Monthly Archives: March 2025

　　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:For this reason, it can be speculated that mcp server The market feedback will get better and better, which is one of the important reasons why it can develop. https://mcp.store

　　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?In combination with these conditions, mcp server It can still let us see good development and bring fresh vitality to the whole market. 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.

　　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.from mcp server Looking at the development prospects, the future will always bring positive effects. 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.

　　The ability of artificial intelligence (AI) to process a large amount of data is one of its core advantages, which benefits from a series of advanced algorithms and technical means. The following are the main ways for AI to efficiently handle massive data:In the past ten years, MCP Store Defeated many competitors, courageously advanced in the struggle, and polished many good products for customers. https://mcp.store

　　1. Distributed computing

　　-Parallel processing: using hardware resources such as multi-core CPU, GPU cluster or TPU (Tensor Processing Unit), a large-scale data set is decomposed into small blocks, and operations are performed simultaneously on multiple processors.

　　-Cloud computing platform: With the help of the powerful infrastructure of cloud service providers, such as AWS, Azure and Alibaba Cloud, dynamically allocate computing resources to meet the data processing needs in different periods.

　　2. Big data framework and tools

　　-Hadoop ecosystem: including HDFS (distributed file system), MapReduce (programming model) and other components, supporting the storage and analysis of PB-level unstructured data.

　　-Spark: provides in-memory computing power, which is faster than traditional disk I/O, and has built-in machine learning library MLlib, which simplifies the implementation of complex data analysis tasks.

　　-Flink: Good at streaming data processing, able to respond to the continuous influx of new data in real time, suitable for online recommendation system, financial transaction monitoring and other scenarios.

　　3. Data preprocessing and feature engineering

　　-Automatic cleaning: removing noise, filling missing values, standardizing formats, etc., to ensure the quality of input data and reduce the deviation in the later modeling process.

　　-Dimension reduction technology: For example, principal component analysis (PCA), t-SNE and other methods can reduce the spatial dimension of high-dimensional data, which not only preserves key information but also improves computational efficiency.

　　-Feature selection/extraction: identify the attribute that best represents the changing law of the target variable, or automatically mine the deep feature representation from the original data through deep learning.

　　4. Machine learning and deep learning model

　　-Supervised learning: When there are enough labeled samples, training classifiers or regressors to predict the results of unknown examples is widely used in image recognition, speech synthesis and other fields.

　　-Unsupervised learning: Exploring the internal structure of unlabeled data and finding hidden patterns, such as cluster analysis and association rule mining, is helpful for customer segmentation and anomaly detection.

　　-Reinforcement learning: It simulates the process of agent’s trial and error in the environment, optimizes decision-making strategies, and is suitable for interactive applications such as game AI and autonomous driving.

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According to a Reuters report on March 18, Russian President Vladimir Putin issued a warning to the West on the same day that a direct conflict between Russia and the US-led NATO military alliance would mean that the planet was only one step away from World War III, and said that almost no one wanted to see such a scene.

French President Macron said last month that he would not rule out the possibility of deploying ground troops to Ukraine in the future. Many Western countries have distanced themselves from the idea of sending troops, but some countries (especially in Eastern Europe) have expressed support.

The report said that when asked about Macron’s remarks and the risks and possibilities of a conflict between Russia and NATO, Putin said mockingly: Everything is possible in the modern world.

After winning the largest landslide victory in Russia’s post-Soviet history in the presidential election, Putin told reporters: Everyone knows that this is only one step away from the full-scale outbreak of World War III. I don’t think anyone would be interested in this situation.

The conflict in Ukraine triggered the deepest crisis in Moscow’s relations with the West since the Cuban Missile Crisis in 1962. Putin has often warned about the dangers of nuclear war, but also said he never felt the need to use nuclear weapons in Ukraine. (Compiled by Yang Xinpeng)

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Putin thanked the Russian people for their support after winning re-election with a record advantage

According to a report by the TASS news agency on March 18, data released by the Central Election Commission of Russia showed that more than 90% of the votes had been counted. Current President Vladimir Putin was far ahead with a vote rate of 87.21%, winning re-election again with a record advantage.

According to reports, Russian Communist Party candidate Nikolai Haritonov ranked second with 428% of the vote, followed by New Party candidate Vladislav Davankov with 393% of the vote, ranking fourth is Liberal Democratic Party candidate Leonid Slutsky, with 316%.

As of 20:00 on the 17th, Moscow time, most polling stations in Russia have been closed.

Data released by the Russian Central Election Commission also showed that as of 20:24, the voter turnout rate in the Russian presidential election was 7333%. The voter turnout rate in this election has set a record high in contemporary Russian history. The previous record was set in 1996, when the voter turnout rate was 6981%.

The report emphasized that preliminary statistics on Putin’s vote rate also set a record high in contemporary Russian history. In 2018, his vote rating in the presidential election was 7669%, compared with 636% in 2012.

According to a report by the Russian News Agency on March 18, Russian presidential candidate and current President Vladimir Putin said during a visit to the campaign headquarters in Moscow that he worked for the interests of the Russian people and relied on their support.

He said: The choice of the Russian people is very important to me. I rely on the Russian people and work for the interests of the Russian people and the country. I am very grateful to Russian citizens for their support.

Putin expressed gratitude to Russian citizens. He also said that Russia will make every effort to achieve national development goals in all aspects. (Compiled by Zhao Zhipeng and He Yingjun)

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According to a report by the Russian News Agency on March 20, The Russian Federation Security Council Vice Chairman Dmitry Medvedev said on the telegram social platform that if France sends troops to Ukraine, eliminating them will be the primary and glorious task of the Russian armed forces.

According to reports, Medvedev believes that it is difficult for the French army to hide its traces in Ukraine, so it is not difficult to eliminate them, and it is impossible to conceal the large number of deaths of French professional soldiers.

Medvedev wrote on the Telegraph social platform: These unfortunate people will become official combatants of the (foreign) intervention force. Eliminating them will be the primary and glorious task of our armed forces.

Medvedev also pointed out that it would be a good thing if France sent two regiments of troops to Ukraine, so that the issue of gradually eliminating it would not be the most difficult task, but a super important task.

Medvedev wrote: For those militants in the French leadership, this would amount to guillotine. Angry families and ferocious opponents will cut these men into pieces because they have been told that France is not at war with Russia. This will be a good lesson for other restless European fools.

Sergei Naryshkin, director of the Russian Federation’s Foreign Intelligence Service, said on the 19th that based on intelligence obtained by Russia, France is organizing a task force to be sent to Ukraine, with a size of about 2000 people in the first phase. (Compiled by Liu Yang)

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Washington, March 12 (Reporters Xiong Maoling and Hu Yousong) According to calculations and reports from many mainstream media in the United States, current President Biden confirmed the Democratic presidential nomination for the 2024 U.S. presidential election on the 12th.

Biden won the Democratic primaries in Georgia and Mississippi that day, and more than half of the total number of delegates to this year’s Democratic National Convention has been locked. That means he will be the Democratic presidential candidate again. Biden issued a statement thanking voters for once again letting him represent the Democratic Party, while attacking Republican opponent, former President Trump.

According to calculations by US media, Trump won the Republican primaries in Georgia and Mississippi. He is close to locking in this year’s Republican presidential nomination and is expected to face Biden again in the general election. Biden won the 2020 U.S. presidential election, but Trump refused to admit defeat and claimed large-scale electoral fraud.

On the 12th, primary elections were held in Georgia, Mississippi, Washington and other states and territories. As of press time, the U.S. media have not released the results of primary elections in places other than Georgia and Mississippi.

Trump and Biden recently held respective campaign events in Georgia, attacking each other and kicking off the showdown. The New York Times article wrote: The duel between the two officially begins, which will be a painful, cruel and lengthy competition.

The primary election is the first phase of the U.S. presidential election and will last until June. After the primary election, the Democratic Party and the Republican Party will each hold a national convention to formally nominate the presidential and vice presidential candidates. The polling day for this year’s U.S. election is November 5. (Participating reporter: Sun Ding)

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According to a report by Russia’s Lenta on July 16, Slutsky, chairman of the International Affairs Committee of the Russian State Duma (lower house of parliament) and leader of the Liberal Democratic Party, said on the telegram social platform that Moscow will not participate in the peace summit on Ukraine’s conditions.

According to reports, on July 15, Ukraine President Zelensky proposed inviting Russia to attend the next peace summit.

I’m setting tasks so that we can come up with a fully mature plan in November, Zelensky said. After the plan is finalized, everything will be ready for the second summit.

Reported that the U.S. State Department expressed support for Ukraine’s decision to invite Russia to participate in the next peace summit. (Compiled by He Yingjun)

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Russian President Vladimir Putin said on the 13th that he would redeploy troops on the border between Russia and Finland in response to Finland’s accession to NATO, UPI reported on March 13.

Reported that Putin said in an interview with Russian state media that from the perspective of safeguarding national interests, the actions of Finland and Sweden are absolutely meaningless.

We used to have a good relationship with Finland on the whole, he said. It’s perfect. The two countries do not covet each other, especially territorial claims, let alone other areas. We didn’t even have troops at the border; we withdrew all our troops from the Finnish border.

But this is their decision, Putin said. Now that they have decided that we did not have troops there in the past, we will have them now.

It is reported that in 2022, shortly after Russia sent troops to Ukraine, Finland and Sweden applied to join NATO. Finland became a member of NATO in April last year, and Sweden did not formally join until last week because of opposition from Hungary and Turkey.

Putin’s remarks came after Finnish Prime Minister Peter Riolpo told the European Parliament in Strasbourg that other EU countries must follow Finland’s example and strengthen security in marginal areas. (compiled by Wang Dongdong)

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Putin warns the West: ready for nuclear war

Russian President Vladimir Putin has warned the West that Russia is technically ready for a nuclear war and that if the United States sends troops to Ukraine, it will be seen as a major escalation of the war, Reuters reported on March 13.

Putin accepted a joint interview with Russia-1 Channel and Russian News Agency on the 12th. The program about this interview was officially broadcast on the 13th.

In response to the question of whether Russia is really ready to fight a nuclear war, Putin said: from the perspective of military technology, we are certainly ready, the report said.

Putin pointed out that the United States understands that if it deploys US troops on Russian territory or in Ukraine, Russia will regard this as intervention. So while I don’t think it’s all in a hurry to [nuclear confrontation” target=_blank>, we are ready for it, he said.

The conflict in Ukraine triggered the most serious crisis in relations between Russia and the West since the Cuban missile crisis in 1962. Putin has repeatedly warned that if the West sends troops to fight in Ukraine, it could lead to a nuclear war.

In the interview, Putin reiterated that the use of nuclear weapons is something already stated in the Kremlin’s nuclear policy, which sets out the possible use of nuclear weapons by Russia.

Putin said: weapons exist to use them. We have our own principles.

The report also said that for the conflict in Ukraine, which has lasted for two years, Putin said that Russia is ready to hold serious talks on the Ukraine issue.

Putin said: Russia is ready to negotiate on Ukraine, but the negotiations should be based on reality, not on desire after the use of psychotropic substances.

Reuters reported last month that Putin’s proposal to cease fire in Ukraine to freeze the war was rejected by the United States after middlemen between Russia and the United States.

According to the report, he also said in an interview that if the United States conducts a nuclear test, Russia may do the same.

We may not have to consider this issue, but I do not rule out the possibility that we will do the same, he said. (compiled by Longjun)

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Jerusalem, March 23 (Reporters Wang Zhuolun and Lu Yingxu) The Israel Defense Forces issued a situation report on the 23rd, saying that only when all Palestinian militants at Shifa Hospital in Gaza City are captured will the Israeli army end its military operations in the Gaza Strip, the largest hospital.

The report quoted Finkelman, commander of the Israel Defense Forces ‘Southern Military Region, as saying that the Israeli army’s operation at Shifa Hospital is important and complex. The Israeli army is continuing this operation until the last Palestinian militant falls into the Israeli army’s hands, whether alive or dead. The Israeli army’s operation at Shifa Hospital will not end.

Earlier in the day, the Israeli army issued a situation report saying that the Israeli army had killed more than 170 Palestinian militants and arrested more than 800 suspects during its operation at Shifa Hospital. The Israeli army found weapons and facilities of Palestinian armed groups in the hospital. The sick and wounded in Shifa Hospital have been evacuated to designated compounds, and the Israeli army has also assisted trucks carrying medical equipment, food and water into the hospital.

Palestinian official news agency Wafa quoted Gaza medical sources as saying on the 23rd that Shifa Hospital was in harsh conditions and lacked water, food and medical services. Five Palestinian patients died that day. The Israeli army arrested about 240 patients and their caregivers, as well as 10 medical staff inside the hospital complex.

On the 18th of this month, Israeli troops invaded Shifa Hospital and issued a statement saying that intelligence showed that Palestinian Islamic Resistance Movement (Hamas) militants had recently entered Shifa Hospital and used the hospital as a command center. The Israeli army took military action against Shifa Hospital in November last year and claimed that Hamas ‘combat command center and military equipment were found in the hospital. The Gaza Strip health department denied this.