanghai Stock Exchange Sci-Tech Innovation Board Artificial Intelligence Index (950180) experienced a decline of 1.73% as of July 9, 2025, with mixed performance among constituent stocks [3] - The latest scale of the Sci-Tech AI ETF reached 4.429 billion yuan, marking a new high since its inception, ranking first among comparable funds [4] - The fund's tracking error over the past six months was 0.238%, indicating the highest tracking precision among comparable funds [5] Performance Summary - The Sci-Tech AI ETF saw a net outflow of 66.5 million yuan recently, but had a net inflow of 158 million yuan over the past five trading days [4] - The fund's net value increased by 11.26% over the past six months, with a maximum monthly return of 15.59% since inception [4] - The fund's management fee is 0.50%, and the custody fee is 0.10%, which are relatively low compared to comparable funds [4] Market Trends - AI applications are entering a rapid development phase, with AI becoming a core driver of business processes rather than just an auxiliary tool [3] - The rise of serverless and pay-as-you-go models is becoming mainstream, providing more refined cost management and optimization tools [3] - The index's valuation is at a historical low, with a price-to-book ratio (PB) of 7.56, below 92.37% of the time since the index's inception, indicating strong valuation attractiveness [5] Key Holdings - As of June 30, 2025, the top ten weighted stocks in the index accounted for 68.03% of the total, including companies like Cambricon Technologies (688256) and Langchao Technology (688008) [6]

Core Insights - The article highlights the launch of a new financial model solution by Huoshan Engine, focusing on enhancing customer service and internal efficiency for financial institutions through AI-native applications and digital employees [1] - The financial sector is identified as a leading area for the large-scale application of AI models, with Huoshan Engine's collaboration with financial institutions accelerating since the release of the Doubao model in May 2024 [1] - Huoshan Engine's AI solutions have already reached 70% of systemically important banks and numerous brokerage and fund companies, emphasizing the importance of customer service and internal efficiency in the financial industry [1] Financial AI App - The AI App serves as a mobile platform that utilizes AI models to provide intelligent investment advice, trading, services, and information interactions, already implemented in several brokerage firms [3] - The app aims to transform the user experience of financial applications [3] Capability Framework of AI App - The AI App solution is structured into three layers: - The intelligent interaction layer includes financial clients and Doubao App, featuring expert intelligent agents like market assistants [4] - The middle platform capability layer integrates intelligent control, data-knowledge-intelligence analysis, and model evaluation to ensure the iterative development of AI applications [4] - The infrastructure layer is built on the Doubao model, AI cloud-native security, and computing power management [4] - The Huoshan Engine Data Agent has effectively created investment advisory intelligent agents for multiple enterprises, enabling users to access multi-dimensional market analysis and real-time tracking of trends and fund movements [4] Digital Employees - The digital employee solution encompasses six key scenarios, creating an inclusive AI tool matrix: - Business assistants automate the entire due diligence cycle, shifting from experience reliance to AI-driven processes [5] Intelligent Customer Service and Risk Control - Intelligent customer service integrates ticket extraction, AI Q&A, and quality inspection to enhance service efficiency and compliance [6] - Intelligent risk control replaces traditional OCR with VLM to automatically extract multi-modal risk factors, upgrading risk insight models [6] Collaborative Ecosystem - The article discusses the importance of ecosystem collaboration for the large-scale implementation of AI-native applications, with Huoshan Engine signing partnerships with ten financial technology pioneers to co-create a new financial intelligence ecosystem [8] - The collaboration aims to drive innovation and accelerate the financial industry's transition towards intelligence [8]

Core Insights - The Chinese relational database market is expected to experience a rapid growth rate approaching 25% by 2025 due to factors such as software localization, rapid development of AI-native applications, and macroeconomic recovery [1] - By 2029, the market size of China's relational database software is projected to reach $11.03 billion, with a compound annual growth rate (CAGR) of 20.8% from 2024 to 2029 [1] Market Trends - The growth in the relational database market is driven by the trend of software localization and the increasing adoption of AI technologies [1] - The macroeconomic recovery is also contributing to the positive outlook for the relational database market in China [1]

Core Viewpoint - ByteDance's Doubao large model family has made significant advancements, including the release of Doubao 1.6 and Seedance 1.0 pro, showcasing top-tier performance in complex reasoning and multi-turn dialogue while reducing customer costs significantly [1][4]. Model Capabilities and Market Position - Doubao 1.6 has achieved a daily token usage exceeding 16.4 trillion, a 137-fold increase since its initial launch in May last year [4]. - According to IDC, Doubao holds the largest market share in China's public cloud large model market at 46.4% [4][29]. Financial Industry Applications - The financial sector is leading the way in the large-scale application of AI, with major banks and securities firms adopting AI solutions for various functions, including AI apps and digital employees [4][5]. - A survey by NVIDIA indicated that 98% of financial institutions plan to increase AI infrastructure investment by 2025, with over 40% of Chinese respondents citing operational efficiency as the primary advantage of AI [7]. AI Native Applications - The demand for AI native applications in finance has surged, with institutions actively developing AI capabilities to enhance service quality and operational efficiency [6][10]. - Fire Mountain Engine's financial industry general manager emphasized that AI native applications are essential for the digital transformation of financial services, enabling a shift from traditional models to more intelligent, data-driven approaches [12][17]. Specific Use Cases - Financial institutions like Guotai Junan Securities and Huayin Securities are developing AI applications to improve investment research and customer service, leveraging Doubao's capabilities [9][18]. - The "Guotai Stock Assistant" and "Dolphin App" are examples of AI applications designed to provide personalized financial services and enhance user experience [18][19]. Challenges and Solutions - Despite the potential of AI applications, challenges such as model hallucination and data utilization remain prevalent in the financial sector [20]. - Fire Mountain Engine offers targeted solutions to address these challenges, focusing on cost-effective model selection and implementation strategies [21][22]. Growth and Future Outlook - The growth trajectory of AI applications in finance is steep, with Fire Mountain Engine leading in market share and project wins in the financial sector [29][30]. - As financial institutions continue to invest in AI, the development of intelligent risk control and automated decision-making is expected to accelerate [30].

Core Insights - The demand for enterprise-level AI Agents is expected to explode by 2025, with Minglue Technology at the forefront of AI technology exploration in various industry scenarios [1] - Minglue Technology has launched the AgentShow website, showcasing nearly 20 AI Agents tailored for different industry applications, demonstrating the company's capabilities in complex scenario development [1] - The AI Agents are built on self-developed large models and leverage years of experience in data intelligence, ensuring precise user intent understanding and efficient task handling [1] - Minglue Technology has partnered with Dify, an open-source large language model application development platform, to provide private deployment and technical support, facilitating seamless integration of generative AI from foundational technology to business applications [1] Company Strategy - Minglue Technology believes in creating long-term, sustainable business growth through technology, focusing on customer-centric approaches and understanding the challenges faced during digital transformation [2] - The company aims to deepen its development of AI applications in vertical fields, expanding the application scenarios and methods for enterprise-level Agents [2]

Core Insights - The current trends in AI applications include richer interactive experiences, more efficient model usage, and quicker application development, which are being addressed by Tencent Cloud's continuous product updates [1][5] - Tencent Cloud has launched the "Tencent Cloud Voice PaaS Solution," integrating advanced ASR and TTS models with real-time communication capabilities to enhance user interaction experiences for enterprises [2][7] - The TI platform has undergone comprehensive upgrades to improve model training capabilities, including support for various training methods and enhanced resource scheduling, which significantly reduces costs for enterprises [8][9] Group 1: AI Application Trends - The integration of large language models and multimodal models is evolving user interactions from text to voice and video, increasing the penetration of AI applications [5] - Efficiency in training and inference is improving through better resource management and optimization, leading to lower model usage costs and broader application scenarios [5] - The rapid deployment of intelligent agents is lowering the barriers for enterprises to build AI applications, enabling quick implementation through tools like the intelligent agent development platform [5][10] Group 2: Product Innovations - The "Tencent Cloud Voice PaaS Solution" creates a full-loop interaction model that allows for low-cost and rapid deployment of voice interaction solutions for enterprises [2][7] - The TI platform has been upgraded to support more training methods, including distillation and reinforcement learning, and has introduced capabilities for autonomous driving model training [8][9] - The platform's resource scheduling improvements allow for better utilization of computing resources, enhancing overall efficiency in AI development [9] Group 3: Intelligent Agent Development - The intelligent agent development platform has been upgraded to include advanced RAG technology and comprehensive agent capabilities, enabling users to quickly build intelligent agents in the era of large models [10][11] - The platform supports a multi-agent collaboration system, allowing for efficient task management and execution across various business scenarios [13][16] - A robust permission configuration system is in place to manage access at multiple levels, ensuring secure and flexible operations for enterprises [14][15]

Core Viewpoint - Alibaba's Q4 FY2025 financial results show steady revenue growth driven by core e-commerce and cloud business, with a notable increase in AI-related demand [3][4][6]. Financial Performance - Alibaba reported Q4 revenue of 2364.5 billion RMB, a 7% year-on-year increase, slightly below market expectations [6][8]. - Adjusted EBITDA reached 326.2 billion RMB, up 36% year-on-year, with an EBITDA margin of 13.8% [7][8]. - Adjusted net profit was 298.5 billion RMB, a 22% increase year-on-year, resulting in a net profit margin of 12.6% [6][7]. Business Segment Analysis - The core e-commerce segment, Taobao and Tmall, generated 1013.7 billion RMB in revenue, a 9% increase, with customer management revenue growing 12% to 710.8 billion RMB [8][9]. - Alibaba Cloud's revenue growth accelerated to 18%, driven by strong demand for AI-related products, marking a significant increase from the previous quarter's 13% [11][19]. - International digital commerce revenue grew by 22% to 335.8 billion RMB, while Cainiao's revenue declined by 12% to 215.7 billion RMB [8][9]. AI and Future Outlook - AI demand is driving significant growth in Alibaba Cloud, with AI-related product revenue achieving triple-digit year-on-year growth for seven consecutive quarters [11][19]. - The company is positioned to benefit from the ongoing AI narrative, with expectations of continued revenue growth from cloud services as AI applications proliferate [20][22]. - Analysts predict that Alibaba Cloud's revenue could double in the next three years, with AI-related revenue potentially increasing from 14% to nearly 40% of total revenue [26][27]. Valuation and Market Position - The current market valuation of Alibaba is seen as undervalued compared to its potential growth, with estimates suggesting a comprehensive valuation of around 380 billion USD for FY2025, indicating at least a 25% upside from current levels [32][33]. - The company is expected to leverage its AI capabilities and cloud infrastructure to drive future growth, similar to the previous expansion cycles seen in the cloud computing market [30][31].

Group 1: AI Going Global Landscape and Opportunities - The current global AI going-out landscape is divided into North America, Europe, and Southeast Asia, with technological innovation and localization being key opportunities and challenges for companies [4] - Companies must invest in localization as it is a necessity rather than an option, as many enterprises have faced elimination due to neglecting this aspect [4] - There is an opportunity for "arbitrage between different language systems," particularly in the Japanese and Korean markets, where competition is lower compared to Europe and the US [4] Group 2: AI Application Growth and Infrastructure - AI applications have entered a rapid growth phase, with a significant increase in the number of applications globally, where China accounts for 356 out of 1890 applications, with 143 being overseas products [7][8] - The cost of running inference models is decreasing, with annual reductions exceeding 90%, making it more feasible for companies to adopt AI solutions [7] - Companies need to choose GPU services that can provide global data center coverage and elastic scaling capabilities to support their AI applications [8] Group 3: AI Native Applications and Database Importance - The transition to AI native applications requires three key pillars: large models, Model Context Protocol (MCP), and databases designed for large language models (LLMs) [12] - Traditional databases are often not designed for LLMs, which necessitates a new approach to data storage and access to support personalized services [12] Group 4: Compliance and Legal Challenges - Companies must navigate complex legal and regulatory frameworks when going global, focusing on areas such as data protection, consumer rights, and intellectual property [18] - A systematic compliance management strategy is essential, including establishing AI regulatory teams and developing internal policies to address potential risks [18] Group 5: Successful Strategies for Going Global - Companies like PixelBloom have successfully captured market share by leveraging AI products and creating a complete commercial loop from user acquisition to vertical market penetration [22] - VAST is building a creator ecosystem through its 3D model platform, focusing on community engagement and open-source technology to foster growth [26] - Bocha AI is entering the global market with its LangSearch API, which has seen significant usage and aims to compete with established players like Bing [29][30] Group 6: Sustainable Global Expansion - The current domestic market is characterized by severe homogenization, prompting companies to seek opportunities abroad, particularly in regions like the Middle East and Japan [33] - Companies should focus on deepening their understanding of local markets and developing differentiated, industry-specific applications to create sustainable competitive advantages [33]

Core Insights - The 2025 AI Partner Conference, hosted by 36Kr, focused on the transformative impact of AI applications across various industries, emphasizing the emergence of "Super Apps" and the concept of AI-native applications [1][4] - The conference highlighted significant breakthroughs in AI, particularly with the launch of DeepSeek and Manus, which are expected to drive a new wave of AI application development in 2025 [1][4] Group 1: AI Application Trends - The conference featured discussions on how AI technologies are reshaping business logic and industry structures, with a focus on the potential of AI-native applications [1][4] - Key speakers shared insights on their experiences with AI innovations, noting that AI is fundamentally changing traditional production chains and enhancing operational efficiency [7][10][11] Group 2: Industry Perspectives - Various industry leaders discussed their companies' advancements in AI, such as 趣丸科技's AI voice creation platform, which significantly reduced production cycles and costs in content creation [7][10] - The emergence of DeepSeek was compared to the impact of ChatGPT, indicating a paradigm shift in AI understanding and application [10][11][12] Group 3: Challenges and Opportunities - The panelists identified challenges in AI application deployment, including the need for specialized knowledge bases to enhance user experience and the importance of addressing specific cultural nuances in translation [51][52] - The discussion emphasized the necessity of aligning AI capabilities with real business needs and the importance of commercial viability in AI applications [68]