Large model application exploration covers the entire industrial chain

The report provides an in-depth analysis of the exploration of the application of large models in the entire industrial chain. In the field of R & D design, large models improve R & D efficiency by optimizing the design process; In the field of manufacturing, large models expand the boundaries of intelligent manufacturing applications; In the field of operation and management, the big model improves the level of operation and management based on the assistant mode; In the field of products and services, the big model promotes the intelligence of products and services based on interactive capabilities.

CMA132 The report details specific application cases in each field. For example, in the field of research and development design, CALA, a fashion design platform, provides generative design tools based on Open AI, which can quickly transform designers’ creativity into design sketches, prototypes and products. Nvidia has launched a 43 billion parameter large model ChipNeMo, which can effectively help chip designers complete related chip design tasks. In the field of product services, Tencent’s new generation of intelligent cockpit solution TAI4.0 starts from the scene and user experience, deeply utilizes the car’s perception ability and the learning and understanding ability of large models to build a complete intelligent closed-loop experience from multi-mode interaction to personalized service.

CMA132

Challenges and prospects of large industrial models

The report points out that industrial large model applications face three major challenges: data quality and security, reliability, and cost. First of all, data quality and security are the primary concerns of industrial large model building. The quality of industrial data varies. The industrial field covers a wide range, including 41 industrial categories, 207 industrial classes, and 666 industrial subclasses, resulting in diverse data structures and uneven data quality. Industrial data security requirements are high. Secondly, industrial large-scale models need to meet the requirements of high reliability and real-time. Industrial production environments often involve complex processes, high-precision operational controls, and stringent safety standards. Errors in any model prediction or decision making can lead to production accidents, quality problems, or economic losses. Finally, high costs limit the input-output ratio of industrial large-scale model applications. Large models often require large data sets and high-performance computing clusters to train, further driving up training and inference costs, and long-term operating costs are high.

The application of industrial large-scale models will continue to accelerate and deepen along with technological evolution. First of all, a large number of industrial apps are quickly built based on a small number of large industrial base models to meet the needs of industrial fragmented applications. CMA132 As the industrial scene is complex and presents a fragmented pattern, through the combination of industrial base large model and industrial APP, it can widely and quickly respond to the challenges in the industrial field and promote the intelligent upgrading of various industrial scenes. Secondly, new breakthroughs in large models bring new scenarios for industrial applications. With the development of new technologies such as Agent and embodied intelligence, large models will open up more application scenarios in the industrial field, making equipment and machines more intelligent and improving production efficiency and safety. Finally, the reduction in the cost of large models will accelerate industrial applications. Techniques related to large model compression, such as pruning, quantization, and distillation, will effectively reduce the number of parameters and computational requirements of the model, thereby reducing the cost of training and deployment. This will make the large model more suitable for resource-constrained environments and accelerate its application in the industrial sector.