ps. Present today's update, by the way, pull a vote for the starting point 515 fan festival, everyone has 8 votes, and the vote will also give the starting point coin, kneel and beg everyone to support and appreciate!

Although the mining of bitcoin was not successful, it was not completely fruitless, at least through this bitcoin mining, we can know that the computing power of the notebook is far beyond expectations. Pen × fun × Pavilion www. ｂｉｑｕｇｅ。 ｉｎｆｏ

According to the model of Bitcoin mining, the amount of Bitcoin obtained is equal to the proportion of computing power, which is the proportion of the total computing power of all mining computers in the entire Internet of a certain computer.

From this point of view, since Mo Hui is here to risk bitcoins, he can mine more than 20 in ten minutes, then in other words, the computing power of this notebook accounts for at least 90%. This is only a rough estimate of Mo Hui, and it is likely to be higher.

90% of what is the concept, probably means that this small notebook has at least nine times the computing power of all other mining computers combined!

On one end is a laptop for personal use, and on the other end are millions or even tens of millions of mining computers......

To put it another way, the computing power of this notebook is at least equivalent to the combined computing power of nearly 10 million computers......

Tens of millions of computers......

Mo Hui was taken aback by this data, this is too scary, all the existing supercomputers are scum in front of it.

However, this also gave Mo Hui inspiration, since its computing power is so good, the most suitable way for him to make money should be large-scale computing.

Mo Hui suddenly laughed, this is really stepping on iron shoes and finding nowhere to go.

Mo Hui is a code farmer, and he is still a code farmer who plays big data, which is really a professional counterpart, as long as he writes the big data program well and lets this super notebook calculate it, then there are a lot of things that can be done.

As long as Mo Hui can develop a big data software, let it automatically collect relevant information on the network, and then conduct in-depth data analysis, then it is easy to analyze the actual business status of a company.

As long as these data are used well, they can be used in the stock market, as long as there is infinite computing power as a guarantee, then the analysis results will be infinitely close to the real situation, and even the chairman of the company will accurately grasp the future development status of the enterprise.

Mo Hui thought about it for a while, and felt that this idea should be feasible enough, the program should be written by itself, and the public channels on the Internet can also provide enough information, as long as the data analysis algorithm is well designed, the final output result will have great reference value.

However, this is a big project for software development, and I am afraid it is difficult to complete it alone in a short period of time, but there is no need to worry too much. Find all kinds of open source software on the Internet, and then stitch these software together to make the first version of big data financial analysis software.

After the first version of the software comes out, actually runs the test, and starts to help him make money by trading stocks, he can use the money to hire people to help develop the software.

At that time, he can divide the whole software into many modules, and each module will be sent a package, whether it is to an individual or to another software company, so that he can decompose and develop, and finally assemble it with him. At that time, he will be a project manager, as long as he controls the overall development progress, he can remotely control a large team to help him develop.

Mo Hui has already thought of the name of this software, it is called the god of stocks, and he is going to develop version 1.0 of the god of stocks first.

The development cycle is unpredictable for the time being, but it is conceivable that even if he does a splicing and assembly job, there will be a lot of interface development work in the middle, and he needs to do it himself to assemble the adhesive and assembly platform that stitches these software together.

If the open source software happens to be able to find the right one, the cycle will naturally be much shorter, if it is unfortunate that there is no suitable software, it is estimated that he will have to develop it himself, and the time consumed will be endless.

Mo Hui made a work schedule for himself, and began to complete and advance item by item according to this schedule.

If you want to "save" a stock god 1.0, then there are several necessary key functional modules, such as the brain of stock god 1.0, which will be a big data analysis module, which is responsible for sorting out and processing all the collected information, and extracting guiding analysis conclusions from it.

This data analysis module must have both explicit causal analysis and implicit causal analysis capabilities.

For example, the decline in pig inventory data will inevitably lead to the subsequent increase in pork prices. There is an inevitable causal relationship between the number of live pigs and the price of pork, and the data analysis module must have the ability to identify this obvious causal relationship that can lead to effect.

For example, the rupture of the oil pipeline in the Southeast Strait will inevitably lead to an increase in the price of oil products in the southeast region of the empire, which also has a certain inevitable causal relationship. It's just that unlike the pig inventory data, the pig inventory data is a normalized data, which is there every day and floats every day, while the tubing rupture is an occasional event.

Although tubing rupture is an occasional event, the data analysis module must have the ability to identify such an accidental event and then give the inevitable consequences that it will cause subsequently.

There are many similar causal related events or data, and the data analysis module must have the ability to identify such explicit causal connections.

The counterpart to these explicit causal links is implicit causal connection.

The famous case of beer and diapers is actually a hidden causal connection, between which there is not necessarily an inevitability, but there is often a contingent connection between cause and effect.

In a single case, this causal link may not be true, but when it is placed on a large enough cardinal base, it becomes prominent, which is a causal relationship in the probabilistic sense.

There is another case based on this probabilistic causality. A search company that wants to study the possibility of a flu outbreak this winter, but it's looking at it from a very interesting angle, not from a medical point of view, but from a program and algorithm point of view.

It analyzes 50 million of the most frequently retrieved words, compares them with data from disease centers during the five-year period of seasonal influenza transmission, and builds a specific mathematical model to look for correlations and hidden possible connections, and finally it successfully predicts influenza outbreaks, even down to specific regions and cities.

If explicit causality only needs to be labeled and set in advance, then implicit causality obviously needs to be mined and searched, and how to find these implicit causality is the main function of the data analysis module, and it is also a landmark indicator of whether the module is successfully designed.

[It's about to be 515, I hope to continue to hit the 515 red envelope list, and the red envelope rain will be able to give back to readers and promotional works on May 15. A piece is also love, and it must be better! 】