标签归档 南京桑拿

Ignite the "fire" of winter tourism

Source: [Ningxia Daily]

This winter, Yinchuan focused on emerging consumption hotspots, new consumption formats and trendy consumption scenes, and created five characteristic themes, 66 winter tourism projects and 112 sub-activities according to local conditions, presenting new products, new formats, new scenes, new ways of playing and new concessions of Yinchuan’s winter cultural tourism in multiple dimensions, and giving full play to the promotion of winter tourism marketing to the cultural tourism market.

Offering tourists a "big meal" of cultural tourism with rich cultural flavor and many new ways to play, so that tourists can experience the different winter in magical Ningxia in one stop. It must be said that the relevant departments have really made great efforts in tourism promotion. When it comes to visiting Ningxia, most people think that the best time period is the warmer weather season, and winter is the off-season of tourism. In fact, tourism has no off-season market, only off-season ideas. Seasons have never been the key factor that restricts the development of tourism. The key is whether the seasons can make a different feeling. Even if winter is not the most beautiful season in the traditional sense of Ningxia, as long as it is done with characteristics, it can ignite the "fire" of off-season tourism and give tourists a different experience.

To "break the ice" in the off-season, thoughts must be "thawed" first. Pursuing the "difference" of winter tourism is rooted in the change of thinking mode and working mode. Continue to explore the characteristic culture, enrich the tourism format, gather the tourist popularity, improve the industrial chain, carefully study what are their own characteristics and advantages, and then, with the confidence of winning and effective measures, promote the winter tourism market to flourish, which will surely make more tourists feel the unique winter scenery, come to Ningxia and fall in love with Ningxia.

This article comes from Ningxia Daily and only represents the author’s point of view. The national party media information public platform provides information dissemination and dissemination services.

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Warriors Clippers reached a 3-for-1 deal! George teamed up with Curry! Paul returned to Los Angeles.

The Warriors Clippers reached a three-for-one deal, and George teamed up with Curry Paul to return to Los Angeles. With the deepening of Hugh Secchi, many teams have completed the reinforcement of their lineup. For the Golden State Warriors, their lineup is not perfect enough.

I have to admit that Chris Paul still has some trading value on the court, and many players played in his series for the Suns last season, and Booker is very grateful to Paul.

He said, in fact, when I was young, I learned to play like Paul, but I never had the opportunity to join hands with him. After joining hands with him, I also made up for my previous organizational deficiencies, and he will become one of the most important teachers in my basketball career. Paul himself must be very happy to have such praise.

According to saxophone, the management of Golden State Warriors is currently in contact with the management of Clippers, and they seem to want Paul George very much. The Los Angeles Clippers also think they need a mature point guard, so the Warriors may exchange Chris Paul for Paul George. What do you think of this deal?

Brief introduction of Artificial Intelligence (AI)

The development history of Artificial Intelligence (AI) can be traced back to 1950s. The following are the main stages of the development history of AI:

  1. Logical reasoning and problem solving (1950s-early 1960s): The early AI system was based on symbolic logic, and solved problems through logical reasoning of facts and rules. However, this method has limitations, and it is difficult to deal with a large number of uncertain and fuzzy information.
  2. Machine learning and pattern recognition (1960s-1980s): The research of AI began to turn to machine learning and pattern recognition. Machine learning is a method to learn and optimize algorithms by training data, while pattern recognition is a method to realize intelligence by identifying and classifying patterns. These methods have been widely used in image recognition, speech recognition and natural language processing.
  3. Expert system and knowledge representation (1980s-1990s): AI research began to pay attention to expert system and knowledge representation. Expert system is an intelligent system based on expert knowledge and inference rules, which can simulate the decision-making process of human experts. Knowledge representation is a method to organize knowledge and information into a form that can be processed by computer, and it is an important foundation to realize AI.
  4. Statistical learning and deep learning (1990s-2010s): With the continuous development of computer hardware and algorithms, AI research began to pay attention to statistical learning and deep learning. Statistical learning is a machine learning method based on statistical model and data analysis, which can handle a large number of data and complex nonlinear relationships. Deep learning is a machine learning method based on neural network, which can handle more complex and high-dimensional data.
  5. Self-learning and multi-modal AI(2010 to present): AI system is gradually realizing the ability of self-learning and self-optimization, and can continuously improve its own model and algorithm according to feedback and data. Multi-modal AI is an AI technology that can handle a variety of data types and perceptual information, including images, voices, texts, etc., and can realize more comprehensive and intelligent human-computer interaction.

Important events:

  • In 1956, the concept of artificial intelligence was put forward at Dartmouth Conference, which marked the birth of AI.
  • In 1962, Arthur Samuel developed a self-learning program, which was an early application of machine learning.
  • In 1969, Marvin Minsky and Seymour Papert published Perceptrons, which revealed the limitations of single-layer neural networks and promoted the development of neural networks.
  • In 1975, John Holland developed genetic algorithm, which is an optimization algorithm that imitates the process of biological evolution.
  • In 1981, Japan launched the first commercial robot WABOT-1.
  • In 1997, IBM’s deep blue supercomputer defeated Kasparov, the world champion of chess, indicating that computers can surpass human intelligence in some fields.
  • In 2011, IBM’s Watson artificial intelligence system defeated human players in the program "Dangerous Edge".
  • In 2016, AlphaGo defeated Li Shishi, the world champion in the Go competition, marking an important step in the application of artificial intelligence in complex games.
  • In 2018, the GPT-2 model developed by OpenAI made a major breakthrough in the field of natural language processing, which can generate high-quality natural language texts.

The latest development trend:

  1. Self-learning: AI system is gradually realizing the ability of self-learning and self-optimization, and can continuously improve its own model and algorithm according to feedback and data.
  2. Deep learning: Deep learning is a machine learning method based on neural network, which can handle a large number of data and complex nonlinear relationships, and is one of the main trends of current AI development.
  3. Artificial intelligence chip: Artificial intelligence chip is a chip specially designed for AI application, which can realize efficient calculation and data processing and is an important technical support for AI popularization and application.
  4. Multi-modal AI: Multi-modal AI is an AI technology that can handle a variety of data types and perceptual information, including images, voices, texts, etc., and can realize more comprehensive and intelligent human-computer interaction.
  5. AI and Internet of Things: The combination of AI and Internet of Things can realize more intelligent and efficient automatic production and management, including intelligent energy, intelligent transportation, smart home and other fields.
  6. AI Ethics and Law: With the continuous development and application of AI technology, AI ethics and legal issues have attracted more and more attention, including privacy protection, data security, and responsibility distribution.

In short, the development trend of AI technology is diverse, involving algorithms, chips, data and applications. In the future, AI technology will continue to develop and apply in depth, bringing more convenience and innovation to mankind.