This article is from the WeChat public account: Notesman WeChat ID: Notesman Content source: On December 17, Professor Zeng Ming and his team held a public class at Hangzhou Normal University titled "Looking Ten Years Ahead: Zeng Ming Academy Public Class" Today's note taker: Ke Zhou from Notesman; Editor: Su Wenbing The note invites you to think first:
- What are the reasons behind the decade's dramatic changes?
- When enterprises are lost, how can they open up new patterns?
- How is intelligent business composed?
I. Look Ten Years Ahead, Work One Year Over the past 20 years, I have witnessed too many changes and ups and downs. My deepest feeling is the understanding of "momentum." First, reverence. Times create heroes. No matter how capable an individual hero is, they must respect business laws and grasp the overall trend. Three to five years can determine the fate of an enterprise. Second, dare to seize the momentum, even create it. If you cannot use momentum, you cannot become a leader of the era. Understanding and using "momentum" are two sides of the same coin. From 1997 to 2007, among the world's top ten companies by market value, only ExxonMobil and Microsoft remained on the list. This was a major era change. The bigger change came from 2007 to 2017. Except for Microsoft and Exxon, the other eight companies were new to the list for the first time, especially six internet companies. These internet companies basically had market values above $500 billion, with Apple and Google running faster. What caused such huge changes in this decade? Let's look at a specific example: two projects in the same industry that were "rivals in talent." In the early 1990s, although Jobs and Apple pioneered personal computers, Dell later caught up. Around 1998, Dell said that in this industry, they couldn't see the necessity of Apple's existence. At that time, Jobs had made many mistakes and had been kicked out of Apple. Apple's market share was only about 2% at its lowest. When Jobs returned to Apple, he didn't launch computers but successively launched the iPod and iPhone, which everyone didn't understand, bringing remarkable changes to Apple. Interestingly, in 2006, as Dell's market value was falling and Apple's was rising, one day their stock prices crossed. At $80 billion, Jobs sent a short email to all employees: "Today we surpassed Dell. Let's continue to work hard." After that divergence, Dell eventually went private, now estimated at $10 billion, while Apple exceeded $800 billion. When I started as a professor, Dell's case was the most used. Its innovation disrupted the PC industry. Watching a hero of the era gradually fade from the stage was quite impactful. Besides the core reason of individual innovation, it was also because they didn't grasp the most important core changes of the future and didn't use the momentum. When an era is undergoing drastic change and transformation, it's hard to see the future clearly. The more so, the more you need a relatively long-term perspective. You need the determination to "look ten years ahead" and gradually cultivate the ability to do so. This "looking ten years ahead" is Vision. How far and clearly you can see. Vision determines your vision, pattern, breadth of mind, and ultimate potential. This is the core capability of entrepreneurs in times of change. Let me share with you the Alibaba strategic meeting held in Ningbo from September 28 to 30, 2007. This should be the most important strategic meeting in Alibaba's history. First, the group's situation was not good at the time. Although today's Alibaba is developing rapidly, back in September 2007, the company's market value was at most around $10 billion. After Taobao's rapid expansion, where should it go next? At that time, the Taobao president brought in six vice presidents at once, and each had fierce debates about how the company should develop in the future. Taobao and Alipay were fighting fiercely. Should Alipay serve as one of Taobao's functions, serving Taobao's needs, or develop independently? After I joined Alibaba, for the first half year, I spent most of my time coordinating the fight between Taobao and Alipay. Moreover, after about two years of efforts, the acquired Yahoo China still showed no improvement, and Alibaba Software hadn't found its direction. The group's development was still quite confused. The meeting's agenda was to discuss where Alibaba should go in the next ten years and what strategy it should have. After discussion, a sentence suddenly emerged: Build an open, collaborative, and prosperous e-commerce ecosystem. That was September 2007. Now these words are common, but at the time, it was a huge insight. I remember my opening remarks at the strategic meeting were about the arrival of the post-industrial era. How would we differ from the basic economic laws of the industrial era? I started from abstract, future-oriented angles like mass customization, social logistics, and personalized marketing. At that time, I managed China Yahoo and was forced to stand on the internet's most cutting-edge battlefield—search. So I gained a direct understanding of the most core technological concepts and product concepts like cloud computing, search bidding, and communities. As someone who didn't understand technology at all, I had to analyze with the business presidents and explain what API (Application Programming Interface) was. But in this process, I discovered that the ecosystem was the real key to Alibaba's future. Until this year, Ma Yun and the partners held three more meetings and finally proposed a new future goal: Alibaba should actively promote the creation of an internet economy. This concept is also an upgrade of the e-commerce ecosystem, with a consistent line of thought. Let me share a chart. If we achieve this Vision, we could become a $100 billion company. The term "$100 billion" was first perceived by us. What is the core of building an ecosystem? It is customers, data, information flow, capital flow, and logistics. Connecting data across all subsidiaries' businesses is the entire group's future "Moon Project." It was because of the "Moon Project" that the meeting clearly stated Alibaba must find a CTO within a year to lead the company in completing the Moon Project and move toward the future through data. That's why Dr. Wang Jian later joined Alibaba and created the legend of cloud computing. The source was the understanding of data's strategic significance at this strategic meeting. Second, the core is open APIs. Opening data to the outside means that outsiders can use our infrastructure to create another Taobao, supermarket, department store, or shop to compete with Taobao. At that time, I realized that if we could truly connect data and open APIs to the outside, Alibaba should be able to create an unprecedented economic miracle—that is, an ecosystem. The ecosystem should have the possibility of $100 billion. I first realized that future competition would be about trillion-dollar competition in 2013, when Alibaba just decided to launch its IPO. At that time, I looked at many benchmark companies, including GE and Walmart. The first goal was to surpass Walmart in retail, the second was GE, the representative of the industrial era, and the final, hardest goal was to beat Amazon. Excluding Ant Financial, we first surpassed Amazon about a month and a half ago, with a valuation exceeding Amazon for about a week. When I looked at this chart in 2013, I sent a text to Ma: "I think after our IPO, it's just a new beginning. Our real competition is which of these companies will first reach one trillion." I give this example to illustrate that when you feel the future is unclear and your business is lost, spending time to ponder and judge the future can actually bring a new pattern to the company. Without that meeting, Alibaba definitely wouldn't be where it is today. Today's strategy is completely different from traditional strategy. The core of today's strategy is built on Vision. Vision is to look ten years ahead, to constantly think about assumptions and beliefs about the future, to judge the most likely industry endgame, to be constantly tested by practice, and then corrected. Since it's an imagination of the future, there's always uncertainty. When you finally make a decision, it must be a leap based on belief. Ma Yun has a great saying: "Because we believe, we see." Because you believe and work in that direction, it gradually becomes reality. Vision is ultimately to be proven, not to be challenged. It's because I believe that I can finally make it happen. Vision is a combination of rationality and sensibility. On the rational side, you must constantly challenge yourself and correct your judgments; on the emotional side, you must trust yourself and your beliefs. This is a very important dialectic. How to adjust Vision? The core of the entire action is to find the right point within a one-year or even half-year time frame. Let Action find its focus. In today's era of great change, strategy is short-circuited. The original formal strategic process has been replaced by rapid iteration between Vision and Action. It requires you to have the ability to think long-term and react quickly, and the organic combination of both determines how far you can go.
II. The Nuclear Fusion of Intelligent Business What is the future I see? The big trend we see today is not a 10-year trend; it's likely a 20-year, 30-year, or even 50-year trend. Everything we see today is the beginning of a new era. It's a new beginning from agricultural civilization to industrial civilization to the intelligent era. It's a major change in civilization. Today's intelligent business is just starting the process of nuclear fusion. We have too many opportunities and challenges. Comparing the 2007 and 2017 tables, what did the seven internet giants on the right do right? First, the three axes of intelligent business In the three important directions of "online, networked, and intelligent," they did at least two things right, and even made major breakthroughs in all three directions: 1. Online Our era is the internet era. The most important first point is whether you are connected to the internet and online. If so, the advantages of the internet can be used for you; otherwise, the world is getting farther and farther away from you. This is the most important first step: mapping the physical world to a virtual world on the internet. Why has Microsoft been on the list for 20 years? In 1996, when Bill Gates faced challenges, he made a firm decision to fully promote the IE browser, won that war, occupied the most important infrastructure of the PC internet era—the browser—and then derived Microsoft's search services, etc. If Alibaba had acquired hao123 (PC internet navigation), we would have had a stable traffic source, and our search would have had a base for sustainable development. Without that acquisition, there would have been no traffic source, and the subsequent search battle couldn't have been fought. Microsoft's ability to occupy a place in search was because it occupied the most important infrastructure of the PC era—the browser. Apple became the world's most valuable company because it pioneered the mobile internet era. The iPhone set the hardware standard, and the App Store determined the form of application and service acquisition in the mobile internet era. On this basis, Apple integrated a series of intelligent services. Apple is a company that integrates hardware, software, services, and ecosystem in the mobile internet era. This is the most important foundation of its success in the past decade, helping society complete mobile internetization. 2. Intelligence Where is Google's success? The most important thing is that it promoted the entire process of business intelligence. Search is the first large-scale commercial application of intelligent services. Anyone entering a keyword in the search box can have the world's knowledge serve them, quickly obtaining the information they want in seconds. Only intelligent business can achieve such a breakthrough. The second core intelligent service product is recommendation. Amazon was the earliest to move in recommendation, which is an important foundation for its huge breakthrough in retail efficiency on the marketing side. Another important breakthrough was putting the entire logistics process online, bringing a huge improvement in logistics efficiency. 3. Networked Tencent and Facebook are the farthest in social networking. Alibaba, especially Taobao, has formed an ecosystem where network collaboration and intelligence are tightly combined and mutually reinforcing. The real source of Google's advertising system's profitability is the efficient ecosystem between millions of small advertisers and millions of websites. Facebook's success in recent years is also a breakthrough in advertising technology. The most successful internet companies have made major breakthroughs in networking and intelligence on the basis of being online. This is a very simple and effective analytical and thinking tool. Look at the second batch of Chinese internet companies that have emerged recently: Didi completed the onlineization of taxi services, with the premise of widely popular smartphones and map services, making online location positioning very clear, turning taxi services into online services, and then optimizing through algorithms, achieving Didi's success. Toutiao moved from traditional search to China's best recommendation service, breaking through on intelligence, achieving explosive growth in the past few years. Meituan, on the one hand, onlineizes traditional life services, and on the other hand, builds a life service network. The second batch of most successful companies have made major breakthroughs on the three axes of "online, intelligent, and networked," only then can they establish a leading position in a field. Second, the characteristics of intelligent business Intelligent business has several very typical characteristics that traditional enterprises cannot achieve. The direction for traditional enterprises to transform and upgrade is the direction of intelligent business: 1. Use the advantages of the internet and algorithms to serve massive users in real time at low cost. These internet companies have users in the billions. Serving massive users, Taobao has hundreds of millions of users every day. Only with such scale can there be such profitability. 2. Meet the personalized needs of every user. Search is precise to each keyword. In the past decade, search has worked on personalization, giving different content based on personal search history, personality traits, and background information, making search results more personalized. Now Taobao has "thousands of people, thousands of faces," where each person sees a different page, also leveraging the rapid progress of artificial intelligence technology in the past few years. This personalized precision is reflected in accuracy (increasingly precise, finer granularity) and precision (increasingly accurate, serving more precise services in smaller time periods). 3. The speed of self-renewal and self-iteration is very fast It can learn quickly like a human, and even in many fields, it improves faster than humans. Once these companies get on track, the efficiency, level, and satisfaction of the entire service are rapidly improving. Essentially, without technology, no matter how much you talk about operations, today's Alibaba wouldn't exist. These cutting-edge companies are companies that use the most advanced technology to comprehensively change business efficiency. The core is to use the internet and algorithms to reconstruct business logic and operational laws. The future of business is intelligent business. This is a true dimensional attack. Traditional business is vulnerable in front of intelligent business. This is the most important trend. Third, the double helix of intelligent business: network collaboration and data intelligence This is the most important concept. How is intelligent business composed? Network collaboration and data intelligence are the two most important sub-components of intelligent business. The two are yin and yang. All networks are becoming more intelligent, and all intelligence is network intelligence, not individual intelligence. The social value created by human society today is largely not due to the development of individual brains. Individual brain evolution is very limited, but the ability of social collaboration has been rapidly expanding at an extremely fast pace. Today's human civilization is not about individuals being smarter than before, but about the increasing ability of overall social collaboration. This is the greatest advantage of this era. Network collaboration will drive the development of data intelligence, and data intelligence will drive the expansion of network collaboration. You can use these two to check whether your company's business is moving toward intelligent business. I will focus on these two core concepts: 1. Network collaboration: large-scale, multi-role real-time interaction to solve a big problem. For an enterprise to become an intelligent enterprise and intelligent business, the first important standard is whether your enterprise has achieved network collaboration. Have you completed all collaborative work of an important matter in real time on the internet? I'll give two specific cases to help you understand the laws of network collaboration operations. The first is Wikipedia. We are so familiar with it, but we may overlook how remarkable an achievement Wikipedia is. It is a pioneering knowledge co-creation platform. In principle, everyone in the world can contribute thoughts and content, has the right to modify any entry, and can also maliciously attack any entry. But based on simple online editing tools (one important feature is one-click restoration of modified content; if someone changes it and you think yours is more correct, you can change it back) and a very simple set of collaboration rules, without central authority coordination or traditional command mechanisms, people around the world cooperate to edit an online free knowledge base. Traditional encyclopedias are determined by experts. Wikipedia is a non-profit organization, and its expenses are covered through community donations. For the first time in human history, a large-scale, spontaneous collaboration without central government coordination completed the editing of an online knowledge base. A very remarkable task. The second is Taobao. Taobao is not retail; it doesn't own any products. It is a retail ecosystem and a platform that empowers sellers. The reason Taobao can create such a miracle is that it eventually evolved into a large platform for social collaboration. This has accidental factors and is also related to Vision. In 2006, we realized that in seller stores (which were originally free, simple text links), store decoration and image quality had a big impact on sales. We launched Wangpu (a store decoration service). But later we found it couldn't meet the ever-changing personalized needs of sellers, so we made a historic decision: provide only the most basic Wangpu functions for free to all sellers, and open the personalized Wangpu template design to society. So Taobao saw the first batch of independent software engineers helping sellers design stores, which later developed into profitable software companies, and then derived various software service providers, such as inventory management, customer service management, and online customer management. Today's Taobao sellers can collaborate with hundreds of service providers online at the same time. You only need an API link to mobilize relevant data and services, connect to Weibo social channels, Ant Financial's financial services backend, third-party marketing tools, etc. Taobao itself is a complex collaborative network. This collaborative network brings huge social value creation. The original linear communication industry is reconstructed on the internet platform, becoming a real-time interactive, networked communication pattern. This is the most important first step for any enterprise to move toward intelligent business. If your information flow is still one-way and linear, you are still operating in a traditional network; if the information flow becomes concurrent, simultaneous, and diverse, and becomes real-time interaction, you have taken an important step toward online collaboration. 2. Data intelligence The essence of data intelligence is that machines replace humans in making decisions directly. This is completely different from traditional BI (Business Intelligence). BI analyzes data and provides decision support, with the core service group being executives. Data intelligence means that operational decisions are directly made by machines. For example, Taobao has nearly 10 billion products and tens of millions of merchants. What products to show users cannot be decided by humans; it must be machines. This is something humans cannot do. There are several very important prerequisites for letting machines replace human decision-making: cloud computing, big data, and algorithms. Without cloud computing, there is no way to store and compute massive data at such low cost. So cloud computing and big data complement each other. Because of cloud computing, we can process big data. Because of the need to process big data, the requirements for cloud computing are getting higher and higher. Ultimately, these two drive the continuous high-speed development of the entire data industry. The reason both can truly develop is because there is a brain behind them. This brain is the algorithm. The algorithm is a machine, but not a machine; in a sense, it is an algorithm engineer. Imagine how a person thinks when making a specific decision. Machine algorithms abstract human decision-making into a model, then use mathematical methods to find an approximate solution to the model, and then use code to turn that solution into commands that the machine can execute, ultimately completing the construction of a machine brain. The so-called algorithm is a person's understanding of a specific thing, converted into a model and code that the machine can understand and execute. The difference between this model, code, and the human brain is that the core relies on massive data for continuous learning to optimize its decisions. Big data and algorithms are also a combination of yin and yang. Without the scenario of big data, algorithms become a meal without rice or water without a source. But if you have data and don't use an algorithm engine for real-time computation to produce decision results, then all data is wasted. The combination of big data and algorithms is the essence of machine learning. The combination of the two produces the so-called rapid iteration and rapid optimization. Last year, AlphaGo defeated the world's top Go champion because its computing power was particularly strong, its learning efficiency was very high, and it could learn all the game records in human history. A few months ago, AlphaGo Zero made an even bigger breakthrough. It could do without human historical data, not look at historical game records, rely on left-right hand self-play, rule formulation and evolution, to achieve a stronger algorithm, defeating AlphaGo. We can see that there is still a lot of room for algorithm breakthroughs in the future. Cloud computing and big data are interdependent combinations. Understanding algorithms and big data is like the relationship between a production line and steel. Without algorithms, there is no way to process data, and there is no way to optimize results. The business of data intelligence has three core components: algorithms, data, and products, all indispensable. Algorithms are the brain, the engine of machine learning; A very important point about data is that it must circulate and form a feedback loop. I often call it "live data" because live data determines whether a business intelligence can continuously optimize. Big data only describes its volume; the essence is live data; The hardest to understand is the feedback loop completed by the product interface that interacts with users online, thereby iterating product value. How does Google Search interact with massive users in real time? Two extremely simple product interfaces: the search box and the results page. Enter a keyword in the search box, and the results page appears. You see a list, sorted by relevance, and then you just click. Three steps: enter keyword, get results page, click, complete a search. The most important thing is that these two product interfaces complete real-time customer feedback. For example, whether you clicked the first item. A good search engine should give you the most desired result in the first row, sorted by relevance. The further down you click, the worse the original relevance algorithm was, indicating worse results. Every click you make helps Google train its machine algorithm and machine intelligence. If Google used traditional methods to ask users if they are satisfied and where they are dissatisfied, efficiency would be reduced. So the feedback loop of machine learning must be a natural organic part of the business, letting the data left by your behavior help machine learning. This is the natural intelligent business cycle. Therefore, there is an important inference: in the future, any enterprise is a service enterprise, because what customers really want is service, not products. Any future enterprise will have an internet product interface to interact with users in real time, only then can it bring users online, complete the first step of onlineization, and have the opportunity to interact with them online in real time. The first important direction: Any enterprise will inevitably have an interface to interact with target customers online in the future. The second important direction: Any hardware manufacturer will no longer exist as an independent enterprise in the future but will become the carrier of a service closed loop, or establish its own toC communication channel. Only by finding a way to interact directly with users can you record their feedback in real time, find optimization algorithms, and optimize your service. Whoever completes this closed loop first has the greatest advantage. How can traditional industries complete onlineization through a beautiful product design and then start the path of intelligent development? For the vast majority of enterprises, the hardest part of entrepreneurship in the next decade is creatively discovering a product and service method that brings originally offline users online and generates continuous interaction. The composition of an intelligent business and data intelligence requires product, data, and algorithms, all indispensable. The hardest part is completing such a feedback loop with the user's online interface, so that the entire machine learning can exert its value. Fourth, the "Black Hole Effect" Having explained the double helix operation of network collaboration and data intelligence, we can see why internet companies show such strong vitality and have such great energy. Why can large companies continue to maintain high growth for many years? What is the reason behind it? Black holes have huge energy fields, so I propose a new concept: the "Black Hole Effect." Why is there a "Black Hole Effect"? How is this energy field composed? 1. Network collaboration naturally has network effects, and with network effects, there is exponential expansion. 2. Learning effect. Data intelligence naturally has a multiplier advantage: the learning effect. Machine algorithms continuously improve their intelligence level through data processing. This runs 24 hours a day, 7 days a week without stopping. This learning effect is multiplicative; the more you learn, the smarter and better you become. 3. Data pressure and network tension. Networks naturally generate data pressure, driving the development of data intelligence. In the process of network expansion, data is naturally recorded, so data becomes more and more. When the network becomes more complex, humans cannot manage it at all, so it naturally drives the development of data intelligence. In 2008, Taobao felt that traditional category classification methods could not handle the many merchants and products on the platform, and consumer choice efficiency was declining sharply. So it replaced traditional browsing with search engines to hold the explosive development of Taobao's complex network. For search engines, handling 100 million products or 10 billion products, its scalability can fully carry it. So complex networks drive data intelligence, and data intelligence naturally has network tension. If oil, natural resources, and steel were the most important means of production in the last century, data is the most important means of production in this era. But there is a fundamental difference between data and matter. Any matter is like this glass of water: if I drink it, you can't drink it. But information can be shared, copied, and disseminated. The cost of copying and dissemination is almost zero, and it naturally wants to spread across the network. Physical things, no matter how they are disseminated, are constrained by speed and cost. Data also has a big feature: the use of data and information is a process of value creation. The use of matter is a process of depletion; the more you use it, the less it becomes. The use of data is a process of value addition. Who saw it, how many people saw it, itself contains huge information content. If that person clicks like, writes a comment, and forwards it, the value of the entire information increases geometrically. The design of any interactive product is very valuable because it turns information consumption into information reproduction and re-creation of information value. On the network, more interaction can create greater value. 4. Heterogeneous connection of information. The same information has different value to different people. Traditional material pricing can be based on cost. The cost of editing and copying information is zero. What method is used for pricing? For specific information, it is hoped to travel far on the network. From the perspective of market effectiveness, information has a great willingness to reach different groups of people to obtain additional information premium. These are the three characteristics of data. Data itself is like a black hole, always wanting to become bigger and reach more people. It has a natural network tension. Leading internet companies in intelligent business have overlapping advantages, plus network effects, learning effects, data pressure, and network tension. The efficiency improvement from the multiplication of each advantage is enormous. So once intelligent business rises, it completely crushes traditional business. Traditional business has no power to fight back. The value they create is on a completely different scale. This is a very practical enterprise upgrade guide: First, network as much as possible; Second, introduce machine learning as much as possible to complete network effects; Third, in the process of network expansion, use machine decision-making to replace human decision-making as much as possible; Finally, can I make my data exchange with more different types of data? Each direction is a process of huge energy increase and can create huge value. The "Black Hole Effect" only began to emerge in our era. The world's three core elements: matter, energy, and information. In the information dimension, there are two core axes: one is communication and telecommunications, and the other is processing and computing. Agricultural civilization: On the one hand, beacon towers transmitted signals through fire, and post stations reached more people; on the other hand, knotting ropes to record events, Arabic numerals, geometric laws, and algebra; Industrial civilization: There were telegraphs, telephones, and machines (100 years ago, IBM was the earliest to make calculators, NCR was the earliest to make payment machines. Any simple machine that could contain a certain computing power was the most cutting-edge technology at the time). These were the great developments of the industrial revolution. Intelligent era: The nuclear fusion of intelligent business can be traced back to 1989 when the first personal computer went on the public internet. Communication and computing merged into one. The personal computer was both a computer and a communication node (a point of network collaboration). Network collaboration and data intelligence began to become a double helix, starting a strong coupled development, thus laying the foundation for the intelligent era. The composition of this world is big cities, lights, and highways. This is the foundation of civilization. Through billions of years of evolution, we have completed the physical connection of the world. Carbon-based energy plus steel and lighting constitute this world. The future intelligent world will complete the connection of creativity, knowledge, and wisdom on the basis of physical connection. The next intelligent era will first be the connection of human brains. Scenes from science fiction movies seem to be getting closer and closer to our society. Fifth, this is the era of "i" We live in the cloud, in our friend circles. Everything seems to be in surplus, but everyone is anxious. On the one hand, everyone wants to show their individuality. On the other hand, we are extremely loyal to the very small communities we identify with online. This is the beginning of a brand-new era. The precise goal of intelligent business is not to satisfy faceless individuals in the industrial era, but to satisfy completely different people in the development of completely different societies. This is the world of "i." Through these 20 years of looking at China's manufacturing, internet, and future technology development, I can feel a brand-new future. This is a future that is exciting and sometimes frightening.
III. Where Are the Opportunities in the Next Ten Years? After the past 20 years of development, we have already nurtured the first batch of companies that may be worth a trillion dollars. In the next ten years, perhaps in the process of the big bang, the pattern of intelligent business will be preliminarily determined. By 2027, who will be on the list of the world's top ten most valuable companies? Do you have a bit of ambition and fantasy, fantasizing that you will also be here? In 2007, Alibaba was only worth $10 billion. At the end of the year, when B2B went public, the entire group jumped to $20 billion. At the time of the IPO, all employees were given a choice: you could convert 30% of your group shares into B2B listed company shares, or stay and wait for the group's future appreciation, mainly the future appreciation of Taobao and Alipay. At that time, almost everyone believed in the rapid growth of the listed company rather than the future of Taobao. This was 2007. Looking back, we are grateful that the company only allowed us to convert 30%. By 2012, before Alibaba's IPO, the last financing was at a valuation of less than $40 billion. The same story, we were allowed to sell 30%, and we basically sold it all. In 10 years, many things can happen. In 2007, Facebook had just been founded for about four years, with a valuation of $15 billion. Tencent was only $12 billion. Now it's $472 billion, about 50 times growth in ten years. Perhaps in the next ten years, there can be 100 times growth. Are you willing to join the new explosion era and start to unfold your dreams and creativity in the era of intelligent business? Even if you think these companies are so powerful, they have only made breakthroughs in online advertising, online retail, and online social networking. There are still many fields that are open arenas that can be changed with the ideas of intelligent business. In the next ten years, these are still the three main lines. You must have sufficient development and breakthroughs in at least one of these directions to have an advantage in the future: 1. Online: That is IoT (Internet of Things). From PC internet to mobile internet, the next step is definitely IoT, ultimately achieving the Internet of Everything, real-time online interaction. The physical world will have a mapping in the virtual world. Due to the rapid development of chips and sensors and the sharp decline in costs, IoT will be extremely penetrating for social development and will greatly expand the boundaries of intelligent business. Of course, milestone products of IoT have not yet appeared, so this era has not truly arrived. 2. Intelligence: AI technology will greatly enhance black hole energy. In the past decade, AI innovative technology has already produced great value, and the progress of AI technology will continue to develop at high speed. 3. Networked: Collaborative networks will expand sharply, and the networking process of the economy will accelerate. We can see two more important trends: the existing intelligent ecosystem will continue to explode, and diverse species will flourish. People think that the ecosystems of Alibaba and Tencent are too powerful and may inhibit certain innovations. In fact, they have incubated many valuable enterprises, allowing various species to be greatly improved. Opportunities worth $10 billion or 10 billion RMB will be very numerous. Just like the Taobao brands ten years ago, that wave of companies has started to go public. Also, many open companies on Tencent's platform will become listed companies in the next year or two. Furthermore, there are two paths for the emergence of new black holes (similar to Alibaba's ecosystem): Traditional industries upgrade to intelligent business, including education, health, transportation, and other large industries worth trillions. In the process of transforming to intelligent business, platform-level and ecosystem-level leading enterprises will emerge. Disruptive technologies form new black holes, including blockchain, AI, AR, blockchain, and Bitcoin. Due to the reconstruction of production relations, they will bring huge changes to the entire society. The speed of technological progress has not slowed down. This is one reason we emphasize the evolution of intelligent business so much. The source of technological progress is still developing. Let me expand on my specific judgments on these three axes: First axis: Milestone products of IoT The essence of IoT is the transformation of human-computer interaction interfaces. PC internet was locked by the keyboard, mobile internet was locked by the phone, and in the IoT era, it is locked by the five senses. Human senses are greatly expanded, and all senses can be extended by computing. Speech recognition is already basically mature technology. This year's Chinese smart speaker war is because voice is a very important interaction foundation. Including many interactions in cars, when your hands are occupied, voice will become a very important interaction because it has reached a certain stability and accuracy. Vision is also a big breakthrough. Face recognition is an extension of visual perception. Application-level AR devices rely on vision, and ultimately will make you unable to distinguish between reality and virtual reality, making your eyes unable to judge where the source comes from: virtual or real? It interacts with your brain nerves, and it is likely that through changes like eye focus, it can mobilize computing power. It is a new way of human-computer interaction. When the five senses and the brain can be directly connected to the computing network in some way, the improvement in efficiency is unimaginable. This is the essence of IoT. Similarly, interactions between physical products are becoming more intelligent because they have signals, communication modules, computing modules, processing modules, and perception modules. Objects can connect, talk, and judge with each other. In the early days, when we looked at IoT, we kept looking at smart speakers and smart homes. Later, I found that the milestone and comprehensive product of IoT should be the smart car industry, which will bring great IoT. In the field of autonomous driving, in the next two or three years, the technology should be quite mature. Since this is a huge industry, when the industry is broken through, the costs of chips, sensors, and AI algorithms will drop geometrically. Previously, we thought that for industries to be IoT-ized, the return on investment couldn't be calculated. For a small application scenario, no matter how much money you invest, the customer value may not be enough. But in the field of autonomous driving, because the customer value is large enough, it can bear very large fixed capital investment and early R&D investment. Once the R&D breakthrough is achieved, the world will be changed because the cost of chips and sensors will become almost negligible, and many scenarios that couldn't apply IoT will become intelligent. In your industry, the customer pain points you see, is it possible to use IoT technology to turn a traditional, physical, isolated, fragmented situation into an online, continuous, interactive scenario? Second axis: Network collaboration expansion and reconstruction Google only onlineized advertising, and Taobao only onlineized retail. After that, we naturally want to digitize and network the entire logistics process. In the past two years, the development of internet celebrities has shown that creativity and marketing have also begun to be internetized. When front-end applications are all internetized, it will naturally lead to the reconstruction of the entire chain from manufacturing to procurement. If you want to reconstruct the clothing industry and further achieve personalized services, the constraint is not in the front but in the entire supply chain system. Including fabric procurement, fabric quality verification, and quality testing, which are still all done by human eyes. These links are still completely offline. They will gradually be onlineized and integrated into the collaborative network to better meet customer needs. Almost every industry will experience a process from a traditional, closed, linear supply chain to an open, value collaborative network. There are huge business opportunities in this process. Third axis: Intelligence First, most companies worry about how difficult algorithms are and can't recruit algorithm engineers. Algorithms will become infrastructure like cloud computing. Google, Facebook, Alibaba, and Tencent have all opened basic algorithm libraries. In the future, when every enterprise does applications, it doesn't need to develop algorithms itself. You don't need an algorithm engineer; you only need an AI trainer to adjust parameters in your specific scenario to make the results more optimized. Algorithms themselves will not be a barrier for most application enterprises; instead, they will be a very good application tool. Second, deep learning and reinforcement learning will be increasingly applied in every industry. The so-called Industry 4.0 is automation based on rules, not machine learning. Letting machines make decisions anytime and anywhere is the real development of intelligence. Basically, the algorithms used by all companies are designed by computer scientists and are in black boxes. When we enter increasingly complex fields, like Taobao's scenario, as long as people are involved, there will be gaming. Gaming is not a simple black box simulation. At this time, how to introduce good economic research and sociological research, bring the concept of mechanism design into platform management, and even become part of the algorithm, organically integrating them, becomes a very important and innovative field. For social sciences, this is also a huge opportunity for innovation. Because social sciences can finally do experiments. Just as physics is considered a science because it can do experiments, now there are many online environments for large-scale economic and sociological experiments, thereby promoting these disciplines to become more scientific and bringing about the improvement of the entire social value. To succeed in such a new intelligent business era, some basic ideas of strategy need to be rewritten. I strictly prohibit anyone in Alibaba from reporting industry analysis because it cannot reflect the key to strategy formulation in the new era. So besides traditional "positioning," an important new concept in new strategy is: point, line, surface, and body. In future competition, the first core of an enterprise's strategic decision is: what kind of network competition do you want to be in? Are you a surface, a network platform, leading the development of an ecosystem, or a point or line in a specific network? For example, a seller can choose to serve on Taobao, choose JD.com, or choose WeChat. This choice itself largely determines your future evolution trajectory. Because the speed and scope of resource flow on the internet are greater than before, winning future competition does not depend on what resources you own. Even if you have many, they are limited. The key is what resources you can mobilize. The barrier to competition has shifted from what you own to what you can mobilize. It lies in the value of your relative position in the network, not in the amount of resources you own within the enterprise. The importance of external connections is far greater than internal management. This is an important way of thinking in new strategy. From ten years, pull back to focus on the direction that is visible and tangible in the next three years: the breakthrough of industrial internet. Why are we optimistic about the internet industry? So far, most platforms have only completed very shallow connections, while many industries have very complex interactions and interest distribution. In complex industries, how to move offline to online, complete network collaboration, and embed data intelligence is a huge challenge. Why has industrial internet been completed slowly in the past few years? People originally thought that "Internet +" could be solved by adding the internet and traditional industries together. In fact, this is not the case. What we really need is "Internet ×," the collision, reconstruction, and innovation of internet technology, internet tools, and internet thinking with the basic laws of a certain industry. Ant Financial had an important strategic discussion about the nitpicking of a word: Is Ant Financial tech-fin (technology finance) or fin-tech (financial technology)? Overseas internet finance companies are all called fin-tech. In the past two years, Ant Financial has become more and more like fin-tech, serving financial companies. But Ant's original intention was tech-fin, which is innovative financial services based on innovative internet technology. Tech is the foundation, and fin is innovation. Finally, Ma Yun went to Ant Financial again and said to return to the original intention, clarifying whether we are a technology company or a financial company, so that we can have a benchmark fundamentally. Ant Financial is a company that uses technology to innovate financial services, not a company that uses technology to improve financial efficiency. These two are very different. This requires everyone's understanding of the internet, deep thinking in specific scenarios, and ultimate breakthrough. In the past 20 years, we have seen the prototype of intelligent business. In the next 30 years, we will see the big bang of intelligent business. And in the next 10 years, we will see the preliminary determination of the pattern of intelligent business. At the same time, in this process, the strategy we understand is being redefined. The rapid iteration of vision and action becomes the new strategic thinking of this era. "Point, line, surface, and body" becomes the most important thought in new positioning.
This is the fifth most important class in my history Why the fifth? Alibaba, Cheung Kong Graduate School of Business, Hupan University, and Alibaba Business School all have great dreams and lofty goals. I want to have a small garden of my own for happy communication. This was the original intention of initiating Zeng Ming Academy more than a year ago, to discuss the future of business with like-minded and interesting people. The most basic duty of a professor is to teach a good class. This time, using the form of a public class, I want to repay the friends who have supported us over the past year or more, and I also hope for more interaction in the future. In 1998, I joined Insead (Note: INSEAD, one of the world's leading and largest graduate business schools, European Institute of Business Administration). My first class was teaching marketing MBA. I was unlucky. At that time, the Asian financial crisis occurred, and all theories about Asian success were overturned. The miracle of the "Four Asian Tigers" (Note: Japan, South Korea, Singapore, Taiwan) was theoretically overturned. How to teach? I was forced to face reality. I couldn't talk about Asia's past success anymore. The stock market was crashing every day. I could only temporarily review the past and then think about theories that fit the future, whether they could be self-consistent. So the first class was very difficult, but I barely managed to get through it. The second class was the first class at Cheung Kong in November 2002. At that time, the students in the first class were all coaxed by the professors themselves. They didn't get the diploma from the education committee, so the students didn't pay tuition. At that time, the dean told me that if the class went badly, two-thirds of the students might not pay tuition. I prepared for a long time and taught a case with Professor Yan Aimin for two full days. At that time, it was quite brilliant. The third class was the first CEO class at Cheung Kong. By chance, the top CEOs were invited to the same classroom. The day before the class, everyone said that if he comes, I will come. If Guangchang comes, Niu Gensheng will come. If Feng Lun comes, Wang Shi will come. So on the night before the class, we didn't know who would come, but fortunately, at the last moment, all the big shots walked into the classroom. I was under a lot of pressure in that class, although I had some research on China's economy at that time. At that time, Fang Hongbo of Midea Group was a student. He recently talked about the impact that class had on him. There is a small correction: there is a rumor outside that after Ma Yun attended a class, he recruited me to Alibaba. That's not true. In 2000, because I wrote a case on China's internet for INSEAD MBA, I met Ma Yun in 2001, not at the Cheung Kong CEO class. After joining Alibaba in 2006, I basically didn't teach outside. In 2015, the first class of Hupan University started. For the first time, my age was higher than the students'. Facing post-80s, post-85s, and post-90s entrepreneurs, I found that the experience accumulated in school could no longer be used, including the experience and theories accumulated at Alibaba, which needed to be revised in the process of interaction with students. I began to return to the feeling of research classes. This is my fifth important class, and I have made innovations in both form and content. Thank you very much! Public class video review ↓ -END-