Chapter 240 It is impossible to roll the paper

Lin Hui's previous work on the generative summary algorithm, which invisibly mobilized the busyness of many scientific research institutions around the world, doesn't that illustrate this situation?

One person's busyness makes a group of people have to be busier and pay more.

What would this phenomenon be called in the language of the previous life?

Yes, that's right, it's "volume".

In previous lives, computer industry rolls were the norm.

So much so that after his rebirth, Lin Hui unconsciously brought over some habits from his previous life.

Although it was just an unintentional act, he was still a reborn person after all.

If the reborn person is not the king of rolls, should he take the lead and lie down?

Lin Hui will sooner or later kill all the potential hostile forces in this time and space.

…

At 3 o'clock in the morning on the 26th BJ time, Lin Hui was busy.

There were many people chasing Lin Hui behind Lin Hui.

Of course, although there are many people chasing me.

But there are many who are lost, and there are also many who feel despair when they see the gap.

It's exactly 11 a.m. in California.

Many researchers are still busy in the NOTEXIST laboratory on the campus of Stanford University in California.

But not everyone is busy.

There are also fishermen.

Looking at the time on the watch, it was almost noon.

Dr. Eclair Kilcaja is ready to leave work at 1 o'clock.

Working hard is the most important thing.

It is impossible to roll the roll, it is completely unnecessary.

The key is that it can't be rolled at all.

Since LIN HUI introduced the generative text summarization algorithm.

Dr. Eclair Kilcarga and his team have recently been following up on this technology together with the team of Professor Jules in the Department of Mathematics at Princeton University.

At the beginning, the entire team was still very ambitious.

But interest quickly faded.

The reason for the initial smugness was that Dr. Eclair Kilcaja and his team discovered the direction of long-term and short-term neural networks.

Dr. Eclair Kilcarga and his team once thought that this direction was the right research direction.

Compared with ordinary recurrent neural networks, the long-short-term neural network is less sensitive to the length of gaps in the text when applied.

Long short-term memory neural networks This category of neural networks has good performance in processing longer sequences.

It is precisely because the characteristics of the long short-term memory neural network are consistent with some of the characteristics of the practical application of the generative summary algorithm in LIN HUI.

At that time, Dr. Eclair Kilcarga and his team thought they had found the right direction.

After recent algorithm tracking research on LIN HUI.

Dr. Eclair Kilcaja and his team found that although their guess was right, it was not entirely right.

LIN HUI even uses long and short-term memory neural networks in generative text summarization.

But it is absolutely impossible to apply the most basic long and short-term memory neural network very superficially.

The high probability that LIN HUI is used in the algorithm is a more special neural network that relies on certain modifications of the long-short-term memory neural network.

Although it is unclear what type of modification is applied to LIN HUI.

But it must have been modified.

It's hard to say what modifications were made.

What one person hides may not be found by ten thousand people.

Similar reasoning, although LIN HUI may have only been slightly modified.

What exactly this change is about is impossible for Dr. Eclair Kilcarga and his team to figure out in a short period of time.

The only thing that can be understood is that LIN HUI uses an extremely clever application of long short-term memory neural network.

So helpless.

As the research deepens, there is some progress.

But the problem is that what is gained is not only progress, but also a better understanding of the opponent.

I haven’t discovered much about the true meaning of technology.

On the contrary, I fully realized the power of LIN HUI technology.

Dr. Eclair Kilcaja and his team seem to understand what it means to:

——The closer you are to your opponent’s strength, the more you understand how powerful your opponent is.

This is how Dr. Eclair Kilcarga and his team felt when facing LIN HUI.

Although it may be possible, the technology involved in generative text summarization is not purely technical.

Behind this is the market.

Technical problems can afford to wait, but can commercial problems afford to wait?

It’s almost time for competitors to tap into the market potential.

What's the use of re-entering?

The most critical thing is that Dr. Eclair Kilcaja and his team are now collaborating with the Department of Mathematics at Princeton University.

Cooperating with these people often has a counterproductive effect on project progress.

These math nerds always try to solve problems that are originally applied problems using mathematical methods.

The awkward situation of this cooperation often reminds Dr. Eclair Kilcarga of the dilemma of the Man-Moon myth.

In the face of various roadblocks.

He felt that it was impossible to catch up with Lin Hui’s generative text summarization algorithm in a short time.

Dr. Eclair Kilcarga and his team members decided to report to the Google marketing department on the follow-up status of the generative summary algorithm.

And give suggestions from a market perspective.

To be honest, as a technician, I give advice from a market perspective.

It seems to be a low profile.

But Dr. Eclair Kilcarga has nothing to do about it.

If it's purely theoretical, maybe you can play some word games in the report.

But algorithms like generative text summarization are closely related to applications.

It can be measured by actual text processing capabilities.

There is no room for tricks here.

Dr. Eclair Kilcaja recently learned a word called tang, ping from a game called R.R.

Perhaps this word is more suitable for his mentality at this time.

Fortunately, when Dr. Eclair Kilcarga presented the report to the marketing department earlier, the marketing department almost without thinking agreed to seek algorithmic authorization for Lin Hui's generative text summarization.

This reaction even surprised Dr. Eclair Kilcarga.

If he had agreed so readily, he and his team would not have had to fight for so long.

Later, Dr. Eclair Kilcaja learned that it was LIN HUI that made generative text summarization, a Chinese-derived technology recognized by the Chinese government.

In order to avoid encountering some technical protection from the administrative level.

Google, which is bent on pursuing generative text summarization to bring a broad market but has been slow to follow up in terms of technology, seems to be unable to wait any longer.

Of course, it doesn't seem to be "delayed". In fact, Google's actions are not slow.

But I don’t know why all the actions of LIN HUI seem to be pressing the fast forward button.
Chapter completed!