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Philosophers have been studying human thinking and non-human thinking for more than two thousand years. However，they have not yet obtained satisfactory answers.Below，we will combine our own understanding to define Artificial Intelligence.
Human intelligence is the ability of humans to understand and learn things. In other words，intelligence is the ability to think and understand rather than the ability to do things instinctively. Others think intelligence is the ability to apply knowledge to deal with the environment or abstract thinking ability measured by target criteria.
Intelligent Machine is a kind of machine that can show human intelligent behavior，and this intelligent behavior is human using the brain to consider problems or create ideas. There is another definition of Intelligent Machine. Intelligent Machine is a machine that can perform various anthropomorphic tasks in an uncertain environment to achieve expected goals.
The term Artificial Intelligence was first coined by John McCarthy in 1956 when he held the first academic conference on the subject. But the journey to understand if machines can truly think began much before that. In Bush’ s seminal work As We May Think ，he proposed a system which amplifies people's own knowledge and understanding.Five years later，Alan Turing wrote a paper on the notion of machines being able to simulate human beings and the ability to do intelligent things，such as playing chess. No one can refute a computer's ability to process logic. But to many it is unknown if a machine can think. The precise definition of think is important because there has been some strong opposition as to whether or not this notion is even possible. For example，there is the so-called Chinese room argument. Imagine someone is locked in a room，where they were passed notes in Chinese. Using an entire library of rules and look-up tables，they would be able to produce valid responses in Chinese，but would they really understand the language？ This argument has been refuted in numerous ways by researchers，but it does undermine people’ s faith in machines and so-called Expert Systems in life-critical applications.
The main advances over the past sixty years have been advances in search algorithms ，Machine Learning algorithms，and integrating statistical analysis into understanding the world at large. However，most of the breakthroughs in AI aren't noticeable to most people. Rather than talking machines used to pilot space ships to Jupiter， AI is used in more subtle ways，such as examining purchase histories and influencing marketing decisions. What most people think of as “ true AI ” hasn't experienced rapid progress over the decades. A common theme in the field has been to overestimate the difficulty of foundational problems. Significant AI breakthroughs have been promised “in 10 years” for the past 60 years. In addition，there is a tendency to redefine what “ intelligent” means after machines have mastered an area or problem.This so-called “AI Effect” contributed to the downfall of US based AI research in the 80s.In the field of AI，expectations seem to always outpace reality. After decades of research，no computer has come close to passing the Turing Test ，which is shown in Fig. 1.1 below；Expert Systems have grown but have not become as common as human experts；and while we’ ve built software that can beat humans at some games，open ended games are still far from the mastery of computers. Is the problem simply that we haven’ t focused enough resources on basic research，as is seen in the AI winter section，or is the complexity of AI that we haven't yet come to grasp yet？ And instead，like in the case of computer chess，we focus on much more specialized problems rather than understanding the notion of “understanding” in a problem domain.
Fig. 1.1 Turing Test
If someone asked you what your definition of AI or Artificial Intelligence was，what would you say？ In my own seminars，I try to keep things simple，defining AI as using computers to do things that normally require human intelligence. For a more detailed and complete definition，however，I personally like this one from the online publication Quartz ：
“Artificial Intelligence is software or a computer program with a mechanism to learn.It then uses that knowledge to make a decision in a new situation，as humans do. The researchers building this software try to write code that can read images，text，video，or audio，and learn something from it. Once a machine has learned，knowledge can be put to use elsewhere.”
In other words，we might say that AI is the ability of machines to use algorithms to learn from data，and use what has been learned to make decisions like a human would.Unlike humans，though，AI-powered machines don’ t need to take breaks or rest and they can analyze massive volumes of information all at once. The ratio of errors is also significantly lower for machines that perform the same tasks as their human counterparts.
Artificial Intelligence is a complex topic. For that reason，there are several definitions that you might encounter. Here is one of the most accurate ones：“ The theory and development of computer systems make it possible to perform tasks normally requiring human intelligence，such as visual perception，speech recognition，decision making，and translation between languages.”
Initial efforts at AI involved modeling the neurons in the brain. Artificial Neuron is treated as a binary variable that is switched either on or off. This notion was first proposed and was furthered by Hebb when he developed Hebbian learning for neural networks. In 1951，Marvin Minsky and Dean Edmonds built the Stochastic Neural Analog Reinforcement Calculator （ SNARC ），the first neural network computer. Following this accomplishment and Turing’ s development of the Turing Test，researchers became increasingly interested in the study of neural networks and intelligent systems，resulting in McCarthy organizing a 2-month workshop involving interested researchers at Dartmouth University in 1956. He coined the term Artificial Intelligence at that workshop.Attendees included Minsky，Shannon（the developer of information theory），and many others. AI emerged as a new discipline whose goal was to create computer systems that could learn，react，and make decisions in a complex，changing environment.
Abandoning the philosophical question of what it means for an artificial entity to think or have intelligence，Turing developed an empirical test of Artificial Intelligence，which is more appropriate to the computer scientist endeavoring to implement Artificial Intelligence on a computer. The Turing Test is an operational test；that is，it provides a concrete way to determine whether the entity is intelligent. The test involves a human interrogator who is in one room，another human being in a second room，and an artificial entity in a third room. The interrogator is allowed to communicate with both the other human and the artificial entity only with a textual device such as a terminal. The interrogator is asked to distinguish the other human from the artificial entity based on answers to questions posed by the interrogator. If the interrogator can not do this，the Turing Test is passed and we say that the artificial entity is intelligent. Note that the Turing Test avoids physical interaction between the interrogator and the artificial entity；the assumption is that physical interaction is not necessary for intelligence. For example，HAL in the movie Space Odyssey is simply an entity with which the crew communicates，and HAL would pass the Turing Test. If the interrogator is provided with visual information about the artificial entity so that the interrogator can test the entity's ability to perceive and navigate in the world，we call the test the total Turing Test. The Terminator in the movie of the same name would pass this test. Searle took exception to the Turing Test with his Chinese room thought experiment. The experiment proceeds as follows. Suppose that we have successfully developed a computer program that appears to understand Chinese. That is，the program takes sentences written with Chinese characters as input，processes the characters，and outputs sentences written using Chinese characters. If it is able to convince a Chinese interrogator that it is a human，then the Turing Test would be passed. Searle asks “ Does the program literally understand Chinese，or is it only simulating the ability to understand Chinese？” To address this question，Searle proposes that he could sit in a closed room holding a book with an English version of the program，and adequate paper and pencils to carry out the instructions of the program by hand. The Chinese interrogator could then provide Chinese sentences through a slot in the door，and Searle could process them using the program's instructions and send Chinese sentences back through the same slot. Searle says that he has performed the exact same task as the computer that passed the Turing Test. That is，each is following a program that simulates intelligent behavior. However，Searle notes that he does not speak Chinese. Therefore，because he does not understand Chinese，the reasonable conclusion is that the computer does not understand Chinese either. Searle argues that if the computer is not understanding the conversation，then it is not thinking，and therefore it does not have an intelligent mind. Searle formulated the philosophical position known as strong AI，which is as follows：The appropriately programmed computer really is a mind，in the sense that computers given the right programs can be literally said to understand and have other cognitive states.
Based on his Chinese room experiment，Searle concludes that strong AI is not possible. He states that “I can have any formal program you like，but I still understand nothing.” Searle's paper resulted in a great deal of controversy and discussion for some time to come（see，for example）. The position that computers could appear and behave intelligently，but not necessarily understand，is called weak AI. The essence of the matter is whether a computer could actually have a mind（strong AI）or could only simulate a mind（weak AI）. This distinction is of greater concern to the philosopher who is discussing the notion of consciousness. Perhaps a philosopher could even argue that emergentism might take place in the Chinese room experiment，and a mind might arise from Searle performing all his manipulations. Practically speaking，none of this is of concern to the computer scientist. If the program behaves as if it is intelligent，computer scientists have achieved their goal.