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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.