Core Insights - Tesla's stock price has risen for the fourth consecutive day, indicating a potential recovery of momentum lost recently [1] - The company launched an autonomous taxi service in Austin, Texas, in June, contributing to the positive stock performance [1] - The estimated delivery date for the Model Y has been extended from one to three weeks to four to six weeks, signaling increased orders and demand [1] Demand Factors - The increase in demand is partly attributed to the federal tax credit of up to $7,500 for vehicle purchases, which is set to expire due to the tax and spending bill passed on July 4 by Trump [1] - Some buyers may be rushing to purchase vehicles before the subsidy expires, potentially driving demand forward [1]

Core Insights - Embodied intelligence is a hot topic this year, transitioning from previous years' silence to last year's frenzy, and now gradually cooling down as the industry realizes that embodied robots are far from being productive [1] Group 1: Industry Trends - The demand for multi-sensor fusion and positioning in robotics is significant, with a focus on SLAM and ROS technologies [3] - Many robotics companies are rapidly developing and have secured considerable funding, indicating a promising future for the sector [3] - Traditional robotics remains the main product line, despite the excitement around embodied intelligence [3] Group 2: Community and Resources - The community has established a closed loop across various fields including industry, academia, and job seeking, aiming to create a valuable exchange platform [4][6] - The community offers access to over 40 technical routes and invites industry leaders for discussions, enhancing learning and networking opportunities [6][20] - Members can freely ask questions regarding job choices or research directions, receiving guidance from experienced professionals [83] Group 3: Educational Content - Comprehensive resources for beginners and advanced learners are available, including technical stacks and learning roadmaps for autonomous driving and robotics [13][16] - The community has compiled a list of notable domestic and international research labs and companies in the autonomous driving and robotics sectors, aiding members in their academic and career pursuits [27][29]

Group 1 - Tesla CEO Elon Musk announced that the new FSD 14 will be released in six weeks, emphasizing its significance as potentially the most important update to date [2] - The new FSD system will feature a tenfold increase in parameter volume and improvements in handling rare road conditions, while reducing the driver's attention requirements significantly [2][6] - There are indications of an upgrade to the visualization system for the Autopilot and FSD, transitioning from a lightweight Godot engine to a more advanced Unreal Engine, enhancing interactivity and detail [6][7] Group 2 - Musk confirmed the halt of the Dojo supercomputer project, citing the need for difficult personnel decisions, and indicated that Dojo 3 may integrate multiple AI6 chips on a single motherboard [11][13] - The decision to close Dojo was influenced by the performance leap achieved with the AI5 chip, leading to a focus on integrating AI5/AI6 chips into a new supercomputer cluster [15] - Despite facing challenges such as declining revenue and reduced global deliveries, Tesla remains a leader in autonomous driving technology, with its FSD system significantly impacting the automotive industry [17]

Core Insights - The dissolution of Tesla's Dojo supercomputer project marks a significant shift in the company's AI strategy, which was once valued at $500 billion by Wall Street analysts but has now been deemed a failure [1][4][14] - The end of Dojo raises uncertainties and challenges for the next phase of AI development in the automotive industry, prompting companies to reconsider their strategic paths [3][12] Group 1: Dojo Project Overview - Dojo was initiated with the ambition to create a supercomputer specifically optimized for video data, aimed at enhancing Tesla's Full Self-Driving (FSD) capabilities [6][8] - The project faced numerous challenges, including internal team turmoil and technological complexities, leading to delays and ultimately its termination [8][12] - Key personnel, including Peter Bannon and Ganesh Venkataramanan, have left the project, indicating a significant shift in Tesla's AI development team [4][8] Group 2: Industry Implications - The automotive industry is increasingly recognizing AI as a core component of its future, with companies like Xpeng and Li Auto positioning themselves as AI-centric firms [9][11] - The definition of automotive products is evolving from mere transportation tools to intelligent mobile spaces, emphasizing the importance of computational power and AI models over traditional mechanical performance [12][15] - The shift towards AI-driven business models is evident, with a move from one-time hardware sales to sustainable revenue streams such as FSD subscriptions and software services [12][14] Group 3: Future Directions - Tesla plans to rely more on technology partners like NVIDIA and AMD for computational capabilities, indicating a strategic pivot from in-house development to collaboration [14] - The integration of AI in vehicles is expected to deepen, with advancements towards true Level 4/5 autonomous driving and the emergence of generative AI for enhanced in-car interactions [15]

Core Insights - Tesla has officially obtained a ride-sharing permit in Texas, allowing it to operate autonomous taxi services in the state, marking a significant step in the commercialization of its self-driving technology [1][3] - The new Texas law effective September 1 will regulate autonomous vehicle ride-sharing in the same manner as human-driven services, enabling Tesla to operate without a safety driver present in the vehicle [3] Group 1 - Tesla's autonomous taxi service has been in trial operation in Austin, Texas, since late June, offering rides to selected users at a flat fare of $4.2 per trip, using the latest Model Y vehicles [5] - During the trial, a Tesla staff member has been present in the passenger seat as a safety officer, although the driver's seat remains unoccupied [5] - CEO Elon Musk expressed confidence that by the end of 2025, Tesla could provide autonomous ride-sharing services to half of the U.S. population [5]

证券日报网讯金溢科技（002869）8月11日在互动平台回答投资者提问时表示，单车智能与车路协同是 相辅相成、协同发展的关系，车路协同可以为单车智能提供更丰富的信息输入和决策支持，能够有效弥 补单车智能在感知范围、成本、极端天气应对、全局优化等方面的局限性，是实现更高级别自动驾驶、 提升交通整体效率和安全的重要支撑和有效补充。中国在车路协同领域的政策支持力度大、基础设施建 设走在世界前列，将为车路协同产业的发展提供广阔的市场机遇。公司将持续聚焦智慧交通领域，秉 承"零死亡、零事故、零拥堵、零碳"的交通使命，沿着"ETC—V2X车路协同—大车路云—车、能、 路、云—iACT网联交通智能体和CCTE网联交能复合体"的业务发展路径稳步前进，共同推动智慧交通 产业的发展。 ...

上海街头可以打到"主驾无人"的自动驾驶汽车了！ 看似仅仅两字之差，背后却蕴含着巨大的突破。在"示范应用"阶段，自动驾驶车辆虽可上路测试，但不向用户收取费用。而此次"示范运营"牌照的发放， 意味着自动驾驶车辆正式跨出了商业化的重要一步，上海的大街小巷即将迎来更多Robotaxi（无人驾驶出租车）。 10 秒应答 不会"走神" 从叫到车到等到车，《IT时报》记者用时约5分钟。在小马智行App上填写好出发地和目的地后，一键叫车，不到10秒，一辆距离2公里左右的自动驾驶汽 车便应答接单。 "请系好安全带，我们准备出发了。"上车后，自动驾驶车辆后排显示屏发出语音提醒。主驾上没有司机，仪表盘、方向盘等部件在自动驾驶系统的运作下 有序工作。车辆平稳启动，在复杂的城市道路上穿梭前行，途中遇到红灯时精准刹车，绿灯亮起时又平稳加速，掉头利落，一把转过了十字路口，整个行 驶过程顺畅而平稳。 自动驾驶技术经过多年发展，如今已取得质的突破。小马智行、百度、赛可智能等公司是最早入行的一批科技公司，小马智行的自动驾驶车辆在全球范围 内积累了超过5000万公里的公开道路测试里程。 据了解，小马智行自动驾驶车辆全身共配备了4个激光雷达、7个毫 ...

出品：新浪财经上市公司研究院 文/夏虫工作室 核心观点：格灵深瞳实控人赵勇在资本市场运作上市是否玩转"一鱼两吃"套利局？一方面，格灵深瞳曾 以1元总价转让专利技术给驭势科技，如今驭势科技估值暴涨数倍，目前正在港股冲刺上市；另一方 面，格灵深瞳顺利闯关科创板并募得巨额资金。值得注意的，格灵深瞳上市前后业绩反差较大背后，上 市前部分业绩依赖外部顾问绑定，其上市究竟有没有包装成分？ 近日，驭势科技冲刺港股上市引来新的进展，收监管境外上市的备案反馈意见。 颇为引人关注的是，驭势科技与格灵深瞳及其实控人赵勇关系密切。格灵深瞳实控人赵勇作为驭势科技 联合创始人之一，在格灵深瞳冲刺科创板前夕辞任驭势科技的董事一职。 值得注意的是，格灵深瞳曾以1元总价转让专利技术给驭势科技，同时实控人等也入股该标的，如今该 标的估值暴涨。为何格灵深瞳为何当初"贱卖"专利？这背后又有何种套利局？ 1元送专利标的估值暴涨数倍 招股书显示，驭势科技成立于2016年2月，专注于真无人、全场景的L4级自动驾驶技术。公司核心产品 包括向机场、厂区等企业客户及商用车及乘用车制造商提供自动驾驶解决方案。该等解决方案包括搭载 L4级自动驾驶功能的商用车、自动 ...

Core Viewpoint - Tesla has halted its Dojo chip design project, reallocating resources to focus on AI5 and AI6 chips, which are expected to enhance AI and autonomous driving capabilities [1][3]. Group 1: Project Changes - The Dojo project leader, Peter Bannon, is leaving Tesla as the company shifts its strategy [1]. - Elon Musk confirmed that the decision to stop the Dojo project was due to the inefficiency of spreading resources across two different AI chip designs [6]. Group 2: Chip Production and Partnerships - The AI6 chip will be manufactured by Samsung Electronics, with a contract value of at least $16.5 billion [1]. - The AI5 chip will be produced by TSMC, initially in Taiwan, before moving to Arizona, USA [2]. - TSMC was considered a potential partner for the Dojo project but was ultimately not included, indicating a preference for Korean suppliers [2]. Group 3: Technical Insights - Musk stated that integrating multiple AI5 or AI6 chips on a single motherboard will significantly reduce complexity and costs [3]. - The AI5 chip is expected to provide substantial performance improvements, meeting the needs for Tesla's Full Self-Driving (FSD) architecture [3][7]. - Future efforts will focus on the AI6 chip, which will incorporate features from the Dojo project, such as a 5x5 grid chip arrangement for high-speed data transfer [5][6].

光大证券指出，1）国内外Robotaxi商业化规模上量或迎拐点突破，看好具备技术+生态+运营资质优势 的自动驾驶企业；2）反内卷或带动行业从压价/降价冲量向技术升级/技术降本模式转型，关注后续反 内卷战略在地方层面的落实情况。 智能网联汽车ETF紧密跟踪中证车联网主题指数，中证车联网主题指数将内容与服务提供商、软件提供 商、硬件提供商、汽车厂商等相关上市公司纳入车联网主题，以反映车联网上市公司的整体表现。 数据显示，截至2025年7月31日，中证车联网主题指数(930725)前十大权重股分别为上汽集团(600104)、 宁德时代(300750)、宏发股份(600885)、大华股份(002236)、德赛西威(002920)、科大讯飞(002230)、汇 川技术(300124)、华域汽车(600741)、欧菲光(002456)、比亚迪(002594)，前十大权重股合计占比 49.41%。 智能网联汽车ETF(159872)，场外联接A：021080；联接C：021081；联接I：022885。 截至2025年8月11日 11:06，中证车联网主题指数(930725)强势上涨1.64%，成分股皖通科技(002331 ...