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ChatGPT is hot out of the circle？ Wait, the pig farm also has black technology.

Recently, ChatGPT has been popular. Before that, Wang Huiwen, the co-founder of Meituan, released the AI ? ? hero list, announced that he would pay for himself, and set up Beijing Lightyear Technology Co., Ltd. to confirm his entry. Later, there was an extreme dialogue between programmers from big factories and ChatGPT. From emotional consultation, project management to novel creation, ChatGPT was almost omnipotent and omnipotent (PS, Xiaobian was trembling with fear).

Behind the explosion of ChatGPT is everyone’s embarrassment and concern for the field of artificial intelligence. So is there any application of artificial intelligence technology in the field of pig breeding? How do they combine?

The Origin and Development of Artificial Intelligence Technology

Artificial intelligence technology is a branch of computer science. The original intention of its creation is that scientists hope that computers can imitate human intelligence, so that machines can handle complex things.

Artificial intelligence can be traced back to 1950, and Allen Matheson Turing put forward the famous "Turing Test" [which refers to asking questions to the testee through some devices (such as keyboards) when the testee is separated from the testee (a person and a machine). After many tests, if the machine makes the average participant make more than 30% misjudgment, then the machine has passed the test and is considered to have human intelligence.

In the same year, he published the paper "Computing Machine and Intelligence", and put forward and tried to answer the question "Can a machine think?". After the paper was published, it received extensive attention and discussion, and Turing was later called "the father of artificial intelligence".

In 1956, John McCarthy (computer scientist and cognitive scientist), an assistant professor in the Department of Mathematics at Dartmouth College, located in the small town of Hannos in the eastern United States, invited a group of big coffee scholars including Marvin Minsky (winner of Turing Prize in 1969) and Claude Shannon (founder of information theory) to hold an academic conference. The conference mainly discussed topics such as machine imitating human intelligence, including: how to program computers, neural networks, calculation scale theory, mechanical theory (referring to self-learning), randomness and creativity.

Dartmouth Conference has been held for more than two months. Although the participants did not reach an agreement, they agreed on a word for the discussion: Artificial Intelligence (AI). At this point, the word artificial intelligence began to appear in people’s field of vision, and 1956 was also called the first year of artificial intelligence. After that, the theoretical research and practical application in the field of artificial intelligence continued to break through (see the development history of AI for details).

(Image from Demeo Consulting Wang Wei)

Before ChatGPT, the last time artificial intelligence was widely concerned was in May 2017, when Alphago defeated Li Shishi, the world Go champion, by a score of 4: 1, and will face Ke Jie, a player from China, at the world internet conference in Wuzhen. You know, after Li’s defeat in artificial intelligence, Ke Jie made a statement in the media: Even if Alpha Dog beats Li Shishi, it can’t beat me.

Before the start of the competition, Ke Jie had high hopes and was once regarded as "the last hope of mankind". However, the reality is cruel. Alphago(Master) beat Ke Jie, a talented teenager in China, with a score of 3: 0.

After the on-site interview, Ke Jie once choked:Playing chess with AlphaGo is too painful, AlphaGo is too calm, it is too perfect, and I can’t see any hope of victory.. So why is "artificial intelligence" technology so powerful?

Analysis of artificial intelligence technology

Artificial intelligence mainly includes five core technologies, namely computer vision, machine learning, natural language processing, robotics and biometrics.

Computer vision is a science that studies how to make machines "see", which means that cameras and computers are used to identify, track and measure targets instead of human eyes, and further graphic processing is carried out, so that computers can be processed into images that are more suitable for human eyes to observe or send to instruments for detection.

Machine learning is the core of artificial intelligence technology, which enables intelligent machines to simulate human behavior independently with the support of algorithm complexity theory, convex analysis, statistics and other disciplines. Machine learning refers to how to improve the performance of specific algorithms in empirical learning, that is to say, machine learning is based on massive data or past experience to optimize the performance standards of computer programs.

To put it simply, this process is similar to personal self-reflection, which is to review past experiences and then adjust the optimization behavior so as to do better next time. But different from personal reflection, personal reflection has limited sources of experience, while machine learning is based on a huge database given by developers, with wider sources of experience and data and more timely feedback based on goals.

Natural Language Processing (NLP) is a variety of theories and methods to study how to achieve effective communication between people and computers in natural language. Natural language processing is a science integrating linguistics, computer science and mathematics, which can be mainly applied to machine translation, public opinion monitoring, automatic summarization, viewpoint extraction, text classification, question answering and so on.

Robot refers to performing tasks such as working or moving through programming and automatic control. Robots have the basic characteristics of perception, decision-making, execution, etc., which can assist or even replace human beings to complete dangerous, heavy and complicated work and improve work efficiency and quality. At present, sweeping robots have entered the daily life of the public.

Biometric technology is closely combined with high-tech means such as optics, acoustics, biosensors and biostatistics through computers, and uses the inherent physiological characteristics (such as fingerprints, faces, irises, etc.) and behavioral characteristics (such as handwriting, voice, gait, etc.) of human bodies/creatures to identify their identities, such as "face recognition" and "pig face recognition".

Therefore, artificial intelligence can be understood as imitating human information input (images, words, sounds, etc.), information processing (based on the correct thinking model in the past) and then action execution, and constantly strengthening various abilities in the process to achieve the set goals and continue to improve. The core of artificial intelligence lies in deep learning, that is, continuous feedback and continuous optimization based on strategy.

The mechanism of deep learning is similar to the deliberate practice learning method proposed by Florida psychologist Anders Millard J. Erickson. Anders pointed out that the key factor to distinguish a person’s mediocrity and Excellence in the professional field is the degree of deliberate practice. The longer the deliberate practice, the higher the professional level. Deliberate exercises mainly include four elements:Clear goals, staying away from the comfort zone, concentration and timely feedback.. Different from human deliberate practice, the deliberate practice process of the machine has no emotion, so it is more efficient to execute.

Just a few months after Alphago(Master) defeated Ke Jie, in October of 17, DeepMind team published a new paper in Nature magazine, and launched a new generation of product AlphaGo( Zero). The paper points out that Alphago(Zero) reached the level of Alphago(Master) in only 21 days, and when Alphago(Zero) played the 40th day, it had already defeated all previous programs and won the world Go championship.

Afterwards, the industry put forward three cores for Alphago to quickly reach the top level in the world: first, it adopted a learning algorithm combining machine learning and neuroscience; Second, in Google’s powerful cloud computing system, more than 30 million steps of professional chess player’s chess manual have been learned through a large amount of data analysis; Third, throughThe ever-increasing self-gameFind a better idea than the basic chess manual. Artificial intelligence technology is created by human beings, and the achievements in some aspects are far beyond human beings, which may also be worth thinking and learning.

Application of artificial intelligence technology in pig farm

The combination of artificial intelligence technology and agriculture can be traced back to March 2015. Li Keqiang, then Premier of the State Council, put forward the action plan of "internet plus" for the first time in his government work report; In July of the same year, the State Council issued the Action Plan on Actively Promoting the internet plus (hereinafter referred to as the Action Plan).

The Action Plan clearly puts forward to actively promote the modern agriculture in internet plus, and points out that it is necessary to establish standardized scale livestock and poultry breeding bases and aquatic healthy breeding demonstration bases,Promote the popularization and interconnection of intelligent devices such as accurate feed delivery, automatic disease diagnosis and automatic waste recycling.. The release of Action Plan opened the historical curtain of agriculture in internet plus.

After that, AI technology, like other emerging Internet technologies, was gradually applied to the practice of agricultural industry. On the one hand, new cutting-edge technology, on the other hand, traditional agriculture, how do they combine? What kind of sparks will break out?

Scenario 1: Pig farm monitoring and pig inventory

Since the outbreak of African swine fever in 2018, biosafety has been crucial for aquaculture enterprises. Under the traditional breeding mode, people and things inside and outside the pig farm are complicated, and materials, vehicles, birds and animals come in and out frequently. It is extremely difficult and time-consuming to achieve effective supervision. For example, in the process of dissecting dead pigs, improper wearing of protective clothing by operators may cause the spread of diseases in pig farms. It is difficult to pass the manual on-site review, and it is impossible to supervise all the time. By using technologies such as artificial intelligence and Internet of Things, employees’ misconduct can be identified and early warning signals can be conveyed to managers in time, which can effectively avoid the risk of disease spread.

In addition, artificial intelligence technology can also be used to count and estimate the number of pigs. In the traditional breeding process, pig dealers need to go to the pigsty for on-site counting and weighing in the pig selling process. By using the camera above the pig farm combined with artificial intelligence technology, the pigs in the pen can be counted in real time, so as to achieve the effect of remote pig watching and real-time weight estimation.

The AI patrol and early warning interface of "Pig Xiao Zhi" of rural credit cooperatives.

Scheme of intelligent pig farm with integrated rural credit, mathematics and intelligence for message or private message consultation

Scene 2: Intelligent dung cleaning robot and inspection robot

Pig farm is a model of large-scale farming. Large-scale farming and high manure output are difficult problems that plague the operation of enterprises. In traditional farming mode, manual cleaning is usually needed, and the labor input cost is high in the process of manual cleaning. Some pig farms use water to clean manure, which consumes a lot of water, and at the same time, it is easy to cause high humidity in pig houses and cause health problems of pigs. By using artificial intelligence technology to develop a dung sweeping robot, it can effectively solve the problems of difficult cleaning, reducing water consumption and saving costs.

Similarly, robots developed by combining intelligent speech recognition and visual recognition technologies can cruise around the pigsty all day, find abnormal pigs (such as fever and shivering) in the pigsty in time, prevent and control diseases in advance, and effectively resolve the risk of disease infection.

Mu Yuan inspection robot

The above are only typical application scenarios of artificial intelligence technology in pig farms. With the expansion of business scale and the improvement of cost control and biosafety requirements of enterprises, the combination of artificial intelligence technology and pig breeding is becoming closer and closer.

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At last year’s Deep Bay Meeting, in view of the application of intelligence in pig farms, Qin Yinglin, chairman of Mu Yuan Co., pointed out: "It takes three years for us to train an excellent employee, and many employees are unqualified for three years, which takes five or even ten years. But we want to make a machine in the assembly line, and gather all our wisdom of raising pigs. We are producing this very quickly now, and producing thousands of units a day is equivalent to producing the corresponding number of laborers. "

It can be seen that artificial intelligence technology has been applied on a large scale in the farms of some enterprises. With the continuous development and mature application of technology, it is certain that "unmanned pig farms" and "unmanned farms" will eventually come true.

References:

Talking about the development of AI from ChatGPT, consulting with Deme.

Nature is heavy: human beings have misunderstood the dopamine mechanism in the brain! ? Top Edition AlphaGo Enlightens Brain Science, Quantum Bit

Qin Yinglin’s Sharing in Deep Bay Meeting, Wandou Agricultural Science.

Guiding Opinions on Actively Promoting "internet plus" Action, the State Council

Brief introduction of Artificial Intelligence (AI)

The development history of Artificial Intelligence (AI) can be traced back to 1950s. The following are the main stages of the development history of AI:

Logical reasoning and problem solving (1950s-early 1960s): The early AI system was based on symbolic logic, and solved problems through logical reasoning of facts and rules. However, this method has limitations, and it is difficult to deal with a large number of uncertain and fuzzy information.
Machine learning and pattern recognition (1960s-1980s): The research of AI began to turn to machine learning and pattern recognition. Machine learning is a method to learn and optimize algorithms by training data, while pattern recognition is a method to realize intelligence by identifying and classifying patterns. These methods have been widely used in image recognition, speech recognition and natural language processing.
Expert system and knowledge representation (1980s-1990s): AI research began to pay attention to expert system and knowledge representation. Expert system is an intelligent system based on expert knowledge and inference rules, which can simulate the decision-making process of human experts. Knowledge representation is a method to organize knowledge and information into a form that can be processed by computer, and it is an important foundation to realize AI.
Statistical learning and deep learning (1990s-2010s): With the continuous development of computer hardware and algorithms, AI research began to pay attention to statistical learning and deep learning. Statistical learning is a machine learning method based on statistical model and data analysis, which can handle a large number of data and complex nonlinear relationships. Deep learning is a machine learning method based on neural network, which can handle more complex and high-dimensional data.
Self-learning and multi-modal AI(2010 to present): AI system is gradually realizing the ability of self-learning and self-optimization, and can continuously improve its own model and algorithm according to feedback and data. Multi-modal AI is an AI technology that can handle a variety of data types and perceptual information, including images, voices, texts, etc., and can realize more comprehensive and intelligent human-computer interaction.

Important events:

In 1956, the concept of artificial intelligence was put forward at Dartmouth Conference, which marked the birth of AI.
In 1962, Arthur Samuel developed a self-learning program, which was an early application of machine learning.
In 1969, Marvin Minsky and Seymour Papert published Perceptrons, which revealed the limitations of single-layer neural networks and promoted the development of neural networks.
In 1975, John Holland developed genetic algorithm, which is an optimization algorithm that imitates the process of biological evolution.
In 1981, Japan launched the first commercial robot WABOT-1.
In 1997, IBM’s deep blue supercomputer defeated Kasparov, the world champion of chess, indicating that computers can surpass human intelligence in some fields.
In 2011, IBM’s Watson artificial intelligence system defeated human players in the program "Dangerous Edge".
In 2016, AlphaGo defeated Li Shishi, the world champion in the Go competition, marking an important step in the application of artificial intelligence in complex games.
In 2018, the GPT-2 model developed by OpenAI made a major breakthrough in the field of natural language processing, which can generate high-quality natural language texts.

The latest development trend:

Self-learning: AI system is gradually realizing the ability of self-learning and self-optimization, and can continuously improve its own model and algorithm according to feedback and data.
Deep learning: Deep learning is a machine learning method based on neural network, which can handle a large number of data and complex nonlinear relationships, and is one of the main trends of current AI development.
Artificial intelligence chip: Artificial intelligence chip is a chip specially designed for AI application, which can realize efficient calculation and data processing and is an important technical support for AI popularization and application.
Multi-modal AI: Multi-modal AI is an AI technology that can handle a variety of data types and perceptual information, including images, voices, texts, etc., and can realize more comprehensive and intelligent human-computer interaction.
AI and Internet of Things: The combination of AI and Internet of Things can realize more intelligent and efficient automatic production and management, including intelligent energy, intelligent transportation, smart home and other fields.
AI Ethics and Law: With the continuous development and application of AI technology, AI ethics and legal issues have attracted more and more attention, including privacy protection, data security, and responsibility distribution.

In short, the development trend of AI technology is diverse, involving algorithms, chips, data and applications. In the future, AI technology will continue to develop and apply in depth, bringing more convenience and innovation to mankind.

Gao Zhidan： In view of the serious problems in the field of football, we are studying solutions and ways.

On the morning of March 12th, the first session of the 14th National People’s Congress held its fifth plenary meeting in the Great Hall of the People. After the meeting, the third "Ministerial Channel" interview was held, and some responsible persons of relevant ministries and commissions in the State Council were invited to attend the meeting.

A reporter asked Gao Zhidan, director of the State General Administration of Sports: Football, basketball and volleyball are deeply loved by the masses, and the development of the three big balls has attracted much attention from all walks of life. However, the current situation of promoting the development of the three big balls in an all-round way in China is not ideal. What do you think of this problem? What is the next work plan of the General Administration of Sports for revitalizing the three big balls?

In this regard, Gao Zhidan said that football, basketball and volleyball, the three major collective ball events, have a large population and great social influence, and are deeply loved by the broad masses of the people, especially young people. The results of the three big balls are not only the outcome of a game, but also the spirit of collectivism and patriotism.

Historically, China’s three major events, especially women’s events, have achieved good results in the world. China women’s football team once won the runner-up in the Olympic World Cup and was known as the "sonorous rose". China women’s basketball team won medals in the Olympic World Championships in 1980s and 1990s, and won the second place in the World Cup last year, showing a good momentum of continuous progress and development. China Women’s Volleyball Team, which has been tempered through hard training, has struggled from generation to generation, winning the world championship for ten times in three world competitions and winning honor for the motherland. Their women’s volleyball spirit of the motherland first, unity and cooperation, tenacious struggle and never give up, which is condensed by struggle and hard work, has inspired generations of Chinese people to make unremitting efforts to realize the Chinese dream of the great rejuvenation of the Chinese nation.

Gao Zhidan said, but realistically speaking, for a long time, the development of China’s three major sports, especially men’s events, was not satisfactory, and the level of men’s football was declining all the way. There were many chaos in the football industry, which was in sharp contrast with the requirements and expectations of the CPC Central Committee and the people all over the country. It is a sign of a sports power that the three major goals should be achieved, and it is also a short board that we must make up to speed up the construction of a sports power. Recently, in view of the serious problems in the field of football, we have been deeply rethinking and studying solutions and ways, and are prepared to systematically treat them from the aspects of ideological education, style construction, deepening reform, and doing a good job in the current work, so as to do a good job in all the work of the three goals in the spirit of re-taking the Long March.

The influence of artificial intelligence on human beings

Artificial intelligence has become a hot topic, and one of the main topics is that robots will replace human work. In fact, many people have lost their jobs because artificial intelligence has replaced their work tasks. Nevertheless, people still need to work for machines, especially those jobs that are considered low-skilled. In this paper, we will discuss the influence of work artificial intelligence on human beings and the significance of this phenomenon to our economy and society.

Work disappears because of artificial intelligence.

The development of artificial intelligence technology has made some jobs redundant, which may be some traditional industries such as logistics, factory manufacturing, customer service, etc. These jobs needed manual operation in the past. Nowadays, the application of artificial intelligence technology has made these tasks more efficient and reduced labor costs, so the demand for staff has also declined. The application of artificial intelligence technology can make the production efficiency higher and reduce the working time and cost. However, workers are also at risk of unemployment, because machines and artificial intelligence technology will replace manpower.

Wages are cut by artificial intelligence

Artificial intelligence technology can also allow employers to reduce employees’ wages. If a company can replace labor with machines, then they can cut labor costs, which also makes staff face greater economic pressure. In addition, with the application of machines and artificial intelligence technology, the skill level required for many jobs will be reduced because many tasks will be completed automatically. This means that staff need to have more skills and knowledge to stay in this industry.

Ideology brought by artificial intelligence

The ideology behind artificial intelligence technology may make us recognize the value of machines more. The real meaning behind this ideology is that if we no longer need the help of artificial intelligence, then we have no value. Artificial intelligence technology makes us believe that only with the latest technology can we maintain market competitiveness. This idea makes people believe that they are out of date and need to be eliminated.

The Influence of Artificial Intelligence on Economy and Society

The development of artificial intelligence will have a far-reaching impact on economy and society. Artificial intelligence technology can make our economy more efficient, but artificial intelligence may also lead to some negative effects. On the one hand, the unemployment rate may increase, because artificial intelligence technology will replace many jobs. On the other hand, artificial intelligence may make our society more divided, because those without technology and knowledge may be eliminated. In addition, the application of artificial intelligence technology may bring more social problems, such as more crimes and social insecurity. These problems will require us to find solutions.

The self-promotion of technological capitalism

The self-promotion of technological capitalism means that technological capitalism thinks that technology can solve all problems, thus making our economy stronger. Advocates of technological capitalism believe that technology can bring more productivity and efficiency, thus promoting economic growth and creating more wealth. In this view, technology is regarded as a magic solution, which can help us solve all problems.

However, this idea also brings some problems. First of all, advocates of technological capitalism often ignore the problems brought by technology itself, such as technological unemployment and technological dependence. Secondly, they often put economic benefits above human nature and social values, and even sacrificed these values to pursue economic benefits.

In the eyes of the admirers of technological capitalism, technology is a magical solution that can help us get rid of all problems. However, technology itself is not a magic solution, it will also bring some problems and challenges. For example, technical unemployment and technical dependence are challenges brought by technological development.

In addition, the self-promotion of technological capitalism will also bring some problems in values. In the eyes of the admirers of technological capitalism, economic benefits are supreme, and other values can be sacrificed to pursue economic benefits. This view often leads people to ignore other values, such as human nature and social responsibility. Therefore, the self-promotion of technological capitalism may lead us to lose some important values and sense of responsibility.

The relationship between artificial intelligence and capitalism

The relationship between artificial intelligence and capitalism is an important issue facing the development of social economy and science and technology. The core of capitalist economic system is to pursue profits, and the application of artificial intelligence technology can improve production efficiency and reduce staff, thus reducing labor costs and increasing the profits of enterprises. This makes the capitalist economic system more inclined to the application of artificial intelligence technology, but it also brings some social problems.

First of all, the application of artificial intelligence technology may lead to an increase in the unemployment rate. With the development of automation and machine learning technology, many jobs have been automated, including simple assembly line jobs and some service jobs. Some forecasts show that more jobs may be automated in the future, which will lead to a large number of workers losing their jobs. This is why some people worry that with the development of artificial intelligence technology, more people will be eliminated.

Secondly, the application of artificial intelligence technology may also lead to social inequality and division. The application of automation and machine learning technology requires a high degree of technology and professional knowledge, and those who do not have these skills and knowledge may be eliminated. This will lead to social division and aggravate the gap between the rich and the poor.

In addition, the application of artificial intelligence technology may also bring some moral and ethical problems. For example, some people worry that automation technology may weaken workers’ rights and interests, and workers’ rights to survival and development may be infringed. In addition, the application of artificial intelligence technology may also lead to privacy and security problems, such as data privacy and information leakage.

However, the application of artificial intelligence technology also has many positive aspects. For example, it can help enterprises improve production efficiency, reduce costs, and at the same time improve the quality and reliability of products. In addition, the application of artificial intelligence technology can also promote economic development and innovation, and improve the competitiveness of enterprises.

Real artificial intelligence

The development of artificial intelligence has made great progress, and many industries have begun to apply artificial intelligence technology to improve production efficiency and reduce workload. However, with the continuous development of artificial intelligence technology, people are beginning to worry about whether artificial intelligence technology will replace human work.

True artificial intelligence means that human beings no longer need to do reasonably paid work, which means that we no longer need absolute slaves. The development of real artificial intelligence technology should be used to reduce people’s workload, not to replace human work. Therefore, we should explore how to apply artificial intelligence technology to those boring, dangerous or high-pressure jobs to improve work efficiency and reduce the burden on staff.

In fact, the application of artificial intelligence technology can help us better manage and protect our resources, thus solving global problems, such as climate change, environmental pollution and food shortage. At the same time, the application of artificial intelligence technology can also help us to better manage the medical and health field, such as strengthening medical diagnosis, monitoring chronic diseases and predicting the condition by using artificial intelligence technology.

However, the application of artificial intelligence technology has also brought some problems. First of all, artificial intelligence technology may lead to more unemployment because it can replace many jobs. Secondly, the application of artificial intelligence technology may make our society more divided, because those without technology and knowledge may be eliminated. In addition, the application of artificial intelligence technology may bring more social problems, such as more crimes and social insecurity.

Therefore, we should explore how to make rational use of artificial intelligence technology, so as to minimize its negative impact. We need to regard artificial intelligence technology as an auxiliary tool for human beings, rather than a tool to replace human work. We need to work together to solve the problems brought by artificial intelligence and apply artificial intelligence technology to those areas that can improve work efficiency. Only in this way can we realize the greatest potential of artificial intelligence technology and bring more benefits to our society and economy.

The development of artificial intelligence needs joint efforts.

All artificial intelligence technologies are developed on the basis of human society, so we also need to work together to solve the problems brought by artificial intelligence. The government can formulate more reasonable policies to help those who have lost their jobs regain employment opportunities, and at the same time, it can encourage enterprises to apply artificial intelligence technology to those areas that can improve work efficiency. Educational institutions can also provide help and support for those who need to re-learn skills and knowledge.

In addition, we should also think about how to use artificial intelligence technology to solve global problems, such as climate change, environmental pollution and food shortage. The application of artificial intelligence technology can help us manage and protect our resources better, thus promoting sustainable development.

Bournemouth vs Liverpool first-half statistics： shooting 3-9, possession rate 34.2% vs 65.8%.

Live on March 11 th, in the 27th round of Premier League, Bournemouth led Liverpool 1-0 at half time with Billing’s goal, and Sqauwka counted the data of the first half of the two teams.

Bournemouth vs Liverpool first half statistics (Bournemouth first)：

Expected goal-0.87 to 0.71

Shoot-3 to 9

Straight shot-1 to 5

Touching the ball in the opponent’s penalty area-8 to 14

Ball control rate-34.2% vs 65.8%

Corner kick-2 to 6

The core technology of ＂making the brain＂ serves the important needs of the country

In today’s world, the level of human science and technology has reached an unprecedented height. With the entry into the intelligent era, a new round of scientific and technological and industrial revolution characterized by the deep integration of information technology and manufacturing industry has flourished, and technical groups in many fields have broken through and merged, which has promoted profound changes in manufacturing production methods. Countries all over the world have taken a series of major measures, hoping to rely on the manufacturing revolution with intelligent manufacturing as the core, consolidate the foundation of innovation and development of manufacturing industry, and build new kinetic energy and new advantages. As a manufacturing power in the world, China has listed intelligent manufacturing as the main direction determined by Made in China 2025, which is not only the key to promote the transformation and upgrading of China’s manufacturing industry, but also an important strategy to become a manufacturing power in the world.

Professor Song Xuan from the Department of Computer Science and Engineering in south university of science and technology of china, whose main research direction is artificial intelligence and its related fields, including big data analysis, data mining and urban computing, has applied the research results to disaster emergency and epidemic prevention of major infectious diseases, and achieved good results. At present, in the series of research in the field of intelligent manufacturing, it contributes scientific research strength to promote the development of intelligent manufacturing in China and accelerate the pace of building a manufacturing power in China.

Intelligent analysis of data model is committed to tackling the key core technology of "intelligent brain"

Since 2013, China’s development strategy has specifically pointed out that "the country’s strength depends on the real economy and cannot be bubbled" and "the innovation-driven development strategy is deeply implemented to enhance the core competitiveness of industry". "Made in China 2025" clearly emphasizes the need to accelerate the integration and development of a new generation of information technology and manufacturing technology, and take intelligent manufacturing as the main direction of deep integration of the two; Efforts will be made to develop intelligent equipment and products, promote the intellectualization of production processes, cultivate new production methods, and comprehensively improve the intelligent level of R&D, production, management and service of enterprises. Intelligent manufacturing can effectively improve the production efficiency of manufacturing industry, shorten the product development cycle and reduce the defective rate of products, which is the key to building a digital China, realizing "Made in China 2025" and breaking the chip blockade.

The national science and technology strategy points out that "it is necessary to cultivate a large-scale team of young scientific and technological talents, focus on the policy of cultivating the strength of national strategic talents, and support young talents to take the lead and play the leading role." As a young scientist born in 1980s, Professor Song Xuan is currently presiding over the national key R&D project "Multi-dimensional data space and service theory of manufacturing product life cycle value chain". The project focuses on the key technology of "manufacturing brain", which is the key theoretical model and technical method of tackling the problem, and provides technical support for the intelligent upgrading of high-end manufacturing industries (such as automobile manufacturing) in China.

Professor Song Xuan said that there are some problems in the process of data storage and analysis in manufacturing industry, such as chaotic data interface, inefficient storage, low level of intelligence and opaque information, which affect the quality of product collaboration and data value-added in manufacturing industry and are not conducive to the sustainable development of manufacturing intelligence. In view of this situation, the project puts forward a set of multidimensional data space and service theory of manufacturing product life cycle value chain, which integrates data sharing and integration and data analysis service. The multi-dimensional collaborative data space prototype model theory of product life cycle value chain based on blockchain proposed by this project can guide safe and efficient data sharing and assist product R&D collaboration; The data analysis method based on deep learning and knowledge generation technology proposed by the project can realize causal inference, speed up the traceability of problems and shorten the product development cycle. Taking intelligent manufacturing as an opportunity and the actual upgrading demand of manufacturing industry as a guide, the project focuses on the two cores of "manufacturing brain": data flow and intelligent analysis, which is of great significance for China’s manufacturing industry to build a competitive advantage in the industrial chain and further improve the intelligent level of manufacturing industry. The project also puts forward a set of multi-dimensional data space and service theory of manufacturing product life cycle value chain, which integrates data sharing and integration and data analysis service.

Professor Song Xuan believes that intelligent manufacturing needs a "manufacturing brain", and manufacturing data is the "blood" of "manufacturing brain"; Algorithm models such as deep neural network are the main part of "manufacturing brain" and play the role of thinking and decision-making; Data flow is collected in the "manufacturing brain", which can automatically complete data analysis, intelligent decision-making and product life cycle prediction and deduction, and realize efficient intelligent manufacturing. The theory of multi-dimensional collaborative data space prototype model of product life cycle value chain based on blockchain proposed by Song Xuan can guide safe and efficient data sharing and assist product R&D collaboration. The data analysis method based on deep learning and knowledge generation technology proposed by the project can realize causal inference, speed up the traceability of problems, shorten the product development cycle, and predict and simulate the product life cycle.

Building an urban brain platform and focusing on building a smart city

From December 2019 to December 2022, with the liberalization of the epidemic, the pneumonia epidemic in Covid-19, which lasted for three years, finally came to an end, and the epidemic situation was gradually controlled. In this epidemic prevention and control, Professor Song Xuan led the project team to develop the "novel coronavirus (Covid-19) communication modeling, prediction and simulation deduction platform driven by human flow big data and AI", which played an important role. Based on artificial intelligence (AI) technology, the model of potential infection sources and risk areas was mined on the city scale, and the communication modeling, prediction and simulation deduction platform for COVID－19 was built. For the big data analysis and AI modeling platform for novel coronavirus communication, the prediction and simulation deduction model was complete. Made outstanding contributions to the prevention and control of the epidemic.

In addition, Professor Song Xuan, as the project leader, has developed an "epidemic prevention chain" APP on the mobile device side. The APP on the mobile phone side can assess the risk of epidemic or major infectious diseases (such as new crown pneumonia, seasonal influenza, etc.) in real time by sensing the contact between users and others and analyzing various urban environmental big data (such as crowd density, air quality, environmental humidity and temperature, etc.).

In fact, as early as 2011, the big data analysis and modeling of people flow carried out by Song Xuan’s team contributed to the fight against viruses and natural disasters. In March 2011, after the earthquake in Japan and the Fukushima nuclear accident broke out, Song Xuan led the team to develop a number of emergency flow prediction models and a system to help the Japanese government analyze the evacuation and migration of victims after the disaster and formulate more efficient post-disaster reconstruction policies. In 2016, in response to the Ebola outbreak in West Africa, the research of Song Xuan’s team helped the International Telecommunication Union to analyze the flow of people in West Africa and the spread and infection of Ebola virus, which played an important role in the prevention and control of Ebola virus.

Professor Song Xuan has been deeply involved in the field of artificial intelligence for 15 years. He deeply realized that the main place for modern people to live and work is the city, and the core of urban management is to make people’s life in the city safer, more comfortable and more convenient. With the proposal of building a smart city, Song Xuan now pays attention to urban data and tries to alleviate or solve various "urban diseases" such as traffic congestion, environmental pollution and natural disasters. His team realized the simulation and prediction of the large-scale movement of urban people by building a modeling model of urban mass people movement, thus realizing efficient urban intelligent management. Song Xuan is currently tackling key problems and building an urban brain platform, bringing together all aspects of urban informatization and the whole process of urban management through high and new technologies to carry out control and support, so as to ensure travel safety, give full play to the efficiency of urban infrastructure, improve the operational efficiency of transportation system and the level of urban governance, alleviate all kinds of "urban diseases" to the greatest extent, and help urban governance to be more scientific, refined and intelligent.

"Scientific research should always serve the public" is precisely with such a sense of mission and responsibility. In the future scientific research, Song Xuan will always focus on his mission, aim high and live up to his youth, take data as the core and science and technology as the weapon, and strive to build an intelligent brain, help build a smart city and build an intelligent manufacturing power.

What does offside mean in football match？ Will your own team be offside in the half court？

Offside is a professional term in football match, which first appeared in the Rules of Football Match promulgated in 1874. It is defined as: when the ball is passed in front of the attack direction, when the football kicks out, if the teammate of the defensive half is closer to the goal than the penultimate defender of the other side, and wants to use this position to interfere with the game or gain benefits, the player will be sentenced to offside.

There are many technical terms in football matches, such as penalty kick, corner kick, sideline kick, offside, etc. Among them, offside is often heard by many people, but its basic meaning is still ambiguous, and sometimes it is impossible to make an accurate judgment under special circumstances. Let’s explain it in detail below.

When we watch a football match, we often see a sideline referee raise a flag just after a player scores the ball into the opponent’s goal. The player who scored the goal has to shake his head helplessly and throw himself back into the attack. Naturally, the goal just scored will not count. Why? Because he was offside, he was offside at the moment when his teammates passed the ball to him.

Which position on the court is offside? In fact, there is no specific position, depending on the position of the players. First of all, offside can only happen in the opponent’s half court. At the moment when our own players pass the ball, we should observe the positions of all the players. When the player who is ready to catch the ball is at the forefront of all the players (excluding the goalkeeper of the opponent), he is offside. This position is not the position of his feet, but the position of his body, and his shoulders and head are leading.

In the past, offside was judged by the sideline referee with the naked eye, which naturally could not be absolutely accurate. But now, with the introduction of high-tech VAR technology, many offsides between millimeters can’t escape from the "eyes". However, although VAR makes the game fairer, it also reduces the excitement of the game to a certain extent and makes many beautiful goals invalid.

There are some special situations about offside on the court. For example, although the attacking player who receives the ball is ahead of all the defensive players (except the goalkeeper), he is still in his own half, so he is not offside at this time.

If a player on the attacking side is offside at the moment when the player passes the ball, but he doesn’t catch the ball or participate in the next attack, then he is not offside.

The last situation: although a player on the attacking side is in an offside position, he just runs with him, participates in the stall, and creates shooting opportunities for his own players, but he never touches the ball from beginning to end. Is he offside? Real fans, please tell me in the comments section.

Tevez revealed that he hated Sir Alex Ferguson and informed him to move to Manchester City before the Champions League final! Revenge on Manchester United and renege

Argentine star Carlos Tevez, nicknamed "The Beast", is an enhanced version of Wehorst, who can score goals and catch up with his own bottom line from the front line. However, because of the transfer, he finally fell out with Sir Alex Ferguson, and even raised the slogan "Sir Alex Ferguson rests in peace" after moving to Manchester City. Even now that he has retired, the 39-year-old Tevez still resents the way Sir Alex treated him at Manchester United.

Tevez was loaned to Manchester United in 2007, during which he performed well, scoring 34 goals in various competitions and winning two Premier League titles and the Champions League trophy. However, Tevez did not complete the permanent transfer to the Red Devils. In 2009, he joined rival Manchester City, where he spent the next four seasons. Tevez insists that Sir Alex Ferguson was the reason for his decision to move to Manchester City.

The Argentine Beast stressed that he wanted to stay at Old Trafford, but Sir Alex made a false promise to him. Manchester United didn’t buy him out, so he didn’t hesitate when he received the invitation from Manchester City. "I don’t need to think too much, because I am angry with Ferguson. Tevez told ESPN, "As a coach, he is a phenomenon. He has been teaching at a club like Manchester United for so long, but something happened between me and him. 」

Tevez explained in detail: "I was loaned to Manchester United, and finally he told me:" Manchester United will buy you out, but I will bring Berbatov. Don’t worry, I brought him in to compete fairly with you. We will talk to your agent and reach an agreement on the contract and transfer. But in the end, they didn’t call the broker, and nothing happened. Time is running out. They began to want to lower my price. Every time I play, I perform, and the fans shout names. This is a year-long digestion process. 」

According to Tevez, before the 2009 Champions League final, he told Sir Alex Ferguson that he would join Manchester City as a revenge for United’s reneging on their words in the past year. "I have more or less accepted Sheikh Mansour’s proposal. After the final, I will take a private jet to meet him in Abu Dhabi with my family and solve the contract problem with Manchester City. All this happened before Manchester United’s Champions League final," Tevez added. "The day before the Champions League final against Barcelona, I told him that I would join Manchester City. 」

Tevez started 18 games in the Premier League that season and scored 5 goals, which he was not satisfied with. In that Champions League final, Sir Alex Ferguson finally arranged for him to play as a substitute in the second half, playing 20 minutes earlier than Berbatov, but neither of them played a role. Barcelona beat Manchester United 2-0. "Ferguson kept saying that he was going to buy me that season, and then he brought in Berbatov and didn’t let me play in the league. "The beast vomited.

Tevez then added: "It was like a dagger for him to tell him before the final that I was going to join Manchester City. But it is also true for me, because I love Manchester United. But for me, he didn’t keep his promise for a whole year, and he made me miserable. It hurts me a lot because I love Manchester United. I like playing football at Old Trafford. Playing football there is like a bomb explosion. It gives me that feeling. Then the chief came, and they told me that they wanted me to be the standard bearer of Manchester City. He showed me the blueprint for the future, just like the club is today. 」

After the official transfer of Tevez, Manchester City released a controversial advertisement in the local area, in which Tevez opened his arms and the poster read "Welcome to Manchester". Tevez later made 148 appearances for Manchester City, scored 73 goals and assisted 35 times, which helped the team win the Premier League and the FA Cup. However, his time with the Blue Moon also ended in a broken relationship because of falling out with coach Mancini.

After 3-0, 1-2, the Serie A champion team became worse, shooting 28 goals, making it the first defeat in history, and Milan had a good chance.

In the 26th round of Serie A, Naples won 2-0, which means that they are back on the right track after the last round of defeat. They scored 68 points and were far ahead in the championship, which also shows that the other four teams can only reach the second place at most. From the point of view of points, originally Inter Milan was most likely to hold the second place in the standings. After all, after the first 25 rounds, their points reached 50 points, temporarily ahead of Lazio, AC Milan and other teams!

However, with the end of the 26th round, Inter Milan, the 19th champion of Serie A, almost ruined its advantage. In this round of competition, the Nerazzurri played against spezia, and in the first round, Inzaghi led a 3-0 victory. In addition, the starting price of Vispe Zia of Inter Milan is 278.1 million euros, which shows that the Nerazzurri have won completely. Even the Nerazzurri are considered to have the strongest lineup in Serie A, and it seems that they deserve to win again. Unfortunately, things didn’t work out, and the "Nerazzurri" finally faced defeat under the frequent waste of opportunities.

From the 5th minute when lautaro got the chance to play, to the end of the first half, Inter Milan launched more than 5 attacks, but all failed, including a penalty. However, lautaro missed the penalty in the first half and became the player who missed the penalty the second time since the 2021-2022 season: 8 penalty kicks and 4 penalties. In the second half, Inter Milan stepped up their offensive. From the 46th minute to the 83rd minute, lautaro and brozovic launched attacks in vain, and finally the score was rewritten with the help of Lu Kaku’s penalty.

However, spezia’s luck was even better. In the 55th minute, Danielle Maldini was unguarded and scored from the front of the restricted area. In the 87th minute, Spezia relied on a penalty to kill the game directly, and Inter Milan lost 1-2. What we need to know is that the possession rate of the "Nerazzurri" in this battle is 38 percentage points higher than that of the opponent, and the number of shots reached 28 times, which is 7 times that of the opponent. However, it is still embarrassing that it is still impossible to win.

Interestingly, the defeat of this game is also the first defeat of Inter Milan against spezia. In the previous nine games, the Nerazzurri won eight games. It seems that the team’s instability has seriously affected a series of records! Of course, the defeat of Inter Milan is undoubtedly a good thing for AC Milan in the same city. After the first 25 rounds, the Rossoneri accumulated 47 points.

In other words, if we win this round, then AC Milan points can also reach 50 points, which is consistent with Inter Milan, and then better compete for the second place. You know, in the first 18 rounds, AC Milan beat Inter Milan and held the second place in the standings. Now it seems that Pioli is expected to lead the team to restore the victory!

Sassuolo executives： Will Fratesi join Rome？ We will try our best to meet the requirements of the players.

Live broadcast: On March 11th, when interviewed by the reporter of Corriere dello Sport, Carnevali, CEO of Sassuolo, talked about the rumors of Fratesi and Rome.

Carnevali said: "We should have a correct attitude. Sassuolo should be regarded as a springboard for players to join the giants. Fratesi has all the strength to make a leap forward, and now we must try to reach an agreement that can satisfy our three parties. We will find the best solution. In addition to economic factors, we will also try our best to meet the requirements of the players themselves. "

"We have been investigating Bovi and volpato in Rome. Before that, Rome sent many high-potential teenagers to us for training, giving us a high split, such as Politano and Lorenzo pellegrini."

According to the whole market, besides Roma, Juventus are also paying attention to Fratesi.

(real steel fist)

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