Reading as a god

Chapter 223 Private Jets
Although many people have many doubts about the development of artificial intelligence, Zhang Shan still thinks it is worthwhile to vigorously deploy artificial intelligence.

And without delay, now is the best time to enter the game.

Because from the industry information that Zhang Shan has learned now:
Because of the research on artificial neural networks, the technology related to machine learning has developed to a whole new stage.

Why do you say this way?
It’s a long story!

Speaking of research on artificial neural networks has a long history.

In 1943, Warren McCulloch and Walter Pitts created a computational model of neural networks based on mathematics and an algorithm called threshold logic.

This model makes the study of neural networks split into two different research ideas.

One focuses on biological processes in the brain, and the other focuses on the application of neural networks to artificial intelligence.

In the late 40s, psychologist Donald Hebb developed a hypothesis for learning based on the mechanism of neuroplasticity, now called Hebbian learning.

Hebbian learning is considered a typical unsupervised learning rule, and its later variants are early models of long-term reinforcement.

Beginning in 1948, researchers applied the idea of ​​this computational model to the Type B Turing machine.

In 1954, Farley and Wesley A. Clark first used a computer (then called a calculator) to simulate a Hebbian network at MIT.

Later, Frank Rosenblatt created the perceptron.

This is a pattern recognition algorithm that implements a two-layer computer learning network using simple addition and subtraction.

Rosenblatt also used mathematical notation to describe circuits not found in the basic perceptron, such as XOR circuits.

Such loops could not be handled by neural networks until Paul Webers (1975) created the backpropagation algorithm.

It seems that progress is good, but since then, the study of neural networks has stagnated.

Two key problems with neural networks were discovered.

The first is that basic perceptrons cannot handle XOR loops.

The second important problem is that computers do not have enough power to handle the long computation times required by large neural networks.

Research on neural networks progressed slowly until computers became more computationally powerful.

Until 1975, Paul Webers invented the backpropagation algorithm.

This algorithm effectively solves the XOR problem, and more generally the problem of training multilayer neural networks.

In the mid-80s, distributed parallel processing (then called connectionism) became popular.

The textbook by David Rumhart and James McClelland provides a comprehensive treatment of the application of connectionism to computer simulations of neural activity.

Neural networks have traditionally been considered a simplified model of neural activity in the brain, although the connection between this model and the physiological structure of the brain is controversial.

It is unclear how well artificial neural networks can reflect brain function.

After that, people's interest in artificial neural networks became negative.

In 2014, the residual neural network appeared, which greatly liberated the depth limit of the neural network, and the concept of deep learning appeared.

It can be said that deep learning has rekindled people's interest in neural networks.

This is also the opportunity mentioned by Zhang Shan.

Artificial neural networks and machine learning are closely related.

Machine learning is a branch of artificial intelligence.

The history of artificial intelligence research has a natural and clear vein from focusing on "reasoning", to focusing on "knowledge", and then focusing on "learning".

In the past 30 years, machine learning has developed into a multi-field interdisciplinary subject, involving probability theory, statistics, approximation theory, convex analysis, computational complexity theory and other disciplines.

Machine learning theory is mainly to design and analyze some algorithms that allow computers to "learn" automatically.

Machine learning algorithm is a kind of algorithm that automatically analyzes and obtains laws from data, and uses the laws to predict unknown data.

Because a large number of statistical theories are involved in learning algorithms, machine learning is particularly closely related to inferential statistics, also known as statistical learning theory.

In terms of algorithm design, machine learning theory focuses on achievable and effective learning algorithms.

Many inference problems are unprogrammable, so part of machine learning research is the development of tractable approximation algorithms.

Machine learning has been widely used in data mining, computer vision, natural language processing, biometric recognition, search engines, medical diagnosis, detection of credit card fraud, securities market analysis, DNA sequence sequencing, speech and handwriting recognition, strategy games and robotics.

In layman's terms, machine learning is a way to realize artificial intelligence, that is, to use machine learning as a means to solve problems in artificial intelligence.

Neural networks and machine learning are closely related.

According to this logical chain, it is not an exaggeration to say that the development of neural networks has made artificial intelligence popular again!
~~~~~~
After hearing Zhang Shan's idea, Gu Youyou also felt that it is not too much to devote more attention to the artificial neural network.

In the field of machine learning and cognitive science, artificial neural network is a mathematical model or computational model that imitates the structure and function of biological neural networks, and is used to estimate or approximate functions.

Although in the final analysis, the construction of neural networks is only a practical application of mathematical statistics methods.

Through the standard mathematical methods of statistics, we can obtain a large number of local structure spaces that can be expressed by functions.

But the value of artificial neural networks goes far beyond that.

The role played by artificial neural networks in the development of artificial intelligence is undoubtedly extremely important!
Like other machine learning methods, neural networks have been used to solve a wide variety of problems.

~~~~~~~~~
Objective technical advantages, these are external conditions~
As for the internal cause, it comes from Zhang Shan’s strong financial resources~
For Zhang Shan now, money is just a string of simple numbers.

Maslow (1943) stated that people need motivation to fulfill certain needs and that some needs take precedence over others.

Maslow's Hierarchy of Needs is a theory of motivation in psychology that includes a five-level model of human needs, often depicted as levels within a pyramid.

From the bottom of the hierarchy upwards, the needs are: physiological (food and clothing), safety (job security), social needs (friendship), esteem, and self-actualization.This five-stage model can be divided into deficiency needs and growth needs.The first four levels are often referred to as defect requirements (D requirements), while the highest level is known as growth requirements (B requirements).

But now Zhang Shan obviously cares more about respect and self-realization.

So instead of letting this money sit coldly in a bank account, it is better to let this money play some social role.

Hearing that Zhang Shan initially planned to hit [-] small goals in the field of artificial intelligence, even Gu Youyou was a little uneasy~
Uh, although Gu Youyou's family business is quite large, according to her superficial understanding~
I feel that the total revenue of all the companies under Zhang Shan is only less than [-] million per year~
This?
Although knowing that Zhang Shan, a person like his father, has a capital chain, it is definitely not just the size of the company on the surface.

But is it okay to take out 20 billion at once?
Among other things, how will Zhang Shan explain the source of funds.

Zhang Shan had thought about it a long time ago. It may be troublesome to conceal the source of funds when he has no money, but it is completely easy to do when he has money.

To put it simply, sell, sell, sell, and it's over~
In the process of continuous upgrading after he applied the [Crazy Promotion Card]:

In terms of fixed assets, he has harvested 88 villas, 4 courtyard houses and [-] office buildings.

In addition to these fixed assets, Zhang Shan also received about 10 billion yuan worth of soft sister coins.

sell house, sell stock~
There is no need to really sell all of them, after all, just put on a show and stop some messy criticisms.

After all, Zhang Shan is not short of money.

In addition to stocks, the system also gave Zhang Shan more than 80 billion yuan in cash (temporarily stored by the system).

In addition to the funds in Zhang Shan's hands before the upgrade, Zhang Shan's current cash flow is as high as 100 billion yuan~
But there are some things that Zhang Shan really wants to sell.

It is the property that the system gave to Zhang Shan before~
According to the saying after level [-], everything including the Bauhinia Bookstore and 彡wood Bread Workshop have become free-category industries.

Instead of foolishly distinguishing [industries donated by the system] and [industries donated by the system for public welfare].

Since then, all the income of the enterprise obtained by Zhang Shan from the system and the corresponding physical stores are all controlled by Zhang Shan himself.

Then sell them all~
~~~
Beyond investing in AI.

Speaking of the dream after owning tens of billions of wealth~
Zhang Shan thinks it is necessary to arrange a private jet!
Tsk, isn't it every man's dream to fly fast!
A business jet is a jet airliner used to transport private individuals, corporate personnel and government officials.

Unlike airlines that sell tickets to individual passengers, business jets that are privately owned are known as private jets.

But it can't be too absolute. If this kind of aircraft is purchased by a company, it is called a corporate jet.

In addition to the above-mentioned operating forms, there are also specialized operators that specialize in business jet rental services; renting business jets from these companies can also be called charter flights
In "The Great Gatsby", Leonardo DiCaprio drove the bright yellow 1929 Dowsenberg through Long Island, New York, and it was no accident that he stole all the limelight. The struggle at the bottom requires nothing more than attention at this moment.

This seems to be the same reason that rich people like to own their own private jets. Which boy has not imagined that the moment he walks down the private gangway in a three-piece suit, he gets the same reaction as Gatsby?

This may be the reason why airplanes have been the "standard equipment" for the top rich since they were invented by the Wright Brothers in 1903.

And Chinese wealthy people, who never lag behind the rest of the world, quickly joined the hobby of this new mechanical toy.

Marshal Zhang xl owns the first private jet in China. He owned his first private jet in the 20s - the German Junkers F.13. At that time, Fitzgerald's " The Great Gatsby has only just come out.

As for the private jet, Zhang Shan preferred the Gulfstream G650.

After all, Zhang Shan’s first car was a Mercedes-Benz G65, and Zhang Shan felt that his first airplane should also be a G650.

Although somewhat far-fetched, Gulfstream's achievements in the field of private jets are obvious to all.

湾流航太于2005年5月开展G650公务机的研制计划，2008年3月13日首次向公众披露。

And said at the media conference that this is the largest, fastest and most expensive private jet of Gulfstream Aerospace.

The G650 can cruise at high speeds of Mach 0.85 to Mach 0.9, and its maximum speed can reach Mach 0.925, making it the leader among aircraft in its class.

The maximum flight distance is 13 kilometers, which means that you can fly non-stop from Chicago to Shanghai, from Los Angeles to Sydney, or from New York to Dubai without needing to land and refuel on the way.

The aircraft is equipped with a separate galley, but also can choose a variety of entertainment facilities, such as satellite phone and wireless network.

其引擎采用由劳斯莱斯股份有限公司提供的BR725A1-12发动机，能产生17，000磅的推力。

Gulfstream Aerospace said that the weight of the aircraft is only 45 tons, which allows the aircraft to avoid busy large airports and land at small airports to save customers time.

In order to make the interior space more abundant, Gulfstream Aerospace has designed the fuselage section of the G650 as an ellipse instead of the traditional circle.The cabin is about 2.59 meters wide and 1.96 meters high, with 16 portholes on both sides.The cabin is made of metal, while the empennage, winglets, rear pressure bulkhead, engine fairing, and cabin floor structure are largely made of composite materials.

The G650 completely adopts fly-by-wire flight control, so there is no mechanical control structure between the cockpit, the wings and the tail, and each moving part of the fuselage is controlled by two sets of independent hydraulic systems.Nowadays, more and more aircraft are beginning to adopt wire-by-wire flight control, but only the Dassault Falcon 7X is equipped with the same equipment. The G650 and G550 share the same joystick.

The G650's wing design was completed back in 2006 and passed 1400 hours of wind tunnel testing, which lasted until 2008.The cabin has also passed the air pressure test and can withstand a maximum pressure equivalent to 18.37 standard barometric pressure.

The reason why we did not choose the latest one in recent years is because this aircraft is relatively stable.

It has been several years since the test flight.

(The first test flight is planned for the second half of 2009.

2009年9月26日，G650第一次用自己的动力开始滑行，并于29日向公众展示实机。2009年11月25日进行了处女航。）
It’s a pity that this kind of aircraft is still subsonic~
On May 2010, 5, the test result reached a maximum speed of Mach 4. On August 0.925 of the same year, Gulfstream Aerospace submitted a report stating that in an 8-hour endurance test, the pilot let the nose of the aircraft dive down and The end result is a top speed of Mach 26.

Although almost all airliners are currently subsonic, Zhang Shan is still not happy.

After all, human beings’ pursuit of speed is endless.
(some exceptions)
(End of this chapter)