These stories make the Kaltix trio shine with something called worship.

After a pause, Ning Zimo added, "This search engine is called bing. Now it has been developed and uses crawlers to crawl network information. But currently, our [bing] team has encountered problems with the search algorithm.

There was a problem. So much so that my epoch-making plan for big data in search engines encountered obstacles.”

"And these obstacles," Ning Zimo said solemnly, turning his fingers from himself to the three Kaltix people, "are the main reasons why I asked Hoffman to find you search experts."

"Big data epoch-making plan?" Sepp pondered in confusion. Finally, he raised his head and asked Ning Zimo, "It sounds like a very huge project."

"Yes, it is a very huge project. Because currently, for people who do not understand the value of search, search engines are just windows that bring people results. But to truly discuss the value of search engines, the best place to reflect its value is

It must be the epoch-making search engine era of big data.

Think about it, in the past, when we performed data analysis and statistics, we were only limited to the database, where we performed statistical analysis on the data tables. And limited by the amount of data and computing power, we could only perform statistics and analysis on the most important data.

.

Search engines have transcended this limitation and can become a large database that stores almost all accessible web pages in the world, the number of which may exceed one trillion, and all of which require tens of thousands of disks to store.

Although it seems that Fengyu is already doing this, Fengyu's plans for the future are not as clear as I imagined.

Because if we continue to develop further, I want Bing to be able to uniformly store and manage all kinds of text, pictures, videos and other things corresponding to technology, culture, knowledge, information, news, etc., to form a large database for the entire human race.

It records all the past data of human civilization and provides various supporting conditions for future development. Build it into a human Noah's Ark to benefit all mankind.

I can simply give a few stage-by-stage examples, such as a certain early stage of big data - the data warehouse era of big data applications.

Bing can break away from the concept of database to perform SQL operations and realize data statistics and analysis. In other words, people will get much more data storage and computing power at a cheaper price on Bing than before.

We can put running logs, application collection data, and database data together for calculation and analysis to obtain data results that were previously unobtainable, and the enterprise's data warehouse will also expand exponentially.

If you think about it, in the era of data warehouses, as long as there is data, statistical analysis must be carried out. If the data scale is relatively large, we will think of using big data technology. The development of technology also promotes the application of technology, which also provides a good foundation for the future.

Next, big data applications enter the era of data mining, laying the groundwork.

The data mining era of big data applications must be superior to the data warehouse era of big data applications. For example, merchants discovered through data a long time ago that people who buy diapers usually also buy beer, so they are smart

Merchants put these two products together to promote sales.

You can have various interpretations of the relationship between beer and diapers, but if it were not for data mining, you might not be able to think of a relationship between them without breaking your head.

In a business environment, it is not important how to interpret this relationship. What is important is that as long as there is a correlation between them, correlation analysis can be performed. The ultimate goal is to allow users to see the products they want to buy as much as possible.

In addition to the relationship between products and products, you can also use the relationship between people to recommend products. If two people buy many products that are similar or even the same, no matter how far apart they are, they must have something in common.

a relationship.

For example, they may have similar educational backgrounds, financial incomes, and hobbies. Based on this relationship, related recommendations can be made to let them see the products they are interested in.

In addition to product sales, data mining can also be used to mine interpersonal relationships. The six degrees of separation theory believes that two people in the world who do not know each other only need a few middlemen to connect them. The experimental results of this theory in the United States are

, you can contact two unknown Americans in just six steps.

In the future, like our [Lingying] or even [myspace], various social software will record our friend relationships. Through relationship graph mining, almost all interpersonal networks in the world can be mapped.

Modern life is almost inseparable from the Internet. Various applications collect data all the time. This data is constantly being analyzed and mined in the big data cluster in the background.

Of course, we can also give a high-level example and talk about the industry related to the legend Richard Bing - medical care.

For example, leukemia and lupus erythematosus, which are currently difficult for humans to conquer, can be gathered together by collecting data on the patient's living habits, growth environment, DNA, disease development and other information, and turn small special pathologies into large-scale cases that can be used for reference.

data.

Then, through continuous data mining, we can analyze the causes of these cases. Then scientific researchers will have more reference basis for these incurable diseases, turning the originally small possibility into a possibility that can be broken through with high probability.

Perhaps it is possible for people suffering from these conditions to be cured, or perhaps it is possible for embryos with potential genetic defects in their genes to avoid pain during the pregnancy process.

Whether these analyzes and mining brings us happiness or fear depends entirely on the efforts of big data practitioners. But it is certain that no matter what the final result is, this process will only accelerate and will not stop, and you and I can only invest in it.

But in any case, it is worth doing. Even in order to improve efficiency, we can hand over some tedious and regular work to artificial intelligence, which will make the big data era develop into the machine learning era of big data applications.

Like in the example just now, there is a pattern in the data, and this pattern is followed by all data. What happened in the past followed this pattern, and what will happen in the future will also follow this pattern. Once this pattern is found, what is happening now will

, we can make predictions according to this rule.

In the past, we were limited by data collection, storage, and computing power. We could only obtain a small part of the data through sampling, and could not obtain complete, global, and detailed rules. But in the future, with big data, we can collect all the data.

Historical data are collected, their patterns are statistically calculated, and then what is happening is predicted.

This is machine learning.

For example, let me give you another example: store all the chess data of human Go games in history, and record which moves can get a higher chance of winning for each board. After getting this statistical rule, you can use this rule to interact with people.

Play chess.

Each move is calculated where it will land to get a greater chance of winning, so we get a robot that can play chess. Maybe one day this robot will learn thousands of chess games in a few years and learn through commonalities and

The learning of local strategies, by analyzing the intentions of human moves, overwhelmingly defeated the top human chess players."

Regardless of the stunned four people around him, Ning Zimo took a sip of coffee to moisten his throat and continued:

"When I finish talking about these examples, I believe you have a longer-term view of the search engine in my mind. Yes, it is huge. It is more than just a window that can provide people with search results.

It is a window into the era of big data.

What bing has to do is to store all the information retained by human civilization from its birth to its development to this day, turning it into a huge database, allowing it to provide people from all walks of life with a large amount of data that can be verified, allowing human beings to

Make fewer mistakes and suffer less while traveling.

But maybe, that's just my wishful thinking. Because of the greed of human nature, we will have such advanced technology in time, but we still can't avoid so many problems.

But there is nothing wrong with technology. It all depends on the method we apply it and whether we practitioners can have a ruler to measure justice.

I can't do that much to measure justice, but in my lifetime, I just want to make technology go further and let the team around me contribute to human civilization.

As for what will happen when that great era arrives in the future, I believe that even if I get old, there will still be countless people of insight who can do more outstanding things than me.
Chapter completed!