Core Viewpoint - The article discusses the significance and application of Diffusion Models in various fields, particularly in autonomous driving, emphasizing their ability to denoise and generate data effectively [1][2][11]. Summary by Sections Introduction to Diffusion Models - Diffusion Models are generative models that focus on denoising, where noise follows a specific distribution. The model learns to recover original data from noise through a forward diffusion process and a reverse generation process [1][2]. Applications in Autonomous Driving - In the field of autonomous driving, Diffusion Models are utilized for data generation, scene prediction, perception enhancement, and path planning. They can handle both continuous and discrete noise, making them versatile for various decision-making tasks [11]. Course Overview - The article promotes a new course titled "End-to-End and VLA Autonomous Driving," developed in collaboration with top algorithm experts. The course aims to provide in-depth knowledge of end-to-end algorithms and VLA technology [15][22]. Course Structure - The course is structured into several chapters, covering topics such as: - Comprehensive understanding of end-to-end autonomous driving [18] - In-depth background knowledge including large language models, BEV perception, and Diffusion Model theory [21][28] - Exploration of two-stage and one-stage end-to-end methods, including the latest advancements in the field [29][36] Learning Outcomes - Participants are expected to gain a solid understanding of the end-to-end technology framework, including one-stage, two-stage, world models, and Diffusion Models. The course also aims to enhance knowledge of key technologies like BEV perception and reinforcement learning [41][43].

以下文章来源于42号电波 ，作者大吉 42号电波 . 42HOW 旗下专注 AI 智能硬件与具身智能的科技媒体，致力于深度报道和洞察前沿科技，探索智能技术如何重塑未来生活。 2025年，锦秋基金已完成对地瓜机器人的投资 。 锦秋基金，作为12 年期的 AI Fund，始终以长期主义为核心投资理念，积极寻找那些具有突破性技术和创新商业模式的通用人工智能初创企业。 2025年8月29日，42号电波对地瓜机器人进行了报道，以下为此次报道的转载。 对话地瓜机器人隋伟：VGGT、数据闭环与具身智能，机器人产业的新篇章 人工智能正经历一场新的范式转变。十年前， 自动驾驶 还是技术最前沿的舞台：从早期的模块化感知与规则驱动，到 2019 年之后的 BEV 与 Transformer 融合，再 到如今端到端的大模型路线，行业经历了数次迭代，如今已进入工程收敛期。但与此同时，另一条平行线—— 机器人 ——正在悄然兴起。 在 2023 年， 隋伟 选择从地平线转向地瓜机器人，正是因为看到了这种交汇的拐点。他在采访中坦言，自动驾驶的技术栈已逐渐收敛，后续更多是工程优化；而机 器人则正处于一个早期未解之地：硬件形态尚未统一，算法框架 ...

Core Viewpoint - The article discusses the advancements in autonomous driving technology, particularly focusing on WePilot AiDrive, a new end-to-end ADAS solution developed by WeRide, which aims to enhance the driving experience and safety through advanced AI capabilities [5][9][10]. Group 1: WeRide's New Technology - WeRide has launched a new end-to-end ADAS solution named WePilot AiDrive, which is set to be mass-produced within the year [5]. - The system integrates sensor data input and vehicle trajectory output into a single model, enhancing the efficiency and responsiveness of autonomous driving [10][24]. - The new system demonstrates improved performance in complex driving scenarios, such as navigating through urban villages and recognizing pedestrians in challenging lighting conditions [12][14][24]. Group 2: Comparison with Previous Systems - The previous two-stage model used separate perception and control models, which often led to data loss and limited understanding of driving environments [25][30]. - The new one-stage model allows for direct learning of the relationship between input data and output trajectories, significantly improving the system's performance [33]. - The transition from a rule-based approach to a more integrated model aims to overcome the limitations of earlier systems, which struggled with generalization and adaptability [32][35]. Group 3: Market Implications - The collaboration between WeRide and Bosch aims to make advanced driving capabilities accessible across various vehicle price segments, not just high-end models [41][44]. - Currently, less than 20% of vehicles in the Chinese market are equipped with advanced intelligent driving features, indicating significant growth potential for WeRide's technology [42]. - The goal is to push L2+ capabilities beyond the "value inflection point," making advanced driving technology more mainstream [44].

Core Viewpoint - Huawei's automotive business has achieved significant milestones, including 1 million vehicles equipped with its driving technology and over 100 million units of laser radar shipped, showcasing its long-term strategic vision in the automotive sector [3][4]. Group 1: Achievements and Strategy - As of July, 1 million vehicles have been equipped with Huawei's QianKun intelligent driving system, and the cumulative mileage for assisted driving has reached 4 billion kilometers [3]. - Huawei's automotive business has been investing since 2014, focusing on R&D rather than immediate commercialization, which has led to current profitability [4][5]. - The company has launched 28 models in collaboration with various brands, indicating a strong market presence [3]. Group 2: Technology Approach - Huawei prefers the World Action (WA) model over the Video Language Action (VLA) model for achieving true autonomous driving, believing WA is a more direct and effective approach [5][13]. - The WA model processes information directly from various inputs like vision, sound, and touch, bypassing the need to convert data into language [5][14]. - Huawei has developed the WEWA model based on the WA architecture, which will be deployed in ADS 4.0 [6]. Group 3: Business Model and Pricing - Huawei's CEO emphasizes that there is no such thing as a free service in the automotive industry; costs are often hidden or transferred [7][17]. - The company believes charging for assisted driving systems is justified due to ongoing costs for updates and maintenance throughout the vehicle's lifecycle [8][18]. - Huawei's approach to lifecycle management ensures that users receive continuous upgrades, enhancing their experience over time [18]. Group 4: Future Plans - Huawei aims to achieve L3 capabilities for highway driving and L4 pilot capabilities in urban areas by 2026, with plans for large-scale commercial use by 2028 [11]. - The company is also working on transforming the intelligent cockpit into a "digital nanny," integrating AI to enhance user experience [11]. Group 5: Safety and Technology Enhancements - Huawei's increase in sensor configurations, such as additional laser radars, is driven by a commitment to safety rather than merely increasing product pricing [19][20]. - The company focuses on enhancing the precision of its systems to prevent accidents and improve user safety in various driving scenarios [20][22].

Core Viewpoint - The launch of the new XPeng P7 is seen as a strategic move to regain a top position in the electric sedan market priced above 200,000 yuan, with a focus on advanced technology and design [1][2]. Group 1: Product Launch and Market Positioning - The new XPeng P7 was launched with four Ultra versions priced between 219,800 and 301,800 yuan, aiming to compete with models like the Xiaomi SU7 and Tesla Model 3 [1][5]. - The target for the new P7 is to achieve sales that place it among the top three in the competitive 200,000 to 250,000 yuan electric sedan market, which has seen a 60% year-on-year sales increase [2][5]. - The P7 received over 10,000 pre-orders within 7 minutes of its launch, indicating strong market interest [5]. Group 2: Production and Profitability - XPeng is ramping up production capacity for the P7, with a focus on quality control and a rapid production pace, aiming for a monthly sales target of around 4,200 units to secure a top market position [5][6]. - The P7 is expected to enhance the company's overall gross margin, with analysts suggesting it could act as a profitability accelerator for XPeng [5][6]. Group 3: Technological Advancements - The P7 features three Turing AI chips, enhancing its intelligent driving capabilities, with a significant update expected by the end of the year [6][7]. - The company has invested nearly 5 billion yuan in the VLA (Vision-Language-Action) technology, indicating a strong commitment to AI development in the automotive sector [10]. Group 4: Future Outlook - XPeng's CEO anticipates that the automotive industry will see higher profit margins in the AI era, with a potential shift from small to significant profits as technology and production capabilities improve [11]. - Despite current challenges, XPeng aims to close the valuation gap with leading competitors like Tesla, with expectations of improved market recognition in the near future [11].

Group 1 - The establishment of the Embodied Intelligence Heart Technology Exchange Group focuses on various advanced technologies including VLA, VLN, remote operation, Diffusion Policy, reinforcement learning, VLA+RL, sim2real, multimodal large models, simulation, motion control, target navigation, mapping and localization, and navigation [1] - Interested individuals can add the assistant's WeChat AIDriver005 to join the community [2] - To expedite the group entry process, it is advised to include a note with the institution/school, name, and research direction [3]

Core Viewpoint - The article emphasizes the recruitment of business partners for the autonomous driving sector, highlighting the need for expertise in various advanced technologies and offering attractive incentives for potential candidates [2][3][5]. Group 1: Recruitment Details - The company plans to recruit 10 outstanding partners for autonomous driving-related course development, research paper guidance, and hardware development [2]. - Candidates with expertise in large models, multimodal models, diffusion models, and other advanced technologies are particularly welcome [3]. - Preferred qualifications include a master's degree or higher from universities ranked within the QS200, with priority given to candidates with significant conference contributions [4]. Group 2: Incentives and Opportunities - The company offers resource sharing related to autonomous driving, including job recommendations, PhD opportunities, and study abroad guidance [5]. - Attractive cash incentives are part of the compensation package for successful candidates [5]. - Opportunities for collaboration on entrepreneurial projects are also available [5].

Core Insights - Huawei's automotive business has achieved significant milestones, including 1 million vehicles equipped with Huawei's QianKun intelligent driving system and over 1 million units of laser radar shipped as of July this year [1] - The company emphasizes a long-term strategic vision, having invested in the automotive sector since 2014, which has led to current profitability without setting explicit commercialization goals [1][4] - Huawei's CEO of the Intelligent Automotive Solutions BU, Jin Yuzhi, believes that focusing solely on commercialization can be counterproductive, advocating for a commitment to technology development and user needs [1] Automotive Business Performance - As of August, 28 models have been launched in collaboration with Huawei, including brands like Audi and Avita [1] - Cumulative mileage for assisted driving has reached 4 billion kilometers [1] - The company has adopted a full lifecycle management approach for its products, ensuring continuous upgrades and maintenance for users [5][16] Technology Strategy - Huawei prefers the World Action (WA) model over the Video Language Action (VLA) model for autonomous driving, believing WA is the ultimate solution for achieving true autonomous driving [3][10] - The WA model processes information directly through vision inputs, eliminating the need to convert data into language, which is seen as a shortcut [3][11] - Huawei has developed the WEWA model based on the WA architecture, which will be deployed in ADS 4.0 [4] Future Plans - Huawei aims to achieve Level 3 (L3) autonomous driving capabilities on highways and Level 4 (L4) pilot capabilities in urban areas by 2026, with plans for large-scale commercial use of L4 by 2028 [9] - The company is also working to transform smart cockpits into "digital nannies," integrating AI as an AI Agent [9] Pricing and Business Model - Jin Yuzhi asserts that there is no such thing as free services in the automotive industry, as costs are often transferred in different forms [4][15] - The pricing for assisted driving systems is justified due to the ongoing costs of iteration, maintenance, and over-the-air updates [5][15] - Users who initially purchase the first version of ADS benefit from continuous upgrades, making the long-term cost of ownership more favorable [16] Safety and Sensor Technology - Huawei's increase in sensor configurations, such as additional laser radars, is driven by a commitment to safety rather than merely increasing product pricing [17][18] - The company aims to enhance safety in various driving scenarios, including parking and urban driving, by improving system precision through advanced sensor technology [17][18]

Group 1 - The article announces the recruitment of teachers for embodied intelligence training, targeting both B-end (business) and C-end (consumer) training services, with compensation above industry standards [1] - The training covers various advanced topics including VLA, VLN, remote operation, Diffusion Policy, reinforcement learning, sim2real, multimodal large models, simulation, motion control, and target navigation [2] - B-end training is aimed at enterprises, universities, and research institutions, while C-end training focuses on students and job seekers, with responsibilities including curriculum design and material preparation [3] Group 2 - Candidates are required to have a doctoral degree or higher (including those currently enrolled), with a preference for those who have published two papers in A-level or Q1 journals/conferences, or have two years of industry experience [3] - Interested individuals can add a specified WeChat contact for further inquiries [4]

Core Viewpoint - Huawei's automotive business is rapidly expanding, particularly in the field of assisted driving, with various collaboration models with car manufacturers being explored [2][3]. Group 1: Collaboration Models - Huawei's automotive business unit (BU) collaborates with car manufacturers through multiple models, including component supply, single intelligence (either smart cockpit or assisted driving), dual intelligence (both smart cockpit and assisted driving), and full-stack solutions [2]. - The collaboration process involves Huawei supporting car manufacturers throughout the entire lifecycle, from product definition and design to manufacturing and marketing [2][7]. Group 2: Technology Approach - Huawei's approach to assisted driving does not align with the Vision-Language-Action (VLA) model favored by some car manufacturers; instead, it emphasizes the World and Action (WA) model, which directly controls the vehicle through sensory inputs [3][9]. - The WA model is considered by Huawei to be the ultimate solution for achieving true autonomous driving, bypassing the language processing step [9]. Group 3: Commercialization and Market Strategy - Huawei does not have a specific short-term commercialization goal for its assisted driving technology, focusing instead on long-term user-centered strategies and sustainable investment [7]. - The company believes that the market for assisted driving features will evolve, and that pricing strategies should reflect the ongoing development and maintenance costs associated with these technologies [12]. Group 4: Industry Trends and Future Outlook - The number of players in the autonomous driving space is expected to decrease as the industry consolidates, with future success relying heavily on data-driven approaches [10]. - The differentiation in assisted driving technology is minimal, as the primary goal remains zero accidents and fatalities, with pricing determined by perceived value to consumers [11].