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Opportunity, for those who are unreliable, is nothing but a \"scam\"”； And a \"scam\" is an opportunity for those who are reliable. So, whether it’s an opportunity or a scam for you, there is only one key factor: whether you are reliable! Today, I would like to talk to you about my current understanding of Industry 4.0. Following the convention of cultivation novels, the author divides Industry 4.0 as understood today into three stages: The first stage of Industry 4.0: “Industrial manufacturing automation.” The underlying technological drivers here are industrial robots and industrial automation. This is easy to understand: by using various robots and automated devices, human intervention is reduced, ultimately leading to a \"human-free factory.\" I remember it was around 2013; Siemens had an old man named Ruswo who came to China to give a speech, and I happened to attend the live version. At that time, he was already focusing on manipulating the term “Industry 4.0,” but after talking in a confusing way for ages, I still had no idea what he was actually trying to say. At that time, Brother Rabbit felt that he himself didn’t really understand it either… So from 2013 to 2015, the understanding of Industry 4.0 within that industry remained rather vague; although there were many interpretations, it essentially referred to various upgrades in industrial automation: more use of robots, unified communication interfaces, improved levels of automation, and maybe some fancy artificial intelligence features – all with the ultimate goal of using fewer humans. To this day, many people in China still have this understanding of Industry 4.0; you can see that in many places, as soon as smart manufacturing is introduced, billions are invested in building robot industrial parks, and funds are provided to support various automation manufacturers in applying to become model units – and that’s because they remain at this level of awareness. I can’t assert categorically that this must be wrong, but if all this effort is put into the \"Fourth Industrial Revolution\" just to save two people’s salaries, it seems a bit petty after all. The second realm of Industry 4.0: “Automation of data flow.” The underlying technological drivers include the Internet of Things, industrial software, cloud computing, big data, and artificial intelligence. This is much more complex; it was only after reading many articles written by my mentor, Mr. Guo Zhaohui, as well as former Minister An Xiaopeng of the Ministry of Industry and Information Technology, that I became aware of the existence of this realm. Let’s first consider the logic of development in industrial society: Industrial 1.0 referred to mechanization, replacing human labor with machine power, which enabled a significant increase in production efficiency. But there is a problem here: machines are not humans after all, and their mechanical structure prevents them from performing overly complex actions, so the improvement in efficiency is quite limited. It’s like taking a QQ and installing a Ferrari engine – no matter how powerful it is, if the chassis can’t keep up, it’s useless. Industrial 2.0: many people refer to it as electrification, but it is more accurate to describe it as a \"assembly line\". The so-called “pipeline” involves breaking down a production process into several steps, with each step involving very simple actions. Because the actions are simple, machines can carry them out, which enables electrification and makes it possible for machines to replace humans on a wider scale. Industrial 3.0, with its emphasis on scale, automation, and information technology, was actually developed to address the negative effects of Industrial 2.0. As mentioned earlier, Industry 2.0 brought about division of labor. But does such division necessarily lead to higher efficiency? Actually, that’s not correct; there is one key dimension missing, which is “collaboration”. In an era without division of labor, the entire production was carried out by a single person, and the efficiency depended solely on that person’s \"work efficiency.\" And with the division of labor, cooperation becomes necessary; “cooperation efficiency” then determines the efficiency of the entire production system. It’s like when Rabbit Brother plays Honor of Kings – team combat awareness is essential; no matter how skilled an individual is, if they’re paired with incompetent teammates, there’s nothing that can be done. Therefore, Industry 3.0 requires the concept of “Taiji giving rise to the Two Principles,” developing along two separate paths in order to address the collaboration issues posed by Industry 2.0. Among them, “automation” addresses the issue of efficiency in collaboration between machines ； And “informatization” addresses the issue of efficiency in collaboration among people. The entire process of Industry 3.0 was aimed at addressing the issue of collaboration efficiency faced by humanity following the division of labor in Industry 2.0. It is precisely because it solved this problem that, starting with Industry 3.0, we moved from an era of material scarcity to an era of overcapacity. At this point, human society faces the eternal problem, which shifts from \"insufficient production\" to \"insufficient demand\". In this sense, the first stage of Industry 4.0, namely industrial manufacturing automation, is actually merely an extension of Industry 3.0, as it still addresses the issue of insufficient production. Industry 4.0: producing customized products on assembly lines. With Industry 4.0 starting from the second phase, we must truly address the remaining issues from the post-Industry 3.0 era. Automation leads to overcapacity, while digitalization eliminates information asymmetry; both of these factors result in the same problem – namely, manufacturing becoming unprofitable. We say today that it’s difficult to operate in the real economy, and then we turn our anger on finance, asking, “Why the hell don’t you support the real economy?” It’s just as unreasonable as Uncle Wang at the entrance of the alley – the shift of finance away from the real economy is a result of businesses not making profits, not the cause. If you don’t make money, financiers naturally won’t invest in you; the less money you make, the fewer people will invest in you. It’s a simple principle. The real reason why it’s difficult to succeed in this field is that there are too many people doing the same thing as you, and the market is highly transparent. So how can you make a profit? Even if banks chase after you to lend you money, and venture capitalists chase after you to invest in you, it’s just so that you can cause more damage to that money. At this point, if you want to make money, there’s only one thing to do: do what others don’t do—customization. Custom products – one of a kind; no need for price comparison, less competition, opaque market – great for making money. But you’ve forgotten one thing: if everything you produce is custom, you’ll be exhausted. In fact, the mass production of Industry 3.0 represents the ultimate ideal state for industry: it offers the highest production efficiency, the lowest energy consumption, and the fewest defective products—but it is not profitable. With the production of custom products, each item may be different, making it impossible for employees to carry out repetitive or experience-based tasks, and it is also difficult to standardize the production process using assembly lines. Therefore, the production efficiency must be low, energy consumption must be high, and there will definitely be many defective products. The second level of Industry 4.0 addresses exactly this issue: how to produce customized products on assembly lines while minimizing the negative effects associated with customization. Automation in industrial manufacturing alone is not sufficient; the higher the level of automation on a production line, the lower its flexibility usually is. If humans are involved in the production process, it’s enough to train them each time a different product needs to be produced, but with a machine-based production line, it’s impossible to adjust the line in time every time a product change occurs. That’s why you see that clothing manufacturing companies mostly rely on manual labor and use very few machines – it’s for this reason. In the clothing market, there are various styles available throughout the four seasons – spring, summer, autumn, and winter. On top of that, there are occasional trends that emerge, and things change so rapidly that machine production cannot keep up; therefore, human labor is necessary. To enable a production line to manufacture customized products, in addition to specially designing the production units, the most crucial aspect is being able to quickly \"train\" the machines each time a different product is to be produced – and this is what is meant by \"automated data flow.\" Automation of data flow has two meanings: first is the “liberalization of data flow,” meaning we “want the data to go wherever it wants to go.” This relies on the Internet of Things, which creates high-speed networks for data transmission; industrial software is then used to create \"digital twins\" of machines in the physical world. Various information technology software systems, such as ERP, MES, PLM, and so on, serve this purpose. This step is called “Smart Manufacturing” – that is, a manufacturing system capable of responding quickly to rapidly changing external markets. Only thereafter does true “automation of data flow” occur, with data going wherever it needs to go. This requires the use of industrial cloud computing technologies, industrial big data analysis techniques, as well as artificial intelligence technologies; together these elements constitute the complete second stage of Industry 4.0, namely true “Intelligent Manufacturing”, the full form of smart manufacturing. Since the Industrial Revolution, we have been gradually turning humans into machines; today, we want to turn machines into humans. In this sense, I fully agree with my mentor, Mr. Guo Zhaohui’s view: Industry 4.0 is not in an iterative relationship with Industries 1.0, 2.0, and 3.0, but rather they coexist side by side. Not all companies need to adopt Industry 4.0, nor do all industries need to evolve to that level; it depends mainly on whether you are already operating in a market characterized by \"overcapacity and information transparency.\" If you are already in this market, then you must strive for Industry 4.0; whereas if your market is not yet at that stage, then 2.0 or 3.0, or even 1.0, is the best option. Take Swiss watch shops for example; what they seek is entirely manual production, which belongs to the pre-1.0 era. Will it evolve towards 4.0? It doesn’t need to, because its market isn’t one characterized by \"overcapacity + transparency of information\"; in fact, if it evolves to version 2.0, 3.0 or even 4.0, no one will buy it. So we don’t need to rush to adopt Industry 4.0 today; for some industries, Level 3.0 represents the optimal state forever. For example, in certain chemical industries, the products remain unchanged for years, and large-scale production is the best approach; trying to move to Level 4.0 would merely be a waste of time. Looking back, the second stage of Industry 4.0 is \"automation of data flow.\" Large companies in Germany and the United States, such as Siemens and GE, are focusing their efforts on this level; they also refer to this process as \"digitalization.\" Rabbit Brother’s original understanding remained at this level; when I started working on the transformation of factories, I also focused my efforts on exploring solutions for digital factories. It was not until recently, inspired by the digital research experts, that I realized there is a third level to Industry 4.0. The third realm of Industry 4.0: “Automation of economic operations” – The underlying technological driver: blockchain (http://yunrun.com.cn/news/2775.html). There is only one underlying technology for the third realm of Industry 4.0, and that is blockchain. Speaking of which, Brother Rabbit was one of the first investors in digital currencies in China, and I also made my first fortune from Bitcoin. But it was only recently that I realized that blockchain is the truly core technology of Industry 4.0, as it can bring about a whole new era – one of automated economic operations. Actually, I think there is something wrong with the translation of the term “Industry 4.0”; in English, both “industry” and “industrial sector” are expressed as “Industry”. Therefore, a more accurate translation for “Industry 4.0” should be “Industry 4.0”. It was industrial service providers such as Siemens who first introduced this concept to China, and it was deliberately translated as “Industry 4.0.” This gives the impression that “Industry 4.0” is related only to the digitization of factories and manufacturing, which in effect turns it into “Factory 4.0.” So I think it would be best to revive the term “Industry 4.0” – one that encompasses not only manufacturing but also the internet, gaming, entertainment, finance, and so on. Only through an overall digital transformation of all sectors of society can it truly be called the “Fourth Industrial Revolution”. So what exactly is “Industry 4.0”? Why does it have to be based on blockchain as well? This phenomenon cannot be explained from the perspective of digital technology; it needs to be discussed at the level of digital thinking. I’ve seen a friend, Professor Han Feng from Tsinghua University, write about the history of computer development; I think this history would fit well within the context of digital thinking. Digital thinking is divided into three generations: ① The representative of the first generation of digital thinking is Turing, who invented the Turing machine; the characteristic of the Turing machine is that \"programs are programs, and data is data.\" Its programming was fixed, similar to that of vacuum tubes; therefore, the earliest computers were extremely large in size. Their programming was determined by hardware, and data was entered via paper tapes. They could only accept data, not programs, and each computer had only one program, which meant it could perform only one task. For example, Turing machines were used to crack Nazi codes. ② The representative of the second generation of digital thinking was von Neumann, who brought about a major transformation in computers by creating a general-purpose computer and shifting programs from various vacuum tube hardware to software; from then on, \"programs could also be considered data.\" When we use computers, we don’t just input data; we also enter programs as data, which are then processed uniformly within the computer. This advantage not only allows for smaller computers, but also enables a single computer to carry out various tasks; there is no need to switch to a different computer each time a task changes – simply switching to a different program is sufficient. All of our modern computer systems are based on this way of thinking. Does it look familiar? Industry 4.0 involves the production of customized products on assembly lines; digital technologies are used to create a “digital twin” of the machines, and automation through data flow enables the same assembly line to carry out various tasks. There is no need to change the production line when changing products – this is also a result of this second-generation digital mindset. ③ Speaking of this, the third generation of digital thinking is undoubtedly the blockchain technology created by Satoshi Nakamoto. Because blockchain represents a fundamental breakthrough at the conceptual level; it is no longer about first entering a program and then inputting data, with the program handling that data. Instead, it allows the \"data itself to contain programs,\" with data and programs becoming one. Since the data comes with a program, it has the ability to recognize things; thus, the data can have its rights established and become an asset. This enables the traditional “information internet” to evolve into the era of the “value internet”. “The term “value internet” is quite abstract; let me give a simple example to illustrate it: ● Physical world: There is an apple, and if I give it to you, I no longer have it. ● Traditional Internet era: There was a photo from Apple in someone’s phone; it was sent to you, and now it’s in your phone as well as in theirs. ● The era of value networks: There’s a photo from Apple in someone’s phone; it’s sent to you, and now it’s in your phone, but it’s no longer in theirs. This is what excites me about blockchain technology. We often say these days that “data is an asset,” but in the era of the information internet, data has no value because it can be replicated infinitely. How can data that can be replicated endlessly have any value? In other words, the so-called “digital twins” promoted by all the giants in the Industry 4.0 sector today are a pseudo-concept; since data can be replicated infinitely, what we actually have are “digital multiples.” These multiples do not correspond one-to-one with the physical world, so their value is very limited. Only data with programs, data whose ownership can be determined, data that can be guaranteed to be unique and transferred directly, and data that can be trusted, has value. Furthermore, data containing programs can be compared with traditional economic contracts to become “smart contracts”. In fact, a “smart contract” is similar to our ordinary electronic contracts: when a certain trigger condition is met, a corresponding outcome is triggered. For example, “Every time Zhang San rides the yellow bike, he has to pay the shared bike company.” The input data is “ride the yellow bike”, and the result processed by the program is “pay the shared bike company”. It sounds simple, but it is difficult to implement in the second phase of Industry 4.0. First, where should I enter the data for “riding an electric bike”? Little Yellow Cars may belong to different companies; there are Mobike, ofo, and there might also be “Tiger Brother Car Rental” and so on. Each company has its own backend database; if I happen to be riding a bike from one particular company, I have to download a bunch of apps, otherwise it’s not possible to complete the contract automatically. And then, which program should be used to process it? Mobike may charge 1 yuan, ofo charges 1.5 yuan, and TuGe Car Rental charges 2 yuan. Each service uses its own app, so the data cannot be shared, which makes it impossible to handle things uniformly; large-scale optimization is nothing but a fantasy. Thanks to the decentralized consensus algorithm of blockchain technology, Brother Rabbit no longer has to worry about determining which backend database or program should be used to store data; instead, the data itself contains the necessary program, and the data is itself an asset. I just need to turn the Little Yellow Bike into a data entity with its own programming, so that it can keep track of expenses on its own while in use. The company to which the bike belongs is the one to whom this digital asset belongs; there’s no need to take the asset physicalmente away – payments can be made directly from the Little Yellow Bike whenever such funds are needed! Don’t underestimate this small progress, because it will enable the operation of society and the economy to become automated, just like in a factory! Take the UK, for example: it was the first country to elevate blockchain to a **strategic level. The RScoin initiative promoted by the Bank of England already represents an early form of economic automation. It establishes a completely new system separate from the traditional banking and monetary system. Under the RScoin system, individuals and organizations can open their accounts directly with the central bank rather than with commercial banks. This means that in case of a liquidity shortage, the central bank does not need to release liquidity through traditional methods such as purchasing bonds, lowering interest rates for commercial banks, or increasing the money multiplier; instead, it can simply inject funds into the economy that is facing a liquidity crisis! Like a skilled surgeon, address the problems directly to prevent economic crises from arising. Of course, the actual operation of an economy is far more complex than this; for example, how can a digital economy system map digital assets while also mapping digital liabilities? ； How can humans, machines, and completely different organizations reach a consensus ； How can a foundational industrial blockchain support the operation of complex socio-economic systems… These are major challenges faced by blockchain technology, and they are also areas that I, along with the Industrial Blockchain Laboratory, need to focus on exploring in the future. Industrial Blockchain Laboratory, Infrastructure for Economic Automation Platforms. In our old worldview, data was data, assets were assets, and programs were programs; we simply could not comprehend what this change meant for the entire world when data could carry programs within itself, thereby merging data and assets into one. It means that over the next decade, the digital economy centered on blockchain will permeate every corner of society like water, changing our lives – this is true digitization, true \"Industry 4.0\". All physical assets will be digitized and made fluid; future e-commerce platforms will allow not only the buying and selling of physical goods but also of their \"digital twins.\" The principles of economics and management that have governed human society for thousands of years will all be overturned, and we will enter a completely new era. If asked what trend could make Brother Rabbit willing to give up all his past reputation, status, and wealth in order to pursue it with all his might, it would definitely be this wave of digitalization. Brother Rabbit often says that there are two types of people in this world whom you should stay away from: one is the “master,” and the other is the “foolish old man.” The gurus promote their schemes with great enthusiasm, telling you every day that the future has arrived and that you should dive in at all costs, to buy immediately – once this opportunity passes, it won’t be available again. As a result, once you buy it, he makes a huge profit; you are his “future”. The wise old men are exactly the opposite: they tell you every day that Zhang San is a swindler and Li Si is deceitful, urging you to use common sense and see through such people so as not to have your money stolen... Yet although they can assure you that you won’t make mistakes, they don’t tell you what to do to do things right, because though these wise old men see through every scam, they are themselves quite poor. So, in fact, whether something is reliable or not depends on who it is for; the same thing may be reliable for some people, but a scam for others. In the field of blockchain, for example, I began investing in digital currencies in 2012; I am well aware that it is a place full of deception and temptations, a chaotic gray area. Take the “Gray Angel” ICO for digital currencies, for example: it raises tens of millions by relying on a white paper. You might say it’s unreliable and a scam, but you can’t deny that many people who participated in it managed to earn dozens or even hundreds of times more easily. For those people, it represents an opportunity for wealth creation, and it seems legitimate. Whether blockchain is reliable or not is a question; the debates among experts and skeptics about whether it represents an \"ultimate opportunity\" or an \"ultimate scam\" are meaningless. Because it lacks the dimension of which “person” it is. “\"Opportunity\" is nothing but a \"scam\" for unreliable people” ； And a \"scam\" is an opportunity for those who are reliable. So, whether blockchain is an opportunity or a scam for you, there is only one key factor: whether you are reliable or not.