Investment Rating - The report does not explicitly state an investment rating for the industry. Core Insights - Huawei is exploring a "soft and hard integration" strategy to enhance its AI competitiveness, transitioning from merely catching up with industry SOTA models to customizing model architectures for its self-developed Ascend hardware [12][30]. - The evolution of the Pangu model series reflects a shift from parameter competition to a focus on efficiency and scalability, culminating in the adoption of the Mixture of Experts (MoE) architecture [12][30]. - The report highlights the introduction of innovative architectures like Pangu Pro MoE and Pangu Ultra MoE, which aim to maximize the utilization of Ascend hardware through structural and system-level optimizations [36][62]. Summary by Sections 1. Evolution of Pangu Models - The Pangu model series began with PanGu-α, a 200 billion parameter model, which established a technical route based on Ascend hardware [12][30]. - PanGu-Σ, launched in 2023, marked an early attempt at sparsification, exploring trillion-parameter models with a focus on efficiency [15][18]. - Pangu 3.0 introduced a "5+N+X" architecture aimed at deep industry applications, showcasing its capabilities in various sectors [22][23]. 2. Pangu Pro MoE and Pangu Ultra MoE - Pangu Pro MoE addresses the challenge of expert load imbalance in distributed systems through a new architecture called Mixture of Grouped Experts (MoGE) [36][37]. - The MoGE architecture ensures load balancing by structuring the selection of experts, thus enhancing efficiency in distributed deployments [45][46]. - Pangu Ultra MoE emphasizes system-level optimization strategies to explore the synergy between software and hardware, reflecting a practical application of the soft and hard integration concept [62]. 3. CloudMatrix Infrastructure - CloudMatrix serves as the physical foundation for AI infrastructure, enabling high-performance communication and memory management across distributed systems [5][10]. - The infrastructure supports the Pangu models by providing a unified addressing distributed memory pool, which reduces performance discrepancies in cross-node communication [5][10]. 4. Full-Stack Collaboration - Huawei's AI strategy is centered around full-stack collaboration, integrating open-source strategies to build an ecosystem around Ascend hardware [10][12]. - The architecture, systems, and operators form the three pillars of this full-stack collaboration, aimed at enhancing the overall efficiency and effectiveness of AI solutions [10][12].

Core Viewpoint - Horizon Robotics aims to build a foundational platform that empowers various robotic applications, positioning itself as a leader in the robotics era, particularly in the automotive sector [4][10]. Group 1: Company Milestones - Horizon Robotics celebrated its 10th anniversary on June 1, marking its evolution from being the first Chinese company focused on deep neural network computing solutions to becoming the largest mass-production intelligent driving technology company in China [4]. - The company is set to officially list on the Hong Kong Stock Exchange on October 24, 2024, achieving the largest IPO for a Chinese tech company since 2022 and the fastest entry into the Hang Seng Tech Index [4]. - Horizon has been included in the FTSE Global Equity Index Series, effective June 20, 2024, enhancing its visibility to global investors [4]. Group 2: Market Position and Collaborations - Horizon has established partnerships with over 40 automotive manufacturers, including the top ten Chinese car companies, and has achieved over 8 million units of pre-installed production [12][14]. - The company holds a market share exceeding 40% in the Chinese OEM Advanced Driver Assistance Systems (ADAS) market for 2024, maintaining its position as the leading supplier of intelligent driving solutions [14]. - Horizon's technology is currently integrated into one out of every three intelligent vehicles in China, with expectations to surpass 10 million units shipped by the end of the year [12][14]. Group 3: Technological Innovations - Horizon Robotics has consistently focused on the integration of hardware and software, achieving over 1000 times improvement in computing performance over the past decade [23][25]. - The company has introduced significant advancements in its core algorithms, including the end-to-end autonomous driving model UniAD and the next-generation Vision Mamba model, which has gained recognition in the AI research community [24]. - Horizon emphasizes the importance of continuous technological breakthroughs to establish a long-term competitive advantage, with a commitment to high R&D investment, projected at approximately 5 billion yuan for 2024 [21][25]. Group 4: Future Vision - The long-term vision of Horizon Robotics, referred to as "Horizon 2.0," focuses on expanding into the general robotics field, with automotive applications being the initial focus [10][19]. - The company aims to leverage its technology to enhance automation capabilities in various sectors, including elder care, household service robots, agriculture, manufacturing, and logistics [10]. - Horizon's strategy includes deepening collaborations with a wide range of partners to drive advancements in intelligent driving and ensure safer, more efficient transportation solutions for everyone [19].

Core Viewpoint - Company has transformed into a leading supplier of intelligent driving solutions over the past decade, focusing on full-scene intelligent driving solutions and achieving significant revenue growth with a CAGR of 72.2% from 2021 to 2024 [2][36]. Company Overview - Company has established a comprehensive technology stack covering algorithms, dedicated processing architecture (BPU), and development toolchains, positioning itself as a "chip + software" system-level intelligent driving company [4][9]. - The company has formed a complete layout of intelligent driving chip solutions covering levels L2 to L4, with over 310 models targeted by the end of 2024 [4][12]. - The company has built a large and high-quality customer base, including over 40 cooperative automakers and covering more than 290 models [4][36]. Business Segments - The company's revenue is primarily derived from automotive solutions, which accounted for 97% of total revenue in 2024, with product solutions contributing 27.9% and authorized service business contributing 69.1% [28][36]. - Non-automotive solutions, which focus on smart home applications, accounted for 3% of total revenue in 2024 [28][36]. Financial Performance - The company's revenue increased from 467 million RMB in 2021 to 2.384 billion RMB in 2024, with a CAGR of 72.2% [36][41]. - The gross margin has remained stable around 70%, increasing to 79% in 2024 due to the higher contribution from high-margin authorized service business [36][41]. - Operating losses have been controlled, with losses around 2 billion RMB, and the company is expected to achieve breakeven in the coming years as revenue increases and costs are managed [37][41]. Industry Trends - The intelligent driving market is expected to accelerate penetration, with 2025 anticipated to be a pivotal year for "intelligent driving equality," as traditional automakers ramp up their intelligent driving strategies [3][54]. - The price of high-level intelligent driving packages is decreasing, making advanced driving features more accessible to consumers [3][54]. - The integration of intelligent driving technology into mainstream vehicles is expected to become a standard feature, with major automakers like BYD and Xpeng leading the charge [3][54].

Investment Rating - The report maintains a "Buy" rating for the company, indicating a positive outlook on its future performance [4][6]. Core Insights - The company is positioned as a leading provider of domestic intelligent driving solutions, having undergone significant transformation over the past decade. It has established a comprehensive product portfolio that includes both automotive and non-automotive solutions, with a strong focus on intelligent driving technology [1][15]. - The intelligent driving industry is expected to accelerate its penetration into mainstream markets, with 2025 projected to be a pivotal year for "intelligent driving equality." Major automotive manufacturers are increasingly adopting intelligent driving strategies, which will create opportunities for leading suppliers [2][48]. - The company has built a robust ecosystem that empowers partners in the intelligent driving space, leveraging its complete technology stack that spans algorithms, specialized processing architectures, and development tools [3][4]. Summary by Sections Company Overview - The company has evolved into a key player in the intelligent driving sector, providing comprehensive advanced driver assistance systems (ADAS) and high-level autonomous driving (AD) solutions. It has a significant market share in the domestic market, exceeding 40% in the advanced driving assistance segment [15][18]. - The company has established a large and high-quality customer base, with over 310 models targeted for production by the end of 2024, reflecting its strong market presence [29][39]. Industry Insights - The intelligent driving market is witnessing a shift towards affordability, with traditional manufacturers like BYD and Geely launching strategies to democratize intelligent driving technology. This trend is expected to reshape the industry landscape [2][48]. - The report highlights the importance of third-party suppliers in the intelligent driving ecosystem, as they can provide scalable solutions to traditional manufacturers, thereby accelerating the adoption of advanced driving technologies [12][13]. Financial Performance - The company has experienced significant revenue growth, with a compound annual growth rate (CAGR) of 72.2% from 2021 to 2024, increasing from 467 million RMB to 2.384 billion RMB. The automotive solutions segment accounts for 97% of total revenue, with a strong contribution from licensing and service fees [39][46]. - The gross margin has remained stable, with an increase to 79% in 2024, driven by the higher proportion of high-margin licensing and service revenues [39][46]. Future Outlook - The company is expected to continue expanding its market share in the intelligent driving sector, with projected revenues of 3.603 billion RMB, 5.264 billion RMB, and 7.645 billion RMB for 2025, 2026, and 2027, respectively [4][5].

Core Insights - The automotive industry is experiencing a shift from traditional E/E architecture to a centralized architecture, enabling companies to take control of software development and redefine vehicle core functionalities [1] - The trend towards self-developed chips is driven by the desire to capture profits from the high-margin ends of the "smile curve" (chips and algorithms) [1] - The "smart driving equality" movement initiated by BYD presents both opportunities for automakers and a historic chance for smart driving suppliers [2] Industry Dynamics - In the context of intensified competition and the saturation of smart driving solutions, automakers prioritize getting their products to market rather than focusing solely on self-development [2][3] - The window for automakers to capitalize on this trend is limited to approximately two years [3] Competitive Landscape - NVIDIA currently dominates the smart driving market with a 45.4% share, primarily due to its Orin-X chip, which is highly regarded for its AI acceleration capabilities [4] - New entrants in the market, such as Horizon and Black Sesame, have made significant advancements in chip capabilities, allowing them to compete with NVIDIA's offerings [5][8] - The validation timeline for domestic chips is only 2-3 years behind NVIDIA, indicating a narrowing gap in competition [6][8] Chip Development and Cost Analysis - The development of chips is a long-term endeavor, with significant time required for accumulation and iteration [10] - Companies need to achieve a minimum production scale and possess strong iteration capabilities to make self-developed chips economically viable [11] - Cost analysis shows that the manufacturing costs of chips vary significantly based on technology nodes, with the total cost for advanced chips reaching up to 3915 yuan [12] Data and Talent Acquisition - Automakers have a substantial advantage in data acquisition for training smart driving systems, with companies like Tesla and Huawei leading in vehicle deployment [15] - The scale of talent and internal collaboration is crucial for the development of advanced smart driving technologies, with major players employing large teams dedicated to this field [16] Conclusion - BYD, while relying on external suppliers for chips and algorithms, is actively working on self-developed smart driving solutions, indicating a trend among leading automakers to balance self-development with external sourcing [17]

Core Viewpoint - The tightening of regulations in the intelligent driving industry is seen as beneficial for clarifying product definitions and safety levels, leading to more transparent marketing practices [1][2]. Group 1: Regulatory Changes - The Ministry of Industry and Information Technology (MIIT) has emphasized that car manufacturers must avoid exaggerated and false advertising, ensuring clear communication of product capabilities [1][2]. - The MIIT has mandated the standardization of terminology, discouraging the use of terms like "autonomous driving" and "intelligent driving," favoring terms like "L2 assisted driving" instead [1][2]. Group 2: Industry Response - Following the MIIT's directives, companies have rapidly adjusted their marketing materials, with some removing the term "intelligent driving" from presentations before major events like the Shanghai Auto Show [1][2]. - The China Automotive Industry Association and the China Automotive Engineering Society have called for the promotion of safe application of combined driving assistance functions and the elimination of misleading marketing practices [2]. Group 3: Market Outlook - The intelligent driving industry is expected to undergo a淘汰赛 (elimination race) over the next one to two years, with a prediction that only a few key players will remain by 2027 [2]. - The competitive landscape is characterized by strong economies of scale and first-mover advantages, with a forecast that China could produce two to three leading companies in the global market [2]. Group 4: Technological Trends - Leading domestic intelligent driving companies are adopting a soft and hard integration approach, which is viewed as a correct direction for achieving optimal performance and cost efficiency [3]. - The focus on soft and hard integration is expected to enhance user experience and pricing strategies in the intelligent driving sector [3].