Core Viewpoint - The Chinese intelligent driving industry is transitioning into a critical phase focused on "scaled commercialization," with key players like Horizon Robotics leading the way in providing essential technological support for various autonomous driving applications [1][10]. Group 1: Industry Developments - Horizon Robotics hosted the "Towards High Together" 2025 Technology Ecosystem Conference, gathering industry leaders to explore innovative paths for high-quality development in the intelligent driving sector [1]. - The company emphasizes the importance of service providers in the autonomous driving ecosystem, who focus on scenario-based services rather than just vehicle manufacturing [1][10]. Group 2: Partnerships and Collaborations - Horizon Robotics collaborates with various partners to provide key technological support for diverse scenarios such as Robotaxi, unmanned delivery, and trunk logistics, showcasing the results of joint research and product creation [3][5]. - GoGoX and Amigo's founders shared their vision for deploying Robotaxi in Hong Kong, aiming to enhance urban transportation experiences [3]. - The partnership with Xing Shen Intelligent focuses on deep integration of autonomous driving technology with logistics, resulting in a cost reduction of 30% for their L4 urban unmanned logistics solution [3]. - New Stone's collaboration with Horizon Robotics has led to the deployment of over 13,000 L4 unmanned vehicles across more than 300 cities globally [4]. Group 3: Technological Innovations - Horizon Robotics' chips and algorithms are integral to the development of autonomous driving systems, with companies like Yingche Technology achieving over 400 million kilometers in commercial operation using Horizon's technology [5][7]. - The KargoBot Space, developed by Karl Power, utilizes Horizon's chips to enhance cargo space and efficiency, marking a significant step towards profitable L4 autonomous freight operations [7]. Group 4: Industry Insights and Future Directions - Industry experts agree that the commercialization and scaling of autonomous driving depend on strong technological support and ecosystem collaboration [8]. - The transition from technology-driven to value-driven approaches in autonomous driving is seen as a critical milestone for the industry [8]. - Horizon Robotics aims to empower partners through foundational computing platforms and AI technology, facilitating the shift towards fully autonomous logistics and commercial vehicles [10].

Core Insights - The autonomous driving industry in China is transitioning from a technology development phase to a commercialization phase, with significant growth expected by 2025, reaching a market size of 218 billion yuan [1] - The investment landscape is characterized by strategic partnerships between industry capital and technology breakthroughs, particularly in core hardware and software [2][3] Upstream Core Hardware and Software - The investment in core chips and sensors is driven by high R&D barriers and capital requirements, leading to strategic investments between leading tech companies and automakers [2] - Huawei's strategic investment of nearly 1.1 billion yuan in Desay SV is expected to enhance collaboration in intelligent driving domain controllers, with revenue from this segment projected to exceed 35% by 2025 [2] - Baidu's venture capital involvement in Hesai Technology aims to secure long-term supply of customized lidar, with market share in the global automotive lidar market expected to reach 28% by 2025 [2] Financial Capital Focus - Financial capital is targeting technology-scarce entities, with companies like NavInfo receiving significant investments from Tencent and Alibaba to enhance data collection capabilities [3] - Momenta has secured over 5 billion yuan in investments, reflecting the high valuation potential of its end-to-end algorithm technology despite being unprofitable [3] Perception and Decision-Making Layers - The perception layer is evolving with the adoption of multi-modal sensor fusion, leading to increased demand for high-performance lidar and cameras [4] - The shift from optional to standard lidar in L3 vehicles is driving up component value, with costs reduced by nearly 50% through partnerships like Baidu and Hesai [4] - High-precision maps are essential for L3 and above autonomous driving, with NavInfo becoming a key partner for major players like Huawei and Baidu [4] Midstream System Integration - Midstream system integrators are crucial in the supply chain, with investments characterized by mutual binding and ecosystem co-development [6][8] - Strategic investments, such as China FAW's 3.6 billion yuan investment in Zhaoyu Technology, are enhancing the integration of intelligent driving technologies into vehicle models [7] - The valuation of midstream companies is heavily influenced by their ecosystem partnerships, with Desay SV's valuation significantly higher due to collaborations with leading firms [7] Downstream Application Scenarios - Investment strategies in downstream applications are evolving based on the maturity of commercial scenarios, with fully enclosed scenarios attracting significant capital [9] - The partnership between State Energy Group and Northern Shares aims to develop electric unmanned mining trucks, projecting a 120% increase in order volume by 2025 [9] - Baidu's Apollo is expanding its Robotaxi fleet, with user payment rates expected to rise to 62% by 2025, indicating strong commercial progress [10][11]

Core Insights - A domestic intelligent driving chip, the Horizon Journey series, has achieved a production and shipment milestone of over 10 million units, making Horizon the first domestic intelligent driving technology company to reach this level of shipment volume [1] Company Summary - Horizon has become the first domestic intelligent driving technology enterprise to surpass a shipment volume of 10 million units, indicating significant growth and market penetration in the intelligent driving sector [1]

Core Insights - Jinqiu Fund is dedicated to supporting innovative founders in the AI sector and engaging with leading AI pioneers to navigate industry transformations [2][3] - The first "AI Pioneers" list was recently announced, highlighting key figures in the AI field who are shaping the future [3][14] Group 1: Evaluation Process - The evaluation panel for the "AI Pioneers" list included industry experts from investment and media, as well as innovative developers and prominent figures from the Zhihu community [4][6] - The selection criteria focused on five dimensions: innovation, critical thinking, influence, ecological value, and development potential [12][13] Group 2: Notable Figures - The list features prominent individuals such as Wang Xingxing, CEO of Yushu Technology, and other leaders from institutions like Carnegie Mellon University and the Chinese Academy of Sciences [3][24][26] - These individuals are recognized for their contributions to AI technology, including advancements in deep learning frameworks and AI applications across various industries [19][21][23] Group 3: Future Outlook - The "AI Pioneers" list serves not only as a recognition of current leaders but also as a record of those exploring new boundaries and developing innovative tools in the AI landscape [28][29] - The ongoing nomination process for the next list encourages broader participation from the community to identify emerging talents in the AI sector [29]

Core Viewpoint - The article discusses the evolution of autonomous driving technology, highlighting the competitive landscape among major tech companies, automakers, and startups, and how advancements are reshaping transportation methods [2][3]. Group 1: Tesla's Development - Tesla is recognized as a pioneer in autonomous driving, with its aggressive data-driven approach that discards traditional methods like LiDAR and high-definition maps in favor of pure visual perception [6]. - The development path includes the transition from modular designs to end-to-end neural networks, aiming to make AI think and drive like humans [6]. - Key technologies introduced include BEV (Bird's Eye View) and Occupancy Network, enhancing spatial awareness and reducing reliance on high-definition maps [8][12]. Group 2: Huawei's Progress - Huawei's ADS technology has evolved from multi-sensor fusion and high-definition map reliance to a "mapless" approach, enhancing perception algorithms and ultimately leading to end-to-end model applications [23]. - The ADS 1.0 version relied on multiple sensors and high-definition maps, while ADS 2.0 marked a breakthrough in "mapless" driving [25][26]. - The latest ADS 3.0 aims for full scene intelligent driving, integrating advanced perception networks and optimizing hardware for better performance [28]. Group 3: Momenta's Strategy - Momenta employs a dual strategy of data-driven algorithms and mass production of autonomous driving products, creating a feedback loop for continuous improvement [33]. - The company focuses on low-cost automated mapping and crowd-sourced map updates, enhancing its capabilities in complex environments [35]. Group 4: Horizon's Path - Horizon has developed a unique path from automotive-grade AI chips to full-stack solutions, emphasizing software and hardware collaboration for efficiency [47]. - The company has progressively advanced from early ADAS prototypes to L2+ and L3 capabilities, with plans for broader applications in 2025 [49][50]. Group 5: Xiaopeng's Evolution - Xiaopeng's autonomous driving journey reflects a shift from multi-sensor fusion and high-definition maps to a "mapless" approach, driven by AI large models [79]. - The XPILOT series has evolved from basic parking assistance to advanced highway and urban navigation capabilities, with significant improvements in system generalization [81][90]. Group 6: NIO's Development - NIO's approach is characterized by a cautious evolution from collaborative development to full-stack self-research, focusing on safety and reliability [98]. - The introduction of the World Model NWM in 2025 signifies a new phase in NIO's autonomous driving capabilities, enhancing cognitive and reasoning abilities [110].

Core Viewpoint - The report from Huachuang Securities sets a target price of HKD 12.44 for Horizon Robotics-W (09660) and maintains a "Recommended" rating, highlighting the company's positive revenue outlook and its role as a rare third-party full-stack intelligent driving solution provider in China [1] Group 1: Revenue and Market Position - The company is expected to ship 4 million, 5.04 million, and 7 million units of its solutions in 2025-2027, representing year-on-year growth of 38%, 26%, and 39% respectively [1] - Revenue projections for the same period are set at CNY 36.2 billion, 58.5 billion, and 83.9 billion, with year-on-year growth rates of 52%, 62%, and 43% [1] - The company holds the largest market share in China for basic ADAS and overall ADAS solutions at 45.8% and 32.4% respectively [2] Group 2: Product Development and Partnerships - The HSD (Horizon SuperDrive) solution is set for mass production, with the first vehicle featuring this technology, the Chery Star Era ET5, expected to launch in November 2025 [1] - The company has established a European headquarters in Munich and is building deep connections with international clients such as Bosch, Continental, and Volkswagen [1] - The company has achieved a significant increase in chip shipments, with 1H25 seeing a doubling of J series chip shipments to 1.98 million units and a fivefold increase in shipments of chips supporting NOA functionality [2] Group 3: Index Inclusion and Investment Appeal - The company was included in the Hang Seng Composite Index and the Hang Seng Technology Index in March 2025, enhancing its visibility and investment appeal [3] - The company is considered a rare AI-related stock in the Hong Kong market, with both configuration value and risk appetite on the rise [3]

Core Insights - The rapid development of autonomous driving technology in China is highlighted as a global standout, with significant advancements made by companies like XPeng, Li Auto, NIO, Xiaomi, and BYD [2] - The Chinese autonomous driving industry is transitioning from technology validation to large-scale application, with a notable increase in the sales of smart connected vehicles equipped with driver assistance systems [2][4] - The integration of a complete technology ecosystem in China, encompassing multi-modal sensor fusion, deep learning algorithms, and real-time V2X interactions, has established a comprehensive "perception-decision-control" technology stack [2][4] Industry Overview - China's autonomous driving market is characterized by a competitive landscape where leading companies dominate while smaller firms engage in differentiated competition [4] - The supply chain's completeness and the size of the market contribute to the industry's growth, with significant advancements in chip production, algorithm development, and vehicle manufacturing [4] - The vertical integration of "chip-algorithm-vehicle" capabilities has positioned China favorably in the L2+ level driver assistance sector [4] Market Trends - The global shift towards higher-level autonomous driving technologies is accelerating, with L1/L2 functionalities now covering over 50% of new vehicle sales [4] - By 2030, L2+ systems are expected to become standard in new vehicles, with L3 and above accounting for 50% of the market [4] - Chinese manufacturers are leading the way in this transition, with products like XPeng's XNGP and Huawei's ADS 3.0 already implementing advanced navigation assistance features [4] Future Projections - The cost of high-level autonomous driving features is anticipated to decrease significantly, making them essential for vehicles priced above 200,000 yuan starting in 2025 [5] - The emergence of large model training-driven autonomous driving solutions is expected to further lower costs and enhance accessibility [5] - Industry experts predict that China could implement the world's most advanced and largest-scale fully autonomous driving systems within five years [5]

Investment Rating - The report suggests to pay attention to the industry and its developments [4] Core Insights - The high-level intelligent driving technology is becoming more accessible by 2025, with an upward trend in the industry chain's prosperity driven by mature supply-side technologies and demand-side strategies [3][9] - The new paradigm of computing power in vehicles includes DSA heterogeneous integration, cockpit fusion, and RISC-V architecture, which enhances algorithm optimization and cost efficiency [3][10][17] - Domestic alternatives are emerging with quality supply, and there is potential for technology to go abroad, especially in the mid-to-high-end NOA segment [3][24][26] - The trend of integrated hardware and software is leading to competitive intersections among various players, with traditional manufacturers and new forces both investing in self-research and collaboration [3][27] - The economic analysis of self-research in intelligent driving indicates an annual cost of approximately 2 billion RMB, with significant investments in SoC and algorithms [3][28] Summary by Sections 1. New Paradigm of Computing Power - The supply side is seeing advancements in intelligent driving hardware and software, with improved cost-performance ratios [3][9] - The demand side is influenced by traditional manufacturers promoting lower price points for intelligent driving features [3][9] - The architecture is evolving towards a more integrated approach, moving from multi-box systems to single-chip solutions [3][14] 2. Domestic Alternatives and Technology Export - The domestic market is seeing a growing presence of local suppliers in the mid-to-high-end NOA segment, with companies like Horizon Robotics and Black Sesame emerging as key players [3][26] - The low-end segment remains dominated by foreign companies, but domestic technologies are expected to expand internationally [3][26] 3. Competitive Landscape and Self-Research - Leading companies are enhancing their capabilities by integrating computing power, toolchains, and algorithms [3][28] - The competition is intensifying as companies like Huawei and Tesla are investing heavily in self-research and development of their own chips and algorithms [3][27] - The report highlights the importance of a comprehensive approach to self-research, with significant financial commitments required to maintain competitiveness [3][28] 4. Company Analysis - Companies like NVIDIA and Huawei are leading in hardware performance and ecosystem development, while also seeking to strengthen their algorithm capabilities [3][32][39] - Horizon Robotics is positioned as a leader in providing integrated intelligent driving solutions, with a focus on software and service revenue [3][51]