In the era of big data, human life is facing subversion.

In the era of big data, human life is facing subversion.

For the IT field, there are many very new concepts recently, such as cloud computing and Internet of Things. When we just started to have a clear understanding of these concepts, another brand-new concept appeared-big data. What is big data? Where does the concept of big data point and how does it change our lives? Will it bring troubles to our life and work?

The newspaper cooperated with CBN Brainstorming Program to discuss issues in the era of big data. The guests who participated in the discussion included Viktor Mayer-Sch?nberger, a professor at Oxford University who put forward the concept of big data; Xu, chief architect of Microsoft Asia Pacific R&D Group and cloud computing operating system; Wang Xiaoyang, Shanghai informatization expert, expert of various professional committees and dean of Computer College of Fudan University; Sun Jian politician, global partner of Kearney Management Consulting; Yu Wujin, Director of Institute of Modern Philosophy, Fudan University; Hans tung, a partner of Qi Ming Venture Capital Company, and Shi Shusi, a famous financial commentator.

1 What exactly is big data?

Victor: I think this is the new gold. I think it is the most important resource in 2 1 century. This kind of resource plays a very important role in the success and loss of society, enterprises and individuals. It shows that although we all have data before, it is very expensive to analyze the data together, so we pay more attention to physical resources, that is, real money, such as labor. But until recently, we relied on people's knowledge and innovation to create wealth. Furthermore, we can do it according to the data, because in data collection and analysis, the degree of cost increase has changed, and then our data can reach a certain scale. Finally, whatever you are looking for, whether you are a person, a company, an organization or this society, is nothing more than this so-called new gold.

Why has the value of gold fallen sharply recently? Because old gold is worthless, it is not as valuable as new gold.

Dong Hansi: My views are somewhat similar. The first is cloud, the second is relationship, and the third is the future. As Mr. Victor mentioned just now, because of the arrival of the cloud era, the cost of storing a large amount of data is very low, so we can use big data for job analysis. Recently, because of many things, I have learned more about the relationship and can predict the future. In my own words, I spent a lot of time listening to and seeing many friends, whether we are looking for job opportunities or knowing helpful partners. In such a large amount of information, so many people put their own information on it, that is, they have done one thing, that is, analysis. If you want to be the CEO of a creative company at the age of 40, how do you plan for the next 20 years? This is a very interesting thing.

There may be different possibilities in the end, and it's up to you to find the best way in the end. The possibility is in front of us, and the probability is the highest. How to choose is still a personal decision, so big data does not obliterate personal consciousness.

Shi Shusi: Big data first changes the way we look at the world, which will have a fierce impact on many values of this era. For example, in the past, we orientals especially liked a word called cause and effect, thinking that good is rewarded with good and evil with evil. In fact, according to the data investigated by the traffic control department, people who have an accident in the street have nothing to do with morality. Qin Gui's life expectancy is two and a half times that of Yue Fei, and many corrupt officials lived an enviable life before they were discovered. Therefore, through big data, we can look at the world with a brand-new concept. The world is a new type of relationship, which is interrelated and constructed. Only when science and technology develop to a certain extent can we reach such a height.

At the same time, in the era of big data, we should abide by the bottom line, but it does tell us the truth because science is telling us the truth. I have a wish, that is, the big data just mentioned is new gold, and I hope it can be used more for social welfare undertakings, for example, to save the Seismological Bureau. This can avoid many humanitarian disasters and property losses. The conclusion is that we used to think that God was a philosopher or philosopher, but now we find that his old man's house is an old urchin.

2 Does big data have an impact on work and life in various fields?

Wang Xiaoyang: Big data affects wisdom. How to understand it? The concept of big data itself is the collection and processing of data, which can benefit our society and managers to some extent. From the perspective of the city, a manager can collect these data and processing methods, so that we can manage the city with wisdom, and we can manage it from traffic management, public health and other aspects. This kind of management needs data, which generates wisdom, and then in turn manages our model.

For example, in the field of public health, data collection has actually been going on for many years. Its data collection was not originally for big data, but actually for convenience-convenient for everyone to see a doctor. Moreover, your electronic medical record can make you see a doctor more humanized, or make doctors familiar with the disease more quickly and conveniently, but in this case, once these data are collected, we can further understand the health status of the whole city. Therefore, the data of seeing a doctor just now is actually the original intention. When big data comes, we can actually see problems that we could not see before. For example, some big trends, where there are more epidemics, or how it spreads, and so on. We didn't see these things before, and this situation is the help of big data.

Xu: For example, there is a ball and an ant. The ball tells ants that it is great to do things in a three-dimensional world. You can see how many ants are on this line at a glance. The ant said I really don't believe it. I have to climb along this line. I didn't know how many ants there were until the counter was not broken. Visible three-dimensional and two-dimensional difference is one-dimensional, so the difference is so big. So big data is not big data from the beginning, and the same data is not big data. But based on the original two-dimensional and original database, one-dimensional is constructed, giving it a brand-new look. For example, if you are in the United States and you are in debt, other people will be interested in you besides creditors-if you are in debt and suddenly you can pay your debts, then the bank will also be interested in you. 1 1 years ago, American Capital One invented an application of big data. It can find out who owes money to banks and credit cards, and then it will observe your consumption data. When it found that you could start paying back, it immediately bought you back, and since then it has eaten your interest. 200 1, the quarterly growth rate of Capital One Company is 20%. Because of its big data program, it can find this with a high hit rate. Where did it get the data? From Wal-Mart, from various consumption data. As can be seen from this example, big data adds another layer to the original business intelligence of data analysis. Business intelligence cannot tell us what others will do and what they can do.

About our company's prediction of the Oscar Award, except Ang Lee, everything else is right. In fact, our prediction is to give all the staff a probability, so we made a prediction of 19, which is the winner in the first probability, and there are four second probabilities below, so we put him in the second probability and put him behind.

This prediction has a lot to do with big data. First of all, big data needs IQ and IQ, which means this model should be very good. The person who does IQ in our company is David S. Rothschild, who is a member of our research department. There are others, I want to talk about, where is his IQ difference? His IQ uses a very simple aggregation model. What else besides IQ? After IQ, you should be diligent in management and diligence. Being diligent in business means that he is very diligent in finding data, looking for all kinds of data and looking for very practical data, so he looks online and on social networks. Some data can't be found. What should I do? He asked someone to do the investigation, and then asked someone to do it, so he was both intelligent and diligent. Is it enough? That's not enough. This kind of thing could not be done five years ago. Why? Five years ago, if he wanted to do such a large amount of data, he could not do it with a small budget for a graduate student, but with the emergence of cloud computing, he could do it. You can extend this data and use many processors to process it. Now he does this calculation with clouds, and finally he succeeds.

Sun Jian politician: I wrote about opportunities and dangers, that is, crisis. I agree with Victor's conclusion that this is a new gold mine, or a new opportunity, but don't forget that it will also bring many dangers. If we can't handle big data well, especially many China enterprises that we come into contact with in our daily work, most of them are still backward even in the most basic data analysis, which means how can we quickly transition to the era of big data and face the challenges of big data? If we are not prepared, I am worried that this will easily cause many enterprises to learn to walk in Handan, just like many new technologies did in the past.

In our industry, a lot of product innovations have been made because of big data. When we talk about subversive innovation in the era of big data, we are actually talking about the same problem, because at the same time of innovation, we actually have to interpret and subvert many original things, including many services and products in our consulting industry. We must keep pace with the times. For example, we have a large global retail enterprise, which has to deal with massive data every day, so before massive data, it still needs to find a good starting point to solve how to apply big data to business, change business model and bring value to business innovation, despite the technical means. Because it is necessary to make better use of this big data, whether it is cheap or investment, or change. All aspects of software and hardware need to be configured, and even the corresponding organizations need to be adjusted. An enterprise needs to make further adjustments to meet the needs of the era of big data. In order for big data to work. So what we do is to help enterprises find its value creation, establish a business model, and prove that it is worthwhile to make such an investment in this respect and let big data play its role.

Yu Wujin: I want to put forward different views because there is a characteristic of human thinking. He exaggerated his sense of globality. For example, if you see three swans are white, but there are actually 1000 swans, but a black swan is found in Australia, which overturns the principle that all swans are white. I think the problem of big data is very important, but how to treat it correctly should not go to extremes. Big data embodies a way of thinking that people understand life from a quantitative relationship. It has been highly valued since ancient times. Of course, the concept of big data was useless in ancient times.

Numbers themselves are becoming more and more important to life. It is practical from a philosophical point of view. For example, π in mathematics is equal to 3. 14 15926 ... It includes all the big data, and one third is easier to understand. Another way to write one third is 0.333333 infinite extension, so hackers logically emphasize that this infinity is included in one third. Looking at this data from this practical point of view, I think big data plays an important role in contemporary changes, but we should look at it with a vision, not exaggerating or shrinking.

3 how to understand that one third of the data in a lifetime are summarized?

Victor: I don't agree with Teacher Yu. Numbers have a long history, but in the past, the way we handled them was very limited. Technology alone is not enough. We can analyze data, such as numbers, which are just a number to you. This meaning is not important. You can also represent them with a Chinese character or a letter. From this perspective, big data is just a long number, you can remember it with your heart.

But in fact, the value of big data lies in that it needs analysis to understand it during the whole data collection process. For example, how to carry out preventive maintenance and how to prevent the outbreak of the epidemic. We don't simply write this number down or memorize it, but analyze it through analysis, statistical analysis of data and sorting it out. It's not just a matter of memorizing a number. This is a very big difference.

What kind of subversion will the era of big data bring to life?

Victor: First of all, in business, I think there are three elements to remember: First, in the business world, decisions will change, which will prove more and more clearly that we must rely on data to speak.

In the United States, the biggest Internet company is probably Google, with 3 billion search requests every day. One day they plan to use blue on the screen, and then they choose a special blue, but he plans to test 4 1 different blues to see which one is the most popular. He wants to decide for himself: I am the chief designer, so I chose blue. But his boss said, no, I need empirical evidence to tell us which blue is the most popular. But Google's chief designer resigned. He said that I am the chief designer, and I know best. Through many tests, it is found that one kind of blue is not much different from the blue chosen by designers, but the other blue tested is more popular and has more clicks. Decisions made through argumentation are more effective. There are many similar examples, all of which say that I have been in this business for decades, and it must be true. This traditional social concept and way of thinking will be challenged, and our decision-making must rely on data. This is the first point.

Second, when we go out to talk, we should be careful not to misread the data. Wrong data won't do. In other words, if the original data is wrong, the raw materials are rubbish, and the things that come out are definitely rubbish, this company can understand these data more easily, but it may not be the data you should be familiar with.

The third is the challenge. Is the general industry, especially the computer industry, the data will exceed them. This may be a challenging statement. If you don't have enough data, you can't catch up with a relatively mediocre model with a lot of data, which is why data will surpass those industries. Take machine translation as an example. In the 1960s and 1970s, IBM spent a lot of money on machine translation. It wants to put some language rules into the machine, but the effect is not very good. It has a new idea. Instead of inputting the grammatical rules of a language into a machine, it has been introduced into the English-French bilingual translation of the Canadian Parliament and thousands of translation materials. It has a large number of cumulative organization databases, and the effect is better. And Google has more data in this respect, and this translation is more mature and effective at once. It can be said that it is this data that makes it surpass this software. Because of the power of big data today, you can easily get the information you want, but about ten years ago, you needed 500 thousand servers and a lot of data storage and processing modes to start a business. If you want to enter business today, just use cloud computing to test it. For example, there is a company called Tiside, which has many products and prices. It gets some data to predict whether the product will be on the shelves or off the shelves. Although they have a large number of customers, the company has only 65,438+03 employees, so it has many servers and they have a lot of data. It can be seen that not only large companies can do it at this stage, but also innovative small companies can do it.

Wang Xiaoyang: Actually, when it comes to changing our whole way of thinking, the so-called experimental thinking is more important than theoretical thinking. I don't quite understand. In fact, the example given by Victor just now is that many times we use data to verify what we wanted to have before, and some wisdom is really excavated from numbers. This may be a language from different places. How can I put it? Based on the case of big data, there is actually a so-called cycle concept, that is, you have the wisdom to verify its later stage and generate all kinds of wisdom in the verified data to make such an understanding, so from this perspective, I think there is no subversion in the case of big data, but an improvement, which improves our cognitive world. As far as the topic of public health is concerned, one of the most cited examples is that there is a so-called trend prediction in Google, which uses words searched by netizens to predict.

How to predict the so-called flu? It's very simple, that is, analyze the previous data, tell the area where the flu occurred and what words people used to search in that area at that time, so that statistics can be made. After making statistics, what does it mean to use these search words to predict this flu? It doesn't necessarily mean that this kind of data or big data can suddenly give us a new understanding of this flu. Actually, it is not. In fact, those engineers at Google have an idea that we seem to have the flu, which is related to everyone. Everyone will use search to get some information related to the flu, and there is such a connection. How to find this connection? This is to use data to discover and use the so-called big data method to realize some of our existing conceptual things. After realizing it, we can make predictions. So from this perspective, it is not necessary to have big data, so we can lose all our wisdom. We don't need IQ, as long as the data is good, this is definitely not enough. Must be IQ plus data, and then you can have positive and negative concepts. This is what big data should do.

Dong Hansi: I have different ideas. I think what Mr. Victor just said is very interesting, that is, the requirements for wisdom in the era of big data are different. In the era of big data, it is interesting that the requirements for wisdom can be lower and better results can be produced. He just gave an example. It was difficult to translate before. Your rules must be particularly powerful, concise and complete in order to have 60% and 70% accuracy. But in the era of big data, we don't have to think about those complicated rules and routines. We just need to hand over hundreds of millions of translated articles to the computer and find out what the other meaning of the translated words is in a statistical way. The requirement for wisdom is actually reduced, but the effect may be better.

Sun Jian politician: Maybe our understanding of wisdom is vague. I think I understand what Mr. Victor said, because he also has a book called Delete, which is devoted to this triple wisdom and talks about trade-offs. Because with the development of storage technology and Internet, he talks more about knowledge, and his requirements for knowledge can be lower, but I think his understanding of wisdom is different. The wisdom I understand is that you have fundamental and real insight to judge a thing. That is, your insight into a thing is still there, and it will not be weakened or unnecessary because of the existence of big data, but it is precisely because of the existence of big data that you need insight more.

Is the era of five big data really coming?

Wang Xiaoyang: Whether the era of big data will come depends on how you measure it. Now the number and types of these data, as well as the ways and means of collection and processing, have definitely reached the feeling of "unprecedented, no one will come after". In this case, in terms of the ability of data collection and data processing, our era of big data has arrived, but we have just begun to use data.

The era of big data changing our lives has not yet fully arrived, but we have made a lot of preparations for this. This is the management problem of the city. We have made a lot of preparations for the era of big data, such as data collection. How to use these data to build our smart city is the biggest problem.

Xu: From a commercial point of view, I personally think it is coming. For example, Mok, a medicinal material company, can take into account the nature of the weather. For example, this winter is particularly cold, and many allergic animals will hibernate. When it suddenly turns hot in April and May, there will be more pollen, and many people will be allergic this year. By analogy, it will market medicinal materials such as Kemineng through the market.

Viktor Mayer-Sch?nberger: US President Barack Obama once said that despite the government's efforts, it always lags behind enterprises and other social groups. Therefore, engaging in such activities can fully stimulate data and provide it to the public, and companies can also take away these data and let companies use them to have more innovations. This is an idea. There may be some practices, such as business methods. I think it is helpful to give full play to the wisdom of some smart companies like Microsoft, including cooperating with the government to manage society.

Shi Shusi: I have a feeling that when business giants talk about big data in the face of Diaosi, we all have a chilling feeling, because although all of us are fair in the era of big data, we can say that small companies can get fair competition treatment, but in fact, all of them are giants who master big data, and they have unique advantages to steal money from our wallets. It's very difficult for us, because the definition of a company is to make profits within the scope permitted by law. However, we are eager for government departments to use big data to provide us with inclusive services, just like some smart cities can't really manage intelligently, so I am deeply worried about the future of big data coming to China. Also, even if excellent companies use big data, they must face the reality. For example, we advertise like TV stations. Why are there so many people now? Because the gap between the rich and the poor in China is particularly large. If you have all the data of consumers, and most of these data are invalid today, and you still have a process of choosing big data, called big data with purchasing power, then various problems will appear in front of us, that is, society is what we need, but there are many things behind the scenes. We are worried about being used by business giants to further exploit consumers.

Sun Jian politician: I think it's the same problem from the perspective of enterprises. What I want to express before is, first, many domestic enterprises are actually not ready for this big data, because we are still in the era of relatively elementary basic data analysis, and many of our basic data are not used today, let alone big data, and even small data is not used well today. There are still many false data, because the input management of these data is very immature. I have come into contact with many enterprises in my work. Everyone is doing several things that enterprises are doing today. There is an ERP system, there is a database, and the data is stored in it. However, I found that there are a lot of data management of cash in Chinese enterprises, which is not well utilized. There is a worry that after the arrival of the era of big data, China enterprises are not good at using this data analysis. In today's big data, the gap will become even bigger. In the future, international giants will have mature data analysis methods and many sound business models, which will make this gap bigger and bigger.

In the era of big data, what will be the next prediction and what will be the next judgment?

Victor: How can we make life more efficient than it is now, that is, make cities smarter? This is feasible. Why? What I emphasize is that we may improve our public health and education, and we have the ability to collect data. The popularization of public transport can truly meet the needs of citizens, not just politicians, and energy consumption will be better detected, predicted and managed, so that our city will be smarter and life will be better. /kloc-before 0/50, it was predicted that if you live in a city, your life will be shorter; Living in the country will lead to a long life. 150 years later, life expectancy is longer, and we will be better with big data, but there is a condition that those decision makers must use these numbers.

The next step is how the experts do it. In fact, this involves that in the data age, data points are limited, and we can collect enough data to solve the problem. Because it is very complicated and there are few data points, our data points must be collected with high quality. It's not like this now. It's getting messy. Explain that the more things, the more chaotic they are, and the more data points there are. For a phenomenon we want to study, we can do more statistics. For example, in the United States, if you have a DNA genetic map, you only need 2000 dollars to know how the 3 billion things in your whole genetic map are made up, so you can know the 3 billion pairs. Now, if a gene composition may cause what kind of cancer, you can look up the gene map and say I am. If there are more data, there will be some inaccuracies, so I say it is getting more and more chaotic, so it is allowed to be a little inaccurate or a little chaotic here. This so-called chaos means that every data point must achieve the highest accuracy. The result is that 100% is not perfect, but it is in the direction of big data, or you must know a direction at the right data point. Knowing the direction is more effective than knowing the perfect data later. For example, the traffic forecast, maybe the traffic forecast we see now is 20 minutes later than the actual application, and it may seem too late, but if this is the information of forecasting for one week, it is enough.

Wang Xiaoyang: In the era of big data, we have a better understanding of our city. The so-called understanding means that you know what is happening in this city, which is very important. In the past, the management of this city was a slap in the face. Sometimes it is very good, and it is also a great city. But sometimes? It may be too far to pat the head. In this case, how to make good use of it in the era of big data is what we want to say. For political achievements, you can also consider big data. Is this figure good for his political achievements? Is that the name is a big aspect. Big data is not only to understand what happened in our city, but also to understand what people in our city are thinking. This is very important for urban management. A city is not only hardware facilities, but also subways and tall buildings. The people inside are very important.

The above is what Bian Xiao shared for you about the subversion of human life in the era of big data. For more information, you can pay attention to the global ivy and share more dry goods.