What does big data bring to us?

Primary understanding of large data

It seems that overnight, big data has become the most fashionable word in the IT industry.

First, big data is not a completely new thing, Google's search service is a typical large data use, according to customer demand, Google real-time from the global mass of digital assets (or digital garbage) quickly find the most likely answer, presented to you, is a most typical of large data services. Only in the past such a scale of data processing and commercial value of the application is too little, in the IT industry does not form the concept of forming. Now with the global digitization, network broadband, Internet applications in all walks of life, the accumulation of data is increasing, more and more enterprises, industries and countries have found that the use of similar technology to better serve customers, discover new business opportunities, expand new markets and improve efficiency, only gradually develop the concept of large data.

There is an interesting story about luxury marketing. Prada has an RFID code on every piece of clothing in New York's flagship store. Whenever a customer picks up a Prada into the fitting room, RFID is automatically identified. At the same time, the data will be sent to Prada headquarters. Each piece of clothing in which city the flagship store at what time to stay in the fitting room for how long, the data are stored for analysis. If there is a low sales of clothes, the previous practice is to kill directly. However, if the data returned by the RFID show that the clothing although the low sales, but the number of fitting rooms. That would explain some of the problems. Perhaps the end of the dress will be very different, perhaps in a small change in detail will recreate a very popular product.

Another is the story of Chinese food statistics. China's food statistics are a long-standing problem. China's statistics, although organized, there are processes, there are laws, but the central statisticians rely on provincial statisticians, provincial city, county, county, town, village, the last real work or reported is the grassroots part-time investigators, due to the well-known KPI assessment-oriented reasons, Shengar, almost no one believe this survey data, The people in the National Bureau of Statistics are the least trusted. At a meeting in Beijing two years ago, Jingyuan, the former chief economist of the National Bureau of Statistics, told us how they did it. They use remote sensing satellites, through image recognition, all of China's arable land is identified, calculated, and then the Chinese arable land grid, each grid of farmland sampling for tracking, investigation and statistics, and then according to the principle of statistics, calculate (or estimate) the whole of China's overall grain data. This approach is typical of large data modeling methods, breaking traditional processes and organizations, directly to achieve the final results.

Finally, a stock story. The story comes from a 2011 Hollywood high IQ movie, "Never-Ending," about a down-and-go writer Cooper, who took a magical blue pill that could quickly boost intelligence, and then used it to fry the high IQ. How did Cooper fry the stock? Is that he can grasp in a short time countless company information and background, that is, the world already exists in the vast number of data (including corporate earnings, television, decades ago, the newspaper, internet, gossip, etc.) dug out, in tandem, and even face book, Twitter's massive social data mining gets the general public's emotional inclination towards a particular stock, through the mass of information mining, analysis, so that all insider is not inside, so that all trends are in sight, the result in 10 days he won 2 million dollars, the magic of the performance of the side of the professional investors stunned. This movie is simply a textbook movie that shows great data magic, and it is recommended for people who have not seen it.

In these cases, big data is not a very magical thing. As the movie "never-ending" raises the question: Humans usually use only 20% of the brain, if the remaining 80% brain potential is stimulated, what will the world become? In the management of enterprises, industries and countries, it is usually only effective to use less than 20% of the data (or even less), if the value of the remaining 80% data is stimulated, what will the world be like? Especially with the new Moore's law of massive data, the explosion of data, and then the more effective application of data, what about the world?

A single data does not have value, but more and more data accumulation, quantitative change will cause qualitative change, as if a person's opinion is not important, but 1000 people, 10,000 people's opinion is more important, millions of people enough to set off a huge wave, hundreds of millions of people enough to alter everything.

There is more data, but it is worthless if it is blocked or not used. China has a lot of late flights, compared to US flights on schedule. Among them, the United States Air traffic Control Agency a good practice has played a positive role, it is also very simple, that is, the United States will announce each airline, each aviation in the past year of the late rate and the average late time, so that customers in the purchase of air tickets will naturally choose a high punctuality flight, Thus through the market means to traction the airlines to improve the punctuality rate. This simple approach is more direct and effective than any management tool, such as the Chinese government's macro-control approach. Here are one or two more sentences, in the past tyranny of the state internal control is mainly physical violence, is the power of powerful institutions unlimited, to engage in State terrorism, and now a tyranny of the state, mainly rely on monopoly information, blocking information, so that people can not access to a wide range of real information, so as to achieve state control. This information blockade is a blockade of large data.

Without the data of integration and mining, value is not present. Cooper in never-ending is not worth the information if it is not able to integrate the mass of information around a company's share price.

Therefore, massive data generation, acquisition, mining and integration, so that it shows great commercial value, this is my understanding of large data. These problems are not a problem in today's reconstruction of the Internet. Because, I think the big data is the Internet deep development of the next wave of application, is the natural extension of Internet development. At present, it can be said that the development of large data to a critical point, it has become one of the hottest words in the IT industry.

Second, large data will be reconstructed in many industries business thinking and business model

I want to start this topic with the wild imagination of the future car industry.

In one's life, a car is a huge investment. To a 300,000 car, seven-year change cycle to calculate, the annual depreciation fee of more than 40,000 (here is not counted as capital cost), plus parking, insurance (market area), oil, maintenance and maintenance costs, the annual cost should be around 60,000. The automobile industry is also a long industrial chain of leading industry, this aspect only real estate (market area) can be comparable.

But at the same time, the automobile industry chain is a inefficient and slow-changing industry. The car has always been four wheels, a steering wheel, two rows of sofas (Li-language). Such an expensive thing, around the car generated data is less pitiful, the industry chain between the few data transfer.

Here we are wild to imagine, if the car fully digitized, the big data, what will happen?

Some people say that car digitization, is not to add a MBB module? No, it's too small for pediatrics. In my ideal, digitization means that cars can be linked to the Internet at any time, means that the car is a large computing system plus the traditional wheels, steering wheel and sofa, which means that digital navigation, automatic driving, means that you and the car every action is digitized, including every repair, every driving route, Every video of the accident, the status of the key parts of the car every day, and even your every driving habit (such as braking and acceleration every time) is documented. In this way, your car can generate T-bit data every month or even every week.

Well, let's assume that these data can be stored and shared with relevant governments, industries, and businesses. The impact of privacy issues is not discussed here, assuming that the data can be freely shared under the premise of privacy protection.

So what does an insurance company do? The insurance company takes all your data back to modeling and analysis, found a few important facts: first, you drive mainly just to work, Nanshan to Bantian this line is not busy route, the traffic lights are very small, this route in the past year, the accident rate of statistics is very low; your condition (length of service, vehicle) good, This model in Shenzhen is also a low car accident rate, even the statistics of your driving habits, refueling average, temporary brakes less, overtaking less, and the surrounding car to maintain the proper distance, driving habits good. The final conclusion is that your model is good, good condition, good driving habits, frequent line accident rate is low, the past year has not been a car accident, so you can give a more substantial discount. So the insurance company completely reconstructs its business model. In the absence of large data support, the insurance company only made the car insurance customers a simple classification, divided into four kinds of customers, the first is two consecutive years without a car accident, the second has not been a car accident in the past year, the third one in the past year, a car accident, the fourth is the past year two and more accidents, on four types. This kind of simple and rough classification, just like a woman to find a husband, only the man is divided into not married, married, married two times, three times and more married four kinds of men, dare to marry the same. Under the support of large data, insurance companies can really customer-centric, divided into tens of thousands of customers, each customer has personalized solutions, so that the insurance companies operate on a completely different, for Low-risk customers dare to discount, for high-risk customers to report high prices or even refused, The general insurance company is completely difficult to compete with such insurance companies. Insurers with big data and big data will have an overwhelming competitive advantage over traditional companies, large data will become the core competitiveness of insurance companies, because insurance is a business based on probability assessment, large data for accurate assessment of probability is undoubtedly the most advantageous weapon, and is simply a tailored weapon.

With the support of large data, the service of 4S shop is completely different. Condition information will be passed to the 4S shop regularly, 4S stores will be timely to remind owners of the timely maintenance and repair, especially for the possibility of endangering the safety of the problem, in the customer agreed to even take remote intervention measures, but also can be prepared in advance, the owner of one to 4S shop can repair without waiting.

For motorists, when they don't want to drive, with the support of large data and artificial intelligence, the vehicle can drive automatically, and the circuit that you often drive can be self-learning self optimization. Google's self-driving car, in order to predict the surrounding environment, to collect almost 1GB per second of data, no large data support, automatic driving is unthinkable, in and around the vehicle near, will promptly remind the owner to avoid, when commuting, according to real-time large data situation, For the line you often drive to be reminded, around the congestion point, to help you choose the most suitable line; in times of emergency, such as a flat tire, the automatic driving system will automatically take over, improve security (people can hardly encounter a flat tire in a lifetime, people in the emergency response is often disastrous, only worse); to the city center, Looking for parking is a very troublesome thing, but in the future you can go to the mall after the door, let the car to find a parking space, and so want to return to the time, advance notice let the car come to pick up their own.

Vehicles are the largest and most active moving objects in the city, the source of congestion and one of the biggest sources of pollution. Digital vehicles, large data applications will bring a lot of changes. Traffic lights can be automatically optimized, according to the congestion situation of different roads automatically adjust, and even in many places can be canceled traffic lights; city car parks can also be greatly optimized, according to the situation of large data to optimize the design of urban parking spaces, if coupled with the automatic driving function of vehicles, parking can be revolutionized, Can be designed specifically for automatic vehicle parking buildings, underground, floor floors can be as high as dozens of floors, parking floors can be higher, as long as can be higher than the height of the car (or put up to stop), which will have a huge impact on urban planning; In the event of an emergency, such as a landslide ahead, Can inform the surrounding vehicles (especially vehicles heading for the landslide road) at the first time; now the fuel tax can also be revolutionized, can really according to the driving distance of vehicles, or even according to the amount of car emissions to charge, sewage less than the car can even engage in carbon trading, selling emissions to sell high fuel consumption of cars , the government can also announce the actual emissions, taxes, safety and other indicators of various models each year to encourage people to buy more energy-efficient and safer cars.

Electronic commerce and the express industry can also change dramatically. Express car can be driven automatically, do not rush daytime congestion road, night open at your doorstep, design automatic receiver box, through the password to open automatic delivery, as in the past, like newspaper Newsboy.

So imagine, I think, the automobile digitization, the Internet, the big Data application, artificial intelligence, will the automobile industry and the related long industrial chain to produce the unimaginable huge change and the industrial Revolution, has the infinite imagination space, may completely be reconstructed. Of course, to achieve the scene I described, estimated at least 50 years, 100 years later, it is estimated that I will not see in my life.

The following image is centered around the person itself. The digital survival of people is the thing of these decades. My grandparents that life, is in the late life of the time there are photos, is preliminary in the personal image of a little digital, let us and future generations can also know the glorious image of grandparents. And we've had pictures since we were kids, and we've been digitizing more and more these years, identity is digital (is the identity card), the Bank (market area) deposits are digital, photos are full digital, physical examination is also digitized, shopping digitization (Taobao has my dozens of addresses, hundreds of shopping information, tens of thousands of times search information), Digital communication (micro-credit has a new circle of friends), the initial construction of a digital survival status. And our next generation or next generation will be in full digital survival, people from the birth of a genetic map, to follow-up every physical examination, every test, every year, every one months, every day of activity, to the relative of the track, from everyone, to each generation, to the entire family tree, to the whole country, to the whole world, The generation of these massive data will change from quantitative to qualitative, and the excavation and use of these data will have a revolutionary effect on human itself. Here, we also imagine:

For example, when you're looking for someone, you meet a girl you love, a big data system like a fortune-telling system, according to the two sides of the massive data mining, tell you and girls match index is how much, tell you the world of similar couples in the future divorce probability, below a match index, Large data systems will carefully advise you to seriously consider not the girl to go on. Does it sound like the digitization of a particular kind? Of course, you may say, this kind of life is not meaning ah, mistakes are inherently the most beautiful part of life. Oh, I only discuss scientific issues, to you this "romanticism" as the name, in fact, not to marry for the purpose of the bullying-style love, ignore. In fact, my heart also admits, occasionally play bullying is very good. Oh, a joke.

For example, when you're looking for a job, there might be a day, when you interview, HR will calmly tell you, sorry, after our large data analysis, your traditional network stickers, micro-blog, micro-letter overall negative emotions too much, not in line with our enterprise sunny optimistic positive theme, go out left there are subway stations, walking.

For example, on the day of your birthday, happy birthday to friends, Big data analysis system will tell you that your life will enter the countdown, according to the digital data of the body in the past few years, according to the genetic map, according to the relative situation of your relatives, you have 80% probability of death in 20 years, there are 30% The probability of 60 years of age or so due to genetic defects in cerebral haemorrhage, so you have to improve life habits, and focus on monitoring the possibility of cerebral hemorrhage. What would happen if all these things happened? First, it is estimated that human life will be extended for more than 10 years, as many potential outbreaks of sudden-onset malignant disease are significantly reduced. Second, like the car story above, the insurance company can reconstruct the business model based on large data, analyze the large data of each person, and design the insurance business for each person. Third, the pharmaceutical companies may also change the business model, the pharmaceutical companies have your relevant large data, can be tailored for your medicine, suits are tailored to the body, medicine why not? Tailored suits are more fitting, and customized medicines are definitely more targeted and have fewer side effects. Suits the power body custom, is because has your measurements data, the medicine energy body Custom also because has your body the data, the reason is same. Finally, the state's health care policy may be restructured, the State can analyze the overall national quality according to the large data system, analyze the aging situation, analyze the affordability of the pension system, strengthen the medical resources in some areas, or dynamically adjust the endowment insurance rate, or dynamically adjust the retirement age and so on.

The imagination of the auto industry and the digital life is over. Here, I would like to systematically review the development of industrial civilization, the first is the physical world of the industrial civilization, typically the invention of the steam engine, so that cars, ships into life, and then the digital world of industrial civilization, is the use of IT technology, the PC and a variety of electronic products into life, as well as the establishment of enterprise digital system, Making it possible for giant companies such as Wal-Mart to emerge; the next step is the integration of the physical world and the digital world, which is the industry's "industrial Internet", "it 3.0", which in addition to the use of digital technology in the traditional industry (which is in fact widely used), E-commerce in the wide range of channels to implement, More important is the production of large data and mining, use, so that enterprises in the management, market opportunities, product design, marketing, service, business model, and so great changes, this huge change has brought many industries revolutionary change, that is, subversion and transformation. This change in the so-called inefficient large industry will be most obvious with direct. These so-called inefficient industries are characterized by monopolistic characteristics, large industrial scale, long industrial chain, a long history but little change, low level of it application, such as automobiles, finance, insurance, medical care and so on.

At the end of this chapter, I would like to summarize my views on large data.

First, large data makes the enterprise truly capable of changing from self-centered to customer-centric. Business is for the customer, the purpose is to obtain profits for shareholders. Only by serving good customers can profits be achieved. But in the past, many enterprises do not have the ability to do customer-centric, the reason is that the corresponding customer information is small, mining is not enough, the system does not support the current insurance industry is a typical. The use of large data can make the enterprise's business object from the customer's rough induction (that is, the so-called refinement of the "customer base") to restore a living customer, so that the operation of targeted, customer service is better, investment efficiency is higher.

Second, the large data will, to a certain extent, subvert the traditional management style of the enterprise. The management of modern enterprises is derived from the imitation of the army, rely on layer-level organization and strict process, rely on the layer of information collection, convergence to make the right decision, and then through decision-making in the organization of the transfer and decomposition, as well as process specifications to ensure that decisions are implemented, ensure that every business activities have quality assurance, It also ensures a certain degree of risk aversion. It used to be a useful and clumsy way. In the era of large data, we may restructure the management of enterprises, through the analysis of large data and mining, a large number of business itself can be made from decision-making, do not have to rely on the expansion of organizations and complex processes. We are based on large data to make decisions, are dependent on the established rules to make decisions, is superior to the CEO decision, or the first-line personnel decision-making, itself and no big difference, then the enterprise needs so many levels of organization and complex process?

Third, the other important role of large data is to change business logic and provide the possibility of direct answers from other perspectives. Now people's thinking or corporate decision-making, in fact, is a logical force in the dominant role. We go to research, to collect data, to summarize, and finally to form their own inference and decision-making opinions, this is an observation, thinking, reasoning, decision-making business logic process. The logical formation of people and organizations requires a lot of learning, training and practice, the price is very great. But is this the only way? The big data gives us other options, that is, using the power of data to get answers directly. It's like we're learning math, as a child to learn 99 multiplication table, middle school geometry, university also learn calculus, encounter a problem, we are using the experience of years of study and sedimentation to try to solve, but we still have a way, in the online direct search is not there is such a problem, if any, directly copy the answer is good. Many people will criticize that this is plagiarism, is cheating. But why do we have to learn? Just to solve the problem. If I can search the answer anytime, can use the most labor-saving method to find the best answer, such a search can not be a bright road? In other words, in order to get what it is, we don't necessarily understand why. We are not the power of denying logic, but at least we have a new great power to rely on, and that is the power of future big data.

Four, with large data, we may have a new perspective to discover new business opportunities and restructure new business models. We now look at the world, such as analysts in the food (market area) corruption, mainly depends on our eyes plus our experience, but if we have a microscope, we see the bad bacteria, then the analysis is completely different. The big data is our microscope, which allows us to discover new business opportunities from a new perspective and possibly restructure business models. Our product design may not be the same, a lot of things do not guess, the customer's habits and preferences at a glance, our design can easily hit the heart of customers, our marketing is completely different, we know what customers like, hate what, more targeted. In particular, the microscope plus the wide-angle lens, we have more new horizons. This wide-angle lens is a cross-industry flow of data that allows us to see what we can't see, for example, the car case mentioned earlier, driving is driving, insurance is insurance, it is not relevant, but when we drive large data to the insurance company, the entire insurance company's business model has changed, completely reconstructed.

Last but not least, I want to talk about the revolutionary impact of big data development on it's own technical architecture. The foundation of large data is the IT system. Our modern enterprise IT system is basically based on the IoE (IBM minicomputer, Oracle database, EMC storage) +cisco model, this model is scale-up-type architecture, in the solution of the established model of a certain amount of data business process is appropriate, but if it is a large data age, Faced with costs, technology, and business models soon, the need for large data for it will soon go beyond the technical apex of the existing vendor architecture, and large data growth will lead to a linear relationship between IT spending growth that makes it difficult for businesses to afford it. Therefore, the current in the industry to IOE trend, the use of Scale-out architecture + open source software to scale-up architecture + private software replacement, the essence of the large data business model brought, that is, large data will drive the IT industry a new round of architectural changes. To IoE the so-called national security factors in the current trend is entirely secondary.

So, Americans say, big data is resources, like big oilfields, big coal mines, can continue to dig up huge wealth. And the general resources are not the same, it is renewable, is more digging more, digging more valuable, this is against the laws of nature. This is true for business, for industry, for countries, and for people alike. Who doesn't like this stuff? So the big data is so popular that it makes perfect sense.

Third, the birth of new intelligent creatures?

The following imagination is more wild, really want to achieve, estimated at least for our ten or 100 lifetimes after the event. At that time, we were already fathers, ha. Let's just look at science fiction.

Speaking from a recent speech by a Microsoft Vice president. Rick Rashid (Rick Rashid) is Senior vice president of Microsoft Research, and one day he was very, very nervous when he was on the podium in Tianjin, China, and faced 2000 researchers and students to give a speech. There is a reason for this tension. The problem is that he can't speak Chinese, and his translation level was so bad that it seemed destined for the embarrassment.

"We hope that within a few years we will be able to break the language barrier between people," said the senior vice president of Microsoft Office. After an intense two-second pause, the voice of the interpreter came out of the loudspeaker. "I personally believe that this will make the world a better place," he continued. "Pause, then the Chinese translation."

He smiled. The audience applauded every word he said. Some people even shed tears. This seemingly overly enthusiastic response is understandable: Rashid's translation is too difficult. Every word is understood and translated seamlessly. The most impressive thing is that this translation is not human.

This is the natural language of machine translation, but also a long time an important embodiment of artificial intelligence research. Artificial intelligence from the past to the future has a clear and huge business prospects, is the previous IT industry hotspot, its heat is no less than the current "internet" and "Big data." However, human beings in the past to promote the study of artificial intelligence encountered a huge obstacle, and finally almost despair.

At that time, artificial intelligence is to simulate human intelligent thinking way to build machine intelligence. In the case of machine translation, linguists and language experts must take pains to compile large dictionaries and rules related to grammar, syntax and semantics, hundreds of thousands of lexical composition thesaurus, grammatical rules as high as tens of thousands of, consider various scenarios, various contexts, simulate human translation, computer experts to build complex programs. Finally, it is found that human language is too complicated, and the exhaustive approach does not achieve the most basic translation quality. The end result of the road was that after years of technology research and development in artificial intelligence in the 1960 's, scientists painfully discovered that artificial intelligence had come to a dead end in the way of "simulating the human brain" and "rebuilding the human Brain", which led to the limbo of almost all AI projects.

Here's a little episode. When I was in college, I had a teacher who was a top professor of artificial intelligence in China, or vice president of an artificial intelligence research society. He commented that artificial intelligence at the time, not artificial intelligence, but artificial stupidity, the simple behavior of human decomposition, decomposition and then decomposition, and then clumsily simulated, not how intelligent how to learn, but the simulation of learning the most stupid person's simplest action. He said, for the progress of artificial intelligence at that time, some people complacent, said that as if the moon on the lunar plan to further the human, in fact, is to stand on a stone to the moon lyrical, ah, I am closer to you. His cynicism about his career has left me with a deep memory.

Later, some people think, why the machine to learn logic, and difficult to learn, the machine itself is the most powerful computational ability and data processing capabilities, why not to avoid weaknesses, another way to go? This road is the path that IBM "Deep Blue" passes through. The computer "Deep Blue" won the far-reaching "human-computer confrontation" on May 11, 1997, when chess master Kasparov, who was playing chess with IBM's computer "Deep Blue", declared defeat. "Deep Blue" is not rely on the logic, not rely on the so-called artificial intelligence to win, is to rely on the ability to win the calculation of super: think but you, but count your dead.

Similar logic is used for machine translation in the future. Google, Microsoft and IBM have all embarked on this path. The main use of matching method, coupled with machine learning, relying on a large number of data and related statistical information, regardless of the grammar and rules, the original text and the Internet translation data, to find the most similar, the most frequently cited translation results as output. That is, the use of large data and machine learning technology to achieve machine translation. The greater the amount of data available, the better the system can run, and that's why new machine translation is likely to regain ground after the advent of the Internet.

So, there are a lot of computer scientists in these company machine translation teams, but not even a pure linguist, as long as they are good at math and statistics, then they can program.

All in all, using this technology, the computer teaches itself to build patterns from large data. With enough information, you can let machines learn to do things that look smart, regardless of whether it's navigating, understanding words, translating languages, or recognizing human faces, or simulating human conversations. Chris Bishop, of Chris Bishop in Cambridge, UK, said: "You accumulate enough bricks and then step back to see a house." ”

Here we assume that this technology can continue to progress, the future based on large data and machine learning based on artificial intelligence to achieve a relatively smooth simulation of human dialogue, that is, the machine can be a more comfortable dialogue between people. In fact, IBM's "Watson" program is such a technology project, such as trying to make computers a doctor, able to diagnose most diseases and communicate with patients. In addition, it is assumed that the recent emergence of wearable computing equipment has made great progress. How far has this progressed? Is that your pet puppy has a variety of sensors and wearable equipment, for example, there are image acquisition, sound collection, olfactory collection, a small medical device to monitor the health of puppies, and even electronic pills to monitor the digestive situation in puppies ' stomachs. Dogs of course also connected to the Internet, also produced a huge amount of data. At this point, we assume that based on these large data models, can simulate the joys and sorrows of puppies, and then can be personified through the processing of voice expression, in other words, is to simulate the dog to speak, such as the owner home, the puppy wag tail, ask for help, then this attachment to the puppy's artificial intelligence system will say, "Master, It's good to see you home. " Not only that, you can also talk to the puppy's artificial intelligence system, because the AI system can basically understand what you mean and be able to take the place of a puppy as an anthropomorphic expression. Here we simulate possible conversations:

You: "Puppy, how are you doing today?" ”

Puppy: "Good, master, you change today's new dog food taste very good, always feel not eat enough." ”

You: "That's good." We'll continue to buy this kind of dog food later. Is there anyone here today? ”

Puppy: Only the postman comes to deliver the newspaper. In addition, the neighbour's puppy Mary also came to visit, we played together all afternoon. ”

You: "So how are you playing?" ”

Puppy: Very happy. I seem to have entered the first love again. ”

......

We can think of the analog dialogue above as a joke. But in fact, we will find an astonishing fact at this time, is that you are actually facing two puppies, a physical sense of the puppy, one is based on large data and machine learning Artificial intelligence virtual puppy, and virtual puppies than the physical puppy is also smarter, really considerate. So is this virtual puppy a new intelligent creature?

We continue to extend this story, to replace the puppy into the future, people in a lifetime to produce a large number of data, based on these data modeling can directly push a lot of conclusions, such as what kind of movies like watching Ah, like what kind of food, in the face of what the problem will be how to take action ah.

This data has been accumulating until the person dies. We have a bold imagination, can these huge data let this person in some way continue to exist? When there are questions for future generations, such as the key choices in life, such as what the university is going to be, and whether or not to marry a girl, can you ask this virtual person (ancestor) what advice? The answer is certainly yes. In this case, digital survival not only exists in front of life, but also can continue to exist after death. People die, you can continue to exist in the virtual space. A lifetime, a lifetime of people died, these virtual wisdom can continue to exist, assuming that many years have passed, these virtual wisdom ancestors too many too many, the children of the living can even form a "ancestral Joint Staff Committee", preferably those who did well (such as in the top), when the State senior civil servants (such as the prefecture) , as senior executives (such as CEO), as a professor, as a writer, etc. when the ancestors of successful people, dedicated to future generations of counseling, FAQ. Let these fathers die there is competition, do not die will have nothing to do. Is this scene familiar? is the Disney cartoon "Mulan" appeared in the scene, Ah Mulan in the face of whether the father joined the military life of the important moment, to the "Ancestral Joint Staff Committee" to talk about the confusion, got guidance.

More boldly imagine that the science of materials (market area) has made great progress, then can we put these virtual life back into the simulation of human ecology? Of course you can. This new body of intelligence is very much like a real person. Does that count as a resurrection after death? So this new intelligence will not continue to have the previous ID? Can we continue to have previous property? Can we continue to enjoy the pension? Is it necessary to impose certain life-span limits? This wisdom does not learn from self evolution? Will they erupt in war with humanity? Think deeply, feel all messed up, the present ethics, the law and so on are facing the formidable challenge.

What does all this mean? It is with the further progress of large data and machine learning that the world has emerged a new intelligent creature! Large data and machine learning after changing, restructuring and subverting many enterprises, industries and countries, it is time to change the human self! There is a new branch of human evolution!

Scientists have drawn the following picture to describe the two wise creatures. One is based on biological, after millions of years of evolution, one is based on it technology, based on large data and machine learning, through the self simulation, self-learning. The former is more logical, more rich emotion, creative, but life is limited, the latter does not have strong logic, no biological emotions, but there is a strong computational, modeling and search capabilities, theoretically life is unlimited.

Of course, these things will happen very, very far away. Anyway, when we are alive, we can not see, dead also see, because when we die, I believe this is based on large data and machine learning on the virtual life does not exist.

Iv. concluding remarks

The last thing I want to say is that our perception of the future is largely based on common sense and the imagination of the future. According to statistics, The New York Times is now a week of more information than a person's life in 18th century now 18 months of information generated more than the sum of the past 5,000 years, now my home a 5000-yuan computer computing power than I just entered the University of the whole school's computing power more powerful. The progress of science and technology in many times will always exceed our imagination, imagine if in the future we have a computer equipment more than the current global computing capacity of the sum, a person produced more than the current global data volume combined, even your pet puppy produces more information than the current global data volume sum, What will happen to the world? It depends on your imagination.

What do you think about the future?