在AI（人工智能）热潮下，以数字贸易见长的杭州，迎来了第四届全球数字贸易博览会（简称"数贸 会"）。 今年的展会上，"杭州六小龙"首次齐聚，成为全场焦点。来自国内外的4万余名专业客商汇聚于此，寻 找谁是"第七龙"的同时，他们更好奇，这批数字先锋究竟会如何重塑全球数字贸易格局？ 在15万平方米的展会现场，超1700家参展商携前沿技术、创新产品和重磅首秀亮相。《每日经济新闻》 记者看到，人工智能与丝路电商两大展区尤为火热，它们恰如中国数字贸易发展的双引擎，代表着自主 创新的"内生力"与世界互联的"朋友圈"，正为全球数字经济注入源源不断的新动能。 浙江数字贸易规模实现"三连跳" 当前，数字贸易作为数字技术与国际贸易深度融合的新形态，正成为世界各国在全球经济格局深度调整 与不确定性加剧背景下的战略选择。 世界贸易组织（WTO）最新数据显示，2024年全球数字服务贸易规模达4.64万亿美元，同比增长 8.3%，显著高于同期全球货物贸易2.3%的增速。这凸显出数字服务贸易凭借其可数字化交付的特性， 能够有效突破传统贸易的地域和时效限制，展现出持续而强劲的增长韧性。 中国在全球数字服务贸易规模排名中稳居前十强。今年上半年， ...

Core Viewpoint - The strategic partnership between TUSI and UBTECH aims to integrate spatial intelligence and embodied intelligence to enhance the capabilities of humanoid robots, creating a new paradigm for multimodal training and promoting the comprehensive deployment of intelligent robots [1][3]. Group 1: Strategic Collaboration - TUSI, a leader in spatial intelligence, and UBTECH, a pioneer in humanoid robotics, have signed a strategic cooperation agreement to share and innovate on their respective technologies [1][3]. - The collaboration is based on mutual recognition of each other's technological strengths and industrial value, aiming to create highly autonomous and interactive next-generation intelligent robots [3]. Group 2: Technological Capabilities - UBTECH possesses full-stack technology capabilities in humanoid robotics, including advanced hardware, AI technology, and integration of robotics with AI [3]. - TUSI has developed a three-layer strategic system focusing on AIoT infrastructure, AIoT domain models, and AIoT intelligent agents, with nearly 10,000 spatial intelligence project cases since 2015 [3][4]. Group 3: Spatial Intelligence - Spatial intelligence is crucial for robots to interact with the physical world, enabling them to understand complex, unstructured environments [4]. - TUSI's self-developed spatial large model allows for multi-modal integration and reasoning, helping robots to comprehend physical laws and perform complex task planning [4]. Group 4: AIoT Intelligent Agents - TUSI's intelligent agents possess capabilities such as human-like thinking, long-term memory, high-dimensional perception, and teamwork, enhancing robots' decision-making and collaborative abilities in complex environments [5]. - UBTECH's humanoid robots serve as intelligent terminals that can autonomously move and perform precise operations, continuously validating and enhancing spatial reasoning models through real-world interactions [5]. Group 5: Market Implications - The partnership between TUSI and UBTECH is expected to create significant opportunities for business upgrades and global market expansion, especially as TUSI is in the process of an IPO [5].

Core Viewpoint - The article discusses the emergence of 3D content generation models, highlighting the unique approach of Qunhe Technology in developing a spatial large model that addresses the core industry pain point of "spatial consistency" [2][7]. Group 1: Current Landscape of 3D Content Generation - Major players in the 3D content generation space include Google Genie 3 and World Labs, focusing on either video generation or 3D scene generation [5]. - The "video generation faction," represented by Genie 3, can create dynamic interactive content but struggles with maintaining three-dimensional spatial consistency [5]. - The "3D scene generation faction," represented by World Labs and others, can achieve 360-degree roaming but often faces issues with scene collapse and content inconsistencies due to a lack of high-quality 3D data [5][11]. Group 2: Qunhe Technology's Spatial Large Model - Qunhe Technology's spatial large model aims to overcome the challenges faced by existing models, particularly in terms of spatial consistency and realistic roaming capabilities [8][12]. - The model is characterized by three features: realistic holographic roaming scenes, interactivity, and complex spatial processing capabilities [13]. - Qunhe has released two sub-models: SpatialLM 1.5 (spatial language model) and SpatialGen (spatial generation model), which exemplify these features [14]. Group 3: Spatial Language and Interaction - Spatial language, as defined by Qunhe, allows the model to describe 3D scenes in terms of spatial parameters, enhancing its ability to support precise spatial generation and editing [21]. - The model can assist robots in understanding complex spatial tasks by incorporating physical parameters and spatial knowledge [19][21]. - Compared to traditional models, SpatialLM 1.5 demonstrates superior performance in spatial understanding and task execution [30][32]. Group 4: Challenges and Industry Context - The spatial intelligence field is still in its early stages, akin to the GPT-2 phase, facing challenges such as data scarcity, high acquisition costs, and complex scene semantic understanding [32][51]. - Qunhe Technology's strategy involves a "three-in-one" approach, integrating spatial editing tools, spatial synthetic data, and spatial large models to create a positive feedback loop for development [42][45]. - The company has built the largest indoor space deep learning dataset, InteriorNet, with over 441 million 3D models and 500 million structured 3D space scenes, enhancing its competitive edge in the spatial intelligence domain [45]. Group 5: Future Prospects - The article emphasizes the potential for rapid growth in the spatial intelligence sector, driven by collaborative efforts and open-source initiatives [52]. - Qunhe Technology aims to accelerate the evolution of spatial intelligence and expand the industry by fostering a community of developers and researchers [54].