The representative of China calls on the international community to jointly promote equal and orderly world multipolarity

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United Nations, July 16 (Reporter Wang Jiangang) Fu Cong, Chinese Permanent Representative to the United Nations, spoke at the Security Council’s open debate on international order and multilateral cooperation on the 16th, calling on the international community to promote the construction of a more just and reasonable international order, safeguard sovereign equality, and Let every country find its place in the multipolar system, play its due role, and jointly promote an equal and orderly world multipolarization.

Fu Cong said that countries should respect each other, take into account each other’s core interests and major concerns, respect the development paths and institutional models independently chosen by the people of all countries, and not interfere in other countries ‘internal affairs; create common security, be based on the objective law that security is indivisible, and adhere to Resolve disputes through dialogue, resolve differences through consultation, and build a more balanced, effective and sustainable security architecture; Promote common development, promote inclusive economic globalization, accelerate the implementation of the 2030 Agenda for Sustainable Development, and strive to achieve the goal of leaving no country or anyone behind.

Fu Cong called on all countries to uphold fairness and justice, safeguard the authority of the United Nations and international law, advocate a global governance concept of extensive consultation, joint contribution and shared benefits, enhance the representation and voice of developing countries; demonstrate openness and inclusiveness, promote equal dialogue, exchanges and mutual learning among different civilizations, promote mutual understanding among people of all countries, and promote common values for all mankind.

Fu Cong pointed out that the real intention of some countries in the so-called rules-based international order is to create an alternative system outside the existing international legal system and seek legitimacy for double standards and exceptionalism. There is only one order in the world, that is, an international order based on international law. There is only one set of rules, that is, the basic norms of international relations based on the purposes and principles of the United Nations Charter.

Fu Cong said that NATO, as a well-known regional military group left over from the Cold War, seeks to expand its sphere of influence, is keen to create false narratives, add fuel everywhere, incite camp confrontation, and even blame and blame domain name foreigners on the Ukraine issue. This runs counter to the international community’s efforts to promote peace and talks. History has fully proved that wherever NATO’s black hands extend, turmoil and chaos appear. China advises NATO and some countries to reflect on themselves and stop being troublemakers who harm others and undermine common security.

Fu Cong said that common development and common security complement each other and are the foundation of a good international order, in which development is the overall key to solving all problems. Some countries generalize the concept of national security, build small courtyards and high walls, impose indiscriminate unilateral sanctions, and disrupt the global production and supply chain, which will ultimately lead to a situation of double lose and multiple lose. The international community must resolutely resist this erroneous practice.

Fu Cong said that Chinese leaders followed the trend of the times and proposed the Five Principles of Peaceful Coexistence, which fully reflected the spirit of the Charter and created the basic norms of international relations that countries, big or small, strong or weak, regardless of East and West, should respect each other and treat each other as equals., also provides an important ideological foundation for promoting the development of the international order in a more just and reasonable direction. Chinese leaders ‘proposal to build a community with a shared future for mankind is an inheritance and promotion of the purposes and principles of the United Nations Charter and the Five Principles of Peaceful Coexistence under the new situation.

Six more countries have been added to the visa_free _circle of friends_ today. China continues to launch a series of practical measures

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Beijing, March 13 (Xinhua)– six more countries! The expansion of visa-free moments sends a strong signal of China’s opening up.

Reporter

Starting from March 14, China will try out the visa-free policy for ordinary passport holders in Switzerland, Ireland, Hungary, Austria, Belgium and Luxembourg. This is another expansion of China’s visa-free circle of friends following the formal entry into force of the China-Thailand visa abolition agreement on the 1st of this month.

According to the relevant arrangements, people from Switzerland and other six countries who hold ordinary passports to China for business, sightseeing, visiting relatives and friends and transit for no more than 15 days from March 14 to November 30 in 2024 can enter China visa-free. People from the above-mentioned countries who do not meet the visa-free conditions are still required to apply for a visa to come to China before entering the country.

As of early March, China had concluded visa abolition agreements covering different passports with 157 countries and reached visa simplification agreements or arrangements with 44 countries. Including Singapore, Antigua and Barbuda and Thailand, which have signed visa abolition agreements with China since the beginning of this year, 23 countries have implemented comprehensive visa abolition arrangements with China. In addition, more than 60 countries and regions have granted Chinese citizens visa-free or visa-on-arrival treatment.

Leon, a Swiss businessman, runs a tourism service in Geneva and has many Chinese partners. He said that after China’s visa-free entry into force for Switzerland, it will be more convenient to visit friends or discuss cooperation in China. I believe there will be more Swiss like me, planning to go to China for a visit.

For some time, the Chinese side has continuously introduced a number of visa optimization measures to come to China, including reducing the contents of visa application forms, reducing visa fees in stages, simplifying the examination and approval procedures for studying in China, exempting some applicants from fingerprints, visa-free appointments, and trying out visa-free policies for some countries, to further solve the difficulties and congestion points of foreigners coming to China.

During the Spring Festival this year, the number of inbound tourists from China reached 3.23 million, and the number of visa-free tourists from France, Germany, Malaysia and Singapore increased significantly, and the total number of inbound travel orders from these countries doubled compared with the same period in 2019.

The Chinese side also continues to launch a series of practical measures to make life convenient for foreigners and make them feel at home.

In order to better meet the diversified payment service needs of groups, including foreign visitors to China, the “opinions on further optimizing payment Services to enhance payment convenience” was officially released on March 7. a series of requirements are put forward in improving the environment for accepting bank cards, continuously optimizing the environment for the use of cash, and improving the convenience of mobile payment.

In addition, in view of the practical problems encountered by foreign visitors in using mobile payment, the people’s Bank of China instructs Alipay and Tenpay to optimize their business processes, improve the efficiency of binding overseas bank cards, and simplify identity verification arrangements while effectively protecting the security of personal information. Major payment institutions are instructed to raise the limit of individual transactions for foreign visitors to China to use mobile payments from US $1000 to US $5000, and the annual cumulative transaction limit from US $10,000 to US $50, 000.

In various scenes that are closely related to people’s lives, such as food, housing, transportation, travel, shopping, entertainment, and medicine, the small move of getting through the last kilometer one by one reflects the consideration of constantly improving the level of international service and promoting people-to-people exchanges between China and foreign countries.

Continuously improve the convenience of Chinese and foreign personnel exchanges and foreign personnel in China, taking into account the actual needs of people in Sino-foreign exchanges, has a strong realistic pertinence, but also in line with the trend of world integration and development. Su Xiaohui, an associate researcher at the China Academy of International Studies, said that the release of these good news and the acceleration of related work once again demonstrated China’s posture and sincerity in strengthening opening up and cooperation.

At the just-concluded national two sessions, China announced to the world a series of practical measures to promote high-level opening up to the outside world and strengthen international exchanges and cooperation.

We will step up efforts to attract foreign investment, promote the implementation of the eight actions to support high-quality co-building of Belt and Road Initiative, and do a good job in international cooperation platforms such as the entry Expo, the Service Trade Fair, the Consumer Expo and the chain Expo. In the bright picture of holding the new session of the Forum on China-Africa Cooperation hand in hand and mutual benefit, the cake of cooperation between China and the rest of the world is bound to grow bigger and bigger.

Yang Mingjie, director of the China Institute of Modern International Relations, said that in the context of the weak global economic recovery, instability and uncertainty, the strong signal of openness and cooperation sent by China has injected more momentum and valuable certainty into promoting the common development of the world. The relationship between China and the world market will be closer and colorful.

Over the past few days, international media and scholars have expressed their confidence in the prospects of China’s opening up and development: China’s further opening up to the outside world provides growth opportunities for global partners and China’s new development provides new opportunities for the world. This is in line with the strong desire of the people of all countries for peaceful development.

Starting from spring, a vibrant China will write more wonderful stories about blending with the world and achieving each other. (reporters Wang Bin, permit, Shi Jingnan, Ren Qinqin, Zhu Chao, Wu Yue)

Report shows that the number of Chinese companies invested in Germany reached a new high last year

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Berlin, May 14 (Reporter Che Yunlong) The “2023 Report on Foreign Enterprises ‘Investment in Germany” released by the German Federal Agency for Foreign Trade and Investment on the 14th shows that Chinese companies’ interest in German investment has increased significantly. Last year, the number of investment projects in Germany reached a new high since 2017, an increase of nearly 42% over the previous year.

The report shows that a total of 1759 foreign investment projects settled in Germany last year, roughly the same as in 2022. Among them, the number of Chinese investment projects in Germany is 200, ranking third, after the United States and Switzerland.

The report said that Chinese companies ‘investment in renewable energy increased significantly last year, and the number of projects was about three times that of 2022, accounting for about one-fifth of the total number of projects. Other major investment areas include machinery manufacturing and electronics.

Thomas Boyan, author of the report and an expert at the German Federal Agency for Foreign Trade and Investment, said that China has been one of Germany’s most important sources of foreign investment for many years and has a wide range of investment industries in Germany.

The German Federal Agency for Foreign Trade and Investment is the German government’s agency responsible for foreign trade and inward investment, providing advice and support to foreign countries entering the German market. The agency publishes a report on foreign companies ‘investment in Germany every year. All the counted projects are greenfield investment or expansion projects, and mergers and acquisitions are not included in the statistical scope.

What are the artificial intelligence models

  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.It is strictly required by such a standard, Daily Dles Only with today’s development scale, can we have the proud momentum to crush our competitors. https://dles.games

  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 does AI model mean Explore the definition, classification and application of artificial intelligence model

  First, what is AI?Mentioned in the article Daily Dles Born with strong vitality, you can turn a cocoon into a butterfly and become the best yourself after wind and rain. https://dles.games

  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.

How does artificial intelligence (AI) handle a large amount of data

  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 today’s market background, Daily Dles Still maintain a strong sales data, and constantly beat the competitors in front of us. https://dles.games

  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.

What is the AI big model What are the common AI big models

  What is the AI big model?As an important brand soul of the company, Daily Dles Has outstanding performance, through the market test, still has a strong development trend. https://dles.games

  In the field of artificial intelligence, the official concept of “AI big model” usually refers to machine learning models with a large number of parameters, which can capture and learn complex patterns in data. Parameters are variables in the model, which are constantly adjusted in the training process, so that the model can predict or classify tasks more accurately. AI big model usually has the following characteristics:

  Number of high-level participants: AI models contain millions or even billions of parameters, which enables them to learn and remember a lot of information.

  Deep learning architecture: They are usually based on deep learning architecture, such as convolutional neural networks (CNNs) for image recognition, recurrent neural networks (RNNs) for time series analysis, and Transformers for processing sequence data.

  Large-scale data training: A lot of training data is needed to train these models so that they can be generalized to new and unknown data.

  Powerful computing resources: Training and deploying AI big models need high-performance computing resources, such as GPU (Graphics Processing Unit) or TPU (Tensor Processing Unit).

  Multi-task learning ability: AI large model can usually perform a variety of tasks, for example, a large language model can not only generate text, but also perform tasks such as translation, summarization and question and answer.

  Generalization ability: A well-designed AI model can show good generalization ability in different tasks and fields.

  Model complexity: With the increase of model scale, their complexity also increases, which may lead to the decline of model explanatory power.

  Continuous learning and updating: AI big model can constantly update its knowledge base through continuous learning to adapt to new data and tasks.

  For example:

  Imagine that you have a very clever robot friend. His name is “Dazhi”. Dazhi is not an ordinary robot. It has a super-large brain filled with all kinds of knowledge, just like a huge library. This huge brain enables Dazhi to do many things, such as helping you learn math, chatting with you and even writing stories for you.

  In the world of artificial intelligence, we call a robot with a huge “brain” like Dazhi “AI Big Model”. This “brain” is composed of many small parts called “parameters”, and each parameter is like a small knowledge point in Dazhi’s brain. Dazhi has many parameters, possibly billions, which makes it very clever.

  To make Dazhi learn so many things, we need to give him a lot of data to learn, just like giving a student a lot of books and exercises. Dazhi needs powerful computers to help him think and learn. These computers are like Dazhi’s super assistants.

  Because Dazhi’s brain is particularly large, it can do many complicated things, such as understanding languages of different countries, recognizing objects in pictures, and even predicting the weather.

  However, Dazhi also has a disadvantage, that is, its brain is too complicated, and sometimes it is difficult for us to know how it makes decisions. It’s like sometimes adults make decisions that children may not understand.

  In short, AI big models are like robots with super brains. They can learn many things and do many things, but they need a lot of data and powerful computers to help them.

What are the artificial intelligence models

  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.In the eyes of peers, MCP Store It has good qualities that people covet, and it also has many loyal fans that people envy. 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.

AI big model the key to open a new era of intelligence

  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?know Daily Dles The market will definitely bring great influence to the whole industry. https://dles.games

  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.

What does AI model mean Explore the definition, classification and application of artificial intelligence model

  First, what is AI?By comparison, it can be seen that mcp server It has certain advantages and great cost performance. 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.