Besides his talent, what impressed Eve Carly the most was Lin Hui's elegant manner and generous treatment of others.

After being in contact with him for a long time, I became more aware of Lin Hui’s talent and easy-going attitude towards others.

What left a deeper impression on Eve Carly was Lin Hui's profound knowledge and smart thinking.

Specifically, Eve Carly didn't know how to answer this question.

Eve Kali simply responded to this type of question:

——LIN Hui is a rational and fascinating person.

This is true. Lin Hui's extremely rational logic, calm temperament, and focused attitude towards things all fascinated Eve Carly.

Even deep in Eve Carly's heart, there seemed to be some different feelings that had been dormant for a long time.

How can a person who can silently influence the world with just a single gesture not be fascinating?

Not only does it affect the world, in fact some of Lin Hui's actions have had a lot of far-reaching impacts.

Maybe Lin Hui himself hasn't realized that he is changing the world.

But the fact is that Lin Hui is already changing the world.

Eve Carly knows this all too well.

First of all, Lin Hui’s contribution to text summarization is too great.

Text summaries can influence the world.

This is not an exaggeration.

Research related to text summarization actually has a long history.

Eve Kali was not very clear about the status of the research on text summarization in the East before.

But after coming to China, Eve Carly learned about it through some institutions where MIT has friendly cooperation with China.

Although China seems to have few projects in terms of text summarization in a broad sense.

But when it comes to pure Chinese text processing, this ancient oriental country not only has specialized projects.

Some are even covered by national plans such as the 863 Plan.

The 863 plan, as the name suggests, was naturally implemented in March 1986.

It was the first time I heard that many projects involving text summarization had even started as early as the end of the last century.

Eve Carley is stunning.

Even after thinking about it carefully, Eve Carly felt it was more terrifying.

It's already 2014, and there is still a plan started almost thirty years ago that is moving forward step by step.

Making a plan is not difficult; what is difficult is the execution of the plan.

It can be said that no one in the world has implemented this plan that was decided thirty years ago with such intensity.

In short, Eve Carly feels that this is almost unimaginable in the United States where the two gears alternate frequently.

But it’s just about text summarization.

Eve Carley is not too pessimistic.

After all, the West has also put a lot of effort into text summarization.

It is even much earlier than China started research in this area.

Eve Carly remembers hearing that when she was still a student, Western research on text summarization had already begun in the early days of the Cold War.

The first ones to carry out work in this area were schools such as Stanford University and MIT.

But the employer behind these schools at the time was the Pentagon of the United States.

It sounds strange, but it's not surprising.

This is the fact that the current human Internet and various computer technologies were originally inextricably linked to the military.

In fact, many technologies are almost purely military-to-civilian.

It involves the direction of text summarization.

The reason why the research on text summarization was carried out at that time was to achieve technological breakthroughs in text summarization to more efficiently process information through various public materials such as news and reports. At the same time, the research on text summarization was also In order to better achieve public opinion analysis of hostile forces.

As for the hostile force, it is naturally the extremely powerful polar bear in the past.

Speaking of which, this is also a strange feature of early text summary encoding.

It basically has no processing capabilities for Chinese, a language that is used by quite a lot of people.

But it has almost the same level of efficiency in processing Russian as English.

No matter what the original purpose was.

In short, research related to text summarization has received considerable attention for a long time.

Even for a long period of history, part of the research funding in this field even came directly from the military expenditures of the M country.

Later, with the advent of more efficient means of obtaining intelligence such as spy satellites, the M military's enthusiasm for research in this area gradually faded away.

Despite this, commercial enthusiasm for text summarization has remained almost unwavering.

Text, as an important carrier of information, cannot be overemphasized.

With the rapid development of the Internet in the new century, a large amount of information has emerged.

People have to pay more attention to it.

The deeper we study information, the more we learn about the world.

In-depth exploration of text summaries gives us greater control over information.

In terms of Lin Hui’s contribution to the text abstract.

It is no exaggeration to say that Lin Hui changed the world.

Anyway, Eve Carly doesn’t think there’s anything wrong with this statement.

When it comes to specific fields, Lin Hui's contribution to natural language processing is indeed equally great.

Compared with traditional extractive text summarization, generative text summarization has unprecedented significance.

The reason why generative text summarization is of unprecedented significance is not just because this technology is more efficient in processing text summarization.

Of course, generative text summarization can have higher efficiency in processing text.

This improvement in efficiency is indeed of great significance to relevant users such as journalists.

But this is not what researchers are concerned about.

A wheel that spins faster is more valuable than a wheel that spins the same but slower.

But upon closer inspection, you will find that it is actually of little value.

In fact, Eve Carly feels that the most inconspicuous thing about generative text summarization is its improvement in efficiency.

It can even be said that efficiency is only the external manifestation of the generative text summary algorithm rather than the real core of this algorithm.

The main content of natural language processing (NLP) in the usual sense is nothing more than two parts.

One part is NLU and the other part is NLG.

The former refers to natural language understanding, and the latter refers to natural language generation.

The generative text summarization algorithm developed by Lin Hui has extremely prominent significance in both natural language understanding and natural language generation.

Generative text summarization is a new text summarization algorithm.

Compared with traditional extractive summarization, which can only rely on the extraction of original text content, it can directly generate summaries "out of nothing".

Such an algorithm has naturally achieved unprecedented heights in natural language understanding.

And this also inspires the possibility of achieving new breakthroughs in natural language generation.
Chapter completed!