理想TOP2·2025-09-13 11:50Core Viewpoint - The core value of VLA (Vehicle Learning Assistant) lies in its ability to effectively utilize data for training foundational models and personal memory, enhancing user experience through self-evolution without the need for OTA updates [2][5][6]. Group 1: VLA Functionality - VLA's memory function captures various driving habits and preferences, allowing for a personalized driving experience that evolves over time [2][12]. - The system operates by tokenizing and summarizing collected data, which is then utilized to enhance the driving experience [10][13]. - Users are encouraged to actively engage with VLA by driving frequently to improve its performance and adaptability [8]. Group 2: Strategic Insights - The strategy involves a decentralized approach to personal memory data, AI infrastructure, and hardware integration, positioning the company to leverage user data effectively [6][20]. - The focus is on creating a unified experience across various devices, similar to Apple's ecosystem, which enhances user reliance on the brand [20][25]. - The importance of foundational model capabilities and the need for proprietary chip development to support advanced AI functionalities are emphasized [22][23]. Group 3: Market Positioning - The company is currently leading in the development of VLA and its memory capabilities, with competitors like Huawei and Horizon still in the early stages [15][19]. - The concept of "persistent memory" is highlighted as a key investment theme, enabling AI to evolve from a one-time tool to a reliable long-term partner [16][25]. - The integration of personalized memory with AI models is seen as a significant challenge but essential for creating customized driving experiences [25].