From University Lecturer to Chief Academician

in the office.

Sigbahn and Alvin worked on the thesis together.

He just read the introduction and immediately realized that the paper might help improve the data model and algorithm.

Sigbahn is different from Alvin. He will not study slowly by himself, but simply calls a few people over, "Everyone put down what you are doing and take a look at this first."

From this point of view, it was more than two hours.

They also concluded, "This method of assisting in building a data model is indeed feasible."

"According to this method, the more data, the higher the efficiency and accuracy, but when there is less data, it is not applicable."

"The difficulty lies in the structure of the original model. It is impossible for us to overthrow the original structure and use this method to reconstruct it."

"The method is new, but it is not easy to apply it."

Sigbahn leads the core algorithm group, and several employees under him can be said to be the elite of the R\u0026D center.

After careful study and discussion, they have a basic understanding of the construction method mentioned in the paper, and can infer the situation after use.

Finally, Sigbahn made a conclusion, "Generally speaking, for data analysis problems, the more data, the lower the accuracy."

"This mode is no exception, but the accuracy drops very slowly. For example, for one hundred data, the construction mode we adopt has a correct rate of 99.9%. If it is ten billion data, it will become eighty percent."

"Using this model to construct the algorithm, the correct rate of 100 data is only 90%, and the correct rate of 10 billion data will not be lower than 85%."

"This model construction method is indeed very meaningful, but in terms of application, it still needs to be studied slowly."

"Many of the papers are just a general introduction, but the method is not a problem. Maybe we can try it out. If there is a suitable project, we can use this method."

...

American, California, San Francisco, Google R\u0026D Center, Data and Data Application Lab.

Blake-Jones is sitting in the office. He has worked at Google for eleven years and has participated in projects such as algorithm customization, Android system improvement, and artificial intelligence. He is an extremely experienced and high-level algorithm engineer.

Now he looks at ordered computer journals.

There were three consecutive papers on it that attracted his attention. He frowned and read it carefully for a long time. He felt that the method described in it was very interesting, so he simply took a photo and shared it with the group of colleagues, "Everyone, take a look at this, the new one. Data model construction method."

"I took a look, it's very interesting."

soon.

Several colleagues who did not order, asked Blake-Jones to take pictures and send a few more pictures, preferably all the papers.

Blake-Jones tried the function of extracting text from pictures, and found that when it comes to mathematical content, many of them were extracted in a mess, so he simply took pictures one by one with a bitter face.

This incident was supposed to be in the past.

In the afternoon, the manager of the technical department found Blake-Jones and others, and said seriously, "Blake, I also read what you posted. It is very interesting, and most importantly, it may be very valuable."

"We have to take it seriously."

"Guys, put down the work at hand and study it together. This method may improve our efficiency..."

...

The same thing happened in the research and development centers of several large Internet companies, and even in national-level data control centers and information centers.

When there is a brand-new data model construction method that can be applied to massive data analysis and improve efficiency and accuracy, it will definitely be valued by Internet-related companies and information centers.

Just one day later, the country also received news.

Feng Youli, Director of the Technology Department of the Big Data R\u0026D Center of Abayun Group, received a report from his foreign employees--

In a paper published in the new issue of "Computer Mathematics and Information Engineering", a new data model construction method is introduced.

"Worthy of attention!"

Special emphasis is placed on employee reporting.

Online ordering and browsing will be delayed for three days, and there is no way to see it in China for the time being, but there are many ways to bypass the delay.

Feng Youli quickly obtained the entire content of the thesis, and he found several high-level technical staff to analyze it carefully.

At the same time, Feng Youli had an idea, "The author of the paper is a faculty member of Xihai University. He must be an excellent talent if he can develop a brand-new data model construction method."

"The easiest and most direct way is to invite him to work in Abayun."

"He is a talent, what Abayun needs most is talent."

"If this method is feasible, it will be perfect for the relevant applications and the revision and improvement of the underlying algorithm to be led by him."

...

When the impact of the paper slowly fermented, Wang Hao was not affected for the time being. He and Zhang Zhiqiang completed the research on "Cauchy non-negative matrix factorization expression", and the paper was also handed over to Zhang Zhiqiang for publication.

Then, he relaxed.

He sat in the office and drank coffee, chatting with others about family matters, talking about the gossip news circulating in the school, and even talking about men and women.

The next day was Thursday, and the morning was still very leisurely.

Wang Hao turned on the system and took a look at Task 2. Unsurprisingly, he found that the inspiration value was only '33'. "It seems that research and research are different."

"Even for research with the same difficulty, the speed of obtaining inspiration points is different."

"For research related to Fourier transform, the growth rate of inspiration value is relatively fast, while for research on the 'Cauchy problem', the growth rate of inspiration value is slower..."

"It probably involves many factors, such as teaching content, students' situation, students' thinking, and so on."

Wang Hao sighed lightly, and simply started to study the "partial differential equation". The inspiration value of the "partial differential equation" research has exceeded 70 points. When this value is reached, it is almost time to start research.

However, progress has been slow.

Two hours of continuous dedication can almost be described as 'no gain', not even a single problem was solved.

"It's hard!"

"The inspiration value is not enough, which means that the knowledge and ideas are not enough to support the completion of the research. It is too difficult to solve the problem without thinking!"

He simply changed jobs.

Write lesson plans!

Other teachers are focused on doing R\u0026D and writing papers, but for Wang Hao, teaching is the root of the matter. He hopes to continue to improve in teaching, not to study how to make students understand the content of knowledge, but to guide students to learn more. Think more.

This is critical.

When students can think more, they can give back more knowledge and inspiration.

"Guide students to think more..."

"How to guide it?"

"The topic of the lecture is better. If it is about basic knowledge, how to increase the content that guides students to think?"

I couldn't think of anything for a while.

Wang Hao and a few people in the office inquired, and also asked Zhou Qingyuan, and found out that an old professor——

Wang Huanxin.

Wang Huanxin is fifty-nine years old, but he is still only an associate professor. The main reason is that there are no breakthroughs in scientific research. Most of the papers he has published are related to teaching. He is recognized as an excellent old teacher in the school. Difference.

It's just a pity.

No matter how good the teaching is, it is difficult to promote his title. He still has not been promoted to full professor.

The people in the office had various gossips, and Zhu Ping said with certainty, "The school is planning to take advantage of the popularity of 'removing thesisism', and wants to mention Wang Huanxin as a full professor, a teaching-type full professor."

This is extremely rare.

Wang Hao knew that Wang Huanxin's teaching ability was very strong, so he went to Wang Huanxin's class in the afternoon, and found Wang Huanxin after class to discuss teaching issues.

Wang Huanxin was very enthusiastic about Wang Hao, and he said with emotion, "I really didn't expect that there are still people who can talk to me about teaching problems."

"Now young teachers like you only care about scientific research and papers, but, teachers, the most important thing is to teach students, and teaching students well is the first priority!"

"If you do a good job in scientific research and write a good thesis, it is better to be a researcher in a laboratory than to be a writer."

Wang Hao nodded in agreement, "I just hope to teach students well and make the courses more efficient."

Wang Huanxin was really happy, and he took the initiative to share his teaching experience.

Wang Hao raised the question of "how to guide students to think", and he also gave several examples in detail to illustrate.

The two talked for more than an hour.

It wasn't until he found that Wang Huanxin was a little tired that Wang Hao thanked him and left. He felt that he had gained a lot, and he also learned several tricks about the problem of "guiding students to think".

Taken together, you can even write a 'teaching' paper.

However, his thinking is still dominated by logic. When it comes to summarizing and writing papers, he immediately thinks of a question, "Guiding students to think more, the teaching effect may not be better."

"For the teaching of basic content, it is enough for students to remember and understand, so how to judge and guide students to think can bring more knowledge and inspiration? Maybe the original teaching method is better?"

This is uncertain.

Wang Hao thought of a way to judge, "If you only give lectures to a few students, the IQ of the students is relatively average, and it is difficult to understand the knowledge content."

"Using two methods, comparing two knowledges with similar difficulty, maybe you can know which method is better?"

"Then who should I look for? Stupid students, stupid students..."

Wang Hao chanted the words "stupid student" continuously, and two girls, one fat and one thin, appeared in his mind.