Core Viewpoint - The company has established a strong technological foundation and differentiated advantages in the field of spatial intelligence, particularly in AI 3D reconstruction [2] Group 1: Technology and Innovation - The company's core technologies include 3DGS, AR interaction, self-developed 3D engine, and industry-level model datasets, validated through vertical scene applications [2] - The self-developed FTE engine combines deep learning and Gaussian splashing algorithms to achieve high-precision environmental perception and dynamic modeling [2] - In industrial robotics, the company utilizes intelligent analysis of multi-angle images/videos for 3D reconstruction, generating interactive 3D scenes and providing AI algorithm support for robotic arm trajectory planning and obstacle avoidance training [2] Group 2: Simulation and Training - The self-developed AI 3D digital engine and simulation capabilities are the core underlying technologies of the company's spatial intelligence, featuring multi-physical field simulation capabilities to model complex environmental variables [2] - The virtual environment constructed by the engine supports millions of action iterations in robot training, significantly shortening the training cycle compared to traditional training methods [2]

Core Viewpoint - The company has established a strong technical foundation and differentiated advantages in the field of spatial intelligence, particularly in AI 3D reconstruction technology [2] Group 1: Technology and Capabilities - The company's core technologies cover 3DGS, AR interaction, self-developed 3D engine, and industry-level model datasets [2] - The self-developed FTE engine combines deep learning and Gaussian splashing algorithms to achieve high-precision environmental perception and dynamic modeling [2] - In industrial robot scenarios, the company utilizes intelligent analysis of multi-angle images/videos for 3D reconstruction, generating interactive 3D scenes and providing AI algorithm support for robotic arm trajectory planning and obstacle avoidance training [2] Group 2: Simulation and Training Efficiency - The self-developed AI 3D digital engine has multi-physical field simulation capabilities, allowing for the simulation of complex environmental variables [2] - The virtual environments constructed by the engine support millions of action iterations, significantly shortening training periods compared to traditional training methods [2]

Core Insights - The Beidou-3 global satellite navigation system was officially launched on July 31, 2020, marking a significant achievement in China's strategic development of satellite navigation technology [1] - Over the past five years, the Beidou system has enhanced its service capabilities and expanded its application scenarios, becoming an integral part of daily life in various sectors such as agriculture, autonomous driving, and smart ports [1][2] Public Applications - In Zhuzhou, Hunan, citizens can use a mobile app to dynamically book buses based on real-time demand, showcasing the Beidou system's role in optimizing public transport [2] - The daily call volume for Beidou positioning services in domestic electronic navigation maps is projected to reach 600 billion times in 2024, indicating widespread adoption [3] - Approximately 98% of smartphones shipped in 2024 will support Beidou positioning, solidifying its status as a standard feature in smart devices [3] Industry Applications - The Beidou system is being integrated into various industries, including robotics, agriculture, and construction, enhancing operational efficiency and precision [4][5] - In agriculture, Beidou technology has improved planting precision to within 2 centimeters, significantly benefiting crop management [5] - The total number of Beidou terminal devices in major industries reached nearly 30 million units by the end of last year, with an application penetration rate exceeding 85% [5] Industry Development - The satellite navigation and positioning service industry in China is projected to reach a market value of 575.8 billion yuan in 2024, with a core output related to satellite navigation technology reaching 169.9 billion yuan, reflecting a year-on-year growth of 5.46% [6] - The number of satellite navigation patent applications in China has surpassed 129,000, marking a 4.8% increase year-on-year [6] - The integration of Beidou with emerging technologies like 5G and AI is fostering new applications such as unmanned farms and digital construction sites, supporting the digital economy [7]

Core Insights - The rapid development of artificial intelligence has highlighted the challenges robots face in understanding real three-dimensional spaces, likened to lacking "eyes" and "brains" [1] - The release of the SpatialLM model by Qunke Technology at the NVIDIA GTC conference has generated significant interest in the AI community, although the specific training methods were not disclosed [1] - Shengjing Technology, a startup based in Shenzhen, has successfully replicated and open-sourced the training methods for SpatialLM, significantly advancing the accessibility of spatial intelligence technology [1][2] Open Source Core Training Methods - Shengjing Technology's open-source contributions provide a clear technical blueprint for developers, focusing on large-scale dataset integration, efficient point cloud processing, innovative spatial encoding, and optimized training strategies [2] - The company has integrated six major global 3D datasets, including Scannet and Matterport, to enhance the model's understanding of local spaces [2] - A unique continuous variable binning strategy was employed to convert complex spatial information into discrete integers, reducing spatial positioning errors by 37% [2] Empowering Embodied Intelligence - The open-source initiative by Shengjing Technology significantly lowers the entry barriers for developers in the field of spatial intelligence [2] - Despite rapid advancements in robotics, indoor spatial perception remains a challenge due to the complexity and variability of indoor environments [2] - The trend towards using synthetic data for training robots is becoming essential to achieve true intelligence in robotics [2] Building Spatial Intelligence Infrastructure - Shengjing Technology has developed the Sengine SimHub platform, which creates interactive 3D scenes based on floor plans, regulations, and user preferences, supporting robot path planning and visual navigation training [4] - The company has gained substantial support from academicians and top institutions, securing significant investments and winning multiple awards, including the national first prize at the Huawei Cloud Developer Competition [4] - The open-source practices led by this Shenzhen-based team are injecting new vitality into global AI innovation, potentially enabling smarter robots to enter households [4]