“卷王”阶跃星辰又卷出新花样，但姜大昕的理想道阻且长

Core Insights - The core focus of the article is the launch of the new 3D model Step1X-3D by the company Jieyue Xingchen, which represents a significant advancement in multi-modal AI technology [1][7]. Model Overview - Step1X-3D is a multi-modal model with a total parameter count of 4.8 billion, consisting of a geometry module with 1.3 billion parameters and a texture module with 3.5 billion parameters [1][3]. - The model has been trained on a high-quality dataset of 2 million samples, addressing the challenges of data scarcity and quality in the industry [3][5]. - The model employs advanced techniques such as enhanced mesh-SDF conversion, improving the success rate of water-tight geometry conversion by 20% [3]. Technical Architecture - The architecture of Step1X-3D is designed to be consistent with mainstream 2D generative models, allowing for the integration of established 2D control techniques [5]. - Users can manipulate various attributes of the generated 3D assets, enhancing the precision of creative outputs [5][9]. - The model achieved the highest CLIP-Score among its peers, indicating superior performance in content and input semantic consistency [7]. Company Positioning - Jieyue Xingchen, part of the "Big Model Six Little Tigers," has established itself in the competitive landscape of AI by releasing over 20 self-developed base models [7][9]. - The company is recognized for its commitment to multi-modal AI, which is seen as essential for achieving Artificial General Intelligence (AGI) [9][10]. - The founder, Jiang Daxin, emphasizes the importance of multi-modal integration for future advancements in AI, despite acknowledging the current limitations in achieving a unified understanding and generation model [9][10]. Market Implications - The advancements in 3D generation technology by Jieyue Xingchen may open new commercial opportunities, particularly in the field of embodied intelligence, where 3D data generation is a significant bottleneck [9][10]. - The company’s ongoing development in multi-modal models reflects a strategic approach to address the evolving needs of the AI industry [10].