Amazon Cloud Technology: Set off a wave of digital transformation in the manufacturing industry, generative AI may provide a new direction

[Global Network Technology Comprehensive Report] In an environment of industrial change led by the booming digitalization wave and new technologies, digitalization and intelligence are providing new opportunities for enterprise transformation and upgrading. Industry 4.0 has accelerated the integration of information technology, digital technology, artificial intelligence and other technologies with the manufacturing industry. The integrated application of digital technology has become an important starting point for manufacturing companies to achieve scale growth.

A noteworthy fact is that the rapid development of generative artificial intelligence is bringing new development opportunities to traditional manufacturing. According to Gartner, by 2027, 30% of manufacturers will use generative artificial intelligence to improve product development efficiency

Gu Fan is the general manager of the Strategic Business Development Department of Amazon Cloud Technology Greater China. He pointed out at a recent industry communication meeting that generative artificial intelligence is rapidly being applied to various business scenarios in the manufacturing industry, and is being used in product development, design, and manufacturing. Operations, supply chain, marketing and sales, intelligent customer service and knowledge base have brought huge business value

Gu Fan pointed out that in the digital transformation practice of China's manufacturing industry from "quantity" to "quality", traditional manufacturing still faces the challenges of long-term technological product innovation, poor activation of overall equipment efficiency in factories, and supply chain efficiency and flexibility. The application of generative AI technology is reshaping the manufacturing industry and helping manufacturing companies create a new overseas pattern.

In the field of intelligent manufacturing, improving the overall equipment efficiency of the factory is the primary challenge of factory management. In fact, traditional industrial conceptual design is generally hand-drawn by hand, which requires the following challenges: long design cycles, challenges between the designer's business carrying capacity and rapidly growing business needs; design quality fluctuations, and output quality due to personnel levels. There are differences, and the design quality is affected by the flow of personnel, etc. The combination of the above factors has led to problems such as high labor costs, low concept output efficiency, and low concept pass rate in the conceptual design stage

The intervention of generative AI effectively improves the corresponding work efficiency. For example, Haier Innovation Design Center cooperated with Nolibox, a computational aesthetics company, to develop the country's first AIGC industrial design solution using the services of Amazon Cloud Technology, which significantly shortened the design cycle and also reduced the cost of conceptual design. The speed of overall conceptual design has increased by 83%, and the efficiency of integrated rendering has increased by about 90%

Gu Fan introduced that Amazon Cloud Technology focuses on key scenarios such as industrial data platform, equipment predictive maintenance, industrial visual inspection, and production and quality optimization. It can open up and analyze factory data, greatly improve productivity, asset availability, and product quality, and help Companies dramatically increase output, optimize production and implement predictive maintenance to increase machine uptime.

In the field of traditional industrial equipment and services, large-scale manufacturing equipment OEM companies are very concerned about how to create new revenue models. Manufacturing companies need to promote their transformation from "manufacturing" to "high-tech" enterprises, improve the performance and value of products through intelligence, thereby creating value-added services and expanding profit models and space. Currently, Amazon Cloud Technology provides powerful Internet of Things (IoT) and data processing and analysis capabilities to help manufacturing companies unlock the value of equipment and machine data to help them achieve sustained revenue and create new product and service models

With the help of Amazon Cloud Technology, Siemens China completed the flexible construction of an intelligent knowledge base and intelligent conversational robot Xiaoyu based on its own model in 3 months. It has core key capabilities such as natural language processing, knowledge base retrieval, and large language model training through data, which greatly improves the efficiency of obtaining internal employee information. In the first week of its launch, more than 4,000 employees used it, and more than 12,000 questions were answered. Moreover, this solution effectively reduces labor costs, and more than 90% of questions can be answered directly by the chatbot.

"Application is king," Gu Fan said: "For To B manufacturing industry, the most important thing in the large model field is to identify core business application scenarios, solve business problems, improve efficiency, reduce costs and increase efficiency. Big The model itself is actually just a tool. Apply different tools to the most appropriate scenario and combine them to find the optimal solution."

Therefore, in the manufacturing industry, the application of generative AI technology needs to be based on practical applications and solutions. Gu Fan believes that within a period of time, large models and small models can coexist, which is a major trend. Finding the right application scenarios and solutions is the best way to balance enterprise costs and efficiency. Gu Fan said: "For manufacturing customers, the core of large model application is to find the balance between model accuracy and inference cost."

Currently, Amazon Cloud Technology is committed to promoting generative AI to reshape the growth path of the manufacturing industry. By lowering the threshold in the critical path of building generative AI applications, it fully penetrates into the manufacturing value chain scenario and works with partners to provide industry Leading end-to-end technology solutions develop customized solutions in scenarios such as industrial design and knowledge base search, allowing manufacturing companies to fully realize the potential of generative AI.

The goal of Amazon Cloud Technology is to lower the critical path threshold for building generative artificial intelligence applications. But Gu Fan believes that the challenge faced by small and medium-sized enterprises is not in technology, but in finding suitable business scenarios and high-quality private data

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