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Li Auto Layout in Electrification, Connectivity, Intelligence and Sharing Analysis Report 2024-2025: Mind GPT, Cockpit Evolution, Multimodal End-to-End Architecture, Complex Task Processing

1. Mind GPT's accuracy reached 98.7% with 120 million daily interactions. 2. OTA 7.0 introduced Mind GPT-3o, enhancing user interaction features. 3. Mind GPT-3o combines speech, vision, and language into a single model. 4. Frequent OTA updates optimize performance based on user feedback. 5. Li Auto aims to position Mind GPT among the top three globally.

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Why Bullish?

Li Auto's focus on advanced AI capabilities may attract more customers and investors, similarly to how Tesla's technology upgrades have positively influenced its stock price in the past.

How important is it?

The article focuses heavily on technological advancements that directly impact Li Auto's competitive position in the market, hence a high importance score.

Why Long Term?

The ongoing development and implementation of Mind GPT-3o can lead to sustained competitive advantage and revenue growth, reminiscent of other tech-driven transformations in the automotive sector.

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Li Xiang regards Mind GPT as the core of Li Auto's AI strategy. As of January 2025, Mind GPT had undergone multiple iterations since December 2023, been installed in more than 500,000 vehicles, processed 120 million interaction requests daily, and performed tasks with the accuracy of 98.7%. Li Xiang proposed the goal of making Mind GPT rank amog the top three in the industry in the next few years.On January 16, 2025, Li Auto officially started pushing OTA 7.0. The biggest highlight is that Mind GPT in "Lixiang Tongxue" was upgraded to Mind GPT-3o. Since the first version came out, Li Auto's Mind GPT has undergone multiple iterations and now boasts an intelligent agent from perception to cognition to active expression. In January 2025, Mind GPT-3o was pushed via OTA 7.0. It can listen, see and remember (connected with Face ID and family accounts, it can remember the preferences and requirements of family members), excel in reasoning (it can understand and dismantle complex problems, and intuitively display the process of perception and thinking through animation, that is, "Lixiang Tongxue Workflow"), express (it has a more human voice and supports dozens of modal particles; it can conduct more colloquial conversations; it is versatile and can sing and imitate animal sounds), and use 300+ tools (such as traffic restriction inquiry, Meituan, etc.). Cockpit evolution: from 'function stacking' to 'active foresight' With the empowerment of Mind GPT-3o, the smart space has achieved all-round evolution via OTA 7.0. The newly upgraded RGB+IR visual module and rich multimodal information input allow "Lixiang Tongxue" to not only understand the instructions of users, but also see the situation in vehicles. The function enables "Lixiang Tongxue" to better understand the intentions of users. For example, when passengers in the vehicle are discussing a certain scenic spot, "Lixiang Tongxue" can quickly provide users with relevant information about the scenic spot, including introductions, navigation, etc. through visual recognition and voice analysis. Advancement of Mind GPT-3o The advancement of Mind GPT-3o stems from Li Auto's full-stack independent R&D, scenario-based deep customization, hybrid deployment architecture, and ecological collaboration. Multimodal end-to-end architecture: the industry's first full-link integration model The 'multimodal end-to-end integration' architecture is the most distinctive feature of Mind GPT-3o. Unlike traditional automotive foundation models that rely on modular stacking (such as independent speech recognition and image processing modules), Mind GPT-3o achieves deep integration of speech, vision, and language understanding through a single model. The complete link from perception to cognition to expression is fulfilled in a closed loop in one model. This design greatly reduces system latency (response in hundreds of milliseconds) and reduces information loss caused by multi-module collaboration. Data scale and rapid iteration. Mind GPT-3o is trained on the basis of 3 trillion tokens of diverse data, covering multiple dimensions such as user habits, road scenarios, and voice interactions, far exceeding the industry average. OTA updates happen frequently. 17 iterations were completed via OTA in 2024, with an average cycle of 19 days. It responds quickly to user feedback and continuously optimizes functions (such as RedNote content call, multi-modal instruction integration), forming a closed loop of 'user feedback - model optimization - experience upgrade'. Collaborative optimization of smart driving and smart cockpit End-to-end architecture collaboration: Mind GPT-3o is deeply coupled with the smart driving system. For example, in scenarios such as highway toll stations and roundabout traffic, vision language models (VLMs) are used to assist end-to-end model decision-making to achieve anthropomorphic driving (such as automatically selecting ETC lanes and dynamically overtaking). However, the cockpits and smart driving systems of traditional OEMs are mostly independent modules with weak collaboration.Full-stack self-developed architecture and in-depth scenario customization Li Auto is the first OEM that launched a fully self-developed multi-modal cognitive model. It uses the self-developed Taskformer neural network architecture to achieve unified feature representation of multi-modal data such as voice, vision, and text, avoiding system fragmentation that relies on third-party models. Flexibility of cloud + edge hybrid deployment Computing efficiency: Through the inference load distribution of cloud GPT and edge NPU, its dependence on hardware computing power is reduced, so that old vehicle models can also run foundation models smoothly. Compared with the edge-only deployment of some competitors (relying on 8295 and Orin), it has stronger compatibility.Complex task processing: an "active assistant" that goes beyond command execution The breakthrough of Mind GPT-3o is to upgrade the foundation model from a "question-answering tool" to a "task planning hub". For example, if a user puts forward a vague requirement like 'a family outing on the weekend', the model can automatically decompose it into sub-tasks such as route planning, attraction recommendation, diner reservations, weather, etc., and coordinate the automotive system with external APIs (such as Meituan and AutoNavi) to complete these sub-tasks.It has 20+ built-in vertical scenario tools such as traffic restriction query, calendar management, fault diagnosis, etc., and supports third-party service expansion. Overview of Li Auto ProfileDevelopment HistorySales Volume and Revenue (2024)Sales Breakdown and Gross Margin (2024)Factory Capacity ConstructionKey Parts Manufacturing and R&D LayoutR&D Investment and Direction (2023)Foreign InvestmentOrganizational Management and Channel ConstructionPerformance Management: Upgrade from OKR to PBCComprehensive Introduction of IPD Process ManagementMatrix Organization ManagementMarketing ChannelsRetail Store DevelopmentLearn all about HuaweiAdjust the Organizational Structure and Release L6Organizational Structure Adjustment: Integration of Products and Businesses Key Topics Covered:1. Li Auto Profile 2. Product Planning and Development Strategy 3. Architecture and Domain Integration 4. Basic Software 5. Cloud Data and Foundation Models 6. SOC and Domain Controllers 7. Intelligent Cockpit 8. Comfort and Sound System 9. Automotive Display 10. Internet of Vehicles and Infotainment System 11. Intelligent Driving System 12. Electrification 13. Power Supply, Energy Replenishment and Thermal Management 14. Chassis Layout For more information about this report visit https://www.researchandmarkets.com/r/vlg6b6 About ResearchAndMarkets.comResearchAndMarkets.com is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

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