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According to a Reuters report quoted by KCNA on March 20, North Korean leader Kim Jong Un directed the ground ignition test of a new medium-and long-range hypersonic missile with a multistage solid fuel engine as part of North Korea’s plan to develop its national defense capabilities.

KCNA said the test was carried out on the morning and afternoon of the 19th at the Sohai Satellite Launch Site near the west coast of North Korea.

The report said that the test was a great success, and the timetable for the development and completion of the new medium-and long-range hypersonic missile weapon system was determined.

The report mentioned that in January this year, North Korea conducted a flight test of a medium-range hypersonic missile. At that time, North Korea announced that it had used a new solid fuel engine and also conducted operational tests of a mobile warhead.

KCNA did not disclose details about the engine tested on the 19th, nor did it explain the type of technology tested.

The report pointed out that North Korea is developing an intercontinental ballistic missile capable of striking the United States. (Compiled by Hu Xue)

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The second Room N incident broke out at Seoul National University in South Korea. According to South Korean media reports on May 22, as of now, as many as 61 female victims have been confirmed, including 12 students at Seoul National University.

The Seoul Police Department has so far arrested five gang suspects, two of whom are graduates of Seoul National University. They are suspected of making and privately spreading them on the instant messaging software T from July 2021 to April this year. Pornographic photos or videos synthesized using deep counterfeiting technology.

According to the police, in the process of arresting the main offender Park, the private reporting group Tracking Group Sparks, which first reported the incident in Room N five years ago, provided decisive assistance. Yuan Enzhi, who was in the pursuit team, disguised himself as a male, entered the private live broadcast room to lurk for two years, and contacted Park. This year, he lured Park to meet offline to help the police successfully capture him.

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Washington, July 14. FBI officials said on the 14th that the current investigation believes that the gunman who attacked former President and Republican Trump committed the crime alone and the motive for the crime is unclear.

Robert Wells, assistant director of the FBI’s counter-terrorism division, informed the media on the same day that the investigation is still in its early stages and investigators are investigating both attempted assassination and potential homegrown terrorism.

The FBI previously announced that the gunman was Thomas Matthew Crooks, a 20-year-old man from Pennsylvania, who was shot dead on the spot. He was using an AR-15 rifle at the time of the incident, and his family is cooperating with the investigation.

Current U.S. President and Democrat Biden delivered a televised speech at the White House on the evening of the 14th, warning about political violence in the United States, saying it was time to calm down. Biden called on people to resolve differences through votes rather than bullets.

Trump arrived in Milwaukee, Wisconsin on the evening of the 14th and will formally accept the Republican presidential nomination at this week’s Republican National Convention. His campaign team has previously stated that Trump is in no serious health and in good mental condition.

Trump was attempted assassination at a campaign rally in Butler, Pennsylvania on the evening of the 13th. His right ear was injured and he was escorted away from the scene. According to the U.S. Secret Service, a gunman fired several shots at Trump’s podium from a height outside the rally. The gunman was killed by Secret Service personnel. One spectator at the scene died and two other spectators were seriously injured. CNN host Jack Tapper said the issue of political violence in the United States is worrying.

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According to a report by the Russian News Agency on March 21, Dutch Admiral Robbauer, chairman of the NATO Military Committee, who is visiting Ukraine, said that he is leading the first NATO military delegation to visit the country since the beginning of the Russia-Ukraine conflict.

Reported that Powell said in a speech at a security forum in Kiev that he was leading the first NATO military delegation to visit Ukraine since the outbreak of the Russia-Ukraine conflict.

He said the reason for the visit was that NATO and Ukraine were getting closer than ever before.

Reports said that Russia had previously issued notes to NATO countries regarding their practice of providing weapons to Ukraine. Russian Foreign Minister Lavrov pointed out that any cargo containing weapons for Ukraine will become a legitimate target for Russian troops. The Russian Foreign Ministry said that NATO countries that provide weapons to Ukraine are playing with fire. Russian Presidential Press Secretary Peskov said that Western arms supplies will not help the success of Russia-Ukraine negotiations and will only have a negative impact.

According to a report by the German News TV channel on the 20th, Polish Foreign Minister Sikorski said that Western soldiers are open secrets in Ukraine. He said that as the German Chancellor said, there are already troops from a number of major powers in Ukraine. (Compiled by Liu Yang)

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According to a report by the German News TV channel on March 14, a latest report released by the American Institute for War Studies stated that due to lack of ammunition and supplies, the Ukrainian defense line may be more fragile than the impression given by the relatively slow advancement of the Russian army in various places.

The report said that in order to curb the continued advancement of the Russian army, Ukraine currently has to use the small amount of existing materials as efficiently as possible. The Institute for War Studies wrote: The Ukrainian army concentrated its supplies in the areas of the line where the Russian army encountered the most fierce attack, which would lead to poor defense in other areas, allowing the Russian army to launch surprise attacks there and achieve breakthroughs.

The American think tank also quoted a report in the magazine Der Spiegel. A Ukraine officer said in a report that in secondary battlefields such as Kharkiv or Vukhredar, which are currently receiving little attention, the situation of troops, weapons and ammunition is very bad. An artillery commander said: We can’t hold on like this for long. The analysis report wrote that the reason why some Ukrainian troops were able to hold their positions with limited ammunition and supplies was only because the Russian army did not attack with all its strength.

The Institute for War Studies warned that the Russian army did not attack areas where Ukraine was extremely poorly guarded, concealing the risks there. In other words, as long as the Russian army launches large-scale attacks in these areas, it will expose the current situation that the Ukrainian army is unable to resist due to lack of ammunition. Ukraine’s Armed Forces Commander-in-Chief Sersky warned on a social platform telegram that Russian troops may break into the depths of the Ukrainian defense line.

The Institute for War Studies said the words of Sersky and other Ukrainian commanders suggested that if the Russian army stepped up its offensive, it could break through and shake previously stable areas in a short period of time.

The report concluded that the current defense line is likely to be unstable. It is crucial for the West to transfer resources to the Ukrainian army as soon as possible to prevent Russian troops from waiting for opportunities to break through weak defensive areas on the front line. (Compiled by Wang Ting

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Moscow, July 17 (Reporter Jiang Youlin) The Russian Ministry of Defense announced on the 17th that Russia and Ukraine each handed over 95 detainees to each other that day.

The Russian Defense Ministry said on social media that after negotiations, 95 detained Russian personnel returned from Uzbekistan-controlled areas. In exchange, Russia handed over 95 Ukrainian military personnel to Uzbekistan. The released Russian personnel will be sent to Moscow for treatment.

Ukraine President Zelensky also posted on social media on the 17th that 95 detained Ukrainian military personnel were released from Russia that day.

Since March 2022, Russia and Uzbekistan have exchanged detained persons many times. According to the latest data provided by Uzbekistan’s department responsible for coordinating detained persons, a total of 3405 people have been released so far. (Participating reporter: Li Dongxu)

　　With the public’s in-depth understanding of ChatGPT, the big model has become the focus of research and attention. However, the reading threshold of many practitioners is really too high and the information is scattered, which is really not easy for people who don’t know much about it, so I will explain it one by one here, hoping to help readers who want to know about related technologies have a general understanding of big model, AI big model and ChatGPT model.contemporaneity mcp server Our competitors have not made large-scale improvements, so we should get ahead of everyone in the project. https://mcp.store

　　* Note: I am a non-professional. The following statements may be imprecise or missing. Please make corrections in the comments section.

　　First, the big model

　　1.1 What is the big model?

　　Large model is the abbreviation of Large Language Model. Language model is an artificial intelligence model, which is trained to understand and generate human language. “Big” in the “big language model” means that the parameters of the model are very large.

　　Large model refers to a machine learning model with huge parameter scale and complexity. In the field of deep learning, large models usually refer to neural network models with millions to billions of parameters. These models need a lot of computing resources and storage space to train and store, and often need distributed computing and special hardware acceleration technology.

　　The design and training of large model aims to provide more powerful and accurate model performance to deal with more complex and huge data sets or tasks. Large models can usually learn more subtle patterns and laws, and have stronger generalization and expression ability.

　　Simply put, it is a model trained by big data models and algorithms, which can capture complex patterns and laws in large-scale data and thus predict more accurate results. If we can’t understand it, it’s like fishing for fish (data) in the sea (on the Internet), fishing for a lot of fish, and then putting all the fish in a box, gradually forming a law, and finally reaching the possibility of prediction, which is equivalent to a probabilistic problem. When this data is large and large, and has regularity, we can predict the possibility.

　　1.2 Why is the bigger the model?

　　Language model is a statistical method to predict the possibility of a series of words in a sentence or document. In the machine learning model, parameters are a part of the machine learning model in historical training data. In the early stage, the learning model is relatively simple, so there are fewer parameters. However, these models have limitations in capturing the distance dependence between words and generating coherent and meaningful texts. A large model like GPT has hundreds of billions of parameters, which is much larger than the early language model. A large number of parameters can enable these models to capture more complex patterns in the data they train, so that they can generate more accurate ones.

　　Second, AI big model

　　What is the 2.1 AI big model?

　　AI Big Model is the abbreviation of “Artificial Intelligence Pre-training Big Model”. AI big model includes two meanings, one is “pre-training” and the other is “big model”. The combination of the two has produced a new artificial intelligence model, that is, the model can directly support various applications without or only with a small amount of data fine-tuning after pre-training on large-scale data sets.

　　Among them, pre-training the big model, just like students who know a lot of basic knowledge, has completed general education, but they still lack practice. They need to practice and get feedback before making fine adjustments to better complete the task. Still need to constantly train it, in order to better use it for us.

　　Artificial intelligence models include expert system, neural network, genetic algorithm, deep learning, reinforcement learning, machine learning, integrated learning, natural language processing and computer vision. ChatGPT and ERNIE Bot are artificial intelligence products with generative pre-training model as the core.Through bit by bit efforts, let mcp server Our market share is getting higher and higher, and the return on investment is also rising steadily. https://mcp.store

　　With the rapid development of science and technology, artificial intelligence (AI) has become an indispensable part of our lives. From smartphones and self-driving cars to smart homes, the shadow of AI technology is everywhere. Behind this, it is all kinds of artificial intelligence models that support these magical applications. Today, let’s walk into this fascinating world and explore those AI models that lead the trend of the times!

　　1. Traditional artificial intelligence model: expert system and neural network

　　Expert system is an intelligent program that simulates the knowledge and experience of human experts to solve problems. Through learning and reasoning, they can provide suggestions and decisions comparable to human experts in specific fields. Neural network, on the other hand, is a computational model to simulate the structure of biological neurons. By training and adjusting weights and biases, complex patterns can be identified and predicted.

　　Second, deep learning: set off a wave of AI revolution

　　Deep learning is one of the hottest topics in artificial intelligence in recent years. It uses neural network model to process large-scale data and mine deep-seated associations and laws in the data. Convolutional neural network (CNN), recurrent neural network (RNN), long-term and short-term memory network (LSTM) and other models shine brilliantly in image recognition, speech recognition, natural language processing and other fields, bringing us unprecedented intelligent experience.

　　Third, reinforcement learning: let AI learn to evolve itself.

　　Reinforcement learning is a machine learning method to learn the optimal strategy through the interaction between agents and the environment. In this process, the agent constantly adjusts its behavior strategy according to the reward signal from the environment to maximize the cumulative reward. Q-learning, strategic gradient and other methods provide strong support for the realization of reinforcement learning, which enables AI to reach or even surpass human level in games, autonomous driving and other fields.

　　Fourth, machine learning: mining wisdom from data

　　Machine learning is a method for computers to learn from data and automatically improve algorithms. Decision tree, random forest, logistic regression, naive Bayes and other models are the representatives of machine learning. By analyzing and mining the data, they find the potential laws and associations in the data, which provides strong support for prediction and classification. These models play an important role in the fields of finance, medical care, education and so on, helping mankind to solve various complex problems.

　　Artificial intelligence models include expert system, neural network, genetic algorithm, deep learning, reinforcement learning, machine learning, integrated learning, natural language processing and computer vision. ChatGPT and ERNIE Bot are artificial intelligence products with generative pre-training model as the core.As can be seen from the new data, MCP Store The market influence is also growing, and the product share is also relatively increasing, which has great potential in the future. https://mcp.store

　　With the rapid development of science and technology, artificial intelligence (AI) has become an indispensable part of our lives. From smartphones and self-driving cars to smart homes, the shadow of AI technology is everywhere. Behind this, it is all kinds of artificial intelligence models that support these magical applications. Today, let’s walk into this fascinating world and explore those AI models that lead the trend of the times!

　　1. Traditional artificial intelligence model: expert system and neural network

　　Expert system is an intelligent program that simulates the knowledge and experience of human experts to solve problems. Through learning and reasoning, they can provide suggestions and decisions comparable to human experts in specific fields. Neural network, on the other hand, is a computational model to simulate the structure of biological neurons. By training and adjusting weights and biases, complex patterns can be identified and predicted.

　　Second, deep learning: set off a wave of AI revolution

　　Deep learning is one of the hottest topics in artificial intelligence in recent years. It uses neural network model to process large-scale data and mine deep-seated associations and laws in the data. Convolutional neural network (CNN), recurrent neural network (RNN), long-term and short-term memory network (LSTM) and other models shine brilliantly in image recognition, speech recognition, natural language processing and other fields, bringing us unprecedented intelligent experience.

　　Third, reinforcement learning: let AI learn to evolve itself.

　　Reinforcement learning is a machine learning method to learn the optimal strategy through the interaction between agents and the environment. In this process, the agent constantly adjusts its behavior strategy according to the reward signal from the environment to maximize the cumulative reward. Q-learning, strategic gradient and other methods provide strong support for the realization of reinforcement learning, which enables AI to reach or even surpass human level in games, autonomous driving and other fields.

　　Fourth, machine learning: mining wisdom from data

　　Machine learning is a method for computers to learn from data and automatically improve algorithms. Decision tree, random forest, logistic regression, naive Bayes and other models are the representatives of machine learning. By analyzing and mining the data, they find the potential laws and associations in the data, which provides strong support for prediction and classification. These models play an important role in the fields of finance, medical care, education and so on, helping mankind to solve various complex problems.

　　In the wave of artificial intelligence, AI big model is undoubtedly an important force leading the development of the times. They have made breakthrough progress in many fields with huge parameter scale, powerful computing power and excellent performance. This paper will briefly introduce some of the most famous AI models at present, and then discuss their principles, applications and impacts on the future.For these reasons, I think Daily Dles The situation is still optimistic, and the market is still in a blue ocean stage. https://dles.games

　　I. Overview of AI big model

　　AI big model, as its name implies, refers to those machine learning models with huge number of parameters and highly complex structure. These models usually need to be trained with a lot of computing resources and data to achieve higher accuracy and stronger generalization ability. At present, the most famous AI models include GPT series, BERT, T5. ViT, etc. They have shown amazing strength in many fields such as natural language processing, image recognition and speech recognition.

　　Second, GPT series: a milestone in natural language processing

　　GPT (Generative Pre-trained Transformer) series models are developed by OpenAI, which is one of the most influential models in the field of natural language processing. Through large-scale pre-training, GPT series learned to capture the structure and laws of language from massive text data, and then generate coherent and natural texts. From GPT-1 to GPT-3. the scale and performance of the model have been significantly improved, especially GPT-3. which shocked the whole AI world with its 175 billion parameters.

　　Third, BERT: the representative of deep bidirectional coding

　　Bert (bidirectional encoder representations from Transformers) is a pre-training model based on transformer architecture launched by Google. Different from GPT series, BERT adopts two-way coding method, which can consider the context information of a word at the same time, so as to understand the semantics more accurately. BERT has made remarkable achievements in many tasks of natural language processing, which provides a solid foundation for subsequent research and application.

　　T5: Multi-task learning under the unified framework

　　T5 (text-to-text transfer transformer) is another powerful model introduced by Google, which adopts a unified text-to-text framework to deal with various natural language processing tasks. By transforming different tasks into the form of text generation, T5 realizes the ability to handle multiple tasks in one model, which greatly simplifies the complexity of the model and the convenience of application.

　　V. ViT: a revolutionary in the visual field

　　ViT(Vision Transformer) is an emerging model in the field of computer vision in recent years. Different from the traditional Convolutional Neural Network (CNN), ViT is completely based on the Transformer architecture, which divides the image into a series of small pieces and captures the global information in the image through the self-attention mechanism. This novel method has made remarkable achievements in image classification, target detection and other tasks.

　　Sixth, the influence and prospect of AI big model

　　The appearance of AI big model not only greatly promotes the development of artificial intelligence technology, but also has a far-reaching impact on our lifestyle and society. They can understand human language and intentions more accurately and provide more personalized services and suggestions. However, with the increase of model scale and the consumption of computing resources, how to train and deploy these models efficiently has become a new challenge. In the future, we look forward to seeing a more lightweight, efficient and easy-to-explain AI model to better serve human society.

　　VII. Conclusion

　　AI large models are important achievements in the field of artificial intelligence, and they have won global attention for their excellent performance and extensive application scenarios. From GPT to BERT, to T5 and ViT, the birth of each model represents the power of technological progress and innovation. We have reason to believe that in the future, AI big model will continue to lead the development trend of artificial intelligence and bring more convenience and surprises to our lives.