What is ai and its importance?

Colloquially, the term artificial intelligence is applied when a machine mimics the "cognitive" functions that humans associate with other human minds, such as: "perceiving," "reasoning," "learning," and "problem solving." Andreas Kaplan and Michael Haenlein define artificial intelligence as "the ability of a system to correctly interpret external data, to learn from that data, and to use that knowledge to achieve specific tasks and goals through flexible adaptation". As machines become ever more capable, technology once thought to require intelligence is removed from the definition.

Artificial intelligence is no longer considered an example of it having become a common technology.

Artificial intelligence is a new way of solving problems, which includes expert systems, robot management and control, and processors, which try to integrate knowledge into such systems, in other words, an intelligent system capable of writing its own program. An expert system is a programming structure that is capable of storing and using knowledge about a certain area. In the same way, AI can be considered as the ability of machines to use algorithms, learn from data and use what has been learned in decision-making just as a human being would do, in addition one of the main focuses of artificial intelligence is machine learning, in such a way that computers or machines have the ability to learn without being programmed for it.

According to Takeyas, artificial intelligence is a branch of computer science that studies models capable of carrying out activities typical of human beings based on two of their primary characteristics.

John McCarthy defined artificial intelligence as the science and ingenuity of making intelligent machines.

There are different types of perception and actions that can be obtained and produced by physical and mechanical sensors in machines, electrical or optical pulse in computers, as well as bit inputs and outputs of software and its software environment.

System control, automatic scheduling, the ability to respond to diagnostics and consumer inquiries, handwriting recognition, speech recognition, and pattern recognition are some of the examples. Artificial intelligence systems have been used in a wide variety of computer programs, strategy games, and video games.

Stuart J. Russell and Peter Norvig differentiate different types of artificial intelligence.

There are two schools of thought about the computer program.

It's also known as symbolic-deductive.

The analysis of human behavior in the face of different problems is based on formal and statistical analysis.

Computational intelligence involves interactive development or learning, for example in connection systems.

The knowledge is achieved by the use of facts.

Computational intelligence has two purposes. Its scientific objective is to understand the principles that enable intelligent behavior, whether in natural or artificial systems, and its technological objective is to specify the methods for designing intelligent systems.

Faced with the possibility of creating machines endowed with intelligence, it became important to worry about the ethical issue of machines to try to guarantee that no harm is done to human beings, other living beings and even to the machines themselves according to some currents of thought. thought ​. This is how a broad field of studies known as the ethics of artificial intelligence arose, of relatively recent appearance, which is generally divided into two branches: roboethics, in charge of studying the actions of human beings towards robots, and the ethics of machines. in charge of studying the behavior of robots towards human beings.

Artificial intelligence development in the 21st century has an impact on other fields. During the second industrial revolution there was a phenomenon known as technological unemployment, which refers to when the industrial automation of large-scale production processes replaces human labor. A similar phenomenon could occur with artificial intelligence, especially in processes involving human intelligence, as illustrated in the story How they had fun! by Isaac Asimov, in which his author glimpses some of the effects that the interaction of intelligent machines specialized in child pedagogy, instead of human teachers, would have with children in school.

The three laws of robotics were created by the same writer who wrote the 1942 story Runaround.

Other more recent science fiction works also explore some ethical and philosophical questions regarding Strong Artificial Intelligence, such as the movies I, Robot or A.I. Artificial Intelligence, in which topics such as self-awareness or the origin of an emerging consciousness of intelligent robots or computer systems are dealt with, or if these could be considered subjects of law due to their almost human characteristics related to sentience, such as power being able to feel pain and emotions or to what extent they would obey the purpose of their programming, and if not, if they could exercise free will. The latter is the central theme of the famous Terminator saga, in which the machines surpass humanity and decide to annihilate it, a story that, according to several specialists, could not be limited to science fiction and could be a real possibility in a post-human society that depended of technology and machines entirely. ​

Law plays a fundamental role in the development of artificial intelligence. Laws establish binding rules and standards of behavior to ensure social welfare and protect individual rights, and can help us reap the benefits of this technology while minimizing its risks.

There are no legal regulations that regulate the use of artificial intelligence. The European Commission presented a proposal for a European regulation for the regulation of artificial intelligence in the EU. The title is a proposal for a regulation of the European Parliament and of the Council to set standards for artificial intelligence.

Artificial intelligence research used concepts of probability and economy to develop methods for dealing with incomplete or uncertain information.

These algorithms proved insufficient for solving large reasoning problems because they experienced a "combinatorial explosion": they became exponentially slower as the problems grew. Thus, it was concluded that human beings rarely use deduction. step by step that early artificial intelligence research followed; instead, they solve most of their problems using quick and intuitive judgments.

Knowledge representation and knowledge engineering are fundamental to classical artificial intelligence research. Some systems try to get the knowledge of experts in a field.

Other projects try to assemble the "common sense knowledge" known to the average person into a database containing extensive knowledge about the world.

The topics that a common sense knowledge base would contain are: objects, properties, categories, and relationships between objects.

knowledge about what other people know

Another objective of artificial intelligence is to be able to set goals and achieve them. To do this they need a way to visualize the future, a representation of the state of the world, and to be able to make predictions about how their actions will change it, as long as they can make decisions. decisions that maximize the utility (or "value") of the available options. Russell and Norvig were in 2003

600–604.

The agent can assume that it is the only acting system in the world, which allows it to be sure of the consequences of its actions. This requires an agent that can assess its environment and make predictions, as well as evaluate them and adapt based on its assessment. Russell and Norvig were in the same year.

Multi-agent planning uses the competition and cooperation of many systems to achieve a goal. Evolutionary and swarm intelligence use emergence behavior like this. Russell and Norvig were in 2003

409–454

Machine learning is a fundamental concept of artificial intelligence research, and it involves the study of computer algorithms that improve automatically through experience.

Unsupervised learning is the ability to find patterns in an input stream without a human being involved. Supervised learning requires a human to label the input data. After a program looks at several examples of input from various categories, Sorting is used to determine what category something belongs to.

Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change. Both classifiers and regression learners attempt to learn an unknown function; For example, a spam classifier can be viewed as learning a function that assigns the text of an email to one of two categories, "spam" or "not spam." Computational learning theory can test students by how much data is required, or by other notions.

Natural language processing allows machines to read and comprehend human language. Natural language user interface and the acquisition of knowledge from human written sources are possible with a sufficiently efficient natural language processing system.

Natural language processing can be used to retrieve information, text mining, question answering, and machine translation. Keyword spotting search strategies are popular but less than optimal, as a search query for "dog" can only match documents with the word "poodle" in them. Statistical language processing approaches can combine all of the strategies and achieve acceptable accuracy at the page or paragraph level. The ultimate goal of processing is to have a full understanding of common-sense reasoning.

Machine perception is the ability to use input from sensors to infer aspects of the world. Speech recognition, facial recognition, and object recognition are applications. Russell and Norvig were in the same year. 885–892 Computer vision is the ability to analyze visual information, which is often ambiguous; a giant fifty-meter-tall pedestrian far away can produce the same pixels as a normal-sized pedestrian nearby, requiring artificial intelligence to judge the relative likelihood and reasonableness of different interpretations, for example, using its "information model." object" to assess that fifty-meter pedestrians do not exist.

Artificial intelligence's ability to completely mimic a human being is one of the main criticisms. There are experts who say that no individual human has the capacity to solve all kinds of problems, and authors who theorize about the solution.

Humans have two aspects to their ability to solve problems, innate and learned. The innate aspects allow for storing and retrieving information in memory, while the learned aspects allow for knowing how to solve a mathematical problem using an appropriate algorithm.

In the same way that a human needs tools to solve certain problems, artificial systems need to be programmed in such a way that they can solve them.

Many people think that the Turing Test has been passed because of conversations in which they don't know they're talking to a program. This situation is not the same as a Turing test, which requires the participant to be aware of the possibility of speaking to a machine.

The Chinese room of John Searle has shown how a machine can mimic thought without actually knowing what it is doing, just reacting in a certain way to certain stimuli, just like a human.

The machine is acting according to a preset program, so this would show that it is not thinking. It is possible for Turing to achieve this effect by means of a priori defined rules, if the fact of deceiving a human being is a sign of an intelligent mind.

Communication with the user is a big problem in artificial intelligence systems. The language is so ambiguous that it goes back to the beginning of the first computer operating systems. Knowledge of the language used by the person communicating with you is related to the ability of humans to communicate with each other. For a human to be able to communicate with an intelligent system, there are two options: either the human learns the language of the system as if he were learning to speak any other language other than the native one, or the system has the ability to interpret the user's message. in the language that the user uses. There may be damage to their installations.

A human learns the vocabulary of his native tongue and is able to interpret the messages despite the polysemy. He needs to know the different meanings to be able to read them, and that's why specialized and technical languages are only known by experts in their respective disciplines.

The artificial intelligence system faces the same problem as a human language, the polysemy of human language.

There is greater consensus among specialists in artificial intelligence development. An expert system is more likely to be used in medicine than in sociology. The problem of consensus among specialists in the definition of the concepts involved and in the procedures and techniques to be used is what is causing this.

In physics there is agreement on how to calculate speed. In psychology, the concepts of etiology, psychopathology, and how to proceed when faced with a certain diagnosis are discussed. It is difficult to create intelligent systems because there will always be disagreement about how the system should act. There are great advances in the design of expert systems for diagnosis and decision-making in the medical and psychiatric fields.

One must not link the fact that the robot interacts with humans to its degree of autonomy when developing a robot.

If the relationship between humans and the robot is of the master-slave type, and the role of humans is to give orders and that of the robot to obey them, then it is possible to speak of a limitation of the robot's autonomy. If the robot is peer to peer, then the presence of humans does not have to be associated with restrictions so the robot can make its own decisions.

) The number of movies on artificial intelligence has increased, and many software companies have started to be produced, because of the development of artificial intelligence. Artificial intelligence is a threat to the survival of humanity, according to Stephen Hawking.

Artificial intelligence has many techniques developed. Artificial intelligence can be used to solve a problem in industry and the daily life of computer program users, but popular perception ignores the origins of the technologies that cease to be useful.

The IA effect is a phenomenon that occurs.