Editor's Note: Amazon's founder and CEO Bezos accepted an interview with well-known technology columnist Dr. WaltMossberg to express three main points: First, when it comes to artificial intelligence for the first time, we are at In the golden age of artificial intelligence; second, Bezos believes that the current voice system can only be regarded as an auxiliary enhancement technology, and can not completely replace the smart phone. Third, to truly use artificial intelligence to serve users, massive amounts of data are essential. We consider the overall privacy and our ability to store massive amounts of information, and use this data reasonably..., consumers will definitely like Amazon. Artificial intelligence system.
If Bezos has already seen the huge market potential of artificial intelligence on the consumer side, the massive data he suggests is the basis. But in the combination of corporate strategy and big data and artificial intelligence, he clearly did not give the main path. The latest article by Huawei, a Chinese innovation company, Mr. Ren Zhengfei, the founder of the company, explains the combination of artificial intelligence, big data, application scenarios and enterprise business from the perspective of strategy, platform and business. Xiaobian editors share with you.
GTS is an abbreviation of “Global Technical Serviceâ€. Ren Zhengfei said that Huawei should develop a unified artificial intelligence software platform and solidify algorithms, knowledge, methods and experiences on the platform. But don't be intelligent everywhere, it will form a blind movement with no result in full bloom, and it is possible to lose all. The following is the original text of the lecture.
The company's huge inventory network is the best stage for artificial intelligence. GTS needs to use artificial intelligence to achieve high-quality and efficient delivery and service, support the services of the "one trillion" dollar inventory network and the automation of fault handling and prevention... And scientific, rational, and efficient delivery of tens of billions of dollars of network support per year. Continue to create value for customers and enhance customer satisfaction, build a living "Great Wall" and become the company's important mobile "Magino Line". Who is the best winner in the world who can provide high quality services at the lowest cost. The company's artificial intelligence research is an enabler that promotes the company's management progress, and does not get lost with the flicker of the argument.
1. High-quality data is the premise and basis of artificial intelligence, and high-quality data output should be used as the standard for job completion.
Why can't we unify the tools of work, and the standards of work. With a data collection aggregator, after the on-site operation, the staff will return to the resident to deal with it, and the group will be sent out at the touch of a button. It is not necessary to go through the office or the regional department. The data is transparent to each stage and there is no level-level summary processing, which is much faster.
We have 4.3 million sites, an annual increase of 960,000, 11,000 contracts, and the reports reported by each base station are so thick because there is no modular classification. If we don't abstract, we will report it. We will handle the pipeline so thickly, so it will be blocked. In fact, it can be summarized in one hundred kinds, and there are less than one thousand modules. We classify information to the supply chain according to the template, the supply chain decoding is opened, and the list is shipped, and our management will be much simplified. Reports are now reported at the layer level, adding a lot of people to each layer, and a lot of reports have not even been read. It is necessary to build a simple automatic reporting system based on the target standard model, so that the intermediate labor is reduced, and the number of employees on the main battlefield is increased. Everyone is based on homework to provide you with accurate data. It's good to focus on your scientificity. With these accurate data, we can improve our efficiency through supervised learning and statistical methods.
There are clear and ambiguous forms in the completed form. The data filled in the deterministic work should be accurate. If there is no audit, the incorrect data will be transmitted. Clear data is constantly updated and accumulated, and new and effective data are constantly being replaced. There is always a fuzzy area, and the ambiguity of the fuzzy data will continue to decrease, but a new blur will be generated. There should be guidelines in places that should not be blurred, and can guide the grassroots engineers to operate clearly. Artificial intelligence relies on tens of thousands of employees to collect data effectively when doing things, and find out the rules in the summary. Clear and accurate field data is an important thing.
We are equipment suppliers and not traffic operators. We should look at the data in real time according to the business scenario. Do not metaphysically go to school. We need to obtain these so-called real-time data according to the necessary needs. For the output of network equipment data, the data output standard can be constructed in a manner similar to “seven-eight-eight-clickâ€, and the serviceability standard can be re-established based on the perspective of artificial intelligence delivery service, and is a necessary condition for product listing.
Therefore, you said that the data is lacking and chaotic, I don't criticize it. I don't think there is any data that I want to criticize. Everyone can wear a tooling and wear an instrument on the body. The data is collected and stored first, and then transmitted to the information base at the push of a button. Those who contribute data can also be rewarded.
2. Focus on investment and dare to invest. Success is only a matter of time.
In key scenarios such as site operations, network integration, network maintenance, and network planning network optimization selected by GTS, investment should be increased in business models, algorithms, platforms, and data. Specific human resources and expenses should be implemented in the future timeline of strategic planning. .
To develop the company's unified artificial intelligence software platform, the algorithm, knowledge, methods, experience, etc. are all solidified on the platform, first in the GTS practice and application, and in the future can also provide support for other businesses of the company. The investment in the data base needs to be increased. As a long-term basic project to build, with a high-quality data foundation, artificial intelligence can play a role.
The scientists in the 2012 lab should work closely with the service engineers. Scientists familiar with theories and algorithms choose the most mature solutions to apply to the service scenarios and work together to improve the business. This is the combination of technology and scenarios. Some people are familiar with the technical theory, some people are familiar with the scene, and the two cooperate with each other in the world. You should first improve our internal improvement. At that time, we will go to the outside and we will consider it.
The failure of new things is also a success. If you make a little progress, you will write it down. This is the process record. You use the radish to engrave the medals. If you accumulate more, you will go to the gold medal. Don't be afraid of mistakes. Others say that Huawei is backward, because we only give awards to successful people and never award winners. Today is better than yesterday, and the Himalayas are half successful. Because we have never been to the foot of the mountain.
3, artificial intelligence should focus on the investment, do not fully bloom, first play the annihilation battle, the flag will open and then expand horizontally
In our business expansion, people did not succeed in linear expansion. The service engineer should focus on the service business and complete the service business while completing the correct data output required by the artificial intelligence. On this basis, the scene analyst, data analyst and model designer are generated. These experts have to invest in the service battlefield for a long time and continuously improve their capabilities by serving customers. For scenario analysts, data analysts, and model designers, my attitude is to see how long it takes to achieve success in the first-line service battlefield within three years. If you don't have successful practical experience, don't promote it quickly. This also ensures that water is not corrupt.
Artificial intelligence should not be too impulsive when investing adequately. It is necessary to rush to run small steps first. Focus on deterministic business and labor-intensive projects. It is better to do less. First, break through the killings at one or two points. Power fights and destroys, do not spread a very broad front. Don't be intelligent everywhere, it will form a blind movement with no result in full bloom, and it is possible to lose all.
For example, the application of artificial intelligence should first aim at realizing the simplified survey, and on this basis, realize the automation design. Massive repetitive actions should be replaced by artificial intelligence technology to achieve automatic document generation, automatic quality review, remote acceptance and automatic invoicing. Then, the successful experience of the artificial intelligence application is extended to the business scenarios such as network maintenance and network planning network optimization, and the passive problem processing is turned into active early warning prevention, which not only improves the efficiency but also improves the quality of service for the customer.
It is necessary to solve the reality and focus on the scene one by one, and choose the relatively mature algorithm that matches the scene. Don't wait for the platform and the data base to mature. The semi-finished products can also be put into internal improved use, and mature in the practice and problem solving. Platform and data base. We have gained experience in these concentrated projects and cultivated new forces. These new forces must go to the grassroots level to implement and implement them, so that it can be applied into habits. On the basis of vertical development, grasp the reasonable rhythm of horizontal expansion. If a cake is pasted and then turned over, it will be a raw cake. We don’t want to "before the teacher does not die, and the hero will be full of tears." What we want is victory and ultimate success. Artificial intelligence is a new thing. In the implementation process, because of the dual-track operation, it is necessary to accept the phased cost increase and achieve clear long-term goals.
There are bound to be many difficulties in the application of artificial intelligence. In the process of advancing, we must encourage more and less criticism, and we can praise the praise that can be praised. When the guns on the battlefield rang, who is the hero, who is not the hero? You said that he is not a hero. At the foot of the mountain, you patted him on the shoulder. He took two dynamite bags and rushed to Shangganling. It might become a hero.
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