Editor’s Note
Great Wall Strategic Consulting has been compiling and publishing the “Enterprise Research Report” since 1995, providing in-depth analysis and development assessments in various fields including technological innovation, industrial upgrading, regional development, government governance, and innovative concepts. This article is edited based on the content of the 396th issue of the Enterprise Research Report, “Characteristics and Typical Business Models of New Quality Service Industry,” to provide readers with insights.
The Industrial Large Model refers to an artificial intelligence model established to meet the needs of the industrial sector, aimed at predicting and optimizing the operation of industrial systems. It is widely used in various scenarios and stages of research and development, production, and management, enhancing industrial efficiency, reducing operating costs, and improving product quality.
The Industrial Large Model has three characteristics: multidimensional modeling, high integration, and intelligent optimization, making it an important engine driving the intelligent transformation of industries.
First, Multidimensional Modeling. Its multidimensional modeling capability allows the industrial system to be presented comprehensively and in detail, covering not only the operational status of physical equipment but also deeply analyzing elements such as process flows, human resource allocation, and supply chain management, constructing a three-dimensional and dynamic mirror of the industrial system. This comprehensiveness ensures that the model can accurately capture every subtle change in the industrial system, providing a solid foundation for precise analysis and decision-making.
Second, High Integration. The Industrial Large Model exhibits high integration characteristics. Within the model, various sub-modules and components work closely together to form an organic whole, achieving cross-domain and cross-system data sharing and collaborative optimization. This integration not only enhances the operational efficiency of the model but also promotes close linkage among various aspects of the industrial system, significantly improving overall effectiveness.
Third, Intelligent Optimization. The deep integration of AI technology endows the Industrial Large Model with powerful intelligent optimization capabilities. Relying on advanced technologies such as big data, deep learning, and machine learning, the model can autonomously analyze vast amounts of data, simulating the decision-making processes of human experts, providing efficient and precise predictions and decision support for industrial production. Additionally, its self-learning and continuous optimization features ensure that the model can keep pace with industrial development trends and continuously adapt to new demands and challenges.
Since the 1990s, the development of Industrial Large Models abroad has undergone profound changes from theoretical exploration to technological breakthroughs and widespread application. In the early stages, the field of artificial intelligence was still in its infancy, with researchers focusing on rule-based expert and knowledge representation systems, laying the theoretical foundation for later developments. Entering the 21st century, especially from 2006 to 2010, the rise of deep learning technology became a key turning point in the development of Industrial Large Models. By constructing deep neural networks, models could automatically learn feature representations of data, significantly enhancing the performance of large models. Landmark events include the research results of Geoffrey Hinton’s team in 2006 and AlexNet’s victory in the ImageNet competition in 2010, marking a solid step in applying deep learning technology in the industrial field.
Since 2018, with the continuous enhancement of data resources and computing power, large-scale pre-trained models have become a new trend in the development of Industrial Large Models. By the end of 2022, landmark achievements such as OpenAI’s GPT series and Google’s BERT model not only demonstrated outstanding performance in various tasks but also pushed the boundaries of AI technology. The application of these models has not only improved the level of intelligence in industrial production but also injected strong momentum into the transformation and upgrading of the global industrial system.
Currently, China’s large model technology is in a golden period of rapid development. In January 2024, the State Council’s executive meeting studied and deployed work to promote the empowerment of artificial intelligence in new industrialization, emphasizing the deep integration of artificial intelligence and manufacturing, focusing on intelligent manufacturing, driving intelligent upgrades in key industries, and vigorously developing intelligent products to empower the industrial manufacturing system at a high level.
In recent years, China has demonstrated strong catching-up and independent innovation capabilities in the field of large model technology, with domestic companies such as Baidu, iFlytek, Tsinghua Zhiyu, and SenseTime rapidly narrowing the gap with international frontiers. Meanwhile, China has also made breakthrough progress in open-source models and multimodal fields, further consolidating its technological foundation.
On June 4, 2023, China’s first self-controllable industrial large model—ZhiGong Industrial Large Model—was officially launched, marking an important step for China in the field of industrial intelligence. This model has been iteratively upgraded to versions 2.0 and 3.0, successfully achieving application in multiple key areas such as energy management and comprehensive management of electric energy equipment. In addition, the ZhiGong Industrial Large Model has won several awards and been included in important lists such as the “AIGC Industry Chain Beijing Specialized New Enterprise Map” and the “2023 AI Large Model Pioneer List TOP50,” fully demonstrating China’s technological strength and market recognition in this field.
At present, the main entities laying out industrial large models can be divided into four categories: AI vendors, industrial technology service providers, innovative growth enterprises, and research institutions/technology giants.
The Industrial Large Model is a key tool for intelligent upgrades and is crucial for industrial enterprises, possessing vast application scenarios. Unlike previous applications of artificial intelligence technology in single industrial scenarios, the Industrial Large Model is based on general large model technology and trained by learning a large amount of industrial data and knowledge. It can not only analyze and judge based on existing data but also output new knowledge and solutions through training, serving as the foundation for promoting the intelligent transformation of industrial enterprises. For instance, the iFlytek Spark’s Antelope Industrial Large Model can achieve various functions such as industrial understanding calculation, industrial knowledge Q&A, industrial code generation, and industrial text generation. With the number of large-scale industrial enterprises in China reaching 500,000, the demand for intelligent transformation of industrial enterprises provides a vast application market for Industrial Large Models. It is predicted that by 2026, the market size of industrial large models in China will exceed $500 million, with a five-year compound growth rate of 116%. Currently, there are many participants in the industrial large model market, including internet platforms (such as Baidu, Tencent, Alibaba), technology companies (such as iFlytek, Huawei), AI startups (such as Innovation QiZhi), and manufacturing enterprises (such as Haier).
The application scenarios of Industrial Large Models span the entire lifecycle of industrial enterprises and can achieve “cross-scenario” empowerment. In the research and design phase, Industrial Large Models can be used in scenarios such as drug development and industrial product design. For example, Innovation QiZhi’s “ChatCAD” can automatically generate industrial design drawings that meet requirements through conversational Q&A and can be exported to traditional software for fine-tuning. In the production and manufacturing phase, it is mainly applied in scenarios such as industrial code generation, safety supervision, equipment management, and product inspection. For instance, the “Feifan Industrial Large Model” from Feite Detection can achieve intelligent Q&A for process experts, interconnectivity of equipment data, and generation of quality reports. In daily operations, it can enhance work efficiency by integrating with management software and improve enterprise knowledge management through Q&A interactions.[2]
The practical application of Industrial Large Models relies on the support of computing power infrastructure. The construction of Industrial Large Models requires a large amount of industrial data and knowledge, with parameter counts of at least several hundred million. For instance, the “QiZhi Kongming Industrial Large Model” released by Innovation QiZhi has reached a parameter count of 75 billion, while new computing power infrastructures like intelligent computing centers can not only provide strong intelligent computing resources for the training and inference of Industrial Large Models but also offer ample storage space to meet the data storage needs of large models, serving as the cornerstone for the practical application of Industrial Large Models.
Huawei Pangu Large Model: A Multi-layered Large Model Empowering Various Industries
The Huawei Pangu Large Model includes a “5+N+X” three-layer architecture: “5” represents five foundational general large models, providing services such as knowledge Q&A and code generation, available for direct use by enterprises; “N” represents N industry large models, which focus on training industry-specific large models based on general large models in fields such as mining, finance, and meteorology; “X” represents specific business scenarios, including lead drug screening, foreign object detection on conveyor belts, and typhoon path prediction. Utilizing the Pangu Mining Large Model, Shandong Energy Group has achieved intelligent leaps across multiple links, such as conducting intelligent analysis of raw coal quality data and process parameters based on Pangu predictive models for different coal seams, seasons, and ash content, improving the recovery rate of clean coal by 0.1%-0.2%; the AI main operation intelligent monitoring system of the Pangu Mining Large Model can accurately identify anomalies such as large coal and anchor rods, achieving 24/7 inspection with an accuracy rate of 98% for foreign object identification.
Simu Technology IndustryGPT: A Multi-modal Large Model Focused on Industrial Manufacturing
Founded in 2019 by experts in machine vision, including a lifelong professor at the Chinese University of Hong Kong and an IEEE fellow, Simu Technology developed the world’s first industrial multi-modal large model—IndustryGPT V1.0. This model can understand and address complex problems in the industrial field through deep learning and big data analysis techniques. The model training data covers over 200 different industrial scenarios, more than 3 million industrial images, and over 50 billion tokens (the basic unit for processing text). In the electronics manufacturing industry, IndustryGPT V1.0 can predict potential equipment failures and conduct maintenance in advance, enhancing the stability and reliability of production lines. In the steel industry, IndustryGPT V1.0 is applied in intelligent quality inspection systems, utilizing image recognition technology to automatically identify minor defects on product surfaces, significantly improving detection speed and accuracy.
Although China has made certain achievements in the development of Industrial Large Models, there are still gaps compared to the international top level in terms of AI penetration in manufacturing, implementation in industrial vertical fields, core production applications, and data integrity and connectivity.In the future, continuous investment in research and development is needed, along with strengthening technological innovation and talent cultivation, to promote the landing and deepening of Industrial Large Models in more application scenarios, and to foster a more open and cooperative posture to jointly promote the prosperous development of global industrial large model technology.
[2] Reference material: China Communication Industry Association “Industrial Large Model Application Report”
This article is excerpted from the Great Wall Strategic Consulting Enterprise Research Report, No. 396
“Characteristics and Typical Business Models of New Quality Service Industry”
(Report authors: Xu Huan, Shen Wenqi, Cao Xing, Zhou Xin)
