点 击 蓝 字 关 注 我 们 本文全文共 1551 字，阅读全文约需 5 分钟 2025世界人工智能大会在沪举办 7月26日至28日，以"智能时代 同球共济"为主题的2025世界人工智能大会暨人工智能全球治理高级别会议 （WAIC）在上海举办。此次大会聚焦AI技术产品首发首展、AI赋能千行百业以及人工智能全球治理等关键话 题，全面展现人工智能领域的最新进展与未来走向。 上海智能网联汽车驶入新阶段 在"模数引领，智行未来"AI赋能自动驾驶创新发展论坛上，《上海高级别自动驾驶引领区"模速智行"行动 计划》发布，总体目标为2027年基本建成全球领先高级别自动驾驶引领区。当天，上海市发放了新一批智能网 联汽车示范运营牌照。 亿咖通集中展示在智能座舱、辅助驾驶和车载AI大模型等领域的最新成果。亿咖通基于"龍鹰一号"打 造"安托拉系列计算平台"，支持单SoC实现"舱行泊一体"功能；基于通用基础AI大模型，实现AI Agent驱动的 全域感知与生成式体验。 多家企业发布不同用途大模型 Robotaxi规模化应用提速 WAIC 2025还设立了无人驾驶体验区。活动期间，上汽智己、小马智行、百度智行（萝卜快跑）、奇瑞汽 车在 ...

Core Viewpoint - The article discusses the emergence of embodied intelligence and the significance of the "world model" as a core component in advancing AI towards human-like intelligence, highlighting the competitive landscape in the AI industry as it evolves towards embodied intelligence [1][2]. Industry Developments - Major companies like Google, Huawei, and ByteDance are launching various embodied intelligence platforms and models, indicating a rapid evolution in this field [3]. - SenseTime, leveraging its expertise in computer vision and multi-modal large models, aims to empower the industry through its "Wuneng" embodied intelligence platform, which integrates years of technological accumulation [3][5]. Technical Challenges - The industry faces challenges such as data scarcity, difficulty in large-scale production, and the need for generalization in embodied intelligence applications [5][13]. - The reliance on computer vision expertise is seen as a potential solution to enhance the learning of world models and improve the capabilities of embodied intelligence [14]. World Model Significance - The world model is recognized as a crucial element for predicting and planning in autonomous systems, enabling robots to interact intelligently with their environments [12][17]. - SenseTime's "Kaigu" world model is designed to provide extensive data and facilitate simulation-based learning, significantly reducing data collection costs [17][20]. Platform Features - The "Wuneng" platform offers a comprehensive approach by combining first-person and third-person perspectives for robot learning, enhancing the understanding of robot behavior [27][29]. - The platform aims to address the data challenges in the industry by providing synthetic data and facilitating the development of various robotic applications [26][31]. Future Implications - As embodied intelligence matures, it is expected to transform human-robot interactions and create new social networks involving robots, enhancing their roles in daily life [36][37]. - The integration of embodied intelligence into common environments like homes and workplaces is anticipated to unlock significant value and functionality [39].

- The GLM-4.5 model, developed by Zhipu, integrates reasoning, coding, and intelligent agent capabilities into a single architecture. It employs a hybrid expert framework with 355 billion total parameters, activating only 32 billion parameters per inference to enhance computational efficiency. The training process includes three stages: pretraining on 15 trillion general text tokens, fine-tuning on 8 trillion specialized data, and reinforcement learning for multi-task alignment. The model achieves a 37% performance improvement in complex reasoning tasks through innovations like deep-layer prioritization and grouped query attention mechanisms [12][14][15] - GLM-4.5 ranks third globally in AGI core capability evaluations, with a composite score of 63.2. It outperforms competitors in tasks such as web interaction (26.4% accuracy in BrowseComp) and code repair (64.2 in SWE-bench Verified). The model demonstrates an 80.8% win rate against Qwen3-Coder in 52 real-world programming tasks, despite having half the parameters of DeepSeek-R1, showcasing its superior performance-to-parameter ratio [15][16][19] - The Agentar-Fin-R1 model, launched by Ant Financial, is a financial reasoning model based on the Qwen3 architecture. It features a dual-engine design: the Master Builder engine translates business logic into executable code, while the Agent Group engine uses consensus algorithms for multi-agent decision-making. The model is trained on a domain-specific corpus covering six major financial sectors, achieving a financial knowledge accuracy rate of 92.3% through weighted training algorithms [20][21][23] - Agentar-Fin-R1 excels in financial evaluations, scoring 87.70 in FinEval1.0 and 86.79 in FinanceIQ. It leads in tasks like risk pricing and compliance review, with a score of 69.93 in the Finova evaluation, surpassing larger general-purpose models. Its compliance system improves review efficiency by 90%, and its credit approval module reduces loan processing time from 3 days to 15 minutes while lowering bad debt rates by 18% [23][24][25] - The Goedel-Prover-V2 theorem-proving system, developed by Princeton, Tsinghua, and NVIDIA, uses an 8B/32B parameter model to achieve state-of-the-art results. It employs scaffolded data synthesis, validator-guided self-correction, and model averaging to enhance performance. The system achieves 88.1% Pass@32 accuracy on the MiniF2F benchmark, with the 8B model reaching 83.3% of the performance of the 671B DeepSeek-Prover-V2 while using only 1/100th of the parameters [58][60][61] - Goedel-Prover-V2 demonstrates exceptional efficiency, with its 32B model solving 64 problems in the PutnamBench competition at Pass@64, outperforming the 671B DeepSeek-Prover-V2, which required Pass@1024 to solve 47 problems. The system's iterative self-correction mode improves proof quality with minimal token consumption increase, and its training process is highly efficient, requiring only 12 hours per iteration on 4 H100 GPUs [60][61][63]

AI Industry Trends - ByteDance has open-sourced its AI Agent "Coze," which supports commercial use and has over 6,000 stars on GitHub, providing a platform for developing intelligent agents without coding[14] - The "Step 3" model by Jieyue features 321 billion total parameters and 38 billion activated parameters, achieving a 300% inference efficiency compared to DeepSeek-R1, with expected revenue of nearly $1 billion in 2025[11] - Ant Group released the financial reasoning model "Agentar-Fin-R1," which outperforms similar models in multiple financial evaluations and is based on a comprehensive financial dataset[16] AI Applications and Platforms - SenseTime launched the "Wuneng" embodied intelligence platform, featuring a multimodal reasoning model that improves cross-modal reasoning accuracy by 5 times compared to Gemini 2.5 Pro[8] - Huawei introduced the AI-Box platform, designed for lightweight edge deployment, supporting local execution of multimodal large models with low power consumption[9] - Tencent's Tairos platform offers modular services for multimodal perception and planning, focusing on enhancing robotic software capabilities[10] AI Model Developments - Zhiyuan released the GLM-4.5 model, which integrates reasoning, programming, and agent capabilities, achieving top performance in global open-source model benchmarks[17] - JD Cloud announced the open-source enterprise-level intelligent agent "JoyAgent," which supports multi-agent collaboration and has been tested in over 20,000 internal applications[18] - ByteDance and Nanjing University developed the CriticLean framework, improving the accuracy of mathematical formalization from 38% to 84%[19] Market Risks - AI software sales are below expectations, leading to adjustments in capital expenditure plans and slower iteration speeds for core AI products[34]

Investment Rating - The report indicates a strong upward trend in the automotive and robotics sectors, particularly highlighting the potential of intelligent driving and humanoid robots as key investment opportunities [3][4]. Core Insights - Intelligent Driving: The sector shows robust growth with increasing penetration rates for smart driving technologies and accelerated commercialization of Robotaxi services. WeRide has obtained the first autonomous driving license in Saudi Arabia, making it the only company with licenses in six countries [1][7]. - Robotics: The industry is experiencing steady growth, with new product launches from leading overseas companies expected to drive acceleration in the sector. The introduction of the "Lingqu OS" by Zhiyuan Robotics aims to create an open-source framework for embodied intelligence [2][14]. Summary by Sections Intelligent Driving - WeRide announced its Q2 financial results and received the first autonomous driving license for its Robotaxi in Saudi Arabia, marking a significant milestone in its global expansion [1][7]. - The establishment of the Changan Group as the third national automotive central enterprise in China, with a registered capital of 20 billion yuan, indicates a strengthening of the automotive industry [1][10]. - The launch of the Li Auto i8, the first mass-produced VLA electric SUV, signifies advancements in electric vehicle technology and market competition [1][8]. - NIO's L90 SUV saw a surge in orders on its first day of launch, reflecting strong market demand for new electric models [1][9]. Robotics - The humanoid robot R1 was launched by Yushun Technology at a starting price of 39,900 yuan, showcasing advancements in consumer-grade robotics [2][25]. - Zhiyuan Robotics introduced the "Lingqu OS," an open-source operating system aimed at enhancing the integration of robotic systems and driving breakthroughs in embodied intelligence technologies [2][28]. - The robotics sector is witnessing increased collaboration among companies, with strategic partnerships being formed to enhance product offerings and market reach [2][20]. Investment Recommendations - The report emphasizes that ROBO+ represents the strongest industrial trend in the automotive sector, with intelligent driving and humanoid robots being pivotal areas for growth. The penetration rate for advanced intelligent driving is expected to see explosive growth by 2025 [3][4]. - Key supply chain components such as chips, LiDAR, and optical devices are anticipated to experience significant growth, with recommendations to focus on leading companies in these fields [3][4]. - The second half of 2025 will be crucial for monitoring technological advancements and market dynamics in the robotics sector, particularly regarding new technologies and component pricing [3][4].

Core Viewpoint - SenseTime has launched the "Wuneng" embodied intelligence platform, which utilizes its embodied world model as the core engine to provide sensory, visual navigation, and multimodal interaction capabilities for robots and smart devices [1][2][10] Group 1: Technology and Functionality - The "Wuneng" platform is based on a complex dynamic system known as the embodied world model, which continuously learns and integrates vast amounts of data to create a digital mirror of the physical world [2][3] - The platform's sensory capabilities allow it to analyze environmental information by integrating various sensor data, enabling robots to recognize furniture layouts and household members in home settings [4] - The visual navigation function helps devices autonomously navigate by planning paths and avoiding obstacles, applicable in structured environments like warehouses [4] - Multimodal interaction supports both voice and visual commands, enhancing user experience by allowing devices to respond to voice instructions and recognize simple gestures [4][8] Group 2: Hardware Adaptability and Application - The platform is adaptable to various hardware, including humanoid robots and service robots, providing flexibility for different applications [5][6] - This adaptability allows for testing in various scenarios, offering technology integration options for hardware manufacturers [6][7] - The platform's ability to embed in edge-side chips reduces reliance on cloud computing, improving response times and functionality in unstable network conditions [8] Group 3: Market Impact and Future Development - The "Wuneng" platform represents a practical exploration of embodied intelligence, pushing the concept into real-world applications and providing new technological pathways for smart device development [11][14] - The platform's current capabilities offer potential for meeting user needs, with ongoing improvements aimed at enhancing user experience and stability [12][14] - Cost control is a critical factor in the platform's implementation, as integration and manufacturing costs will influence its widespread adoption [13][14] - The development of such platforms relies on the speed of technological iteration, market feedback, and the depth of industry collaboration, requiring time to demonstrate final effectiveness [15]

Core Insights - Major tech companies are accelerating their investments and developments in the field of embodied intelligence, with a total of 23 funding rounds reported in 2023 from seven major firms including Tencent, Alibaba, Meituan, Baidu, JD.com, and Xiaomi [6][11][12] - Tencent launched the Tairos platform, a modular software platform for embodied intelligence, which aims to empower the robotics industry by providing essential software capabilities [6][7][8][13] - JD.com has been increasingly visible in the embodied intelligence sector, announcing partnerships with numerous robotics companies and launching its own brand, JoyInside, focused on intelligent interaction [9][10][12] Investment and Development - The seven major companies have made a total of 23 investments in embodied intelligence firms this year, with Alibaba leading with six investments, followed by Meituan with five, and JD.com with four [11] - JD.com has established a dedicated business unit for embodied intelligence, focusing on home applications and leveraging its existing supply chain and data capabilities [12] Product Launches and Collaborations - Tencent's Tairos platform includes multi-modal perception models and cloud services, enabling robots to perform complex tasks autonomously [8][13] - JD.com's JoyInside brand collaborates with various robotics companies to integrate dialogue-driven intelligent agents into robots and AI toys [10][12] - NetEase launched its "Lingjue" model specifically for outdoor mining excavators, achieving an 80% efficiency rate compared to human workers [10][13] Strategic Focus - Major companies are focusing on data, platforms, and models rather than hardware, as they seek to establish a strong position in the embodied intelligence ecosystem [15][16] - The industry is currently in a "positioning" phase, with companies aiming to secure key roles in the future of embodied intelligence [19][20] Technological Advancements - SenseTime introduced its "Wuneng" platform, which utilizes a world model to enhance the capabilities of robots and smart devices [9][14] - Zhiyuan Robotics has developed a comprehensive system integrating robot bodies, motion intelligence, interaction intelligence, and operational intelligence, showcasing a full-stack approach to embodied intelligence [18]

Group 1: Core Insights - Major tech companies are accelerating their investments in the robotics sector, with a total of 23 funding rounds in embodied intelligence enterprises this year [1][6] - Companies like Tencent, Alibaba, Meituan, Baidu, JD.com, and Xiaomi are building their own robotics teams to enhance their capabilities in embodied intelligence [1][6] - The World Artificial Intelligence Conference (WAIC) showcased various products and collaborations from these companies, highlighting their focus on developing industry-specific models and partnerships [1][2][4] Group 2: Company Strategies - Tencent launched the Tairos open platform, which provides modular software solutions for the robotics industry, aiming to empower developers with essential software capabilities [2][8] - JD.com has established its JoyInside brand, collaborating with numerous robotics companies to integrate dialogue-driven intelligent agents into various smart hardware [4][8] - NetEase introduced the "Lingjue" model for outdoor mining excavators, focusing on specific applications and open-sourcing its training dataset [5][10] Group 3: Investment Trends - Among the seven major companies, Alibaba has been the most aggressive with six investments, followed by Meituan with five, and JD.com with four [6][7] - The investments are primarily directed towards startups in the embodied intelligence space, with a focus on enhancing their own technological capabilities [6][11] Group 4: Future Directions - Companies are increasingly focusing on data, platforms, and models rather than hardware, as they seek to establish a strong position in the embodied intelligence ecosystem [11][12] - There is a recognition that while major companies have advantages in data and algorithms, they face challenges in hardware development, creating opportunities for startups [12][14] - The industry is expected to see further consolidation as major players look to acquire companies that specialize in perception and control layers to complete their embodied intelligence ecosystems [14]

Group 1 - The core viewpoint of the article emphasizes the evolution of artificial intelligence (AI) from being merely a tool to becoming empathetic partners, highlighting the importance of responsible AI usage in gaining a competitive edge [1][2] - The development of AI is moving towards deeper understanding and interaction with the physical world, with significant advancements in models that can simulate real-world scenarios, such as the "绝影开悟" model which can generate data equivalent to 10 real vehicles or 100 road-tested vehicles daily [2][3] - The focus on AI agents is becoming a popular trend, with companies targeting the next battlefield in AI capabilities, where large models serve as the brain and AI agents provide the necessary action [3] Group 2 - Concerns regarding the safety and reliability of large models are increasingly being raised, as their accuracy in critical fields like healthcare and finance still falls short of required standards [4][5] - Experts suggest that the challenges of reliability in AI models should not be simplified to mere "hallucinations," but rather addressed through the establishment of engineering frameworks to ensure their effectiveness [5] - The potential risks associated with advanced AI systems necessitate global collaboration to ensure that AI remains beneficial to humanity, with a focus on developing AI that can assist rather than dominate human intelligence [5]

Core Insights - The 2025 World Artificial Intelligence Conference (WAIC) showcased over 3,000 cutting-edge achievements, highlighting advancements in robotics and embodied intelligence [1] - Companies are focusing on enhancing robots with memory, physical perception, language capabilities, and sensory interaction, moving from mere functionality to a more human-like presence [1] Group 1: Embodied Intelligence Developments - The National Local Joint Human-Robot Innovation Center presented the "Qinglong" product system, which includes various humanoid robots designed to create an ecosystem of embodied intelligent robots [2] - The Qinglong Pro robot features a new control system with seven core subsystems, including multi-sensory perception and flexible arm coordination, enhancing its operational capabilities [2][3] - The integration of Huawei Cloud's CloudRobo platform supports the development of diverse robotic applications, significantly reducing data collection costs by 90% [3][4] Group 2: Sensory and Interaction Capabilities - The introduction of adaptive tactile sensors allows robots to possess human-like touch sensitivity, enabling them to handle delicate items without damage [7] - The SenseTime "Wuneng" platform enhances robots' perception and interaction capabilities, allowing them to perform complex tasks and engage in natural language communication [6][8] - The development of a unified public service portal for language data aims to improve the quality and scale of language interactions in AI applications [8][10] Group 3: Industry Applications and Future Prospects - The advancements in embodied intelligence are expected to transform various sectors, including healthcare, elderly care, industrial production, and daily life services, leading to significant changes in human work and lifestyle [10] - The integration of gaming data as training material for embodied intelligence highlights the potential for cross-industry applications, leveraging real-time, interactive data for AI development [9][10] - As technology matures and costs decrease, intelligent robots are anticipated to become integral to everyday life, moving from science fiction to reality [10]