Track Hyper | Tesla AI upgrade reshapes in-car experience

Author: Zhou Yuan / Wall Street News

Tesla's latest Model Y L officially features the Doubao large model provided by ByteDance's Volcano Engine in China, and the DeepSeek (DS) model has also entered Tesla's intelligent cockpit.

This combination is not only a technological iteration but also Tesla's comprehensive layout of the in-car AI ecosystem.

The Doubao model is responsible for vehicle function operations and information inquiries, while the DeepSeek model provides casual conversation and emotional interaction, achieving an upgrade from single voice recognition to multi-layered, immersive interaction.

This marks a key step for Tesla in enhancing the intelligent driving experience and reflects the future development direction of smart vehicles.

Doubao and DS Each Have Their Roles

In-car voice interaction has evolved from the initial rule-matching systems to deep learning-driven end-to-end voice recognition, and now to the application of large models.

Early systems could only respond to limited commands, such as adjusting the air conditioning or switching radio stations; with the introduction of deep learning and natural language understanding, vehicles can comprehend more natural language commands, but multi-turn dialogue and contextual understanding remain limited.

With the advent of large models, vehicles can recognize complex semantics, maintain conversational coherence, and combine functional execution with emotional interaction, forming a complete in-car AI ecosystem.

In the domestic market, competition in smart vehicles is fierce, with various manufacturers investing in in-car AI research and development.

Tesla's choice to collaborate with Volcano Engine allows for the rapid deployment of localized large models while maintaining long-term self-research potential.

This strategy not only reduces initial R&D costs but also provides the possibility for rapid iteration and adaptation to market demands. In the capital market, this means a combination of the speed of technology implementation and quantifiable commercial value, providing investors with clear growth signals.

In terms of division of labor, the Doubao large model is responsible for core functions such as navigation, media playback, air conditioning adjustment, and owner manual inquiries.

Technically, Doubao integrates voice recognition, natural language understanding, and vehicle control interfaces to achieve end-to-end instant response.

The advantage of the Doubao large model lies in its ability to understand multi-turn dialogue and semantic mapping accuracy: continuous commands issued by users can be accurately recognized by the system and mapped to specific vehicle control operations, enabling fast, accurate, and low-latency execution.

The collaboration between the Doubao model at the edge and the cloud is also a key design; core commands are processed locally in the vehicle to ensure low latency and driving safety, while complex reasoning and multi-turn context management are handled by the cloud, enhancing the accuracy and flexibility of command parsing. Through this model, Tesla ensures functional reliability while providing a foundation for future OTA upgrades and value-added services.

Unlike the functional Doubao, the value of the DeepSeek model lies in casual conversation and emotional interaction.

DS can understand contextual nuances, maintain conversational continuity, and assess user emotions through tone, word choice, and semantics, generating appropriate responses. On a technical level, DS relies on large-scale multimodal training and complex reasoning algorithms to provide drivers with a sense of companionship and personalized experience.

This emotional interaction capability not only enhances user stickiness but also upgrades in-car AI from a single functional tool to an intelligent partner In long-distance driving scenarios, DeepSeek can alleviate driving fatigue; during family outings, it can also facilitate fun Q&A and knowledge interaction; in safety scenarios, DS can provide operational reminders or driving assistance prompts, forming a dual guarantee of functionality and experience.

Technical Ecosystem and Computing Power Collaboration

The Volcano Engine provides Tesla with cloud-based large model services that encompass training, deployment, optimization, and real-time updates.

Edge devices handle instant voice recognition and control commands, while the cloud executes complex reasoning and multi-turn dialogue management. The collaboration between the two ensures low latency and high accuracy, addressing the response issues of in-vehicle AI under limited computing power.

Additionally, local data processing and cloud interaction adhere to strict privacy and compliance requirements. Voice data is preprocessed locally and transmitted in an encrypted manner, while the cloud model provides optimized feedback, ensuring both performance and regulatory compliance.

This cloud + edge collaboration model has become a standard practice in the smart automotive industry and provides an ecological foundation for Tesla to introduce value-added services and third-party platform access in the future.

The Doubao and DeepSeek models are designed for different driving scenarios with distinct task divisions, offering differentiated experiences.

User behavior data indicates that smart AI can significantly enhance usage frequency, brand loyalty, and car purchase decision experiences.

Personalized interaction and emotional perception capabilities enhance users' reliance on the Tesla ecosystem, while potentially increasing the second-hand residual value of vehicles, supporting the long-term value of the brand and user stickiness.

In the international market, Tesla's products in the U.S. mainly rely on self-research or hybrid models, focusing on functional commands and driving assistance; the domestic market combines outsourcing with Volcano Engine for rapid implementation and optimization for the Chinese language context.

Compared to domestic Nio, XPeng, and Li Auto, Tesla has gained an advantage in multi-turn dialogue and emotional perception capabilities, but still needs to be cautious of long-term technological dependency risks and supply chain lock-in issues.

This strategy demonstrates the diversified paths of global smart automotive AI deployment: abroad emphasizes self-research control, while domestically emphasizes rapid response and localized optimization.

Tesla's choices in the domestic market balance speed, cost, and long-term potential, providing dual guarantees for market competition and capital value.

The future development direction of in-vehicle AI includes multimodal integration, OTA intelligent upgrades, personalized scenario-based interactions, and international adaptation.

Through continuous iteration of models in the cloud, vehicle functions and interaction capabilities will be continuously enhanced, while supporting third-party applications and content service access, forming an ecological platform.

Multimodal integration will achieve synchronized interaction of voice, visual, and sensor data, creating an immersive driving experience; OTA upgrades will ensure that models and functions are continuously updated to meet users' growing intelligent needs.

This ecological construction not only enhances vehicle competitiveness but also provides a foundation for Tesla to build a complete mobile intelligent terminal. The collaboration of functional and conversational models makes in-vehicle AI a unified system of "tool + partner," creating higher value for users while providing long-term technological and commercial advantages for the company.

Tesla's dual model strategy for the Model Y L demonstrates the leap of in-vehicle AI from functional execution to an intelligent ecosystem.

The Doubao and DeepSeek models not only improve driving operation efficiency but also enhance user experience and brand stickiness, upgrading vehicles from mere transportation tools to mobile intelligent terminals Through AI technology, Tesla is reshaping in-car lifestyles and setting a new benchmark for intelligent driving, which also provides a new deep reference coordinate for the entire smart automotive industry