Crossover: 2014

Chapter 245 Feedback from Professional Users (continued)
Without deep learning in the true sense, there is no artificial intelligence in the true sense.

In a way, deep learning is a subset of machine learning.

It is temporarily unrealistic to use artificial intelligence to promote multi-task progress in text summarization.

After all, Lin Hui still needs a period of time to carry out some deep learning theoretical infrastructure.

As for the present, if you want to achieve multi-task text summarization.

The only more feasible method can only be to use big data to adjust the news summary technology.

Through long-term training, the generative summary algorithm has the multitasking ability to handle news.

Why does training a generative summary algorithm involve big data?

In fact, algorithms are not castles in the air, and generally require long-term exploration in the practice of production and life.

The birth of an excellent model and algorithm is inseparable from continuous debugging and exploration.

Usually, debugging again and again is inseparable from the support of data.

The reason is usually the case.

It is because there will be exceptions in the model/algorithm debugging process that some big guys with super intuition participate in.

These big guys sometimes do not rely on data, but rely on intuition to micromanage to a state of high efficiency.

However, the importance of data cannot be denied.

The intuition of the boss should largely be the experience formed by processing data for a long time.

In short, data is quite important.

The core of big data is to use the value of data.

Reasonable use of big data and some research rules of big data in the process of algorithm adjustment can often get twice the result with half the effort.

A machine learning algorithm for natural language processing such as generative text summarization cannot achieve rapid development without the help of big data.

Although using big data to tune generative text summarization can only be said to be a simple application of big data.

But relying on big data to train and adjust the algorithm also takes time, and it cannot be done overnight.

Lin Hui estimated that according to the normal progress of scientific research.

It will take at least a month or two to use big data to develop a summary algorithm that can handle multi-tasking news.

Although there is a high probability that there is a ready-made algorithm that is perfectly capable of multi-tasking news summaries in Lin Hui's previous life information.

But Lin Hui thinks it is better to carry it scientifically.

In short, it is impossible to carry out the handling in the near future.

Lin Hui has made too much noise recently.

If you get involved in big data in a short period of time, there may be some problems.

Although even if Lin Hui carried it as usual, no one would necessarily question the level of Lin Hui's technology.

After all, Lin Hui is far ahead in terms of text summarization.

Many chasers may already be in a state of numbness that cannot find North.

Under such circumstances, even if Lin Hui made some moves, these people might not be able to catch up with Lin Hui.

But as the saying goes, there is nothing to see and nothing to hide, nothing to show and nothing to see, so a gentleman should be careful about his independence.

The opponent's numbness is not the reason for Lin Hui to act recklessly.

Some things only have the difference between 0 times and countless times.

A logical transfer that does not follow the normal sequence of technological evolution gave Lin Hui a taste of the sweetness.

Lin Hui cannot guarantee that he will not continue to abide by the laws of objective facts in the future.

After all, the temptation of frying fish in fish ponds is quite attractive.

But the price that comes with this kind of "coolness" is danger.

It is very dangerous to engage in wind and rain without observing objective laws.

Maybe one or two illogical moves won't attract attention.

But if things go on like this, it is inevitable that the car will not overturn.

I often walk by the river, how can I not wet my shoes.

To be on the safe side, it is better to follow objective logic.

Long-running water is king.

It's not good if you accidentally roll over.

In short, even if Lin Hui's enterprise-level hard drive in his previous life must have a well-tuned algorithm that is perfectly capable of multi-information processing.

Lin Hui didn't bother to carry out such an algorithm.

At least for a short time, Lin Hui didn't have such thoughts.

What Lin Hui has to do academically now is to cultivate in the direction of generative summarization algorithms.

Although the direction of generative summary algorithm seems to be not worth mentioning.

But behind it is the grand world of natural language processing.

Lin Hui believes that he can reach a very high academic level from this grand research field.

Not long ago, he was nominated for the second prize of the National Science and Technology Progress Award in this direction, which also shows the correctness of this direction.

In short, Lin Hui didn't doubt his choice of route at all.

Lin Hui had already thought about this a lot before.

Lin Hui didn't think he had missed anything.

Once again, Lin Hui has more information resources than others.

Lin Hui believed in the correctness of the direction he chose in making a decision based on this information.

……

……

When it comes to multitasking, although Lin Hui doesn't have a good solution right now.

Even so, facing the opinions put forward by Qiu Jiachun.

Lin Hui still said that he would make proper arrangements as soon as possible.

And arrange a reasonable and proper solution within two months.

After that, Lin Hui continued to ask Qiu Jiachun for advice, asking her if she had any other suggestions.

In addition to proposing multitasking, Qiu Jiachun also suggested to Lin Hui to develop a corresponding macOS version for the professional mode of Nanfeng APP.

Qiu Jiachun said that even the professional mode of Nanfeng APP is now very powerful.

But it is still very inconvenient to perform some corresponding operations on the Apple mobile phone at this time and only have a 4'' screen.

This is not a big problem, and Lin Hui readily agreed to Qiu Jiachun's feedback.

In fact, because Nanfeng APP is an offline software.

When processing data, it mainly relies on the computing power provided by the device itself.

Therefore, more advanced equipment can better play the software performance of Nanfeng APP.

In order to further improve the efficiency of Nanfeng APP, it will be a matter of time to adapt the software to a platform with more advanced computing power.

Previously, Lin Hui had planned to transplant the Nanfeng APP development to the macOS system.

However, due to the complexity of the matter, this matter has not been possible.

The development of macOS applications is actually not a very complicated thing.

Lin Hui used many macOS programs for self-entertainment in his previous life.

Although the current version of macOS is a bit retro, it should not be a big problem.

It doesn't matter if it's a little trouble.

More than 90% of the troubles in this world can be solved with money.

It is really impossible to buy some ready-made macOS programs with similar architecture.

Then directly replace the core algorithm inside.

There may still be some adjustments involved after this.

But the workload will be much smaller.

In addition to finding one that is compatible with macOS, it is not difficult to find a corresponding pad version that is compatible.

After all, the large iOS is running on the pad at this time.

When actually moving, Lin Hui only needs to pay attention to things like rendering resolution.

However, at this time, the efficiency of the Nanfeng APP on the iPad should not be any different than that on the mobile phone.

In Lin Hui's impression, Apple's tablet and mobile phone adopted a differentiated chip strategy only after the iPad Air 2.

(End of this chapter)