Does Greater Paris need to be rebuilt after losing to Bayern in the Champions League?

Giants are not necessarily strong teams, and superstars together may not be able to make a strong team. Greater Paris once again pays for its own giants lineup.

Striker Trident’s strength makes the lineup top-heavy, extremely unbalanced, old and weak. Once Meme’s connection is cut off, the lifeblood of the big Paris attack will be cut off. If you really want to win the Champions League by building a giant, you must be world-class in every position like Real Madrid, and the lineup is balanced. The coach can completely control the locker room, and everyone has defensive responsibility and offensive desire.

After the exit from the Champions League, Obape may be determined to leave the team, because he knows that he may never win the Champions League in Paris, and it is difficult to win the Golden Globe Award. Neymar is a lesson from the past. He was called Messi’s successor when he left Barcelona, but he never entered the top three of the Golden Globe Award after leaving Barcelona, and now he has become mediocre. Mbappé doesn’t have much youth to waste, and the next world may reach its peak, but there is no future in Bali, and Real Madrid doesn’t know whether to take him or not.

Messi may win a Golden Globe with last year’s World Cup champion, but he is embarrassed about where to go. He definitely wants to stay in Europe and play for a strong team, but which club is willing to offer such a high salary and risk destroying the salary structure of the dressing room, Manchester City? Barcelona? Or anything else, it may not be possible.

After the Grand Paris Consortium took office, it spent a total of 1.484 billion euros on the transfer every season, but it didn’t bring a Champions League, which was a failure. Although the Qatar Consortium was not short of money, it couldn’t stand such a toss-up, and the reconstruction of Grand Paris seemed inevitable.

ChatGPT’s Enlightenment to Future Battlefield Intelligence Perception and Decision-making

Author: Liu Xinyu

The combination of artificial intelligence technology and unmanned aerial vehicle will greatly change the existing theory and mode of military operations. The power of artificial intelligence plays a role at all levels of the national defense industry, and the rapid development of artificial intelligence will define the next generation of war. Recently, ChatGPT, a generative artificial intelligence technology developed by OpenAI, has been paid attention to and used all over the world. ChatGPT is a large-scale generative pre-training language model based on transformer. It can train in existing data sets and generate texts similar to human language. This unique ability makes it an ideal tool for military applications. The underlying natural language model and technology that provides power for ChatGPT may completely change the artificial intelligence on the battlefield and have a great impact on the situation awareness and independent decision-making methods in future wars.

Intelligent situational awareness in the whole information domain

In the future military field, there will be a battlefield environment with complex information, high confrontation and changeable tasks. The highly uncertain combat environment puts forward extremely high requirements for the independent perception and cognitive ability of combat equipment. Military equipment needs to have the ability of automatic target detection and identification and multi-sensor data fusion. It can detect and fuse enemy target information and its own support information through autonomous and receiving information acquisition methods, and perceive the battlefield situation and extract important information for subsequent decision-making on the basis of obtaining full information domain.

Based on the demand for intelligent situational awareness, the generative artificial intelligence technology ChatGPT can be integrated into military vehicles, aircraft and other combat systems. With the application of artificial intelligence language robots trained by a large number of models, the required real-time information can be effectively coordinated in a multi-domain environment, and the input data from various sensors can be analyzed to generate a complete, comprehensive and real-time updated operational environment map.

Intelligent technology can play a key role in future military operations. Generative artificial intelligence technology can rely on its strong creativity, understanding and response speed to obtain cross-domain intelligence and battlefield situation data, improve the ability of insight into intelligence, form a highly simulated situation scene, realize dialogue between people and battlefield environment, provide real-time information and situation prediction, enhance the real-time and decision-making of battlefield situation perception, and better support real-time decision-making in military operations.

Real-time and efficient intelligent independent decision-making ability

At present, the autonomous decision-making ability of aircraft has been initially characterized by intelligence and independence. The US Air Force uses artificial intelligence "decision-making assistant tools" in distributed common ground system (DCGS) to help sort out and integrate a large amount of data. This artificial intelligence system connects most airborne intelligence and monitoring and reconnaissance platforms of the US Air Force, and integrates artificial intelligence technology into training to expand into other fields.

If the generative artificial intelligence technology ChatGPT is introduced into the decision-making method of aircraft, it can provide real-time information about enemy positions, movements and capabilities, as well as the advantages and disadvantages of friendly forces in tactical situations based on the prior information database and real-time signal, data and image databases, and at the same time based on the real-time interaction between aircraft and environment, so as to analyze, reason and make decisions, and realize rapid response to battlefield decision-making.

The generative artificial intelligence robot can generate multiple sets of operational plans in a short time when the aircraft is faced with complex and uncertain operational conditions, and preview the battlefield process and results for each set of plans, so as to generate real-time optimal decisions in the face of complex requirements in terms of information acquisition, reaction time, calculation speed, tactical evolution and comprehensive evaluation, and support decision makers with diversified decision plans and deduction results.

Real-time and efficient intelligent autonomous decision-making method can cover the complex situation in real combat environment, play a similar role to human brain in high uncertainty environment, dynamically adjust attack and protection strategies according to real-time situation awareness and operational effectiveness evaluation, and realize efficient confrontation through closed loop of process.

Enlightenment and prospect of intelligent military

Generative artificial intelligence technology breaks the logic of time series calculation, and makes artificial intelligence in multiple sub-fields begin to merge technically. As a new technology in the field of artificial intelligence, deploying ChatGPT in military operations may enhance cross-domain combat capability and realize situational awareness and real-time independent decision-making in all information domains. In the future battlefield, if we can deploy the top-level layout and bottom-level algorithm of generative artificial intelligence with the guidance of military operations and equipment development, with its ability of understanding, responding and interacting with people, we can greatly improve the cognitive and decision-making methods in the battlefield, promote the technical upgrading in key areas, and realize the optimization iteration of combat capability.

From the point of view of data and subsequent development, generative artificial intelligence technology is a more advanced neural network deep learning algorithm, which has high requirements for training data, depends on the authenticity of training data and is easily disturbed by external information. Because of the long training time and billions of parameters, automatic machine learning is needed for multiple lines to generate better calculation results. Therefore, when transforming the technological achievements of generative artificial intelligence, it is necessary to take into account the parameterization requirements of scientific research technology development and the automation requirements of equipment application development, so as to achieve the balance between scientific research liquidity and industrial productization.

Generative artificial intelligence has brought a new paradigm to military applications and set a new route for the next generation of military operations. It is the main problem to apply generative artificial intelligence technology to the military field to actively explore the representation form of situation awareness and decision-making tasks for different military problems and consider how to use effective information for large-scale pre-training. The combination of artificial intelligence technology and military operations and technological innovation will reserve new ways for situation awareness and independent decision-making in future operations, and realize intelligent support for the development of new military equipment.

[Decoding Chatgpt] Yang Qingfeng | Chatgpt: Characteristic Analysis and Ethical Investigation

Since November 2022, ChatGPT, a chat robot developed by American artificial intelligence research company OpenAI, has quickly become the fastest-growing consumer-grade application in history, attracting widespread attention. The emergence of ChatGPT has become the tipping point of the development of artificial intelligence, which has promoted the competition of scientific and technological innovation in various countries to enter a new track. The leap of technology will inevitably lead to in-depth observation in application scenarios. No matter how smart artificial intelligence services become, adapting to and meeting the needs of human development is always the fundamental direction. Facing the future, discussing ChatGPT’s important influence on people’s mode of production, lifestyle, way of thinking, behavior mode, values, industrial revolution and academic research will help us to use and manage this technology correctly and then think about the development prospect of artificial intelligence.

Hegel mentioned the concept of bubble burst in the Ethical System, which meant that the process of destruction was like an expanding bubble bursting into countless tiny water droplets. If we look at the development of artificial intelligence technology with this concept, we will find that it is more consistent. After the artificial intelligence bubble burst in 1956, it became many tiny water droplets and splashed everywhere. There are AlphaGo and so on in chess; There are AlphaFold and so on in scientific research; Language dialogue includes LaMDA, ChatGPT, etc. Image generation includes Discord, Midjourney and so on. These technologies have gradually converged into a force, which has involved mankind in an era of intelligent generation.

ChatGPT: generating and embedding

Generation constitutes the first feature of ChatGPT, which means innovation, but this is questioned. Chomsky believes that ChatGPT discovers rules from massive data, and then connects the data according to the rules to form similar content written by people, and thinks that ChatGPT is a plagiarism tool. This view is somewhat inaccurate. In the process of ChatGPT generation, something new is produced. However, this is not new in the sense of existence, that is to say, it does not produce new objects, but finds unseen objects from old things through attention mechanism. In this sense, it belongs to the new in the sense of attention. In 2017, a paper entitled "Attention is All You Need" proposed transformer based on the concept of attention, and later ChatGPT used this algorithm. This technology uses self-attention, multi-head-attention and other mechanisms to ensure the emergence of new content. Moreover, ChatGPT may also generate text by reasoning, and the results can not be summarized by plagiarism.

Embedding constitutes the second feature of ChatGPT, and we can regard the embedding process as enriching some form of content. The development of intelligent technology is divorced from the track of traditional technology development. Traditional technology is often regarded as a single technical article, and its development presents a linear evolution model. However, the development of intelligent technology gradually shows embeddability. For example, as a platform, smart phones can be embedded with many apps. ChatGPT can be embedded in search engines and various applications (such as various word processing software). This kind of embedding can obviously improve the ability of agents. This is the basis of ChatGPT enhancement effect. According to Statista’s statistics, as of January 2023, OpenAI has been closely integrated with science and technology, education, commerce, manufacturing and other industries, and the trend of technology embedding is becoming increasingly obvious. The degree of embedding affects the friendliness of the robot. At present, ChatGPT can’t be embedded in the robot as a sound program. In our contact, it is more like a pen pal. In the future, companion robots and talking robots may be more important, such as voice communication, human talking, machine listening and responding.

ChatGPT’s black box status

For ChatGPT, transparency is a big problem. From a technical point of view, opacity stems from the unexplained problem of technology. Therefore, technical experts attach great importance to the interpretability of ChatGPT, and they also have a headache about the black box effect of neural network. In terms of operation mode, the operation of ChatGPT itself is difficult to explain. Stuart Russell clearly pointed out that we don’t know the working principle and mechanism of ChatGPT. Moreover, he doesn’t think that the large-scale language model brings us closer to real intelligence, and the interpretability of the algorithm constitutes a bottleneck problem. In order to solve this problem, they can observe the mechanism of neural network and touch the underlying logic through some technical methods such as reverse engineering. And through the mechanical interpretable method, the results are displayed in its visual and interactive form. With the help of these methods, they opened the black box of neural network. However, the interpretability obtained by this method is only effective for professional and technical personnel.

From a philosophical point of view, the emergence of black box is related to terminology. Difficult and obscure terms will affect the acquisition of theoretical transparency. For example, the theoretical concepts on which ChatGPT algorithm depends need to be clarified. In the article "Attention is All You Need", attention mechanism is a common method, which includes self-attention and multi-attention If these concepts are not effectively clarified, it will be difficult for outsiders to understand, and the black box will still not be opened. Therefore, one of the most basic problems is to clarify attention itself. However, this task is far from complete. Ethical problems caused by lack of transparency will bring about a crisis of trust. If the principle of ChatGPT is difficult to understand, its output will become a problem. In the end, this defect will affect our trust in technology and even lose confidence in technology.

Enhancement effect of ChatGPT

ChatGPT is an intelligent enhancement technology. What it can do is to intelligently generate all kinds of texts. For example, generate an outline of data ethics and generate the research status of a frontier issue. This obviously enhances the search ability and enables people to obtain higher efficiency in a short time. This enhancement is based on generativeness and embeddedness. From the generative point of view, it realizes the discovery of brand-new objects through the transformation of attention; In terms of embeddedness, it greatly improves the function realization of the original agent.

As an intelligent technology, ChatGPT can obviously improve the work efficiency of human beings. This brings out a basic problem: the relationship between human beings and agents. We divide intelligence into substantive intelligence and relational intelligence. Entity intelligence, that is, the intelligence possessed by entities, such as human intelligence, animal intelligence and entity robot intelligence; Relational intelligence is mainly used to describe the relationship between human beings and agents, and augmented intelligence is the main form of relational intelligence. It is necessary to purify the enhanced intelligence, make it show the general significance of people and technology through philosophical treatment, and make it have normative significance through moral treatment.

However, ChatGPT, which can enhance the effect, will cause some ethical problems. The first is the problem of intelligence gap. At present, this technology is limited, and there is a certain technical threshold, which will lead to the widening gap among users, that is, the gap caused by intelligent technology. This is the gap and gap arising from the acquisition of technology. The second is the issue of social equity. Unless this technology can be as popular as mobile phones, this fairness problem will be exposed very significantly. People who can use ChatGPT to work are likely to improve their efficiency significantly; Those who can’t use this technology will keep their efficiency at the original level. The third is the problem of dependence. Users will feel the convenience of this technology during use. For example, it can quickly generate a curriculum outline, write a literature review, and search for key information. This will make users gradually rely on this technology. But this dependence will have more serious consequences. Taking searching literature as an example, with the help of this technology, we can quickly find relevant literature and write a decent summary text. Although ChatGPT can quickly generate a literature review, it has lost the academic training of related abilities, so the result may be that researchers and students have lost their abilities in this field.

The relationship between ChatGPT and human beings

In the face of the rapid offensive of ChatGPT, academic circles generally take a defensive stance, especially many universities have banned the use of this technology in homework and thesis writing. However, prohibition is not the best way to deal with it. Technology is like water, which can be infiltrated in many ways, so relatively speaking, rational guidance is more appropriate.

To guide rationally, we need to consider the relationship between agents and human beings. I prefer to compare the relationship model between the two to "make the finishing point". Taking the generation of text outline as an example, ChatGPT can generate a data ethics outline based on data processing links around related ethical issues in data processing, such as collection, storage and use. In a narrow sense, this outline is appropriate and can reflect some aspects of ethical issues in data processing. However, from a broad point of view, this outline is too narrow, especially only from the data processing itself to understand data, without considering other aspects, such as dataization, data and lifestyle. What we can do or want to do is to make the finishing touch on the generated text and make it "live" through adjustment. In this way, the position of intelligently generated text has also begun to be clear: it is the finishing touch of human beings that plays a key role in the generation. Without this pen, the intelligently generated text is just a text without soul. If not, it will be difficult to guarantee the meaning and value of human beings, and the corresponding ethical problems will also arise.

How much did Zhu Ting actually get when he started his Italian league career with an annual salary of 1.2 million? Numbers are touching.

Of course, this is not all the expenses that Zhu Ting needs to deduct. Zhu Ting also needs to pay 1.5%-3% of the agent fees and some miscellaneous expenses of the players’ union. Moreover, because of the talent cultivation, Zhu Ting also needs to pay part of the salary to the Henan mother team. After a full calculation, Zhu Ting’s 1.2 million euros will actually be deducted by nearly 50%, which means that Zhu Ting actually gets 600,000 euros (equivalent to about RMB 4.2 million). But now Zhu Ting obviously doesn’t care about this. To tell the truth, if she wants to make money, Zhu Ting will stay in China. Her annual salary is at least over $1 million, and her income is more than that of studying abroad. Moreover, at home, Zhu Ting has more time to attend business activities, which is also a large amount of income. But for 28-year-old Zhu Ting, she deserves her last chance to fight for her dream. Zhu Ting also knows that if she wants to lead the China women’s volleyball team out of the trough, she must become.