截至目前， 地平线 HSD已与全球近10家汽车品牌达成合作意向，全球首发搭载奇瑞的星途星纪元 E05量产在即 。 截至目前，地平线HSD已与全球近10家汽车品牌达成合作意向。 本文为IPO早知道原创 作者｜ Stone Jin 微信公众号｜ipozaozhidao 据 IPO早知道消息， 地平线 日前 发布 了 有史以来最大升级的高性能城区辅助驾驶产品 HSD （ Horizon SuperDrive） ，其作为 基于征程 ®6P打造的一段式端到端辅助驾驶系统，实现了从"光 子输入到轨迹输出"的系统超低时延，大幅提升 了 辅助驾驶安全、效率、舒适。 值得一提的是， 地平线最新版本的 HSD 现已被誉为 "国内最像特斯拉FSD的辅助驾驶系统" —— HSD可行驶区域覆盖城区、高速、乡间小路、停车场等道路场景 ， 不仅在连续弯道、多出口大型环 岛等复杂道路拓扑环境下，依然能实现精准感知与丝滑通行，还能从容完成高难度直行待行区识别、 盲区遮挡防御性驾驶、潮汐车道通行等复杂城区驾驶任务，并实现不依赖于记忆建图的园区漫游及车 位到车位的流畅驾驶 。 某种程度上而言， HSD 于今年年初的发布及日前完成的进一步迭代，再一 ...

Core Viewpoint - The emergence of Momenta's self-developed driving chip marks a significant shift in the domestic intelligent driving industry, transitioning from a software-only company to a full-stack supplier, posing new competitive challenges to existing players in the market [1][2][20]. Company Overview - Momenta, established in 2016, focuses on high-performance intelligent driving solutions, targeting both L2 and L4 markets, and has partnerships with major global automakers, including SAIC, BYD, and Toyota [2][3]. - The company holds the largest market share in urban NOA technology at 60.1%, with cumulative sales of 114,000 vehicles equipped with its technology [3][19]. Self-Developed Chip Significance - Momenta's self-developed chip is positioned for the mid-range market, offering cost advantages and compatibility with existing products, which enhances its competitive edge [6][19]. - The strategy of "downward integration" is expected to create stronger competitive barriers and higher value capture capabilities for the company [6][10]. Impact on Competitors - The introduction of Momenta's chip poses significant challenges to NVIDIA and Qualcomm, as it allows automakers to transition smoothly from their solutions, increasing competitive pressure on these established players [8][10]. - Domestic chip manufacturers like Horizon Robotics and Black Sesame are also facing heightened competition, as Momenta's software expertise may overshadow their advantages [10][11]. Implications for Automakers - Automakers are reevaluating the necessity and cost-effectiveness of in-house chip development in light of Momenta's competitive offerings, particularly for resource-constrained new entrants [12][14]. - The shift towards Momenta's integrated solutions may lead to a reassessment of self-research strategies among automakers, balancing differentiation with cost advantages [15][21]. Strategic Challenges Ahead - Momenta faces challenges in achieving large-scale production and meeting stringent automotive safety standards, which are critical for its long-term success [20][21]. - The competitive landscape is expected to intensify as established players like NVIDIA and Qualcomm may respond with price cuts or enhanced technology to counter Momenta's market entry [20][21].

传闻与否认之中，也反映出市场对字节在AI硬件领域的高度关注。 截至目前，字节在AI+硬件领域已经布局了什么？ 字节不止一次做过硬件。 2020年，字节推出教育品牌大力教育，并发布大力智能学习灯等教育硬件产品。但随着行业监管趋严， 教育业务线整体逐渐收缩。 8月19日，据晚点报道，字节跳动将在今年底或明年初推出AI手机，由中兴作为ODM厂商代工，暂名 为"豆包手机"，早期主要用于字节内部团队的测试。 对此，豆包方面回应称目前没有推出自己手机产品的计划，正在持续探索将AI能力开放给包括手机在 内的各种硬件厂商，但不涉及自有手机产品的研发与推出。 这并非首次传出类似消息。今年年初还有媒体报道字节跳动将与努比亚合作开发AI手机，字节跳动官 方对此回应称信息不实，没有相关计划。 与此同时，芯片领域也有类似"风声"。8月20日，另一则市场传闻称字节跳动正与芯原股份联手设计一 款先进的AI算力芯片。对此字节再次否认，称字节跳动与芯原股份并无AI芯片相关合作。2023年也有 传闻字节与美国博通公司合作开发AI处理器，将由台积电制造，后被否认。 综合目前信息，字节在AI硬件的布局已经存在且成体系。手机、耳机、眼镜，无论最终以何 ...

Core Viewpoint - The integration of a general brain and general body is the paradigm for constructing general humanoid robots, emphasizing learning from humans as the shortest path to achieve this goal [2][4][15]. Group 1: General Brain and Body Integration - The fusion of a general brain and general body creates a physical world AI evolution flywheel, where a unified model empowers various humanoid robot bodies, adapting to different scenarios and iterating through data feedback [4]. - The ERA-42 general brain model has been released, integrating vision, understanding, prediction, and action, enabling high degrees of freedom in humanoid robot operations through voice commands [4][5]. - The company has developed a fully self-researched supply chain for core components, ensuring high-quality and efficient delivery of products [4]. Group 2: Product Development and Market Position - The company has launched the first full-size bipedal humanoid robot, "Xingdong L7," which surpasses Tesla's Optimus in performance, featuring 55 degrees of freedom and targeting industrial and commercial applications [5][8]. - The "Xingdong Q5" service robot is designed for various scenarios, including retail and healthcare, with over a hundred strategic orders secured from major companies [5][8]. - The company has delivered over 300 products this year, with a significant portion of its market share now coming from overseas, exceeding 50% [8]. Group 3: Software and Hardware Integration - The company has adhered to a "soft and hard integration" approach from the beginning, focusing on developing both the humanoid model and motion control simultaneously [10][11]. - The software is primarily defined by hardware, with models adaptable to various hardware types, ensuring performance optimization [18]. Group 4: Open Source and Industry Trends - The company has released the world's first open-source algorithm for control reinforcement learning, which has gained significant popularity in the humanoid robotics community [20]. - The open-source culture in the AI field has accelerated research and development, leading to a convergence of technology routes [21][22]. Group 5: Future Applications and Market Potential - The company anticipates achieving over 90% efficiency in industrial applications by next year, with ongoing improvements in both software and hardware [26][27]. - The long-term "killer application" for humanoid robots is expected to be in household scenarios, with initial deployments in B2B industrial settings [28][29].

Core Viewpoint - The integration of AI into hardware is essential for creating valuable services and enhancing user experience, marking a shift towards a collaborative and tool-oriented era for large models [1][4][15]. Group 1: AI Hardware Development - The future of AI hardware will excel in scenarios where traditional hardware falls short, with the integration of software and hardware being key to achieving this [4][15]. - Successful products attract top talent, which is crucial for creating competitive offerings in the market [4][15]. - Companies like Plaud and Rokid have gained early advantages by recognizing real user needs and investing in product development before the rise of large models [6][7]. Group 2: Market Dynamics and User Engagement - Crowdfunding success for Plaud was driven by a combination of genuine user demand and strong design appeal, which is critical for hardware products [7][8]. - The AI integration in hardware has led to increased market recognition, with many manufacturers seeking ways to embed AI into their products [8][9]. - The evolution of hardware focuses on lightweight designs to cater to a broader user base, including children and the elderly [9]. Group 3: Competitive Landscape - The competitive edge lies in the ability to gather contextual information effectively, which is essential for differentiating software capabilities [11][12]. - Large companies often overlook the hardware sector due to its challenges, creating opportunities for startups to thrive [12][16]. - The core value of integrated software and hardware in AI applications is to create a seamless user experience, which requires comprehensive team capabilities [12][13]. Group 4: Technical Challenges and Innovations - Multi-modal interaction presents significant technical challenges, particularly in understanding user intent and context [17][19]. - The integration of various data types (audio, visual, etc.) is crucial for enhancing AI's understanding of user interactions [19][20]. - Ensuring user privacy and data security is paramount as multi-modal capabilities expand [23][20]. Group 5: Future Outlook and Market Education - The market for AI hardware is still in its early stages, requiring patience and education to encourage user adoption [26][28]. - The ultimate form of smart wearable devices will be lightweight and unobtrusive, becoming a part of daily life [33]. - Establishing user trust is critical for the success of AI hardware, as users must feel secure in sharing their data [37].

Investment Rating - The report does not explicitly state an investment rating for the AI industry or Huawei's AI initiatives. Core Insights - Huawei is exploring a full-stack AI competitive strategy through the integration of software and hardware, transitioning from merely catching up with state-of-the-art (SOTA) models to customizing model architectures to better leverage its self-developed Ascend hardware [6][20]. - The evolution of the Pangu model series reflects a shift from dense models to sparse architectures, addressing systemic issues in large-scale distributed systems and enhancing efficiency [6][22]. - The introduction of the CloudMatrix infrastructure supports the optimization of AI inference, enabling high throughput and low latency through a unified bus network and various operator-level optimizations [6][20]. Summary by Sections 1. Evolution of Pangu Models - The Pangu model series began with PanGu-α, a 200 billion parameter autoregressive Chinese language model, which established a technical route based on Ascend hardware [6][8]. - PanGu-Σ, launched in 2023, marked an exploration into trillion-parameter models, introducing a sparse architecture to reduce computational costs [8][10]. - Pangu 3.0 introduced a "5+N+X" architecture, focusing on industry-specific applications and enabling rapid deployment of AI capabilities across various sectors [15][16]. 2. Maximizing Ascend Hardware Efficiency - Pangu Pro MoE and Pangu Ultra MoE are designed to maximize the efficiency of Ascend hardware, with Pangu Pro MoE addressing load imbalance through a grouped expert mixture architecture [25][26]. - Pangu Ultra MoE employs a system-level optimization strategy, utilizing simulation-driven design to enhance performance on Ascend hardware [46][47]. 3. CloudMatrix Infrastructure - CloudMatrix serves as the physical foundation for AI inference, addressing new challenges posed by large language models and enabling high-performance computing through a distributed memory pool [6][20]. - The infrastructure supports various software innovations, allowing for efficient communication and optimization of AI models [6][20]. 4. Full-Stack Collaboration Strategy - Huawei's strategy emphasizes open-source models to build an ecosystem around Ascend hardware, integrating architecture, systems, and operators for comprehensive collaboration [6][20].

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].