Chief Operating Officer of Matrix Yuan: Discuss how the industrial Internet uses blockchain and privacy computing

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Xie Hongjun, chief operating officer of Matrix Yuan, believes that the role of blockchain and privacy computing on the industrial Internet is embodied in digital identity, data sharing, and data ownership.

Speech: Xie Hongjun, Chief Operating Officer of Matrix Yuan

On October 28th, on the second day of the 6th Blockchain Global Summit hosted by Wanxiang Blockchain Lab, Xie Hongjun, Chief Operating Officer of Matrix Yuan, brought a wonderful sharing of privacy computing and distributed cognitive industrial Internet.

The following is the speech content:

Xie Hongjun, Chief Operating Officer of Matrix Yuan

I’m Xie Hongjun of Matrix Element. Let me share with you a recent experience. I rushed to Shanghai early in the morning because my family suffered a cardiovascular disease. I handled the entire process from illness to emergency and transfer. It is that the data between different hospitals can not get through, especially blood data, which is constantly repeated for blood tests. There is no connection between the hospital and the hospital, the past medical information and the medical information checked now, which caused me a lot of trouble. The second thing Mr. Kai-Fu Lee said on the Internet on September 12, which helped the two companies obtain a lot of data during their growth. The two companies are immediately clarifying that one said that I had never obtained similar face data, and the other said that they had never deliberately collected such data in the process of cooperation with my consumers and partners.

When this matter was fermenting that evening, Mr. Li Kaifu quickly explained two points. The explanation of these two points is very interesting. First, he said that at the start-up stage of these companies, he did help them find many partners to enhance their technology and improve the recognition rate of the model. The second thing, he helped AI companies and specific scenarios in the process of docking, he did not let the data leave the user’s database, but input AI algorithms into the data application side. There are two interesting points here. First, the relationship between data sharing. Second, about the sharing of models and data. Regardless of the medical data I shared just now, the consumption data of the consumer Internet, and the data in the industrial Internet discussed today, similar problems exist. In his article “Explaining the Distributed Industrial Internet”, Mr. Xiao has a good typical definition of the cognitive industrial Internet. If you are interested, you can take a look.

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The architecture of the Industrial Internet is an excerpt from the “Industrial Internet White Paper 2017”, and it is also shown in Mr. Wang’s sharing. It is nothing more than the equipment layer of its industry itself, including a series of software and applications for industrial processes. Facing such a complex system, how to use blockchain and privacy computing methods, how to solve the problem of data sharing and utilization, mutual training of models, etc., including commercial value. These are some of the pain points of the Industrial Internet, in three aspects. One is the network layer. The network layer is very interesting. When I talked about the industrial Internet with the chairman of Zhejiang Supcon, he said that if the blockchain can help me share the value of useful data in the industrial process, it will be a great benefit. Promotion of the Industrial Internet. He analyzed the status quo of the Industrial Internet. It has very little data used for the control of industrial processes, and a large amount of other generated data is stored there invalidly, and the data here is very valuable. I will calculate two small problems to be solved by using privacy computing later, one is the product traceability of industrial processes, and the other is the financial leasing of industrial high-value equipment.

There are some problems in the network layer, including data deposition in the industrial control network. Second, the network of corporate information is difficult to extend to industrial systems, which is a very obvious problem. In the past, the enterprise information network, these data, management systems, and industrial processes generated data, and the real systems were difficult to connect. Third, supporting high-quality networked collaboration and services is also a major pain point for them. Including data interface, a series of process problems, as well as industrial equipment sensor identification problems, etc., must be resolved.

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The platform system has the problem of data islands and data mining applications. I don’t know how to mine, and how valuable the data generated is. There is also the storage of information. After storage, we will talk about how to authorize management of data. Of course, the traditional industrial Internet, as a computer system, has security issues, so I won’t go into details here.

Look at the process, department settings, and product value chain settings of a typical manufacturing company. There are R&D, production planning, material control, project management, production process, quality, supply chain, marketing, and auxiliary support systems for all processes, such as administration. Starting from customer demand to production, after completing manufacturing and delivering services, how to open up a fully closed loop of data. We call the management of the product’s full life cycle, and we must also manage the data flow. As Mr. Wang said, the data flow, value flow, and future asset flow must be properly connected.

What value can it bring? Its commercial value, industrial manufacturing process involves the management of the product chain, which is its core. From the demand side to production, to quality monitoring and schedule management in the process, data management is required. Including the future integration of logistics, information, assets, etc., including how to improve production efficiency, and the asset chain that opens up with financial institutions. The matter of supervision is well understood. Anything out of supervision has certain limitations for the development of this matter. We use the traceability, evidence deposit, and penetrating supervision of the traditional blockchain, which can not only facilitate the production activities of enterprises, but also facilitate the supervision of the regulatory authorities.

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To briefly talk about the empowerment of the industrial Internet as we understand the blockchain and privacy computing, it can be seen from the following eight aspects.

  1. Trusted digital identity. Solve the problem of equipment, sensors, machines, etc. in the production process. If people are involved, the same is true for people. The establishment, supervision, and circulation of all credible identities.
  2. Trusted data ownership.
  3. Trusted data connection and sharing.
  4. Trusted edge computing.
  5. Trusted industrial distributed ledger.
  6. Visual smart retail. Some industrial applications can be realized in the form of contracts and automated execution in the form of codes.
  7. Efficient multi-party collaboration. Utilize the method of multi-party calculation to realize the use of data and models under strict ownership protection.
  8. Flexible supervision entrance.