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A large group of researchers found that machine learning can be used to help metallurgists find the best metal mixture to make the required alloys. In this way, they found an alloy with a thermal coefficient lower than that currently recorded.

The research was carried out by scientists from Max Planck Institute for Iron Research, who cooperated with colleagues from darmstadt University of Technology, Delft University of Technology and Royal Institute of Technology.

For thousands of years, people have been mixing metals according to their own needs and learned a lot about alloy manufacturing. But finding the right combination always requires some inspiration, patience and luck.

Therefore, most alloys are made from a single base metal (such as iron), and the obtained characteristics are observed by adding a small amount of other metals.

However, in the past few decades, the situation has begun to change-some researchers have begun to make alloys containing several metals in equal parts.

Of course, it is much more difficult to make this alloy with specified characteristics. In this new work, researchers apply machine learning to help this process. They first reduced the test space to only one application-making alloys that will not expand and contract too much when exposed to temperature changes.

In order to create a machine learning application, researchers searched and found metal features that can be used for comparison purposes, and then trained their systems using the information in the currently available databases. In the process, they developed a process to find an alloy suitable for the required goal.

The team’s process was reduced to three main steps: First, they created a new mixture using a model based on information stored in a database describing metal characteristics. Then, they use the second model to help predict the properties of some alloys they created in the first step. The last step is to study the candidate alloys produced by the system and select some of them for practical testing.

Using this system, the researchers obtained 1000 candidates, which were narrowed down to three alloys. Then, they made three kinds of alloys using the mixture described in the system and tested their physical properties.

The team used data from real alloys to train the system and repeated the whole process. They chased it for seven times and found an alloy with a thermal coefficient lower than the current record.

In their paper published in the journal Science, the team described their three-step process and its performance in the test. Scientists from the Institute of Metals, Chinese Academy of Sciences published an article on the prospect in the same issue, describing the work done by the team on this new project.

Reference: https://techxplore.com/news/2022-10-machine-optimal-mixture-metals-desired.html.

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:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.

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.

After losing to Bayern Munich, Paris Saint-Germain once again fell to the last 16 of the Champions League. This is undoubtedly a heavy mental blow to a club that is determined to be crowned king of Europe. Although the team has a top player like sergio ramos, who has won the Champions League four times, his great experience in the Champions League seems to have brought no effect to the team. The Spanish defender also expressed his disappointment with the team after the game.

The former Real Madrid defender said on his Instagram: "Like your fans, we are deeply disappointed with the result. The team has not yet won the Champions League, and we are still immature in how to deal with the key details. Unfortunately, we failed to achieve an important goal. Although it is very painful, the champion teams all grow up from failure and adversity. We will come back! "

Ps: Ramos is actually telling the truth. Paris Saint-Germain still has many problems and does not have the strength to win the championship for the time being. But after all, the team spent so much money to buy so many stars, but the Champions League record failed to meet expectations, which made many fans psychologically uncomfortable and it was understandable to scold him. In other words, this year’s luck in Paris is really bad. In the group stage, we met Benfica (super this year) and Juventus. After the second qualifying in the group, we drew one of the strongest Bayern.