Time Travel: 2014

The first is the series of patents involved in Nanfeng APP.

Among the piles of information about Lin Hui collected from Lao Fu at that time, the one that surprised He Tianchang the most was the pile of patent applications.

When seeing Lin Hui’s complicated patent applications at home and abroad.

He Tianchang felt as if he was seeing a carefully woven web.

As for why we need to weave such a network, it is most likely to build patent barriers.

When he came to this conclusion, He Tianchang admired Lin Hui very much.

After all, it is rare to have such composure at the age of 18.

During this phone call, after He Tianchang brought up the matter, he got confirmation from Lin Hui.

After confirming his judgment.

He Tianchang couldn't help but admire Lin Hui even more.

Of course, He Tianchang knew that the reason why Lin Hui openly admitted this matter without any hesitation was because the barriers built by Lin Hui had been achieved.

He Tianchang has been paying attention to the status of forest ash patent applications.

Therefore, He Tianchang had already noticed the successful establishment of Lin Hui's patent barrier.

He Tianchang felt that if Lin Hui's plan had not been realized yet, He Tianchang would raise the issue even if the two of them had just met for the first time.

Lin Hui may not readily admit this.

Twenty years ago, He Tianchang might have been disgusted with this cautious and calculating character.

But now, He Tianchang admires this kind of character.

_There was a period when research seemed too hungry for progress.

Many technologies are introduced rashly without completing the construction of technical barriers.

Many technologies obviously have great commercial value, but due to lack of preparation, opponents often take advantage of them.

In the end, it was obviously gold inlaid with jade, but it could only be sold at a cabbage price.

It's heartbreaking.

During the exchange with Lin Hui, He Tianchang asked some questions about the generative text summary algorithm.

Of course, what He Tianchang is curious about is not the specific technology itself.

What he was curious about was Lin Hui's scientific research process.

How can a person like Lin Hui, who has not undergone systematic academic study, figure out the world's leading algorithm alone?

He Tianchang asked Lin Hui some general questions.

For example, how did Lin Hui obtain the corpus for language model training?

In fact, this is not the first time Lin Hui has heard this question.

Eve Carly had asked Lin Hui this question in her letter before.

But even if Lin Hui has never heard anyone ask this question before, there is no need to worry about being asked.

When it comes to generative text summarization algorithm patents, the most confusing thing for outsiders in this time and space is the corpus issue.

If you rush to come up with new results in text summarization without thinking in advance about how to explain the corpus issues involved in training the language model, you will easily suffer from various doubts.

Lin Hui had noticed this problem a long time ago.

Forewarned is forearmed, without prejudging the waste.

For this question, Lin Hui prepared at least three alternative answers.

Lin Hui told Professor He Tianchang the speech he had prepared earlier.

He Tianchang felt like he had a sudden enlightenment.

He couldn't help but sigh that the waves behind the Yangtze River pushed the waves ahead.

However, among the several methods mentioned by Lin Hui.

What is strange about He Tianchang is the method of automatically constructing a text corpus using the Internet:

When building a corpus using this method, the user only needs to provide the required text category system.

Then a large number of websites are collected from the Internet, and the content hierarchy of the website and the web content information corresponding to each keyword are extracted and analyzed.

Filter out the texts needed by users from each website as candidate corpus.

The formed corpus is then denoised.

In fact, this method was used. He Tianchang remembered that he had read some journals from foreign universities that seemed to have recorded research in this area.

But the foreign one failed because the collected corpus was too noisy and had too many stop words, making it unusable.

Why did Lin Hui propose this method?

Could it be that Lin Hui must have a unique understanding of the algorithms used for denoising.

In fact, He Tianchang is not very good at NLP or anything like that.

But it's not a big problem. He Tianchang has some old friends in China who are very good at this.

He Tianchang silently wrote this down.

Lin Hui gained a lot from the academic exchanges with He Tianchang.

First of all, through He Tianchang, Lin Hui learned about the domestic research situation in the cutting-edge direction of natural language processing.

What is the current status of domestic research in the direction of NLP?

A simple summary is "a blank sheet of paper"

Of course, the so-called blank paper here does not mean that it is completely blank.

It’s not that there aren’t people doing research on natural language processing in China, it’s just that the progress of these people’s research is roughly similar to that of international research.

In other words, the overall research progress is behind the previous research in 2014.

Under such circumstances, if Lin Hui wanted to be an academic porter, it seemed that he would be in a no-man's land.

The entire two directions of natural language processing and neural network learning are almost a blank sheet of paper in front of Lin Hui.

Waiting for Lin Hui to write a gorgeous chapter on it.

But even so, Lin Hui will not do everything when it comes to specific implementation.

All he needs is Lin Hui to make some key progress in a timely manner.

There is no need to be too greedy for success when it comes to progress in trivial aspects.

After all, academic achievements are not achieved overnight.

Anything that involves the simple theory behind generative summarization algorithms is super troublesome.

Although it is troublesome, the results are worth the hope.

Near the end of the call. Lin Hui thanked Professor He Tianchang several times for helping him apply for some support.

However, He Tianchang insisted that even if there are supportive policies in the future, Lin Hui will still deserve it.

That's what He Tianchang said, and He Tianchang thought the same in his heart.

Although He Tianchang's research direction does not involve natural language processing.

But this does not mean that He Tianchang knows nothing about the research direction involving natural language processing.

Stones from other mountains can be used to attack jade, and there is often a saying in scientific research that draws parallels with each other.

Many times, appropriately learning from research ideas in other industries can inspire your own research direction.

Therefore, even though the main direction of research is not natural language processing.

But this does not affect He Tianchang's focus on other research directions.

At least He Tianchang is very concerned about the progress made in some computers and computer derivatives.

In addition, the direction of natural language processing is relatively friendly and does not require a high threshold.

Therefore, He Tianchang is also involved in natural language processing.

As for what Lin Hui tinkered with.

Because I have recently gained knowledge about the generative summary algorithm and by chance, I participated in some academic conferences related to the generative summary algorithm.

Now He Tianchang still knows a lot about generative summary algorithms.

The importance of abstracts is self-evident.

The ability of summarization quite intuitively reflects people's ability to process information.

In the information age, whoever has stronger information processing capabilities will have information advantages.

While information may have established advantages, other areas may also have advantages.