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中游智驾厂商正在快速抢占端到端人才......
自动驾驶之心· 2025-12-15 00:04
点击下方 卡片 ,关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 智驾的技术焦虑,正在中游厂商快速传播。 周末有机会和一位深耕主机厂L2量产交付的负责人线下交流,其认为 明年才是端到端等前沿技术大规模量产的起点。 智驾前沿的技术发展放缓,业内量产方案趋同,L2整体在走下沉路线。二十万以上的乘用车销量在700万左右,但头部新势力的销量不及1/3,更不用说端到端量产 占比的车型。从落地趋势上来看,端到端技术的成熟反而才是更大规模量产的开端。随着明年L3法规的进一步推进, 中游厂商的技术升级也是迫在眉睫。 所以这 两个月很多公司算法负责人联系自动驾驶之心,迫切的想要了解前沿的技术:端到端、世界模型、VLA、3DGS等等。 端到端不仅仅是一个算法,需要完善的云端&车端基建,数据闭环、工程部署、闭环测试、模型优化、平台开发等等,可以预见,中阶智能驾驶的岗位需求会更旺 盛。而在昨天的2025地平线技术生态大会上,地平线CEO也表示将挺进10万级市场,高阶智驾正在迅速下沉至更多的国民车型。明年,智能驾驶的故事将更精彩。 以上。 基本上可以判断端到端、VLA的招聘需求会更旺盛。最近几个月, ...
对话郎咸朋:VLA 技术论战、团队换血与不被看好时的自我证明
理想TOP2· 2025-11-05 10:29
Core Viewpoint - The article discusses the evolution and strategic decisions of Li Auto's autonomous driving team, particularly focusing on the development of the VLA (Vision-Language-Action) model, which aims to enhance the driving experience by enabling the system to think like a human rather than merely mimicking driving behavior [3][4][20]. Organizational Changes - On September 19, Li Auto restructured its autonomous driving R&D department into 11 secondary departments to promote a more efficient AI-oriented organization [6]. - The restructuring aims to enhance communication and decision-making efficiency, with all department leaders reporting directly to the head of the autonomous driving team [7]. Technical Development - Li Auto's autonomous driving team initially faced challenges due to late entry into the market, but has since made significant progress by adopting an "end-to-end" approach and now focusing on the VLA model [3][4]. - The VLA model utilizes multi-modal AI to improve the driving experience, emphasizing the system's ability to think and reason [3][4][20]. Industry Reactions - Industry experts, including Huawei and Bosch representatives, have expressed skepticism about the feasibility of the VLA model, citing challenges in multi-modal feature alignment and data training [4][22]. - The criticism from competitors is viewed by Li Auto as validation of the VLA's potential, suggesting that the model's complexity is a necessary step for advancement [20][25]. Future Outlook - Li Auto anticipates that by early next year, significant improvements in the VLA model will be evident, enhancing its competitive position in the autonomous driving market [4][25]. - The company aims to achieve L4 level autonomous driving by 2027, with a focus on building a robust data feedback loop to continuously improve the system's capabilities [43][44].
何小鹏:为搞AI“烧掉”20多亿,曾“每月花1个多亿”
Feng Huang Wang· 2025-11-05 07:46
Core Insights - The CEO of XPeng Motors, He Xiaopeng, revealed significant investments in AI and autonomous driving model development, specifically in the VLA technology route [1][3] - The company has invested over 2 billion in training costs for the VLA project, which faced numerous challenges and internal discussions about its viability [3] Investment and Financials - From 2024 to the present, XPeng Motors has utilized 30,000 cards of computing power for its AI research [1] - The training expenses have been substantial, with monthly bills exceeding 100 million, leading to considerable financial pressure [3] Technological Advancements - A breakthrough in the VLA project occurred in the second quarter of this year, allowing the company to shift focus from the standard VLA development to the new technology [3] - This advancement is expected to accelerate the upgrade of XPeng's autonomous driving capabilities by nearly two years [3]
对话郎咸朋:VLA 技术论战、团队换血与不被看好时的自我证明
晚点Auto· 2025-11-04 03:58
Core Viewpoint - The article discusses the evolution of Li Auto's autonomous driving technology, particularly focusing on the development and implementation of the VLA (Vision-Language-Action) model, which aims to enhance the driving experience by enabling the system to think like a human rather than merely mimicking driving behavior [2][3][4]. Development of Li Auto's Autonomous Driving Team - The autonomous driving team at Li Auto was established in 2018 and has undergone three generations of key personnel changes, reflecting the challenges and growth within the organization [4][7][46]. - The team initially lacked resources and had to adapt by retrofitting existing vehicles with laser radar for technology research [3][4]. Shift to VLA Model - Li Auto transitioned to the VLA model to differentiate itself from competitors like Huawei and Tesla, emphasizing the need for next-generation technology rather than merely following existing paths [3][4][17]. - The VLA model utilizes multi-modal AI to improve the driving experience, aiming for a more human-like decision-making process [3][4][21]. Internal and External Challenges - The development of VLA has faced internal team restructuring and external skepticism, with industry leaders questioning its feasibility and effectiveness [3][4][21][22]. - Despite criticism, the company believes that the challenges posed by competitors validate the direction of the VLA model [4][21]. Organizational Changes - In September 2023, Li Auto restructured its autonomous driving department into 11 sub-departments to promote a more efficient and AI-focused organization [6][7]. - The new structure aims to enhance communication and decision-making efficiency, moving away from a centralized development model [8][9]. Future Goals and Expectations - Li Auto aims to achieve L4 level autonomous driving by 2027, with significant milestones set for 2021 and 2023 [37][39]. - The company anticipates that the VLA model will enable self-iteration and improvement, potentially surpassing competitors in the Chinese market [39][40]. Technical Considerations - The VLA model is designed to operate on existing autonomous driving chips, although these chips were not originally optimized for large models [33][34]. - Li Auto is investing in cloud computing capabilities, with a current training capacity of 10 EFLOPS and plans for further expansion [32][33]. Market Positioning - The company is focused on establishing a strong market presence in China before expanding internationally, recognizing the unique challenges of commercializing autonomous driving technology [41][42].