As multimodal large models advance toward cognitive reasoning, which vertical industries will see the earliest implementation?
The Zidong Taichu 4.0 large model, unveiled at the 2025 East Lake International AI Summit, demonstrated cognitive capabilities of "seeing, recognizing, and thinking simultaneously," marking a triple leap for AI technology from pure textual reasoning to fine-grained multimodal semantic reasoning. Artificial intelligence is transitioning from "perception and understanding" to "cognitive reasoning," a shift that is set to fundamentally transform efficiency and paradigms across multiple vertical industries.
The core breakthrough in cognitive reasoning lies in the model’s ability to process and understand multiple information sources—text, images, audio, and even video—simultaneously, extracting deep semantic relationships from them. This capability, akin to human comprehensive judgment, enables AI to genuinely understand the logical chains behind complex scenarios.
1. Healthcare
The medical field is considered one of the first verticals where multimodal reasoning large models will be deployed. Their advantage lies in simultaneously processing clinical images, medical record text, lab data, and other multi-source information to provide comprehensive diagnostic suggestions. A trend exemplified by the "AI Ya Hui Zhen" system developed by a team from Tongji University. This system integrates multimodal technology and algorithmic innovation, building a training database based on over 3,000 oral disease cases. It achieves a comprehensive detection accuracy of 93.4% for oral diseases and reduces patient consultation time by 58%. AI is becoming a key driver for balancing medical resources. The "AI Ya Hui Zhen" system has been piloted and promoted in Shanghai, Yunnan, Gansu, and other regions, enabling grassroots communities to access professional oral screening services. Similarly, a cardiac multi-center project, involving 15 institutions and over 500 clinical cases, aims to establish evaluation metrics for AI technology in CT cardiac imaging, promoting the integrated innovation of domestic CT devices and AI algorithms.
2. Smart Manufacturing
Manufacturing is another hotspot for multimodal reasoning model applications. In industrial settings, AI needs to understand design blueprints, sensor data, equipment status records, operation manuals, and other diverse information—precisely where multimodal reasoning models excel. Jiang Xingpeng, Secretary of the Party Committee of Wuhan Software Engineering College and Wuhan Open University, noted that students can use multimodal large models to design and program complex component process codes, and virtually verify whether the code can generate the corresponding product, thereby enhancing learning efficiency and reducing costs. Professor Chen Qifeng from the Hong Kong University of Science and Technology explained at the 2025 Convergent Intelligence Industry Development Conference that Vision-Language-Action (VLA) models integrate visual, linguistic, and behavioral multimodal information, laying the technical foundation for autonomous decision-making and action execution by robots and vehicles in complex environments. In the field of embodied intelligence, VLA models provide robots with enhanced environmental understanding and decision-making capabilities. Professor Chen described a "cerebrum" and "cerebellum" system: the "cerebellum" handles control, while the "cerebrum" is responsible for behavior planning and decision-making. This architecture enables robots to better adapt to complex environments and perform more precise operational tasks.
3. Law and Public Services
Multimodal reasoning models also show broad application potential in law and public services. The "AI Legal Q&A Mini-Program" developed by the Xianning Municipal Bureau of Justice has become a 24/7 "legal advisor" for the public. The system's backend integrates over 45,000 laws, regulations, judicial interpretations, and guiding cases, forming a comprehensive and structured legal knowledge base. After intensive training, it accurately understands public legal queries and can draft administrative reconsideration applications, complaints, statements of defense, and other legal documents. AI is making professional legal services accessible to all. For small and micro enterprises, individual businesses, and entrepreneurs frequently facing contract risks and compliance challenges, the mini-program can automatically analyze contract content, precisely identify potential issues such as contract loopholes and default risks, and generate assessment reports. In the field of prosecutorial supervision, the Huizhou District Procuratorate explores a "drone + big data" workflow, integrating data captured by drone aerial photography with big model clues for analysis, enabling efficient and convenient verification and promoting the practical application of prosecutorial large model supervision. This multimodal information fusion significantly enhances the accuracy and efficiency of legal oversight.
In the coming years, as technology matures, multimodal reasoning models will find applications in more fields such as finance, transportation, and agriculture. This trend is foreshadowed by the Wuhan "AI + Meteorology" Innovation Studio established through the collaboration of the Wuhan Artificial Intelligence Research Institute and the Wuhan Meteorological Observatory, as well as the application of VLA models in autonomous driving demonstrated by Yuanrong Qixing.
