群核科技发布空间大模型，旨在解决AI视频空间一致性难题

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]