Monthly Archives: April 2025

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Amman, May 12 (Reporter He Yiping) The Jordanian Armed Forces announced on the 12th the start of the 2024 Thirsty Lion Joint Military Exercise. The military exercise will last until the 23rd, with 33 countries including the United States and Jordan participating.

Jordanian Armed Forces spokesman Mustafa Shiari said at a press conference on the same day that the thirsty lion joint military exercise is one of the most important military exercises in the Middle East. In addition to the sea, land and air forces of the participating countries, there are also some government and non-governmental agencies and humanitarian organizations participate. The military exercise will be held in northern, central and southern Jordan. It is the largest since the launch of the Kashi Lion joint military exercise, but it has nothing to do with the regional situation.

It is reported that this military exercise aims to allow participating countries to reach consensus on combating emerging and cross-border threats such as terrorist organizations and their supporters, the proliferation of drones and weapons of mass destruction, and find the best response methods and means. At the same time, coordinate the participating countries ‘action plans and goals in land, sea and air military operations, logistics support, response to natural disasters and epidemics.

Jordan has held the Thirsty Lion joint military exercise since 2011 and is held once a year except for suspension in 2020, 2021 and 2023. This year is the 11th time that Jordan has held the thirsty lion joint military exercise.

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From May 7 to 13, a COVID-19 variant named KP2 was spreading all over the world. In early May this year, the World Health Organization (WHO) listed the KP2 subvariety as a surveillance variant.

MVK, head of COVID-19 technology in World Health Organization (WHO), said that KP2 is a descendant pedigree of JN1, while JN1 is the main strain in the world, and KP2 spike protein has an extra mutation. There are other emerging variants, JN1 continues to evolve, and we will continue to closely monitor the evolution of the virus.

According to the latest “epidemic situation of novel coronavirus infection in China in April 2023” released by the Chinese Centers for Disease Control and Prevention, no two mutants have been found in China. The report shows that from April 1 to April 30, 2024, 31 provinces (autonomous regions, municipalities directly under the Central Government) and Xinjiang production and Construction Corps reported a total of 11299 local cases of novel coronavirus genome effective sequences, all of which were Omicron mutants. The main epidemic strains were JN1 series variants, and the top three were JN1, JN14 and JN116.

On May 13, Zhao Wei, director of the Biosafety Research Center of the School of Public Health of Southern Medical University, told People’s Daily Health client reporter that considering that the infected people already had certain antibody levels and immune barriers, even if there were new mutants, the symptoms of the current variants are still mainly mild and asymptomatic infections. In addition, the emergence of new mutants indicates that novel coronavirus has not disappeared, and the virus is still mutating. from a clinical point of view, although the current mutants have increased the advantage of transmission, there is no difference between the clinical symptoms of the infected person and the previous strains. At present, there is no significant increase in pathogenicity, and the serious disease rate should not increase.

According to the picture, “the epidemic situation of novel coronavirus infection in China in April 2023”.

The KP2 mutant is a derivative of JN1. There is a point mutation of two amino acids on the outermost spike protein, resulting in increased infectivity, which may be the main reason why it has quickly become the mainstream mutant. Internationally, it has surpassed JN1 to become the main epidemic strain in some countries. Therefore, many people are worried about triggering a new round of infection peak, but it needs to be clear that as long as the pathogenicity does not increase significantly. You don’t have to worry too much for the time being. Zhao Wei explained.

According to the reporter, globally, the KP2 mutant has begun to spread in many countries around the world. According to the data released by the Centers for Disease Control and Prevention (CDC) on May 10, a COVID-19 mutant named KP2 has replaced JN1 as the main epidemic strain in the United States. On May 9, local time, GN reported that KP2 quickly dominated Canada. As of April 28, national data showed that KP2 accounted for 266% of all COVID-19 cases in Canada, more than other JN1 subvariants.

From the clinical observation, this mutant is still as contagious as other O mutants, but its pathogenicity is weak. At this stage, the emergence of new variants of the virus will not have a significant impact on everyone’s normal life, but there may still be severe cases for the elderly and people with low immunity, so remind these high-risk people to continue to pay attention to the information released by the relevant departments and do a good job of personal protection during the epidemic. Zhao Wei warned that it is still possible for the virus to mutate in the future to produce strains with more transmission advantages, and even do not rule out the emergence of strains with strong virulence, and it is necessary to continuously monitor virus changes and develop safer and effective vaccines. (People’s Daily Health client reporter Wang Aibing)

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According to a report by Newsweek on July 15, Ukraine President Zelensky issued a severe warning on the insufficient aid provided by allies to Ukraine for F-16 fighter jets. He said the number of F-16 fighter jets Ukraine received from allies this year was not enough to fight Russia.

Zelensky said at a press conference held in Kiev on the 15th: The decision to hand over F-16 fighter jets to Ukraine is strategic, but their number is not strategic.

U.S. Secretary of State Blinken said last week that Ukraine’s NATO allies have begun handing over U.S. -made F-16 fighter jets to Ukraine and announced that the fighters will fly over Ukraine this summer to ensure Ukraine can continue to effectively defend against Russia.

Reported that Denmark, Norway, the Netherlands and Belgium have promised to provide a total of more than 60 fighter jets to Ukraine this summer. However, Bloomberg News quoted unnamed sources as saying on July 12 that Ukraine may receive far less fighter jets this year than expected to receive only 6 this summer, and may receive 20 by the end of the year.

Zelensky told reporters: I can’t say now how many such aircraft (we) will have. But their numbers are not enough. They will certainly strengthen us, but whether these aircraft are comparable to the Russian aviation fleet is not enough. Do we expect more? Of course!

The report mentioned that on May 29, after Belgium promised to deliver the first batch of F-16 fighter jets to Ukraine this year, Russian Foreign Minister Lavrov issued a warning to the West. (Compiled by Long Jun)

　　What is the AI big model?pass MCP Store As can be seen from its market performance, it has strong vitality and strong appeal. https://mcp.store

　　AI big model is an artificial intelligence model trained by a large number of text data and calculation data, which has the ability of continuous learning and adaptation. Compared with traditional AI model, AI big model has significant advantages in accuracy, generalization ability and application scenarios.

　　Why do you want to learn the big AI model?

　　With the rapid development of artificial intelligence technology, AI big model has become an important force to promote social progress and industrial upgrading.

　　Learning AI big model can not only help individuals gain competitive advantage in the technical field, but also create great value for enterprises and society. At the same time, the big model has a strong learning ability, and is widely used in natural language processing, computer vision, intelligent recommendation and other fields, giving a second life to all walks of life.

　　Large model job requirements

　　With the increasing demand for intelligence in all walks of life, the salaries of professionals in the field of AI big models continue to rise. Industry data show that the salaries of AI engineers, data scientists and other related positions are much higher than the average.

　　From January to July, 2024. the average monthly salary of the newly-developed model post was 46.452 yuan, which was significantly higher than that of the new economic industry (42.713 yuan). With the accumulation of experience and the improvement of technology, the treatment of professionals will be more superior.

　　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.By comparison, it can be seen that mcp server It has certain advantages and great cost performance. 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.

　　What is the AI big model?for a long time mcp server It has an extraordinary development speed, and I believe that the future will be as overwhelming as ever. https://mcp.store

　　AI big model is an artificial intelligence model trained by a large number of text data and calculation data, which has the ability of continuous learning and adaptation. Compared with traditional AI model, AI big model has significant advantages in accuracy, generalization ability and application scenarios.

　　Why do you want to learn the big AI model?

　　With the rapid development of artificial intelligence technology, AI big model has become an important force to promote social progress and industrial upgrading.

　　Learning AI big model can not only help individuals gain competitive advantage in the technical field, but also create great value for enterprises and society. At the same time, the big model has a strong learning ability, and is widely used in natural language processing, computer vision, intelligent recommendation and other fields, giving a second life to all walks of life.

　　Large model job requirements

　　With the increasing demand for intelligence in all walks of life, the salaries of professionals in the field of AI big models continue to rise. Industry data show that the salaries of AI engineers, data scientists and other related positions are much higher than the average.

　　From January to July, 2024. the average monthly salary of the newly-developed model post was 46.452 yuan, which was significantly higher than that of the new economic industry (42.713 yuan). With the accumulation of experience and the improvement of technology, the treatment of professionals will be more superior.

　　This paper comprehensively analyzes the concept, principle, classification and application of AI model and its importance in modern society. AI model, namely artificial intelligence model, is a system that can automatically complete specific tasks by inputting known data into a computer for training through machine learning and other technologies. This paper will deeply discuss the principle, construction process, application fields and challenges of AI model, and provide readers with a clear and comprehensive knowledge framework of AI model.Actually, it’s not just this reason, mcp server Its own advantages are also obvious, and it is normal for the market to perform well. https://mcp.store

　　First, the definition of AI model

　　AI model, called artificial intelligence model, refers to a system that can simulate human intelligent behavior through computer algorithm and data training. It uses machine learning, deep learning and other technologies to input a large number of known data into the computer for training, so that the model can automatically learn and identify the laws and patterns in the data, thus having the ability to complete specific tasks.

　　Second, the principle of AI model

　　The principle of AI model is based on neural network and a large number of data training. Neural network is composed of multiple layers, each layer contains several neurons, which are connected by weights to represent the relationship between input data and output data. In the training process, the model minimizes the gap between the predicted results and the actual results by constantly adjusting the weights, thus realizing the learning and prediction of complex tasks.

　　Third, the classification of AI model

　　AI model can be divided into many categories according to different learning styles and task types, such as supervised learning, unsupervised learning and reinforcement learning. Supervised learning means that model learning can find the relationship between input and output by providing labeled training samples to the model; Unsupervised learning refers to making the model automatically generate rules without labels; Reinforcement learning means that the model learns from trial and error to find the best strategy through continuous interaction with the environment.

　　Fourth, the application of AI model

　　AI model is widely used in various fields, such as natural language processing, computer vision, autonomous driving, medical diagnosis and so on. In the field of natural language processing, AI model can be applied to dialogue system, automatic translation, speech recognition, etc. In the field of computer vision, AI model can be used for image recognition, image generation, face recognition, etc. In the field of autonomous driving, AI model is used for path planning, object detection and behavior prediction.

　　V. Challenges faced by AI model

　　Although the AI model has made remarkable achievements in various fields, it still faces many challenges. First of all, AI model needs a lot of computing resources and data support, and its high cost limits its popularization and application. Secondly, the AI model has poor interpretability, and it is difficult to explain the basis and reasons of its judgment, which increases the risk of use and application. In addition, the AI model still has some problems such as incomplete and inconsistent data sets and lack of labeling, as well as its dependence and limitations on specific scenes.

　　summary

　　As the core component of artificial intelligence technology, AI model has brought revolutionary changes to various fields by simulating human intelligent behavior. From natural language processing to computer vision, from autonomous driving to medical diagnosis, the application scope of AI model is more and more extensive, which has injected new vitality into the development of human society. However, the AI model still faces many challenges and needs continuous technological innovation and optimization. In the future, with the continuous progress of technology and the in-depth expansion of applications, AI model will play an important role in more fields and create a better future for mankind.

　　First, what is AI?The above conclusions show that MCP Store To a great extent, it can bring new vitality to the market and make the industry develop well. https://mcp.store

　　First, let’s discuss the meaning of AI. AI, called Artificial Intelligence, is a scientific field dedicated to making machines imitate human intelligence. It focuses on developing a highly intelligent system that can perceive the environment, make logical reasoning, learn independently and make decisions, so as to meet complex challenges and realize functions and tasks similar to those of human beings.

　　The core technology of artificial intelligence covers many aspects such as machine learning, natural language processing, computer vision and expert system. Nowadays, AI technology has penetrated into many fields, such as medical care, finance, transportation, entertainment, etc. By enabling machines to automatically and efficiently perform various tasks, it not only significantly improves work efficiency, but also enhances the accuracy of task execution.

　　Second, what is the AI ? ? big model

　　Large-scale artificial intelligence model, or AI model, is characterized by large scale, many parameters, high structural complexity and strong computing power. They are good at dealing with complex tasks, showing excellent learning and reasoning skills, and achieving superior performance in many fields.

　　Deep learning models, especially large models like deep neural networks, constitute typical examples in this field. Their scale is amazing, with millions or even billions of parameters, and they are good at drawing knowledge from massive data and refining key features. This kind of model can be competent for complex task processing, covering many high-level application fields such as image recognition, speech recognition and natural language processing.

　　Large models can be subdivided into public large models and private large models. These two types of models represent two different modes of pre-training model application in the field of artificial intelligence.

　　Third, the public big model

　　Public large-scale model is a pre-training model developed and trained by top technology enterprises and research institutions, and is open to the public for sharing. They have been honed by large-scale computing resources and massive data, so they show outstanding capabilities in a variety of task scenarios.

　　Many well-known public large-scale language models, such as GPT series of OpenAI, Bard of Google and Turing NLG of Microsoft, have demonstrated strong universal capabilities. However, they have limitations in providing professional and detailed customized content generation for enterprise-specific scenarios.

　　Fourth, the private big model

　　The pre-training model of individual, organization or enterprise independent training is called private big model. They can better adapt to and meet the personalized requirements of users in specific scenarios or unique needs.

　　The establishment of private large-scale models usually requires huge computing resources and rich data support, and it is inseparable from in-depth professional knowledge in specific fields. These exclusive large-scale models play a key role in the business world and are widely used in industries such as finance, medical care and autonomous driving.

　　V. What is AIGC?

　　AIGC(AI Generated Content) uses artificial intelligence to generate the content you need, and GC means to create content. Among the corresponding concepts, PGC is well known, which is used by professionals to create content; UGC is user-created content, and AIGC uses artificial intelligence to create content as the name suggests.

　　VI. What is GPT?

　　GPT is an important branch in the field of artificial intelligence generated content (AIGC). Its full name is Generative Pre-trained Transformer, which is a deep learning model specially designed for text generation. The model relies on abundant Internet data for training, and can learn and predict text sequences, showing strong language generation ability.

　　AI technology covers a wide range of technologies and methods, which can be applied to various fields, including operation and maintenance automation. The following are some major AI technologies and their applications in operation and maintenance:Therefore, Daily Dles Only then will more and more pump owners cheer for it and spread the value and function of the brand. https://dles.games

　　1. MachineLearning, ML)

　　-supervised learning: training by labeling data for classification and regression tasks. For example, predict system failures or classify log information.

　　-Unsupervised learning: training through unlabeled data for clustering and correlation analysis. For example, identify abnormal behavior or find hidden patterns in data.

　　-Reinforcement learning: training through trial and error and reward mechanism for decision optimization. For example, automate resource allocation and scheduling.

　　2. DeepLearning, DL)

　　-Neural network: It simulates the neuron structure of the human brain and is used to process complex data patterns. For example, image recognition and natural language processing.

　　-Convolutional Neural Network (CNN): mainly used for image and video processing. For example, anomaly detection in surveillance cameras.

　　-Recurrent Neural Network (RNN): mainly used for time series data. For example, predict network traffic or system load.

　　3. NaturalLanguage Processing, NLP)

　　-Text analysis: used to analyze and understand text data. For example, automatic processing and analysis of log files.

　　-Speech recognition: converting speech into text. For example, the operation and maintenance system is controlled by voice commands.

　　-Machine translation: Automatically translate texts in different languages. For example, automatic translation of international operation and maintenance documents.

　　4. ComputerVision

　　-Image recognition: Identify and classify objects in images. For example, anomaly detection in surveillance cameras.

　　-Video analysis: analyzing and understanding video content. For example, real-time monitoring and alarm systems.

　　5. ExpertSystems

　　-Rule engine: making decisions based on predefined rules. For example, automated fault diagnosis and repair.

　　-knowledge map: building and maintaining knowledge base. For example, automated knowledge management and decision support.

　　Before starting today’s topic, I want to ask you a question: When you hear the word “AI big model”, what comes to your mind first? Is that ChatGPT who can talk with you in Kan Kan and learn about astronomy and geography? Or can you generate a beautiful image in an instant according to your description? Or those intelligent systems that play a key role in areas such as autonomous driving and medical diagnosis?We have every reason to believe. MCP Store It will become the mainstream of the industry and will gradually affect more and more people. https://mcp.store

　　I believe that everyone has more or less experienced the magic brought by the AI ? ? big model. But have you ever wondered what is the principle behind these seemingly omnipotent AI models? Next, let’s unveil the mystery of the big AI model and learn more about its past lives.

　　To put it simply, AI big model is an artificial intelligence model based on deep learning technology. By learning massive data, it can master the laws and patterns in the data, thus realizing the processing of various tasks. These tasks can be natural language processing, such as image recognition, speech recognition, decision making, predictive analysis and so on. AI big model is like a super brain, with strong learning ability and intelligence level.

　　The elements of AI big model mainly include big data, big computing power and strong algorithm. Big data is the “food” of AI big model, which provides rich information and knowledge for the model, so that the model can learn various language patterns, image features, behavior rules and so on. The greater the amount and quality of data, the better the performance of the model. Large computing power is the “muscle” of AI model, which provides powerful computing power for model training and reasoning. Training a large AI model needs to consume a lot of computing resources. Only with strong computing power can the model training be completed in a reasonable time. Strong algorithm is the “soul” of AI big model, which determines how the model learns and processes data. Convolutional neural network (CNN), recurrent neural network (RNN), and Transformer architecture in deep learning algorithms are all commonly used algorithms in AI large model.

　　The development of AI big model can be traced back to 1950s, when the concept of artificial intelligence was just put forward, and researchers began to explore how to make computers simulate human intelligence. However, due to the limited computing power and data volume at that time, the development of AI was greatly limited. Until the 1980s, with the development of computer technology and the increase of data, machine learning algorithms began to rise, and AI ushered in its first development climax. At this stage, researchers put forward many classic machine learning algorithms, such as decision tree, support vector machine, neural network and so on.

　　In the 21st century, especially after 2010. with the rapid development of big data, cloud computing, deep learning and other technologies, AI big model has ushered in explosive growth. In 2012. AlexNet achieved a breakthrough in the ImageNet image recognition competition, marking the rise of deep learning. Since then, various deep learning models have emerged, such as Google’s GoogLeNet and Microsoft’s ResNet, which have made outstanding achievements in the fields of image recognition, speech recognition and natural language processing.

　　In 2017. Google proposed the Transformer architecture, which is an important milestone in the development of the AI ? ? big model. Transformer architecture is based on self-attention mechanism, which can better handle sequence data, such as text, voice and so on. Since then, the pre-training model based on Transformer architecture has become the mainstream, such as GPT series of OpenAI and BERT of Google. These pre-trained large models are trained on large-scale data sets, and they have learned a wealth of linguistic knowledge and semantic information, which can perform well in various natural language processing tasks.

　　In 2022. ChatGPT launched by OpenAI triggered a global AI craze. ChatGPT is based on GPT-3.5 architecture. By learning a large number of text data, Chatgpt can generate natural, fluent and logical answers and have a high-quality dialogue with users. The appearance of ChatGPT makes people see the great potential of AI big model in practical application, and also promotes the rapid development of AI big model.