Core Viewpoint - The launch of the Traffic Jiahong Operating System by Jiadu Technology marks a significant advancement in the integration of open-source HarmonyOS with smart transportation, aiming to enhance operational efficiency and improve user experience in the transportation sector [1][2]. Group 1: Product Launch and Features - Jiadu Technology officially released the Traffic Jiahong Operating System, which is based on open-source HarmonyOS technology, facilitating deep integration with smart transportation [1]. - The system aims to create a unified distributed data bus and device discovery mechanism, enabling seamless interconnectivity among devices from different manufacturers and subsystems [1]. - By defining standardized device models, communication interfaces, and data structures embedded within the operating system kernel, the system significantly enhances data transmission efficiency and real-time performance [1]. Group 2: Industry Impact and Collaborations - The Traffic Jiahong Operating System is expected to drive the digital transformation of the transportation industry, improving operational efficiency and enhancing the travel experience for users [1][2]. - Jiadu Technology has over 10 years of experience in the smart transportation sector, having developed proprietary technologies and secured multiple subway business orders in cities like Chongqing, Shenzhen, Dongguan, and Changsha [2]. - Strategic partnerships have been established with industry leaders such as Huawei and China Mobile to deepen collaboration in the ecosystem [2]. Group 3: Broader Ecosystem Development - Several A-share listed companies are actively participating in the construction of the open-source HarmonyOS ecosystem, contributing to its application across various industries including finance, healthcare, and energy [3]. - The open-source HarmonyOS ecosystem has expanded its boundaries, with over 70 community-building units and more than 10 billion devices deployed across sectors like energy, finance, and education [3]. - The open-source nature and robust technical architecture of HarmonyOS provide significant growth potential, with expectations for rapid ecosystem expansion in the next 2 to 3 years [4].

网络攻击存在明显的不对称性，黑客只需攻破一个漏洞即可成功，而企业需防御所有漏洞。 5月8日，第一财经记者获悉，由上海市数据局指导，中企通信、上海电信、上海联通、上海移动等七家龙头企业共同发起的智能终端出海服务创新联合体已 经正式揭牌。第一财经记者采访中企通信数据科学及创新高级总监詹东东后了解到，随着中国智能终端出海形式不断变化，企业在出海的过程中将会面临本 地化、安全保障等多个挑战。 詹东东告诉第一财经记者，当前中国智能终端出海已从单一产品出口迈向"产业链+商业模式"的全球化复制阶段。工业机器人、服务机器人、人形机器人等 智慧终端已经成为了出海新势力。根据IDC发布数据显示，2023年，中国工业机器人厂商出海收入达到约95.8亿元人民币，商用服务机器人出海收入则为 15.1亿元。 相比于传统的智能终端，如手机、平板等，机器人的出海更为复杂。"这类终端不仅涉及复杂的数据交互，还需与物理环境实时联动。"詹东东指出，一旦这 类终端遭受网络攻击，可能导致设备失控、数据泄露甚至物理环境破坏，企业需要注意安全隐患。 尽管行业还在发展早期，但人形机器人在海外的业务布局并不少。以国内头部机器人公司宇树科技为例，虽然没有明确披 ...

截至目前，已有上百家合作伙伴基于"天工"平台面向应用场景进行二次开发，涌现出"天工行者"等极具应用能力的 机器人产品。北京大学、华中科技大学等顶尖学府通过联合实验室模式，与北京人形机器人创新中心在本体开 发、具身大脑等前沿领域展开深度合作，形成"基础研究-技术转化-产业应用"的创新闭环。 在具身智能发展的核心要素数据方面，北京人形机器人创新中心联合北京大学推出了大规模多构型智能机器人数 据集和Benchmark "RoboMIND"。截至目前，RoboMIND已在北京人形机器人创新中心官网、HuggingFace平台、北 京人工智能公共算力平台累计下载15000余次。来自清华大学、中国科学技术大学、上海交通大学、复旦大学、香 港大学、宾夕法尼亚大学等中外高校，中国科学院自动化研究所、北京智源人工智能研究院、清华大学无锡研究 具身智能产业当前已进入加速期，作为集人工智能、机械工程、传感器、新材料、脑科学等大量前沿学科于一体 的综合性产业，打造开源生态对具身智能的创新尤为重要。北京人形机器人创新中心以开源为引擎，持续推动具 身智能技术突破与产业协同发展。 作为国家级具身智能机器人创新平台，北京人形机器人创新中心始 ...

核心内容： 4、AI 时代需保留人性多样性并关注 "人的连接"。 要点总结： 一、VLA 司机大模型：从辅助到替代的驾驶革命 1、三阶段进化：1.0规则算法和高精地图，能力受限(昆虫智能)；2.0端到端(E2E)模仿人类，能力提升（哺乳 动物智能)；3.0融合3D/2D视觉、语言推理和行动控制，类人决策。 2、训练体系：训出云端 VL 基座模型，蒸馏成3.2B 端侧 MoE 模型；后训练，加入Action模仿学习模型规模 近4B；强化训练，融入人类驾驶习惯，产出车端运行的VLA 模型。 1、VLA 司机大模型是实现全自动驾驶的 "生产工具级" 技术突破； 2、AI 价值升级需从 "信息工具" 迈向 "生产工具"； 3、技术合作与开源加速行业进步； 二、AI 发展新认知：从工具分级到产业协同 1、AI工具三级价值论：信息工具，存在数据失真与效率瓶颈；辅助工具，提升局部效率，但需人类干预；生 产工具，独立完成专业任务。 2、开源逻辑：开放自研四年的整车操作系统，推动技术共享，目标成为汽车领域的 "安卓生态"。 三、创业逻辑与个人成长：聚焦 "解决问题" 与 "人的能量" 1、创业核心方法论：坚持解决行业痛点，技术 ...

早 报 精 选 1、 外交部回应中美经贸高层会谈：这次会谈是应美方请求举行的。 2、证监会印发《推动公募基金高质量发展行动方案》。 3、中国4月末黄金储备报7377万盎司，环比增加7万盎司，为连续第六个月增持黄 金。 4、上海：下调个人住房公积金贷款利率。 5、吉利汽车：建议私有化极氪，每股作价2.57美元。 宏 观 新 闻 1、 国新办昨日举行新闻发布会，央行行长潘功胜表示，降低存款准备金率0.5个百分 点，下调政策利率0.1个百分点。下调结构性货币政策工具利率0.25个百分点。潘功 胜称，优化两项支持资本市场货币政策工具，将5000亿元证券基金保险公司互换便 利，和3000亿元股票增持回购再贷款两个工具的额度合并，总额度变为8000亿元。 2、国家金融监管总局局长李云泽在国新办新闻发布会上表示，充分发挥保险资金作为 耐心资本和长期资本的作用，加大入市稳市力度，下一步将推出三条措施支持稳定和 活跃资本市场。一是扩大保险资金长期投资的试点范围，为市场注入更多增量资金； 二是调整偿付能力的监管规则，将股票投资的风险因子进一步调降10%，鼓励保险公 司加大入市力度；三是推动长周期的考核机制，促进长钱长投。李云泽称 ...

智东西 编译 | 金碧辉 编辑 | 程茜 智东西5月7日消息，据Stratechery报道，4月28日下午，社交媒体平台Stratechery的创始人、记者本・汤普森（Ben Thompson）在Meta总部对 Meta的创始人、董事会主席兼CEO马克・扎克伯格（Mark Zuckerberg）进行了专访。 从访谈中得知Meta在AI领域的布局以开源大语言模型Llama为核心，实现了生成文本、数学推理、代码生成等能力的跃升，其关键创新在于仅 使用公开数据集训练，并通过1.4万亿tokens的数据量弥补参数规模的不足。这种"小模型大智慧"的技术路径，印证了扎克伯格"效率优先"的AI 哲学。 这是继2021年10月和2022年10月之后，Stratechery对扎克伯格的又一次访谈。访谈前，Stratechery已了解了LlamaCon（Meta的新开发者大会） 的部分公告，并体验了新的Meta AI应用。 一、元宇宙概念持续推进，LlamaCon因开源模型需求诞生 Stratechery在体验Meta AI应用后，扎克伯格透露了这个新应用的更多细节，Meta AI已实现月活跃用户近10亿，成为全球用户规模最大的 ...

Core Insights - DeepSeek, a Chinese tech company focused on general artificial intelligence, has gained significant attention in the global AI landscape with its open-source inference model that is available for free commercial use, supporting specific development and application scenarios [1][2] - The success of DeepSeek highlights the potential for a "periphery revolution," where emerging players can disrupt established dominance in the AI sector, particularly in the context of developing countries gaining access to AI technologies [2][3] - DeepSeek's operational model serves as a case study for the construction and enhancement of AI platforms in China, indicating that mastery of foundational technologies does not guarantee control over the value distribution in the network industry [3][4] Summary by Categories Product and Innovation - DeepSeek's open-source inference model allows for free commercial use and supports complex tasks such as text generation, natural language understanding, and programming, showcasing strong application design and secondary development features [1] - The company's success is seen as a catalyst for the adoption of open-source AI models, marking a significant moment in the AI industry [1][2] Market Dynamics - DeepSeek's emergence suggests a narrowing gap between China and the U.S. in AI capabilities, particularly following the release of its V3 models, which have accelerated the pace of innovation in the sector [3][4] - The shift towards free or low-cost AI services is expected to drive rapid industrial application, as many large model service providers have transitioned to free pricing models [4] Industry Implications - The rise of small teams like DeepSeek demonstrates that significant innovation can come from smaller entities, challenging the notion that only large companies with substantial resources can lead in AI development [4] - The need for a well-designed policy framework for domestic and international industrial cycles is emphasized, ensuring that technological advancements align with national interests while avoiding past pitfalls of reckless competition [5][6] Education and Knowledge Dissemination - The advent of large models necessitates a fundamental transformation in education, shifting focus from rote memorization to innovation and practical application, as these models serve as powerful knowledge aids [7][8] - The concept of "open knowledge" is highlighted, where access to cutting-edge information is democratized through large models, enabling individuals to learn and innovate more rapidly [9][10]

大模型的竞争远远没有结束。 就在刚刚过去的4月，大模型再度经历了新一轮诸神之战。 先是有阿里在4月29日凌晨发布开源模型Qwen，并官宣登顶全球开源模型榜首； 后又有Meta在4月30日举办首届LlamaCon开发者大会，大会上不仅发布了 对标ChatGPT的Meta AI App，还面向开发者推出了Llama API预览版。 Meta的Llama 4系列模型，则是在4月6日抢先对外发布。 也是在首届 LlamaCon开发者大会上，Meta创始人扎克伯格请来了现任微软CEO萨提亚·纳德拉进行了一场半小时的现场对话。 在这场对话中，小扎摇身一变，成了主持人，对这位曾经挽救微软于水火，推动微软巨额投资了OpenAI，如今在推动微软进行又一次改革的传奇CEO进 行了一场精彩访谈。 纳德拉说，我们正处于一个可以构建"深度应用"的阶段； 纳德拉说，一些项目中，我们代码库里的代码可能有20%-30%是由AI编写。 扎克伯格则指出，到2026年，预计会有一半的应用开发工作会由AI完成； 扎克伯格还指出，未来每个工程师都会是技术领导，带领一个自己的智能体小队。 我们将这次两大科技巨头值得回味的对话内容整理如下： 01 "深度 ...

Core Viewpoint - Guangdong Province has introduced policies to support the development of open-source communities and ecosystems, with each receiving up to 8 million yuan in funding, aiming to establish itself as a global hub for artificial intelligence and robotics [1][2]. Group 1: Policy Measures - The policy emphasizes a shift from "single-item support" to "ecosystem construction," focusing on high-level platforms and ecosystem development to drive overall industry upgrades [1]. - Guangdong's AI core industry reached over 220 billion yuan last year, with more than 1,500 core enterprises, positioning it as a leader in the national AI and robotics sector [1]. Group 2: Ecosystem Development - The integration of open-source ecosystem construction into a collaborative system of "innovation chain, industry chain, capital chain, and talent chain" aims to transform Guangdong from a manufacturing province to a strong intelligent manufacturing province [2]. - The establishment of national-level data trading venues in Guangzhou and Shenzhen is intended to facilitate the open flow of data elements, providing high-quality data support for the open-source ecosystem [1]. Group 3: Challenges and Future Outlook - Challenges include avoiding the issue of open-source communities focusing more on construction than operation, and balancing data openness with security, privacy, and copyright protection [2]. - The cultivation of open-source communities and ecosystems is seen as both forward-looking and practically significant, with the potential to create a comprehensive innovation ecosystem in Guangdong that spans basic research, technology breakthroughs, commercialization, technology finance, and talent support [2].

Core Insights - Alibaba's new model Qwen 3 is emerging as a leading force in the Chinese open-source AI ecosystem, replacing previous models like Llama and Mistral [1] - The interview with industry representatives highlights the importance of model fine-tuning, the choice between open-source and closed-source models, and the challenges faced in large model entrepreneurship [1] Model Selection - The majority of the company's needs (over 90%) require fine-tuned models for local deployment, with specific tasks utilizing APIs from models like GPT and Qwen [3] - Commonly used model sizes include 7B, 32B, and 72B, with smaller models (0.5B, 1.5B) for privacy-sensitive applications [3] - Qwen is preferred due to its mature and stable ecosystem, including well-adapted inference frameworks and fine-tuning tools [4] Technical Considerations - Qwen's strong support for Chinese language and its relevant pre-training data make it suitable for the company's focus on emotional companionship and psychological applications [6][7] - The complete series of model sizes offered by Qwen allows for lower fine-tuning costs and easier testing across different model sizes [7] Challenges in Model Usage - In embodied intelligence, challenges include high inference costs and ecosystem compatibility, especially when considering local deployment for privacy [9][10] - Online business faces challenges in model capability and inference costs, particularly during peak usage times [12] Model Capability and Business Needs - Current models do not fully meet the company's needs for nuanced emotional understanding, necessitating post-training to align models with specific business requirements [13] - The goal is to maintain general capabilities while significantly enhancing core domain abilities, with an acceptable trade-off in general performance [13] Open-source Model Development - The expectation is for open-source models to catch up with top closed-source models, with a desire for more technical details to be shared by developers [14] - Qwen and Llama focus on community and general usability, while DeepSeek is more aggressive in exploring cutting-edge technologies [15][16] Entrepreneurial Insights - A significant oversight in AI entrepreneurship is the mismatch between models and product needs, emphasizing the importance of understanding user requirements [17] - The correct approach is to integrate AI as a backend capability rather than a front-end interface, ensuring deeper personalization in user interactions [19] Global Impact of Open-source Models - The rise of Chinese open-source models like Qwen and DeepSeek is accelerating a global technological evolution, providing a path for Chinese companies to innovate and collaborate internationally [20]