作者 | 华卫 当大模型的聚光灯照向实体经济，一个"必答题"浮出水面：数字世界里惊艳的大模型技术，怎样才能变成现实世界中实实在在的生产力？ 在 2025 世界人工智能大会（WAIC 2025）期间，蘑菇车联（MOGOX）发布首个物理世界 AI 大模型——MogoMind。在蘑菇车联展区，MogoMind 作 为首个深度理解物理世界 AI 大模型，成为本届大会最受关注的人工智能技术应用之一。 通过深度整合实时、海量的多模态交通数据，MogoMind 能够从物理世界的复杂数据中抽取意义、从经验中学习规则、在不同场景中灵活决策，形成对 交通环境的全局感知、深度认知和实时推理决策能力，可以为多类型智能体提供实时数字孪生与深度理解服务，成为城市和交通高效运行的"AI 数字基 座"。 依托 MogoMind 大模型能力，蘑菇车联推出多款 L4 级前装量产自动驾驶车辆，包括 RoboBus、RoboSweeper 和 RoboTaxi，深度融入全局感知、深 度认知和实时推理决策能，推动自动驾驶技术在公共交通、城市环卫、无人零售等多场景应用。 其中，自动驾驶巴士 MOGOBUS 搭载端到端"MogoAutoPilot+Mog ...

Core Insights - The MogoMind AI model developed by Mushroom Car Union is introduced as a real-time search engine for the physical world, enhancing capabilities beyond traditional digital models [1] - MogoMind integrates various devices to create a comprehensive perception network for real-time understanding of physical information, including road conditions and vehicle statuses [4] Group 1: MogoMind Capabilities - MogoMind can process multimodal information and real-time data from the physical world, addressing limitations of traditional language models that only handle static text [1] - The model supports emergency response to road incidents, provides over-the-horizon traffic alerts, and enhances real-time risk perception in blind spots for both drivers and autonomous vehicles [3] Group 2: Applications and Impact - Mushroom Car Union has launched multiple L4 level mass-produced autonomous vehicles utilizing MogoMind, integrating global perception, deep cognition, and real-time decision-making capabilities [3] - The autonomous buses equipped with MogoMind have successfully operated in 10 provinces across China, covering over 2 million kilometers and serving more than 200,000 passengers [3]