Crossover: 2014

Chapter 254 Unprecedented Height

In addition to her talent, what left the deepest impression on Eve Carly was Lin Hui's elegant demeanor and generosity.

After getting in touch with him for a long time, I became aware of Lin Hui's talent and easy-going manner.

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

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

For such questions, Eve Carly simply replied as follows:
——LIN HUI is a rational and fascinating person.

As a matter of fact, Lin Hui's extremely rational logic, quiet temperament, and focused attitude towards things all fascinated Eve Carly.

Even in the depths of Eve Carly's heart, there seemed to be some special feelings that had been silent for a long time.

How can a person who can quietly affect the world with every gesture and gesture not make people fascinated?

It doesn't even just affect the world. In fact, some of Lin Hui's actions have already had a lot of far-reaching effects.

Perhaps Lin Hui himself has not realized that he is changing the world.

But the truth is that Lin Ash is already changing the world.

Eve Carly knew this all too well.

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

And text summarization can affect the world.

This is not an exaggeration.

Research on text summarization has a long history.

Eve Carly was not very clear about the status of Eastern research on text summarization.

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

Although there seems to be no project in China 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 special projects.

Some are even covered by national programs such as the 863 Program.

The 863 plan, as the name suggests, was naturally implemented in March 86.

At that time, I heard for the first time that many projects involving text summarization even started as early as the end of the last century.

Eve Carly is stunning.

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

It is already 2014, and there is still a plan that started almost 30 years ago and is moving forward step by step.

It is not difficult to make a plan, what is difficult is the execution of the plan.

As far as the implementation of this plan determined 30 years ago is concerned, it can be said that there is no one in the world.

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

But only in terms of text summarization.

Eve Carly is not too pessimistic.

After all, the West has also devoted a lot of effort to text summarization.

It is even far earlier than Huaguo's research in this area.

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

The first to work in this area were schools such as Stanford University and the Massachusetts Institute of Technology.

However, the employer behind these schools at that time was the Pentagon/Building in the United States.

As weird as it sounds, it's not.

As a matter of fact, all kinds of technologies in the Internet and computers of human beings were originally inextricably linked with the military.

Even many technologies are almost purely military-to-civilian.

It involves the direction of text summarization.

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

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

Speaking of which, this is also a wonderful feature of early text summarization coding.

There is basically no processing ability for Chinese, a language with a considerable number of users.

The processing of Russian is almost as efficient as that of English.

Regardless of the original purpose.

In short, the research related to text summarization has been paid much attention for quite a long time.

Even in a rather long period of history, part of the research funds in this field even came directly from the military funding 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.

As an important carrier of information, text 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 more we study information, the more we can learn about the world.

The in-depth exploration of text summarization allows us to have a stronger control over information.

In terms of Lin Hui's contribution to text summarization.

It is not an exaggeration to say that Lin Hui changed the world.

Anyway, Eve Carly didn't think there was anything wrong with this statement.

When it comes to specific fields, Lin Hui's contributions to natural language processing are equally great.

Compared with the traditional extractive text summarization, the significance of generative text summarization is unprecedented.

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

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

This improvement in efficiency is indeed very meaningful for relevant users such as reporters.

But that's not what researchers care about.

A wheel that turns faster is worth more than a wheel that also turns slower.

But if you dig deeper, you will find that it is actually not worth much.

In fact, Eve Carly thinks that the most inconspicuous content of generative text summarization is its improvement in efficiency.

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

In the usual sense, the main content of natural language processing (NLP) 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.

Lin Hui's generative text summarization algorithm has outstanding significance in both natural language understanding and natural language generation.

Generative text summarization is a new text summarization algorithm.

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

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

And it also inspires the possibility of new breakthroughs in natural language generation.

(End of this chapter)