Dublin, April 07, 2025 (GLOBE NEWSWIRE) -- The "Analysis on Li Auto's Layout in Electrification, Connectivity, Intelligence and Sharing, 2024-2025" report has been added to ResearchAndMarkets.com's offering.
Mind GPT: The 'super brain' of automotive AI
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
- Profile
- Development History
- Sales Volume and Revenue (2024)
- Sales Breakdown and Gross Margin (2024)
- Factory Capacity Construction
- Key Parts Manufacturing and R&D Layout
- R&D Investment and Direction (2023)
- Foreign Investment
- Organizational Management and Channel Construction
- Performance Management: Upgrade from OKR to PBC
- Comprehensive Introduction of IPD Process Management
- Matrix Organization Management
- Marketing Channels
- Retail Store Development
- Learn all about Huawei
- Adjust the Organizational Structure and Release L6
- Organizational 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
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