Crossover: 2014

Chapter 244 Feedback from Professional Users

Chapter 244 Feedback from Professional Users

The Nanfeng APP has been online for a while, and many copies of the professional model have been sold.

But Lin Hui remembers that when Nanfeng APP was first launched, it was actually very hasty.

At that time, Lin Hui only conducted a general market research, but did not conduct market research too deeply.

Even the pricing of the professional model is largely based on Yahoo.

Even after Lin Hui officially launched the Nanfeng APP, he did not pay less attention to the users who commented on the Nanfeng APP.

Because it adopted the comments of users in the Nanfeng APP comment area.

Based on the Nanfeng APP, Lin Hui created a professional model that is more in line with the habits of professionals.

In this version, Lin Hui canceled the input limit of [-] characters for a single Chinese character news in professional mode.

But this is still not enough.

Lin Hui also needs to listen to professional feedback from professionals.

After all, only professionals know what they really need.

There are such excellent reporters sent to our door.

Moreover, before the interview, Lin Hui also noticed that among the reporters interviewing Lin Hui this time, there were also reporters who specialized in text editing.

How could Lin Hui miss such an opportunity.

Through some conversations, Lin Hui learned that the text editor who accompanied Hu Xin this time was named Qiu Jiachun.

A shy-looking girl who looks younger than Hu Xin, probably in her 20s.

Although it looks a little shy, it is a journalist after all.

When Lin Hui asked her for advice, she still expressed her opinion.

She suggested that Lin Hui introduce the ability to process multiple news items in professional mode.

To be honest, this is not the first time Lin Hui has received this suggestion.

Lin Hui has heard more than one user's suggestion in this regard before.

At that time, Lin Hui saw in the comment area of ​​Nanfeng APP that many people suggested that developers add the function of processing multiple news items.

But Lin Hui remembers that there were big differences among the people in the comment area on whether to have multiple news processing functions, and there were even fights in the air.

Proponents argue that multitasking improves productivity;
Opponents argue that multitasking can be distracting and interfere with concentration at work.

At that time, the comment area of ​​the software was very torn, and it was limited by technical problems.

Lin Hui's original approach was to choose to maintain the status quo of this controversial point.

After all, there is no need to fuss about multitasking. Even if you want to engage in professional mode, Lin Hui's workload is much less.

Originally, I thought this matter would be over, but I didn't expect that now I actually got in touch with the excellent customer that Lin Hui talked about.

The first suggestion I heard was to add multitasking.

This is more embarrassing.

However, with Lin Hui's character of either not doing it or doing it perfectly, it is impossible to evade it lightly.

Now that Lin Hui asked the question, it is necessary to find out why those reporters who are mainly engaged in text editing work need to multitask.

According to Qiu Jiachun, when a copy editor deals with original news manuscripts, he often does not just deal with one person's interview materials.

Instead, we need to deal with a lot of news of the same kind.

For example, a youth competition event.

When interviewing at an event, many different contestants are often interviewed.

In actual processing, the speeches of these contestants must be processed separately.

This process often takes a long time if the summary does not have a multi-tasking mechanism.

Therefore, Qiu Jiachun suggested to Lin Hui to add the function of multitasking.

As for the differences among users on whether to increase the multitasking mode.

Qiu Jiachun felt that if Lin Hui had a hard time making a choice about this matter.

Might as well simply leave the decision-making power to the user.

Open the multitasking mode switch in the professional mode of Nanfeng APP.

Users who think that multitasking affects concentration can choose not to turn on the corresponding multitasking mode.

Users who have needs for multitasking can choose to turn on the corresponding multitasking mode.

He listened carefully to Qiu Jiachun's appeal.

Lin Hui learned that Qiu Jiachun's demands basically revolved around multitasking.

In fact, it is not troublesome to introduce multitasking in Nanfeng APP.

Even Lin Hui can make the Nanfeng APP more efficient than Qiu Jiachun imagined.

But in many cases, the development of technology cannot ignore the impact on society.

A technology that really advances by leaps and bounds overnight will bring about many social problems.

For example, if the news digest software is really efficient overnight, it will increase hundreds of times and thousands of times.

Those purely literary journalists like Qiu Jiachun are likely to lose their jobs in place.

In addition, if a lot of forest ash is to be transported out, the rationality of the transport must be considered after all.

In terms of the long-term development of generative text summarization algorithms, Lin Hui has made relatively long-term plans and put them into practical actions.

But these are still not enough.

Even if the technology is advanced for a while, once it stands still, it will eventually be overtaken by the following opponents.

In short, be prepared for danger in times of peace.

Relying on the patents declared by Lin Hui himself and acquired.

Lin Hui has already taken the lead in the world text summarization.

Even if Lin Hui takes the lead, it can only reasonably develop (reasonably move) the generative text summarization technology to the fifth generation.

Only the fifth-generation generative text summarization technology still has limitations in many application scenarios.

Take news/text summarization multitasking for example.

The fifth generation of generative text summarization is not well qualified for this application.

In fact, it is not only the fifth-generation generative text summarization algorithm that is troublesome to deal with multi-task news summaries.

It is not easy for the subsequent generative summarization algorithm to deal with multi-task news summaries.

It is almost impossible to achieve multi-tasking news processing by relying on purely generative text summarization algorithms.

Even in the field of technology, it is rare for a trick to be eaten all over the world.

If you want to achieve efficient processing of news multitasking.

Maybe we have to wait until artificial intelligence matures.

The maturity of artificial intelligence will drive many fields that have encountered bottlenecks to take off.

This includes the aspect of text summarization.

When artificial intelligence matures, natural language processing projects like text summarization will not only generate new possibilities.

Moreover, the cost required by users in the field of natural language processing will also drop rapidly.

The future is bright, but the road is tortuous.

The realization of this rosy prospect is obviously still a long time away.

Especially in this time and space, the progress of many machine learning in this field is not as rapid as that of the previous life.

Now there is no concept of machine learning, but deep learning is still far behind.

(End of this chapter)

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