Core Insights - The article emphasizes the importance of multi-modal sensor fusion technology in overcoming the limitations of single sensors for robust perception in autonomous driving systems [1][4][33] - It highlights the evolution from traditional fusion methods to advanced end-to-end fusion based on Transformer architecture, which enhances the efficiency and robustness of feature interaction [2][4] Group 1: Multi-Modal Sensor Fusion - Multi-modal sensor fusion combines the strengths of LiDAR, millimeter-wave radar, and cameras to achieve reliable perception in all weather conditions [1][4] - The current mainstream approaches include mid-term fusion based on Bird's-Eye View (BEV) and end-to-end fusion using Transformer architecture, significantly improving the safety of autonomous driving systems [2][4][33] Group 2: Challenges in Sensor Fusion - Key challenges include sensor calibration to ensure high-precision spatial and temporal alignment, as well as data synchronization to address inconsistencies in sensor frame rates [3][4] - The design of more efficient and robust fusion algorithms to effectively utilize and process the heterogeneity and redundancy of different sensor data is a core research direction for the future [3] Group 3: Course Outline and Objectives - The course aims to provide a comprehensive understanding of multi-modal fusion technology, covering classic and cutting-edge papers, implementation codes, and research methodologies [4][10][12] - It includes a structured 12-week online group research program, followed by 2 weeks of paper guidance and 10 weeks of paper maintenance, focusing on practical skills in research and writing [4][12][15]

近期，小鹏、蔚来、理想、地平线、华为车BU、博世中国、小米汽车、Momenta等等公司都宣布了2026届校园招聘启 动的消息~ 好消息，汽车行业秋招大批量开启了！ 我们的知识星球也推出最大优惠了，续费5折，新人加入立减88，开学季最好的入手机会。 国内最大的自驾社区，和4000名成员一起交流。 很多同学还在陆续咨询柱哥关于就业、申博方向的问题，自驾领域还有很多问题没有被解决，甚至还没有有效的方 案，所以招聘需求才会持续存在。如果你在工业界，也是一个职业上升的好时机。 自动驾驶之心在此开学季，给大家提供了各类学习教程和科研平台，如果您想自动驾驶方向更上一层楼，或者希望快 速入门，可以来看看我们的教程和平台。诚意满满，是近段时间最大的优惠力度。 课程超级折扣卡 课程超级折扣卡是我们为有需要购买自驾课程同学推荐的。 一年内有效，所有自驾课程7折哦~适合购买2门及以上的 同学，优惠满满！ 知识星球 更多硬件和论文辅导活动 咨询我们 更多内容欢迎咨询小助理微信AIDriver005了解更多。 ...

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Group 1 - The article announces the recruitment of 10 partners for the autonomous driving sector, focusing on course development, research guidance, and hardware development [2][5] - The main areas of expertise sought include large models, multimodal models, diffusion models, SLAM, 3D object detection, and closed-loop simulation [3] - Candidates from QS200 universities with a master's degree or higher are preferred, especially those with significant conference contributions [4] Group 2 - The benefits for partners include resource sharing for job seeking, PhD recommendations, and overseas study opportunities, along with substantial cash incentives [5] - There are opportunities for collaboration on entrepreneurial projects [5] - Interested parties are encouraged to contact via WeChat for further inquiries [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].

Group 1 - The establishment of a Tech communication group focused on large models, inviting participants to discuss topics such as RAG, AI Agents, multimodal large models, and deployment of large models [1] - Interested individuals can join the group by adding a designated WeChat assistant and providing their nickname along with a request to join the large model discussion group [2]

点击下方 卡片 ，关注" 大模型之心Tech "公众号 戳我 -> 领取大模型巨卷干货 >> 点击进入→ 大模型技术 交流群 本文只做学术分享，如有侵权，联系删文 写在前面&笔者的个人理解 人工智能已从单一文本交互迈入多模态理解与智能体自主决策的新阶段。从处理纯文本的 大语言模型 （LLMs） ，到融合图像、音频的 多模态大语言模型（MLLMs） ，再到具备环境感知、任务规划能力的 智能体（Agents） ，大模型的 能力上限持续扩张，但安全风险也随之呈指数级增长 。 其中， 越狱攻击 作为最具威胁性的安全风险之一，始终困扰着大模型生态—— 攻击者通过精心设计的输 入或环境扰动，绕过模型的安全机制，诱导其生成违法、有害、违背伦理的内容 ，小则传播虚假信息、煽 动仇恨，大则引发网络攻击、隐私泄露等严重后果。然而，现有研究多聚焦于 单一形态模型 （如LLMs） 的攻击与防御，缺乏对LLMs-MLLMs-Agents 全演进链路 的系统性梳理，更未形成 统一的攻击分类框架、 评估标准与防御体系 。 在这一背景下，来自河南大学软件学院与中国科学院信息工程研究所的研究团队，对该领域进行了全面的 综述总结。该综述不仅 系 ...

随着自动驾驶、机器人导航和智能监控等领域的快速发展，单一传感器（如摄像头、激光雷达或毫米波雷达）的感知能力已难 以满足复杂场景的需求。 为了克服这一瓶颈，研究者们开始将激光雷达、毫米波雷达和摄像头等多种传感器的数据进行融合，构建一个更全面、更鲁棒 的环境感知系统。这种融合的核心思想是优势互补。摄像头提供丰富的语义信息和纹理细节，对车道线、交通标志等识别至关 重要；激光雷达则生成高精度的三维点云，提供准确的距离和深度信息，尤其在夜间或光线不足的环境下表现优异；而毫米波 雷达在恶劣天气（如雨、雾、雪）下穿透性强，能稳定探测物体的速度和距离，且成本相对较低。通过融合这些传感器，系统 可以实现全天候、全场景下的可靠感知，显著提高自动驾驶的鲁棒性和安全性。 当前的多模态感知融合技术正在从传统的融合方式，向更深层次的端到端融合和基于Transformer的架构演进。 传统的融合方式主要分为三种：早期融合直接在输入端拼接原始数据，但计算量巨大；中期融合则是在传感器数据经过初步特 征提取后，将不同模态的特征向量进行融合，这是目前的主流方案，例如将所有传感器特征统一到 鸟瞰图（BEV） 视角下进 行处理，这解决了不同传感器数据 ...

Core Viewpoint - Tesla has shifted from imitation learning to video learning and is now focusing on developing a world model as the ultimate solution for its Optimus robot, which will enable it to understand and interact with the physical world like a child learns about its environment [5][12][17]. Group 1: Learning Approaches - Imitation learning achieved end-to-end processing but faced issues with data generalization [6]. - Video learning addresses data diversity but struggles with scale and cost [6]. - The world model is proposed as a solution that encompasses physical knowledge of the real world, allowing robots to learn autonomously [6][12]. Group 2: World Model Development - The world model is a large-scale model that learns from real-world videos, understanding physical laws such as gravity and material properties [6][12]. - Google's Genie3 is highlighted as an example of a world model that creates an interactive 3D physical environment, allowing users to engage with it [9][11]. Group 3: Application to Robotics - The Optimus robot will utilize a small amount of real-world video to fine-tune its understanding of physical laws and its own mechanics [12][14]. - Engineers can generate vast amounts of realistic simulation videos based on simple natural language commands, which can then be used to train the robot's AI efficiently [14][16]. - This method allows for near-zero-cost and zero-risk trial-and-error learning in virtual environments, significantly enhancing the robot's robustness and adaptability [16]. Group 4: Industry Context - Many companies in the autonomous driving sector have not yet achieved end-to-end solutions and are still in the earlier stages of data collection and imitation learning [17]. - The article emphasizes the long journey ahead for Tesla's Optimus robot to fully realize the potential of the world model, contrasting it with the current state of many domestic humanoid robot companies [17].

Core Viewpoint - The article focuses on recruitment opportunities in the field of video understanding and artificial intelligence, highlighting the responsibilities and requirements for various positions within the company [2][4][5]. Recruitment Responsibilities - The company is looking for candidates to engage in cutting-edge algorithm research and development for video understanding, specifically targeting tasks such as video question answering, video summarization, temporal action localization, and event detection [2]. - Responsibilities also include building large-scale, high-quality multimodal datasets, distributed training of large models, and collaborating with business teams for practical application and innovation [2]. Job Requirements - Candidates should possess a master's or doctoral degree in computer science, artificial intelligence, electronic information, automation, or related fields [4]. - Experience in top AI conferences or journals is preferred, particularly in areas like computer vision and multimodal learning [5]. Advantages of Joining - The company offers a supportive environment with ample hiring capacity for new graduates, interns, and experienced hires, along with competitive salaries and benefits such as mentorship and participation in significant projects [6]. Community and Resources - The article mentions a community platform for job seekers in autonomous driving and robotics, providing resources like interview questions, industry reports, and salary negotiation tips [7][19].