8月27日—29日，2025AGIC深圳（国际）通用人工智能大会暨产业博览会在深圳国际会展中心盛大召 开！ 本次盛会以"模驱具身 智启未来"为主题，以前沿科技为核心，聚焦具身智能、大模型、机器人等创新 领域，汇聚了全球顶尖的人工智能技术、产品和创新成果，展览面积超8万平方米，吸引了来自世界各 地的1000余家企业同台竞技，共谱一场集科技、洞察与前瞻于一体的行业盛宴。 作为多模态世界模型与空间智能引领者，考拉悠然受邀参展（展位号：12A39），采用"线下演示 + 线 上直播"双渠道呈现方式，向全球集中亮相多款最新空间智能产品，以创新技术诠释人工智能与行业深 度融合的前沿趋势。 展会现场，考拉悠然展区始终保持超高人气，海内外观众、行业专家、合作伙伴及媒体代表络绎不绝。 现场互动热烈，交流深入，观众对公司空间智能产品给予了高度关注。直播间内，累计观看人数破万， 网友们对悠然无界大模型所展现的广阔应用前景表达了热切期待。 除了首次公开亮相的空间智能新品，考拉悠然还携多款创新成果同台亮相，包括专为工业质检打造的智 能检测智能体、赋能城市精细化治理的悠然智擎城市治理空间智能体，以及为各行业量身定制的AI+行 业解决方案， ...

Core Insights - The event "Partnering with 500 Strong to Co-create New 'Quanzhou' Landscape" was held in Quanzhou, Fujian Province, focusing on exploring new cooperation and development opportunities in the context of artificial intelligence [1] - Quanzhou is recognized as a historical and cultural city, an important starting point of the ancient "Maritime Silk Road," and one of the most active cities for private economy in China [1] - Gaode Map's Chairman Liu Zhenfei expressed confidence in deepening cooperation with Quanzhou, emphasizing the city's strategic layout and development potential in the AI sector [1] Company Overview - Gaode Map is a leading provider of digital map content, navigation, and location-based services in China, committed to connecting the real world and creating a dynamic map [1] - By 2025, Gaode Map plans to fully integrate AI, launching the world's first AI-native map application that evolves navigation into an intelligent travel assistant with deep temporal and spatial understanding [1] - The concept of spatial intelligence involves creating a virtual world that deeply understands, reasons, and outputs decisions, aiming for seamless integration between the digital and physical worlds [1] Project Initiatives - Gaode Map has launched the "Aerial Gaode" project, a comprehensive urban smart transportation solution based on spatial intelligence technology [2] - This project aims to build a temporal and spatial digital foundation, aggregating data and resources to provide intelligent and integrated services, particularly in low-altitude scenarios [2] - Liu Zhenfei indicated a desire for deeper collaboration with Quanzhou in various fields to explore new models and pathways for AI development, contributing to the high-quality development of new productive forces in Quanzhou [2]

Core Insights - The company, Qunke Technology, launched its latest spatial models, SpatialLM 1.5 and SpatialGen, during the first Tech Day on August 25, emphasizing an open-source strategy to engage global developers [1][4] - SpatialLM 1.5 is designed to understand and generate spatial language, enabling the creation of structured 3D scene scripts based on user text inputs, showcasing its potential in robotics [1][2] - SpatialGen focuses on generating multi-view images with temporal consistency, addressing current challenges in AI-generated video content [2][3] Group 1: Model Features - SpatialLM 1.5 utilizes a large language model to learn a new "spatial language," allowing it to describe spatial structures and relationships in 3D scenes accurately [1] - The model can generate structured 3D scene scripts and assist in robot path planning and task execution, addressing the scarcity of interactive 3D data [2] - SpatialGen employs a diffusion model architecture to create multi-view images based on text and 3D layouts, maintaining spatial logic and consistency [2][3] Group 2: Strategic Vision - Qunke Technology's strategy revolves around a "space editing tool - space synthesis data - space large model" framework, creating a positive feedback loop to enhance model training and tool experience [3] - The company has accumulated over 441 million 3D models and 500 million structured 3D spatial scenes as of June 30, 2025, leveraging these assets for model development [3] - The open-source initiative, started in 2018, aims to collaborate with global developers to advance spatial model technology [3][4]

Core Insights - The launch of the SMART AI Hub by Aoni Electronics and Abee, powered by AMD's Ryzen AI MAX+ 395, aims to create a smart space hub that enhances multi-modal AI interaction in home environments, promoting a healthier lifestyle and intelligent living spaces [1][2] Group 1: Product Features - The SMART AI Hub is designed as an AI workstation specifically for smart spaces, featuring a compact 7.5L aluminum body for easy installation and space efficiency [2] - It incorporates an innovative liquid cooling system, making it the world's first mini AI workstation with such technology, which enhances performance for AI computing [2] - The device operates at a noise level of 35.1dB under full GPU load, ensuring a quiet user experience [2] Group 2: Technological Innovations - The SMART AI Hub utilizes intelligent control firmware developed by Yinpu Computing, enabling real-time process scheduling, multi-level voltage-frequency curve optimization, and dynamic power management, significantly improving task performance [2] - The solution leverages local foundational large models and multi-modal models to support concurrent processing of various scenarios, including voice and image recognition [2] Group 3: Applications and Benefits - The SMART AI Hub facilitates unified management of various hardware forms, such as home appliances and robots, creating a cohesive smart home ecosystem [3] - It provides real-time monitoring of home environments, supporting elder care and intrusion detection, thereby enhancing home safety [3] - The device monitors children's sleep quality and heart rate, analyzes indoor temperature and humidity, and intelligently identifies food inventory, contributing to health management [3] - It enables intelligent retrieval of important family documents, photos, and videos, building a local knowledge base while ensuring data privacy by not uploading sensitive information to the cloud [3] Group 4: Strategic Collaboration - Aoni Electronics, Abee, Yinpu Computing, and Yuanqi Zhihui have formed a strategic partnership to deepen collaboration in space intelligence and vertical industry empowerment, aiming to advance edge AI development and set a new direction for integrated innovation in the industry [3]

Core Viewpoint - The company, Qunhe Technology, has submitted an updated prospectus to the Hong Kong Stock Exchange after the first one became invalid. The updated financials show a revenue of 399 million yuan for the first half of 2025, a 9% year-on-year increase, and a return to adjusted profitability, but with significant reductions in sales, marketing, and R&D expenses, alongside a high redemption liability of 4 billion yuan [1][4][10]. Revenue Structure - The revenue structure remains heavily reliant on subscription services, with 97.7% of total revenue coming from software subscriptions in the first half of 2025, up from 90.6% in 2022 [4][5]. - The company provides professional services to enterprise clients, contributing only 2.3% to total revenue in the second quarter of 2025 [6][10]. Financial Performance - Qunhe Technology achieved an adjusted net profit of 17.825 million yuan in the first half of 2025, a significant turnaround from an adjusted net loss of 73.196 million yuan in the same period last year [7]. - The company had previously reported adjusted net losses of 338 million yuan, 242 million yuan, and 70.049 million yuan from 2022 to 2024 [7]. Cost Management - Sales and marketing expenses decreased from 171 million yuan in the first half of 2024 to 136 million yuan in the first half of 2025, with a reduction in sales personnel from 615 to 501 [10]. - R&D expenses also saw a reduction of 16.8%, from 180 million yuan in the first half of 2024 to 150 million yuan in the first half of 2025 [10]. Future Plans - The company plans to use the funds raised from the IPO for international expansion, product launches, and enhancing existing product functionalities, particularly focusing on AIGC and geometric modeling [10]. - Qunhe Technology aims to establish a sales team of approximately 250 people and allocate around 20 million yuan for marketing activities over the next 3-5 years [10]. Product Development - Recently, Qunhe Technology launched two new spatial open-source models, SpatialLM 1.5 and SpatialGen, aimed at enhancing AI-generated content capabilities [7]. - The company is also planning to release a 3D technology-based AI video generation product in 2025 to address current limitations in AI video generation [7][9].

Core Viewpoint - The article discusses the emergence of "world models" in AI, highlighting the release of Genie 3 by Google DeepMind and the advancements in 3D spatial models by Qunke Technology, which aim to address the challenges of spatial consistency in AI-generated environments [2][8]. Group 1: Types of World Models - There are two main types of world models: video models like Sora and Genie 3, which simulate the physical world using 2D image sequences, and large-scale 3D models that focus on reconstructing 3D scenes [4][5]. - Video models struggle with maintaining spatial consistency due to their reliance on 2D images, while 3D models face challenges in creating comprehensive spatial content from multiple angles [6][8]. Group 2: Qunke Technology's Innovations - Qunke Technology introduced the first 3D indoor scene cognition and generation model, SpatialGen, which addresses spatial consistency issues by generating a navigable 3D space that supports any viewpoint switching [8][10]. - SpatialLM 1.5, a spatial language model, allows users to generate interactive 3D scenes through natural language commands, significantly enhancing usability for non-experts [10][11]. Group 3: Technical Foundations - SpatialGen utilizes a multi-view diffusion and 3D Gaussian reconstruction technology to ensure that lighting and texture remain consistent across different viewpoints [14][15]. - The models are built on a foundation of extensive 3D spatial data, with Qunke's tools generating structured 3D data that includes physical parameters and spatial relationships [16][18]. Group 4: Market Opportunities and Challenges - The current state of spatial models is likened to early versions of GPT, indicating that while they have foundational capabilities, they are not yet universally applicable [20]. - The demand for AI-generated short films presents a significant opportunity, as these models can improve scene coherence and production efficiency, addressing common issues in traditional AI tools [21][22]. Group 5: Future Directions - Qunke Technology is developing an AI video generation product that integrates 3D capabilities to further enhance spatial consistency in generated content [24]. - The company aims to bridge the gap between virtual and real-world applications, particularly in robotics, by providing structured 3D data that can be used for training [41].

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].

Group 1: Business Performance - The company's rugged intelligent industry terminal business achieved revenue of 173.46 million yuan in the first half of 2025, representing a year-on-year growth of 24.71% [2] - Growth is attributed to four main factors: ongoing global industrial digitalization, enhanced product competitiveness of the "ONERugged" series, increased brand influence and effective sales channel expansion, and successful acquisition of new clients in key sectors such as smart retail and fleet management [2] Group 2: Research and Development - The company has increased its R&D investment, resulting in a rise in the number of R&D projects and new patent applications [3] - Breakthrough R&D outcomes include AI industry terminals, AI enterprise workstations, AI glasses, AI edge computing models, AI digital humans, and AI servers, enhancing the company's ability to meet diverse customer needs [3] - The establishment of the Yidao Research Institute in January 2024 aims to collaborate with major universities and research institutions to advance research in cutting-edge technologies such as AI and cloud computing [3] Group 3: Share Repurchase Plan - The company's share repurchase plan is progressing in an orderly manner, with plans to actively advance the buyback project based on market conditions and company development [3]

Core Insights - The article emphasizes the importance of high-quality spatial data in the development of AI models, particularly in the context of three-dimensional (3D) space understanding [1][4][6] - It discusses the emergence of powerful models like SpatialLM and SpatialGen, which leverage vast amounts of spatial data to enhance AI capabilities in understanding and generating 3D environments [10][20] Group 1: Spatial Data and AI Models - The availability of extensive spatial data is crucial for training robust AI models, which can then improve tools and applications in various fields [2][4] - The article highlights the concept of a "data flywheel," where tools, data, and models continuously enhance each other, particularly in the realm of spatial intelligence [4][6] - The launch of SpatialLM 1.5 marks a significant advancement in spatial language understanding, allowing the model to interpret and generate structured spatial information [13][15] Group 2: Model Features and Capabilities - SpatialLM 1.5 can generate structured scene scripts from simple text descriptions, enabling users to create and manipulate 3D environments interactively [16][17] - SpatialGen focuses on generating multi-view images that maintain spatial consistency across different perspectives, addressing challenges in traditional 3D scene generation [20][21] - The models utilize extensive datasets, such as SpatialGen's dataset, which includes over 1 million images, to ensure high-quality outputs [22][28] Group 3: Open Source and Collaboration - The company aims to foster collaboration by open-sourcing its models and datasets, encouraging innovation and development within the AI community [32][36] - The leadership expresses a commitment to making spatial intelligence accessible, emphasizing that no single company can dominate this emerging market [33][36] - The open-source approach is expected to stimulate advancements in AI, providing opportunities for researchers and developers to contribute to the field [36]

Core Insights - The core focus of the news is the launch of two advanced models by Qunhe Technology, namely SpatialLM 1.5 and SpatialGen, aimed at enhancing 3D scene understanding and generation, as well as addressing challenges in AI video consistency [1][2][3]. Group 1: SpatialLM 1.5 - SpatialLM 1.5 is a spatial language model that allows users to generate interactive 3D scenes through a dialogue system, overcoming limitations of traditional models in understanding physical geometry and spatial relationships [2]. - The model can produce scenes with physically accurate structured information, enabling rapid generation of diverse scenarios for applications like robot path planning and obstacle avoidance, thus addressing data scarcity in robot training [2]. - A demonstration showcased the model's ability to understand commands and autonomously plan optimal action paths in complex environments, highlighting its potential in practical applications [2]. Group 2: SpatialGen - SpatialGen is a multi-view image generation model based on a diffusion model architecture, capable of creating temporally consistent multi-view images from text descriptions and 3D layouts [3]. - The model ensures that the same object maintains accurate spatial properties and physical relationships across different views, enhancing the realism of generated scenes [3]. - Qunhe Technology plans to release a 3D-integrated AI video generation product by the end of the year, aiming to address current limitations in AI-generated video consistency [3]. Group 3: Open Source Strategy - Qunhe Technology emphasizes the importance of open-source initiatives to maximize the value of its technology and contribute to the growth of the spatial intelligence sector [4]. - The company has developed a "space editing tool-space synthesis data-space large model" ecosystem, leveraging data to accelerate model training and improve user experience [4]. - As of June 30, the company has amassed over 441 million 3D models and more than 500 million structured 3D spatial scenes, showcasing its extensive data resources [4]. Group 4: Future Developments - The two models, SpatialLM 1.5 and SpatialGen, will be gradually open-sourced on platforms like HuggingFace, GitHub, and Modao Community, making them accessible to global developers [5].