Core Insights - The article emphasizes the importance of automated 4D annotation data in enhancing autonomous driving capabilities, driven by the need for complex training data formats [2][4] - It highlights the challenges faced in automated annotation, including sensor calibration, occlusion handling, and quality control of annotations [4][9] Group 1: Automated 4D Annotation - The backbone of autonomous driving capabilities is the vast training data generated through automated 4D annotation, which is increasingly complex compared to traditional methods [2] - The shift towards end-to-end data requires synchronized sensor annotations of dynamic and static elements, ensuring the completeness of training data [2][4] Group 2: Challenges in Automated Annotation - Key challenges in the industry include calibrating and synchronizing different sensors, managing occlusion issues, and ensuring the generalization of algorithms [4] - The need for high-quality annotation results and effective automated quality checks are critical pain points in the current landscape [4] Group 3: Educational Initiatives - The article introduces a course focused on automated 4D annotation algorithms, aimed at addressing the industry's needs and enhancing algorithmic capabilities [4][8] - The course covers the entire process of dynamic and static object annotation, including practical exercises to reinforce learning [8]

Core Insights - The article emphasizes the importance of automated 4D annotation data in enhancing autonomous driving capabilities, driven by the need for complex training data formats [1] - It highlights the challenges faced in automated annotation, including sensor calibration, occlusion handling, and quality control of annotations [3] Group 1: Automated 4D Annotation - The backbone of autonomous driving capabilities is the vast amount of training data generated through automated 4D annotation processes [1] - The complexity of training data requirements has increased, necessitating synchronized annotations of dynamic and static elements, occlusions, and trajectories [1] - The significance of automated 4D annotation is growing due to the rising complexity of annotation demands [1] Group 2: Challenges in Automated Annotation - Key challenges in automated annotation include calibrating and synchronizing different sensors across various driving scenarios [3] - Issues such as occlusion between sensors and maintaining algorithm generalization are critical pain points in the industry [3] - The need for high-quality annotation results and effective automated quality checks is paramount [3] Group 3: Course Offering - A course titled "Automated Driving 4D Annotation Algorithm Employment Class" is being offered to address these challenges, featuring insights from industry leaders [3][4] - The course aims to provide a comprehensive understanding of the entire process of 4D automated annotation and core algorithms, along with practical exercises [6] - Key topics include dynamic obstacle detection, static element annotation, and mainstream paradigms for end-to-end annotation [6]

Core Viewpoint - The company has launched a "Super Discount Card" to address feedback regarding high course prices, offering a 30% discount on all courses for a year [2][4]. Group 1: Course Offerings - The company has introduced several new courses in the field of autonomous driving, including "End-to-End and VLA Autonomous Driving Small Class," "End-to-End and Planning Control (Third Session)," and "4D Annotation Algorithm Employment Small Class" [2]. - The "End-to-End and VLA" course has received positive feedback from participants, indicating strong interest and satisfaction [2]. Group 2: Discount Card Details - The "Super Discount Card" is priced at 299 yuan and provides a 30% discount on all courses related to autonomous driving and embodied intelligence, including future courses [4]. - The card is valid for one year from the date of purchase and can be fully refunded if no courses are purchased within that year [4]. - The promotional period for purchasing the discount card is from September 1 to September 14 [4].

Core Viewpoint - The company has launched a "Super Discount Card" to address feedback regarding high course prices in the field of autonomous driving, offering a 30% discount on all courses for a limited time [2][4]. Group 1: Course Offerings - The company has introduced several new courses in autonomous driving, including "End-to-End and VLA Autonomous Driving Small Class," "End-to-End and Planning Control (Third Session)," and "4D Annotation Algorithm Employment Small Class," which have received positive feedback [2]. - Future plans include launching additional courses focused on VLA and model deployment [2]. Group 2: Discount Card Details - The "Super Discount Card" is priced at 299 yuan and provides a 30% discount on all courses related to autonomous driving and embodied intelligence self-research courses, including future new courses [4]. - The card is valid for one year from the date of purchase and is available for a limited time from September 1 to September 14 [4]. - A full refund is available if no courses are purchased within one year of buying the discount card [4].