Dr. Xiao Zhen graduated from Cornell University in the United States. After graduation, he worked as a researcher at ATT Labs (formerly Bell Labs) and IBM TJ Watson Research Center in the United States. During his work at ATT, he won the Research Excellence Award. In 2008, Dr. Xiao Zhen returned to Peking University as a researcher and doctoral supervisor as a member of the Hundred Talents Program. His open class on blockchain technology and applications has been played more than 1.4 million times on Bilibili.
The OKX University Interview series hopes to understand the development of the Web3 industry from the perspective of university personnel through dialogue, and at the same time provide reference for university groups to enter Web3 employment and entrepreneurship. In this issue, we specially invited Professor Xiao Zhen to be the guest speaker of the OKX University Interview, and we hope that his sharing will be helpful to you.
The OKX University Interview series is a special column produced by OKX and hosted by OKX official community ambassador Mercy (@Mercy_okx). It aims to explore the industry perspectives of people from universities around the world and provide reference for friends who are starting businesses in Web3 and looking for jobs.
1. You have conducted in-depth research on underlying blockchain technologies such as Ethereum around 2018. Over the past few years, Web3 and the blockchain industry have gone through multiple stages of development. What significant changes do you think have occurred in terms of technological evolution, industry ecology, and talent?
Our groups traditional field is distributed systems, and most of our past research work has focused on optimizing the network layer, consensus protocols, and other aspects. In recent years, blockchain has made great improvements in performance, and various Layer 2 technologies have emerged, such as Optimistic Rollup and ZK Rollup, which greatly improve network performance by moving most transactions outside the main chain, while maintaining the original decentralization and security to a certain extent. Of course, the degree of decentralization of some Layer 2 solutions is controversial. A landmark event in recent years is the upgrade of Ethereum, the most prominent of which is the transition from PoW to PoS, which has greatly reduced energy consumption, which is consistent with the concept of green environmental protection in todays world.
From the perspective of the industry ecology, DeFi, Metaverse, and NFT have all experienced explosive growth. Peking University has set up a special Metaverse Technology Research Institute, where I am the deputy director, focusing on the combination of AI and blockchain technology. In the past few years, in addition to mainstream blockchain technology and applications, emerging projects such as Theta Network have also brought important innovations and contributions to the blockchain ecology. Theta Network is a blockchain project focusing on decentralized video streaming. It solves the bandwidth bottleneck, high cost, and centralization problems in traditional video transmission by introducing blockchain and cryptoeconomic models. Unlike traditional streaming platforms (such as YouTube and Twitch), Theta Network uses the idle bandwidth and computing resources of users around the world to distribute decentralized video content, thereby reducing the cost of content distribution networks (CDNs).
From the perspective of talent cultivation, many traditional software developers and Web 2.0 developers have transformed into Web 3.0, bringing rich engineering practice experience to the blockchain and Web 3.0 industries, and promoting the specialization and diversification of blockchain application development.
2. You come into contact with students from different backgrounds in your teaching. How do you view the differences between today’s young people’s understanding of blockchain technology and that of a few years ago?
It should be said that a few years ago, the group of students who knew about blockchain technology was relatively small. The big bull market in the cryptocurrency circle in 2017 made many people start to pay attention to Bitcoin and blockchain. I opened two courses at Peking University, Blockchain Technology and Application and Introduction to Metaverse Technology. Most of the students who took my courses were from science and engineering backgrounds. They were interested in the technical principles of blockchain, consensus protocols, Web 3.0 application development, etc. My course assignments included implementing basic cryptographic operations and consensus protocols of blockchain in Go language, and programming smart contracts in Solidity.
At the same time, some students with liberal arts backgrounds are more concerned about the application scenarios, financial attributes, and social impact of blockchain, such as decentralized governance models, privacy protection, digital sovereignty and other socially transformative issues. The interdisciplinary integration and community-based practice of blockchain also make students more open and collaborative in technology exploration, indicating that blockchain technology will achieve more profound applications and changes in more fields in the future. In the past two years, with the popularity of AI technology, I have also added content such as chat bots and AIGC to the course, and also discussed related legal and ethical issues. One of the characteristics of my lectures is to combine theory with practice. There is a special part of the class to talk about currency scams to prevent students from being deceived in the future.
In general, young people today have a more diversified understanding of blockchain and Web 3.0. However, it is still a relatively niche field, and the number of students interested in it is not as large as that of AI, algorithms and other courses.
3. What opportunities and challenges do you think students currently face in starting a business or finding employment in the blockchain or Web3 field?
The current blockchain and Web3 fields are in a stage of rapid development, and there are more opportunities abroad than in China. Mastering programming languages such as Solidity and GO is the basis for entering the field of blockchain development. At the same time, you need to be familiar with development tools such as Remix and Truffle, as well as the process of testing and deploying contracts. Due to policy factors, the domestic industry is mainly based on alliance chains. My research group has cooperative relationships with mainstream domestic alliance chains (Changan Chain, Spark Chain Network, Ant Chain, etc.). In order to improve the system throughput of the alliance chain and improve the user experience, we conducted an in-depth analysis of the existing alliance chain consensus algorithm. The results show that traditional research on improving system throughput by optimizing consensus protocols ignores the impact of data distribution on system throughput, and transfers the performance bottleneck from the consensus layer to the network layer. In order to solve the performance bottleneck in the network layer, we proposed a new data flow framework composed of Predis and Multizone, which allows consensus nodes to use their idle bandwidth to pre-distribute block content in parallel, thereby confirming more transactions in one round of consensus and reducing transmission delays through compression based on block construction rules. In addition, the Multizone strategy further divides the network into multiple zones and combines multicast trees with erasure codes to reduce bandwidth peaks and data propagation delays in data distribution. The results of our cooperation with Ant Chain have been applied to the business scenarios of Ant Group and have achieved remarkable results, and have been awarded the CCF-Ant Research Fund Excellent Application Project.
At the same time, young people should also have the opportunity to accumulate some experience in developing foreign public chain projects. Our groups cooperation with Theta Blockchain public chain is very helpful for students to deeply understand the working principle, consensus mechanism, transmission protocol and other core technologies of the public chain, and it is also the basis for starting a business and finding employment abroad in the future. A major difference between public chains and alliance chains is the incentive mechanism. Designing a reasonable token economic incentive mechanism requires a deep understanding of cryptoeconomics (Tokenomics). A good blockchain project often requires interdisciplinary knowledge and talents in multiple fields such as computer science, finance, and law. At the same time, it is necessary to accurately grasp the user experience and diverse market needs, have a strong product thinking, and design innovative blockchain applications according to user needs. Here I want to emphasize one point: no matter where you are engaged in the blockchain industry, you must abide by the laws and regulations of the relevant countries. Products with financial attributes are subject to strong supervision in many countries. Dont indulge in money-making effects such as speculation and hype, but should work hard to make some influential projects.
4. What key factors should students prioritize when choosing to start a business or find employment in the Web3 industry?
I think the first thing to consider is whether you are targeting the domestic market or the overseas market. There are big differences between the entrepreneurial and employment environments in the Web 3.0 industry in mainland China and overseas: China has strict supervision over the cryptocurrency and blockchain industries, and explicitly prohibits virtual currency transactions, so you cannot rely on issuing coins or ICOs to raise funds or make profits when starting a Web 3.0 business in China. Decentralized finance (DeFi) and NFTs and other products are also strictly regulated in China. For example, there cannot be a secondary market for NFT transactions. This also makes it difficult to raise funds in China, and venture capital institutions are cautious about start-ups in the Web 3.0 industry. China supports the application of blockchain with non-financial attributes, the so-called coin-chain separation. Most domestic blockchain companies focus on alliance chains, and are at the worlds leading level in application fields such as supply chain finance, food traceability, judicial evidence storage, and data security. There are a large number of high-level Internet and Web 2.0 talents in China, but the number of Web 3.0 companies is relatively limited, and most of them are concentrated in technology development, underlying protocol research and other directions. There are not many job opportunities in blockchain-related positions. Many domestic blockchain companies rely on government projects to support their main income.
In contrast, some overseas countries (such as Singapore) have adopted a relatively loose regulatory policy for Web 3.0. The laws and regulations are relatively transparent and stable, which helps startups develop under a foreseeable policy framework. The compliance cost is relatively low, which is conducive to the rapid advancement of companies in financing and marketization. It is worth noting that the regulatory policy in the United States has become stricter, and it is not as easy to issue coins as it was six years ago, such as ICO. However, the financing atmosphere in Silicon Valley is still very good, with mature venture capital and incubator support, and a high degree of acceptance of Web 3.0. Many venture capital institutions are actively deploying in the field of Web 3.0, and startups can relatively easily obtain financial support.
5. Web3 and artificial intelligence (AI) are two major technological trends at present. How do you view their integrated development?
This is a very good question! The research group I lead is precisely focusing on both blockchain and artificial intelligence. In the past few years, our group has cooperated with Theta Labs in the United States to publish a series of papers at internationally renowned academic conferences that apply AI technology to the fields of blockchain and distributed systems. For example, the blockchain sharding paper published earlier this year significantly reduced the proportion of cross-shard transactions while maintaining load balancing through blockchain sharding technology based on deep reinforcement learning, greatly improving the performance of the blockchain system. Our group has cooperated with Theta Labs to develop a series of AIGC demos, such as sketch to 3D, which can convert user hand-drawn sketches into high-quality three-dimensional models within tens of seconds. This technology has broad application prospects in industries such as film, games, and precision manufacturing. We have also innovatively proposed a method to enhance the robustness of computer vision models, which is of great significance for building virtual reality systems such as the metaverse.
In general, the integration and development prospects of Web 3.0 and artificial intelligence (AI) are very broad. Web 3.0 is committed to building a decentralized Internet ecosystem, giving users greater data ownership and control, while AI provides Web 3.0 applications with more accurate interactions and experiences through data processing and intelligent analysis. The two can complement each other in data processing, decentralized services, and privacy protection, adding new functions and application possibilities to their respective ecosystems. Through smart contracts and blockchain technology, developers can create a decentralized AI model market to make the model training and use process more transparent and traceable. Developers can distribute trained AI models to users in the decentralized network, eliminating dependence on centralized platforms and stimulating fair competition in the AI model market. The decentralized data storage and privacy protection features of Web 3.0 can make up for the shortcomings of AI in data security. With decentralized storage, users can control their own data storage and use rights, so that AI algorithms can still obtain training data while protecting privacy.
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