Main questions about artificial intelligence: what is it? Are machine learning and artificial intelligence the same? How has artificial intelligence (AI) impacted society? SummaryRead an overview of this topic. Artificial intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks that are often performed by intelligent beings. The phrase is often used to refer to efforts to create artificial intelligence (AI) that possess human-like cognitive abilities, such as the ability to reason, make sense, generalize, and learn from experience. Since the invention of the digital computer in the 1940s, computers have proven to be programmed with remarkable dexterity to accomplish extremely complex tasks - such as finding proofs of mathematical theorems or playing chess, using software that demonstrates human adaptability to a wider range of jobs or those requiring significant day-to-day knowledge.>On the other hand, some programs have reached the level of performance of human and professional experts in performing certain tasks, so AI in this limited sense is present in a variety of applications, including speech recognition or handwriting, computer search engines, and medical diagnostics. Intelligence - what is it? Even the most complex insect behavior is never interpreted as a sign of intelligence, while everything but the most basic human behavior is attributed to intelligence. What is the difference? Let's take the example of the blow wasp Sphex ichneumoneus. When the wasp returns to her burrow and wants something to eat, she will place her in the doorway, check her cave for intruders, and hopefully bring her something to eat. If food is moved just a few inches from the entrance to the cave while the wasp is inside, the true nature of its innate behavior is revealed: after it comes out, it repeats the same process each time food is moved. . Sphex lacks the intelligence, which must include the ability to change with the 's environment. Psychologists generally do not define human intelligence in terms of a single trait, but rather as a combination of several different abilities. The five pillars of intelligence - learning, reasoning, problem-solving, perception, and using language - have received the most attention in AI research. Learning When it comes to artificial intelligence, there are many different ways to learn. Learning from mistakes is the easiest method. For example, a simple checkmate computer chess program can test several moves before detecting a checkmate. The program can then save the solution with the location so that the computer can retrieve the solution the next time it encounters the same location. It's pretty easy to memorize certain things and procedures on a computer. The implementation of the so-called generalization problem is more difficult. Generalization is the process of adapting prior knowledge to similar new circumstances. For illustration,reasoning involves coming to conclusions that are appropriate to the situation. Inferences are classified as deductive or inductive. An example of the former is: “Fred must be at either the museum or the coffee shop; he's playing instruments; therefore this accident was caused by an instrument failure." The most important difference between these forms of reasoning is that in the deductive case, the truth of the premises guarantees the truth of the conclusion, while in the inductive case, the truth of the premise supports the conclusion without giving absolute certainty. /p>Inductive reasoning is common in science, where data is collected and preliminary models are developed to describe and predict future behavior until the emergence of anomalous data forces a revision of the model. Deductive reasoning is common in mathematics and logic, where irrefutable theorem structures are built from a small set of basic axioms and rules.It was a notable achievement in programming computers to draw inferences, particularly deductive inferences. True thinking, however, involves more than just drawing conclusions; involves drawing relevant conclusions for solving a specific task or situation. This is one of the most difficult problems facing AI.Problem-solving problem solving, particularly in artificial intelligence, can be characterized as systematically scanning through a series of possible actions to achieve a predefined goal or solution. Problem-solving methods are divided into special purpose and general purpose. A particular method is tailored to a specific problem and often exploits very specific features of the situation in which the problem is embedded. In contrast, a general-purpose method applies to a wide variety of problems. A general purpose technique used in AI is means-ends analysis: a gradual or incremental reduction in the difference between the current state and the ultimate goal.The program selects actions from a list of media (in the case of a simple robot these could be UP, DOWN, FORWARD, BACK, LEFT, and RIGHT) until the goal is reached.Through communication with other language users, one has acquired the language and received training to occupy a position in the language community.
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