Time Travel: 2014

This is also the reason why in previous generations, the national level paid so much attention to artificial intelligence.

What were the usual forms of labor and production relations in the past?

Either reform or revolution.

as something that affects labor and production relations.

The connotation derived from artificial intelligence is no less than a revolution!

In previous lives, artificial intelligence was once considered a strategic technology that led a new round of technological revolution and industrial change at that time.

In previous lives, artificial intelligence was officially considered to have a "head goose" effect with strong spillover effects.

The corresponding document directly pointed out that accelerating the development of a new generation of artificial intelligence is an important strategic starting point for us to win the initiative in global technological competition.

The official statement from the previous life is this:

“Humanity has experienced three waves of technological revolutions: the steam age, the electrical age, and the information age. Now, the rapid development of a new generation of artificial intelligence technology is setting off the fourth round of technological revolution, pushing human society towards the intelligent age.

Thinking about the significance of steam engines to the steam age, the significance of electric power technology and internal combustion engines to the electrical age, and the significance of computer and network technology to the information age, we can probably understand the significance of the new generation of artificial intelligence technology to the intelligent age. "

It is not difficult to see that in previous lives, artificial intelligence technology was highly valued.

It’s no wonder that artificial intelligence was taken seriously in previous lives.

In previous lives, artificial intelligence has shown considerable capabilities in many fields.

In air combat, artificial intelligence can defeat an Air Force colonel. This happened in a previous life in 2016 - Alpha, an artificial intelligence system developed by the University of Cincinnati, flew a third-generation F-15 aircraft against Jean, a U.S. Air Force/Army colonel with more than 20 years of flying experience. F-22, the result is Alpha victory;

In medical care, artificial intelligence can defeat senior doctors. This also happened in 2016 - after IBM's artificial intelligence "Watson" studied a large number of medical papers, it made a judgment within 10 minutes when human doctors were helpless about a patient. The patient was diagnosed with rare leukemia and a treatment plan was given;

In Go, artificial intelligence can defeat the world champion. This happened in the previous life in 2017 - Go artificial intelligence AlphaGo defeated the world champion kEJIE 3-0;

In scientific research, artificial intelligence can defeat scientists and accurately predict the advanced structure of proteins. This happened on December 2, 2018 in a previous life - the artificial intelligence AlphaFold launched by DeepMind defeated human experts from various countries in the global protein structure prediction competition CASP. Win the championship.

Due to some disturbances in time and space, these things that happened in the past life may not come as promised in this life.

But these things in past lives fully illustrate the huge potential of artificial intelligence.

Artificial intelligence will be recreated in this life because of its characteristics such as deep learning and cross-border integration.

Also in this life, artificial intelligence is still likely to have a significant and far-reaching impact on economic development, social progress, and the international political landscape.

In short, the coming new wave of artificial intelligence will not be a technological innovation.

To a certain extent, it is not an exaggeration to call the coming new wave of artificial intelligence an alternative revolution.

Such an alternative revolution obviously cannot be driven by Lin Hui alone.

Just Lin Hui’s own words.

Maybe Lin Hui can keep moving technology.

But Lin Hui alone cannot do anything about technology implementation.

If the technology is implemented, it still requires a lot of like-minded people.

Even some technical transfers in the later period unless Lin Hui has sufficient academic status.

Otherwise, even the handling may require some help to enhance the persuasiveness of the technology itself.

After all, many times when technical things are done, someone does not know the corresponding meaning.

Being melodramatic is sometimes a kind of helplessness.

Although these are things for the future.

But Lin Hui believes that this day will eventually come, and the future is even on its way.

That is a future worth looking forward to.

As stated by Eve Carley.

To be honest, whether it was Eve Carly's strong interest in Lin Hui's supplementary content in the paper or her expectations and concerns about the future of artificial intelligence, these were not beyond Lin Hui's expectations. However, Eve Carly's Lin Hui was a little surprised by the previous speculation about the purpose of Lin Hui's acquisition of her patent.

According to Eve Kali's guess, the reason why Lin Hui acquired her patent "A New Method for Text Judgment, Screening and Comparison" was to use it in the automatic text summarization framework (covering content representation, weight calculation, content selection and Make a fuss about content presentation under the four tasks of content organization.

Well, I have to say, Eve Carly is really a smart person.

He was able to understand so quickly why Lin Hui wanted to make such an acquisition.

Lin Hui thought it would take a long time for the pursuers behind him to realize this.

I didn’t expect that Eve Carly would understand part of it so quickly.

However, although Eve Carly guessed correctly, she was only partially correct, not completely correct.

Why did Lin Hui give such an evaluation?

By “content representation” Eve Carley refers to the process of dividing raw text into text units in the process of automated text summarization.

This process includes preprocessing work such as character segmentation, words, sentences, etc.;

Its main purpose is to process raw text through preprocessing into a form that can be easily analyzed by algorithms.

Traditional extractive summarization and traditional automatic text summarization do not pay much attention to content representation.

Generative text summarization and traditional extractive summarization are slightly different in this part.

Generative text summarization still pays more attention to content representation.

In particular, generative text summarization that applies word embedding technology and pre-training mechanism pays special attention to the aspect of "content representation".

There is no way, we have to pay attention to the fact that the importance of each step in traditional text summarization is actually about the same.

However, the work of generating text summarization using word embedding technology and pre-training mechanism is often "top-heavy".

That is, the link at the beginning has the highest weight in the entire link.

In other words, when actually building a generative text summary model, there are many steps to be designed.

But usually the jobs at the front are also more important.

Let’s take “content representation” as an example, when building a generative text summarization model.

In many cases, the level of completion of content representation will directly affect subsequent steps.

The patent "A New Method for Text Judgment, Screening and Comparison" obtained by Eve Carly does have certain value in terms of content representation.

With the help of the value provided by this patent, Lin Hui will be able to reduce some logical loopholes in the process of subsequent upgrades of text summarization in the future.