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Artificial intelligence science popularization
Artificial intelligence science popularization
The frequency of people with artificial intelligence in everyday life is getting higher and higher, a Jingdong smart refrigerator that can help users to buy food; a machine that can be automatically translated; a robot assistant such as Siri, Alexa and Cortana; and unmanned vehicles and AlphaGo have already brought artificial intelligence to "see to feel". . Artificial intelligence is surging in an unprecedented situation, and the total amount of financing in the related fields has been growing steadily year by year, reaching billions of dollars in 2016. So what is artificial intelligence in the end? What are the aspects of this area? What are the goals and tasks of artificial intelligence? The next content will be introduced one by one.
1. what is artificial intelligence
AI defined by Alan Turing is the science that enables computers to accomplish tasks that require human intelligence. Stanford University scholars believe that AI is the science and engineering of intelligent machines, especially intelligent computer programs. The Wikipedia definition of AI refers to the intelligence shown by an artificial system, and the word also refers to the scientific field of how such an intelligent system can be realized and how it is implemented. No matter how it is defined, intelligence can not be separated, but so far human beings have not yet been able to give a unified definition of intelligence, which is usually referred to as a representation of human intelligence. Professor Zhong Yixin, the director of the former China artificial intelligence society, believes that human intelligence includes three aspects of finding problems, defining problems and solving problems, while artificial intelligence has only been able to solve the problem at present. The author thinks that intelligence is an order, a manifestation of information, and an ability to make the world develop in an orderly way. Sadly, according to the entropy principle, no matter what the agent does, the whole universe is always going in the direction of entropy increasing, that is, more and more disorder and chaos. I wonder if this is a deliberate arrangement by God, or is there another world beyond the universe observed by mankind?
2. the history of artificial intelligence
In the early 1950s, AI focused on so-called AI, hoping that machines could complete any mental tasks like human beings. The development of strong AI has stopped, leading to the emergence of weak artificial intelligence, that is, the application of AI technology to narrower fields. Before 1980s, the research of AI has been divided by these two paradigms, and the two battalion is opposite. But in the 1980, machine learning began to become the mainstream, and its purpose was to make computers have the ability to learn and build models, so that they could make predictions in a particular field.
In history, artificial intelligence has three universities: symbolicism, also called logicism, psychologism, or computer school (computerism), whose principles are the hypothesis of physical sign system (i.e., symbolic operating system) and the principle of limited rationality. Connectionism (connectionism), also known as the bionics (bionicsism) or the physiological school (physiologism), is the main principle of the connection mechanism and learning algorithm between the neural network and the neural network. Behaviorism (actionism), also known as the evolutionism or the cybernetics School of Cybernetics (cyberneticsism), is the principle of control and perception action control system.
Symbolism holds that AI is derived from mathematical logic. The term "artificial intelligence" was first adopted in 1956. Later, we developed the heuristic algorithm > expert system > knowledge engineering theory and technology, and made great progress in 1980s.
Connectionism holds that artificial intelligence originates from bionics, especially the study of human brain models. In the 60~70 years of twentieth Century, the study of brain models represented by perceptron was upsurge in the twentieth Century years. Due to the limitations of theoretical models, biological prototypes and technical conditions at that time, the brain model study fell into the low tide from the late 1970s to the early 80s. Until professor Hopfield published two important papers in 1982 and 1984, he put forward the idea that connectionism would rise again after simulating the neural network with hardware. In 1986, Rumelhart and Rumelhart put forward a backpropagation algorithm (BP) in multilayer networks. Since then, the research of the convolution neural network (CNN), the momentum of the connectionism, from the model to the algorithm, from the theoretical analysis to the engineering implementation, for the neural network computer to lay the foundation for the market. In 2006, Hinton published papers on Science and related periodicals, and first proposed the concept of deep belief network (DBN), which pushed deep learning to the academic field and became a hot research direction in the field of artificial intelligence.
Behaviorism believes that artificial intelligence is derived from cybernetics. Cybernetics was an important part of the trend of thought in the twentieth Century 40~50 era, which affected the early AI workers. The control theory and self-organizing system proposed by Weiner (Wiener) and Mike Locke (McCulloch), as well as the engineering cybernetics and biocybernetics proposed by Tsien Hsueshen et al., have influenced many fields. Cybernetics links the working principles of the nervous system with information theory, control theory, logic and computers. The early research work focuses on the intelligent behavior and function of the simulated human in the control process, such as the research on the control theory system, such as self optimizing, self-adaptive, self composing, self organizing and self-learning, and the development of "control theory animal". By the 60~70 years of twentieth Century, the research on these cybernetics systems has made some progress, sowing seeds of intelligent control and intelligent robots, and the birth of intelligent control and intelligent robot systems in 1980s. Actor
1. what is artificial intelligence
AI defined by Alan Turing is the science that enables computers to accomplish tasks that require human intelligence. Stanford University scholars believe that AI is the science and engineering of intelligent machines, especially intelligent computer programs. The Wikipedia definition of AI refers to the intelligence shown by an artificial system, and the word also refers to the scientific field of how such an intelligent system can be realized and how it is implemented. No matter how it is defined, intelligence can not be separated, but so far human beings have not yet been able to give a unified definition of intelligence, which is usually referred to as a representation of human intelligence. Professor Zhong Yixin, the director of the former China artificial intelligence society, believes that human intelligence includes three aspects of finding problems, defining problems and solving problems, while artificial intelligence has only been able to solve the problem at present. The author thinks that intelligence is an order, a manifestation of information, and an ability to make the world develop in an orderly way. Sadly, according to the entropy principle, no matter what the agent does, the whole universe is always going in the direction of entropy increasing, that is, more and more disorder and chaos. I wonder if this is a deliberate arrangement by God, or is there another world beyond the universe observed by mankind?
2. the history of artificial intelligence
In the early 1950s, AI focused on so-called AI, hoping that machines could complete any mental tasks like human beings. The development of strong AI has stopped, leading to the emergence of weak artificial intelligence, that is, the application of AI technology to narrower fields. Before 1980s, the research of AI has been divided by these two paradigms, and the two battalion is opposite. But in the 1980, machine learning began to become the mainstream, and its purpose was to make computers have the ability to learn and build models, so that they could make predictions in a particular field.
In history, artificial intelligence has three universities: symbolicism, also called logicism, psychologism, or computer school (computerism), whose principles are the hypothesis of physical sign system (i.e., symbolic operating system) and the principle of limited rationality. Connectionism (connectionism), also known as the bionics (bionicsism) or the physiological school (physiologism), is the main principle of the connection mechanism and learning algorithm between the neural network and the neural network. Behaviorism (actionism), also known as the evolutionism or the cybernetics School of Cybernetics (cyberneticsism), is the principle of control and perception action control system.
Symbolism holds that AI is derived from mathematical logic. The term "artificial intelligence" was first adopted in 1956. Later, we developed the heuristic algorithm > expert system > knowledge engineering theory and technology, and made great progress in 1980s.
Connectionism holds that artificial intelligence originates from bionics, especially the study of human brain models. In the 60~70 years of twentieth Century, the study of brain models represented by perceptron was upsurge in the twentieth Century years. Due to the limitations of theoretical models, biological prototypes and technical conditions at that time, the brain model study fell into the low tide from the late 1970s to the early 80s. Until professor Hopfield published two important papers in 1982 and 1984, he put forward the idea that connectionism would rise again after simulating the neural network with hardware. In 1986, Rumelhart and Rumelhart put forward a backpropagation algorithm (BP) in multilayer networks. Since then, the research of the convolution neural network (CNN), the momentum of the connectionism, from the model to the algorithm, from the theoretical analysis to the engineering implementation, for the neural network computer to lay the foundation for the market. In 2006, Hinton published papers on Science and related periodicals, and first proposed the concept of deep belief network (DBN), which pushed deep learning to the academic field and became a hot research direction in the field of artificial intelligence.
Behaviorism believes that artificial intelligence is derived from cybernetics. Cybernetics was an important part of the trend of thought in the twentieth Century 40~50 era, which affected the early AI workers. The control theory and self-organizing system proposed by Weiner (Wiener) and Mike Locke (McCulloch), as well as the engineering cybernetics and biocybernetics proposed by Tsien Hsueshen et al., have influenced many fields. Cybernetics links the working principles of the nervous system with information theory, control theory, logic and computers. The early research work focuses on the intelligent behavior and function of the simulated human in the control process, such as the research on the control theory system, such as self optimizing, self-adaptive, self composing, self organizing and self-learning, and the development of "control theory animal". By the 60~70 years of twentieth Century, the research on these cybernetics systems has made some progress, sowing seeds of intelligent control and intelligent robots, and the birth of intelligent control and intelligent robot systems in 1980s. Actor