Generative AI technology provides strong support for manufacturing companies to reduce costs and increase efficiency

In 2023, Artificial Intelligence Generated Content (AIGC) will become the hottest topic in the technology field. There is no doubt that

So for the manufacturing industry, how should they benefit from the emerging technology of generative AI? What kind of inspiration can the majority of small and medium-sized enterprises that are implementing digital transformation get from this?

Recently, Amazon Cloud Technology worked with representatives from the manufacturing industry to discuss the current development trends of China's manufacturing industry, the challenges and opportunities faced by the digital transformation of traditional manufacturing, and the innovative reshaping of manufacturing by generative artificial intelligence. Topics were shared and discussed in depth

The current application status of generative AI in the manufacturing industry

When mentioning the current situation and development trends of China’s manufacturing industry, as well as the opportunities that generative artificial intelligence brings to the manufacturing industry, Gu Fan, general manager of the Strategic Business Development Department of Amazon Cloud Technology Greater China, said that the digital transformation of traditional manufacturing Upgrading is accelerating and deepening, and high-end, intelligent and green have become the main trends in the development of the manufacturing industry. However, at the same time, there are still many problems and challenges in the manufacturing industry in terms of the application of generative artificial intelligence and large language models

First of all, compared with education, medical and other industries, the situation in the manufacturing field is different. The manufacturing scene is very fragmented, and there is relatively little public data on core processes, which makes it difficult to train relevant large-scale models, and it is also difficult to implement generative artificial intelligence in application scenarios

For the manufacturing industry, large models are just a tool. The second and most important thing is to identify the core business application scenarios, apply different tools to the most appropriate scenarios, and combine them to find the optimal solution to solve business problems. , to achieve cost reduction and efficiency improvement

Furthermore, judging from the current status of the manufacturing industry, the coexistence of large models and small models is still a major trend. In terms of small model solutions, Amazon Cloud Technology provides solutions based on small model construction for multiple scenarios such as industrial visual inspection and arrival time prediction. In terms of large model solutions, Amazon Cloud Technology also works with partners to Typical cases such as Siemens Intelligent Knowledge Base and Haier Innovation Design Center have been constructed.

Finally, for manufacturing companies, inference will occur when there are application scenarios. If the cost of inference cannot be controlled and they just blindly pursue the bigger the better model, it will eventually cause the company to be overwhelmed. Therefore, when manufacturing companies implement large model applications, they must find a balance between model accuracy and inference cost.

Challenges of digital transformation for small and medium-sized enterprises

In view of the current difficulties in digital transformation for small and medium-sized enterprises, Gu Fan said that Amazon’s current CEO Andy Jassy once shared the vision of creating Amazon Cloud Technology, which is to hope that all people who have just started their own innovation journey will be able to do so no matter when and where they are. , even in a dormitory or garage, you can have access to the same advanced infrastructure as large enterprises, and realize your own innovation at a very low cost.

Amazon Cloud Technology says this and does this. Since the birth of cloud computing in 2006, Amazon Cloud Technology has enabled thousands of small and medium-sized enterprises to build Internet applications without spending huge sums of money to purchase physical hardware such as servers and storage. Standing on the same starting line.

The currently hot generative AI also has similarities with the cloud computing that emerged that year. Amazon Cloud Technology is working hard to promote generative AI to become truly inclusive, and by lowering its technology and application thresholds, small and medium-sized enterprises can also benefit from this emerging technology. With the help of generative AI, small and medium-sized enterprises only need to identify business scenarios and provide high-quality private data, and then they can reduce costs and increase efficiency by building customized models, and even compete with medium and large enterprises.

Compared with medium and large enterprises, the relatively weak business end of small and medium-sized enterprises has also become a pain point for them to develop generative AI applications. To this end, Amazon Cloud Technology is committed to lowering the threshold in the critical path of building generative AI applications, allowing small and medium-sized enterprises to use the rich functions of Amazon Bedrock to more easily and conveniently access a variety of leading basic models through APIs, and use their own proprietary data to customize the desired model. At the same time, Amazon Bedrock also allows small and medium-sized enterprises to integrate and deploy generative AI capabilities into applications directly through Amazon cloud technology services without the need to manage infrastructure.

Amazon Cloud Technology has many advantages in empowering the manufacturing industry

When talking about Amazon Cloud Technology’s accumulated experience in empowering the manufacturing industry and its competitive advantages over other service providers, Gu Fan said that it is mainly reflected in the following aspects.

The rewritten content is: As the world's largest online retailer, Amazon and its cloud computing subsidiary Amazon Cloud Technology are also manufacturing companies. For example, Amazon's smart hardware products such as Kindle, Fire TV smart TVs, echo smart speakers and robots have all gone through large and complex production and manufacturing processes. Amazon and its cloud computing subsidiary Amazon Cloud Technology have also independently developed IC chips, involving core technologies and processes in the manufacturing industry. Therefore, Amazon Cloud Technology itself has accumulated rich experience in manufacturing automation and factory operations

2. Over the years, Amazon Cloud Technology has been empowering manufacturing customers through digitalization, helping customers organically integrate digital technology with core businesses such as product R&D and design, factory operations, supply chain management, and equipment services, and helping customers use Data analysis and insights improve business operations and deepen digital transformation.

3. Amazon Cloud Technology has a complete and powerful intelligent manufacturing ecosystem, and is committed to working with partners to create "last mile" solutions for customers in the intelligent manufacturing segment, empowering innovation in the manufacturing industry. development and digital transformation. Its partners include well-known international companies such as Advantech, Adlink, Lenovo, Accenture, Deloitte, Dassault, Infosys, etc., as well as Zhongke Yungu, Root Internet, Speedstone Technology, Zhongke Chuangda, Ziyun Technology and Zhongke Cloud Technology. Yiyun and other well-known domestic manufacturers. This huge partner network (APN) all over the world is also a huge advantage of Amazon Cloud Technology over other competitors

Scenario application of generative AI in the manufacturing industry

The difference between generative AI and other IT technologies is that it can bring huge space for innovation to an industry. Gu Fan pointed out that generative AI technology has a variety of application scenarios in the manufacturing industry, and listed some typical application scenarios

In the industrial design scene, traditional industrial conceptual designs are usually hand-drawn. Not only are labor costs high, the design cycle is long, concept output is inefficient, design quality fluctuates, and design quality is easily affected by the flow of personnel, but also designers The business carrying capacity often cannot keep up with the rapidly growing business needs. To this end, Amazon Cloud Technology has teamed up with its partner Computational Aesthetics (Nolibox) to use generative AI to create plans such as Wensheng diagrams and Tusheng diagrams, and carry out rapid concept prototypes and marketing material design, which can quickly generate multiple improved plan diagrams at one time. Haier Innovation Design Center thus created the country's first AIGC industrial design solution, which not only greatly shortened the design cycle, accelerated the overall conceptual design by 83%, increased the integrated rendering efficiency by about 90%, and significantly reduced the cost of conceptual design.

In the marketing scenario, Amazon Cloud Technology can use generative AI technology to create text-based diagrams and diagram-generated diagram solutions to produce marketing materials. By describing the product selling points, it can automatically generate images based on the image for this product and apply to different communication channels. , a complete set of online and offline marketing materials.

In functional support scenarios, considering that 80% of current enterprise data is unstructured data, enterprise employees often encounter pain points such as inaccurate content and difficulty in querying key information when using keywords to retrieve internal documents. Amazon Cloud Technology uses Generative AI technology builds an enterprise-level intelligent knowledge base, integrating search engines and large language models, allowing enterprise employees to quickly find the most accurate and effective content, effectively improving production and office efficiency. 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 only 3 months, which greatly improved the efficiency of internal employee information acquisition and effectively reduced manpower Cost, in the first week of launch, more than 4,000 employees used it, and more than 12,000 questions were answered.

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