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]