Recap: Highlights from Professor Deng’s HeCaiJing Interview

Professor Deng shares his thoughts about Matrix’s Enterprise Cloudchain, AI and more!

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Last week, HeCaiJing (“核财经”), a prominent Chinese blockchain media outlet, interviewed Matrix Chief AI Scientist Professor Steve Deng. In the interview, Professor Deng discussed several topics including the recently revealed YangDong Artificial Intelligence Research Institute and Matrix’s Enterprise-Grade Big Data Cloudchain Solution — tentatively the Matrix Enterprise Cloudchain, for short. The Matrix Enterprise Cloudchain is a high-performance, secure and interoperable enterprise-grade big data platform combining AI, cloud computing, and blockchain technology.

This article serves to share some highlights from the interview with Matrix’s non-Chinese-speaking community. Please note that this is not a direct translation of the original interview. Rather, choice quotes and comments are pulled and given context. The original interview can be found here.

On the Matrix AI Network

On Decentralizing AI

According to Professor Deng, “many enterprises have a lot of data, but they are not willing to give you access to their data to train AI models because they have fears about data privacy and improper data disclosure. Besides these fears, enterprises also worry that once the data has been used to train the AI model, the AI model might be used to generate revenue. They worry that they won’t get a fair share of this revenue.”

Professor Deng believes that the solution to this problem is found in blockchain technology. Blockchain technology makes it possible to guarantee the rights and interests of everyone involved — be it the data providers, AI-model developers and users. With the kind of protection that blockchain provides, major obstacles slowing the development of AI can be overcome. “Data and AI models are inherently digital, so we aim to take into account the interests of all parties using our enterprise-grade big data cloudchain solution,” reiterates Professor Deng.

On AI and Blockchain

On Industrial Big Data

While domestic in nature, these Chinese national strategies have far reaching implications as China is a major player in industrial equipment manufacturing, operations and maintenance industries. For instance, China is responsible for about 80% of the world’s total port equipment, 70% of the world’s high-speed trains, 60% of the world’s excavators, 40% of the world’s marine vessels and 39% of the world’s heavy equipment. However, despite these lofty achievements, inefficiencies abound.

According to recent data, while China created 11.6% of the world’s GDP in 2013, it did so while accounting for 21.3% of the world’s energy consumption. According to Professor Deng, these industries are primed for a revolution. “When only considering the rail industry, a quarter of the world’s transport workload happens in China despite using only 6% of the world’s railway operating mileage,” notes Deng. “This is the highest transport density in the world.”

Unlike traditional internet applications, industrial big data applications tend to have higher and more stringent requirements for real-time processing. As network bandwidth is often limited, it can be difficult to guarantee performance by solely relying on cloud platforms. Similarly, industrial big data has stringent privacy requirements. This means that using existing public cloud solutions is not appropriate. Professor Deng notes that “the cost required for an enterprise to build, operate and maintain a private cloud is prohibitive. It is not a cost-effective or viable option for most enterprises.”

On Equipment Manufacturing, Operations and Maintenance

On Medical Treatments

On Remaining Barriers

On the Future

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