Core Viewpoint - The discussion around VLA (Vision-Language-Action model) is intensifying, with contrasting opinions on its short-term feasibility and potential impact on the automotive industry [2][12]. Group 1: VLA Technology and Development - The Li Auto i8 is the first vehicle to feature the VLA driver model, positioning it as a key selling point [2]. - Bosch's president for intelligent driving in China, Wu Yongqiao, expressed skepticism about the short-term implementation of VLA, citing challenges in multi-modal data acquisition and training [2][12]. - VLA is seen as an "intelligent enhanced version" of end-to-end systems, aiming for a more human-like driving experience [2][5]. Group 2: Comparison of Driving Technologies - There are two main types of end-to-end technology: modular end-to-end and one-stage end-to-end, with the latter being more advanced and efficient [3][4]. - The one-stage end-to-end model simplifies the process by directly mapping sensor data to control commands, reducing information loss between modules [3][4]. - VLA is expected to outperform traditional end-to-end models by integrating multi-modal capabilities and enhancing decision-making in complex scenarios [5][6]. Group 3: Challenges and Requirements for VLA - The successful implementation of VLA relies on breakthroughs in three key areas: cross-modal feature alignment, world model construction, and dynamic knowledge base integration [7][8]. - Current automotive chips are not designed for AI large models, leading to performance limitations in real-time decision-making [9][11]. - The industry is experiencing a "chip power battle," with companies like Tesla and Li Auto developing their own high-performance AI chips to meet VLA's requirements [11][12]. Group 4: Future Outlook and Timeline - Some industry experts believe 2025 could be a pivotal year for VLA technology, while others suggest it may take 3-5 years for widespread adoption [12][13]. - Initial applications of VLA are expected to be in controlled environments, with broader capabilities emerging as chip technology advances [14]. - Long-term projections indicate that advancements in AI chip technology and multi-modal alignment could lead to significant breakthroughs in VLA deployment by 2030 [14][15].

Core Viewpoint - The article discusses the intense competition among Chinese automotive companies for AI talent in the field of assisted driving, highlighting the challenges and strategies involved in talent acquisition and retention [3][5][16]. Group 1: Talent Acquisition and Competition - Automotive companies are increasingly seeking AI talent, similar to tech giants and AI firms, due to the rapid evolution of assisted driving technology [3][6]. - The competition for high-end talent has intensified, with companies like Huawei, Li Auto, and Momenta being the most targeted for talent poaching [3][4]. - Li Auto's CEO mentioned that core team members receive over 20 headhunter calls each, indicating the high demand for skilled professionals [4]. Group 2: Legal and Competitive Strategies - Companies are resorting to non-compete agreements and lawsuits to prevent talent from moving to competitors, which has led to significant legal disputes [4][5]. - Li Auto has pursued legal action against former employees who joined rival companies, with compensation amounts reaching millions [4][5]. - The use of legal measures is a common tactic among automotive firms to safeguard their technological advancements and maintain competitive advantages [5]. Group 3: Technological Evolution and Challenges - The shift from rule-based systems to "end-to-end" models in assisted driving has created new challenges and opportunities for companies [6][23]. - The emergence of multi-modal large models, such as VLA (Visual-Language-Action), represents a new frontier in assisted driving technology [6][25]. - Companies like Li Auto are exploring various technical routes, including city NOA solutions and new generation models, to enhance their competitive edge [9][10]. Group 4: Industry Dynamics and Future Outlook - The assisted driving sector is witnessing a shift in power dynamics, with traditional automakers like BYD and Geely ramping up their self-research efforts while also leveraging external suppliers [16][18]. - The article emphasizes that while some companies may achieve quick results through talent poaching, true innovation requires original thinking and foresight [26]. - The ongoing evolution of assisted driving technology necessitates continuous adaptation and exploration by automotive firms to remain competitive in the market [22][26].

Core Viewpoint - The entry of Tesla's Full Self-Driving (FSD) technology into the Chinese market has created a sense of urgency and anxiety among domestic autonomous driving companies, as they fear the potential competitive threat posed by Tesla's advanced AI capabilities [1][5][24]. Summary by Sections Tesla FSD Performance - Tesla's FSD has shown a mixed performance in China, with instances of both impressive driving capabilities and significant errors, highlighting the challenges of adapting to the complex driving environment in China [2][4]. - The underlying AI technology of Tesla is robust, allowing for smooth driving experiences in regular conditions, but it struggles with unique Chinese traffic scenarios due to a lack of localized data training [4][5]. VLA Model Introduction - The VLA model has emerged as a promising solution to the shortcomings of the end-to-end model, integrating visual, linguistic, and action capabilities to enhance vehicle understanding of complex driving situations [8][9]. - VLA's ability to interpret traffic signs and pedestrian intentions positions it as a potential game-changer in the autonomous driving landscape, especially if it can effectively address the unique challenges of Chinese roads [8][12]. Competitive Landscape - Four key players in the domestic market are actively developing VLA technology: Li Auto, Chery, Geely, and Yuanrong Qixing, each with distinct strategies and timelines for implementation [15][16]. - Li Auto's "MindVLA" aims for high accuracy in complex scenarios but faces challenges in managing dual systems, while Chery collaborates with major tech firms to enhance its capabilities [18][19]. - Yuanrong Qixing stands out for its aggressive development and production of VLA technology, positioning itself ahead of competitors in the market [19][21]. Future Outlook - The competition in the autonomous driving sector is shifting from engineering capabilities to the foundational AI model capabilities, with the upcoming deployment of VLA-equipped vehicles expected to provide clarity on the competitive dynamics between Tesla's FSD and domestic technologies [24][25].