Core Viewpoint - The article outlines various job descriptions and requirements for positions related to multi-modal reinforcement learning, data processing, and embodied intelligence, emphasizing the need for advanced skills in AI and machine learning technologies [6][14][15]. Group 1: Job Descriptions - Responsibilities include research, design, and implementation of cutting-edge multi-modal reinforcement learning algorithms to address complex real-world problems [6]. - Involvement in the collection, processing, cleaning, and analysis of multi-modal data to create high-quality training datasets [14]. - Development and optimization of multi-modal models, including training, fine-tuning, and enhancing performance across different tasks [6][15]. Group 2: Job Requirements - Candidates should possess a master's degree or higher in computer science, artificial intelligence, or robotics, with at least one year of research experience in computer vision or embodied intelligence [13]. - Proficiency in programming languages such as Python and deep learning frameworks like PyTorch is essential, along with strong engineering implementation skills [13]. - Experience in publishing papers at top academic conferences (e.g., CVPR, NeurIPS) and contributions to open-source projects are preferred [13][19]. Group 3: Additional Qualifications - Familiarity with multi-modal data cleaning, labeling, and loading, as well as understanding data optimization techniques is required [14]. - Candidates should have experience with large language models and multi-modal models, including knowledge of their capabilities and applicable scenarios [14]. - High standards for data quality and attention to detail are necessary, along with proficiency in data processing tools like Pandas and NumPy [14].

Core Insights - RoboScience and Qianxun Intelligent have recently added JD Technology Information Technology Co., Ltd. as a shareholder, indicating JD's continued investment in the robotics sector [1] - JD has made significant investments in various robotics startups this year, aiming to build a comprehensive ecosystem in embodied intelligence [1][4] Company Developments - RoboScience, founded in 2024 by a team including former Apple technical lead Tian Ye, focuses on developing a universal embodied intelligence system [2] - Qianxun Intelligent completed a nearly 600 million yuan Pre-A+ round of financing led by JD, while RoboScience secured around 200 million yuan in angel funding, also led by JD [1][2] Technology and Innovation - RoboScience employs a unique "fast-slow brain" model, which enhances the robot's ability to operate in complex environments by separating real-time responses and long-term planning [3] - The company has introduced the VLOA (Vision-Language-Object-Action) architecture, which allows robots to predict object trajectories, improving task understanding [3] Investment Strategy - JD's investment strategy in robotics is systematic, having made multiple investments since May, including in companies like PAXIN, Zhiyuan Robotics, and others, forming a "robotics army" [4][5] - The investments cover various critical segments of the robotics industry, with a focus on enhancing JD's operational capabilities in logistics and retail [4][5] Future Outlook - JD's commitment to embodied intelligence is long-term, with expectations for further investments and the addition of new members to its robotics portfolio [5] - The alignment of JD's business needs with robotics technology creates a feedback loop for innovation and application, enhancing operational efficiency [5]

Core Insights - The year 2025 is anticipated to be the "Year of Embodied Intelligence," driven by significant events and advancements in robotics and AI technologies [1] - There is a growing interest and investment in the field of general robotics, but concerns about sustainability and potential market bubbles persist [1] - Experts are exploring the challenges and advancements in embodied intelligence, focusing on the gap between technological ideals and engineering realities [1] Group 1: Industry Trends - A surge in robotics startups and investments indicates a strong belief in the potential of general robotics [1][2] - The transition from multi-modal large models to embodied intelligence is seen as a natural evolution, requiring substantial data and infrastructure improvements [3][4] - Current AI models face limitations in multi-task scenarios, highlighting the need for better adaptability and learning mechanisms [5][6] Group 2: Technical Challenges - The high energy consumption and training costs of large models pose significant challenges for their application in robotics [4][5] - There is a notable gap between the capabilities of large models and the multi-modal sensory systems of robots, complicating their integration [6][7] - The industry is exploring both modular and end-to-end architectures for embodied intelligence, with a shift towards more unified systems [9][10] Group 3: Research and Development - Research is focused on bridging the gap between human, AI, and robotic intelligence, aiming for better collaboration and understanding [16][18] - The current state of embodied intelligence is limited, with robots primarily executing pre-defined tasks rather than understanding human needs [18][19] - Future developments may involve creating systems that can interpret human intentions directly, bypassing traditional communication methods [20][21] Group 4: Future Outlook - Experts believe that achieving true embodied intelligence will require overcoming significant technical hurdles, particularly in understanding and interacting with the physical world [23][24] - The evolution of AI architectures, particularly beyond the current Transformer models, is essential for the long-term success of embodied intelligence [24][25] - The next five to ten years are expected to be critical for advancements in both hardware and software, potentially leading to widespread adoption of household robots [31][32]

人工智能浪潮下，杭州不断加快脚步。 6月4日，全市人工智能创新高地建设动员会召开，进一步明确了打造人工智能创新高地的目标与路 径，为杭州在人工智能领域的发展注入强大动力。 会上，相关负责人对《杭州市加快建设人工智能创新高地实施方案（2025年版）》进行了解读，政 府部门、高校院所、领军企业代表等齐聚一堂，从前瞻技术攻关到产业生态构建，从数实融合实践到具 身智能新赛道，共同助力杭州人工智能产业高质量发展。 最新任务书和"施工图"即将出台 今年4月25日，习近平总书记在中共中央政治局第二十次集体学习时强调，面对新一代人工智能技 术快速演进的新形势，要充分发挥新型举国体制优势，坚持自立自强，突出应用导向，推动我国人工智 能朝着有益、安全、公平方向健康有序发展。 立足数字经济先发优势，近年来，杭州持之以恒深化人工智能领域创新实践，积极开拓产业应用场 景、强化数据和算力等基础要素支撑、制定完善配套政策体系，为人工智能健康有序发展作出有益探 索。 根据此次即将出台的《实施方案》，到2025年，全市投入市场的智算规模要超过50EFLOPS （"EFLOPS"即每秒百亿亿次浮点运算，是衡量计算机或计算系统浮点运算能力的单位） ...

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