Artificial Intelligence (AI) is the simulation of human intelligence processes by computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction. 


           AI research is highly technical and specialized and is deeply divided into subfields that often fail to communicate with each other. Subfields have grown up around particular institutions, the work of individual researchers, and the solution to specific problems. Some of the most active subfields include:
  • Machine learning, which is concerned with building systems that can learn from data
  • Computer vision, which is focused on building systems that can understand and interpret images and video
  • Natural language processing, which is focused on building systems that can understand and generate human language
Robotics is concerned with building physical systems that can sense, reason, and act in the world.

        AI is a broad field that encompasses many different techniques and approaches. Some of the most important methods used in AI include:
  • Rule-based systems: These systems use a set of predefined rules to make decisions or take actions. They are often used in expert systems, which are designed to mimic the decision-making processes of human experts in a specific domain.
  • Neural networks: These systems are inspired by the structure and function of the human brain and are used to model complex patterns and relationships in data. They are widely used in image and speech recognition, natural language processing, and many other applications.
  • Genetic algorithms: These are inspired by the process of natural selection and are used to find the best solution to a problem from a large set of possible solutions. They are often used in optimization and search problems.
  • Evolutionary computation: This method uses ideas from natural evolution, such as reproduction, mutation, and selection, to find solutions to problems.
  • Fuzzy logic: This is a method for dealing with imprecision and uncertainty in reasoning. Fuzzy logic systems can handle vague or incomplete information and make decisions based on the degree of truth of the information.
  • Bayesian networks: These are probabilistic graphical models that can be used to represent and reason with uncertain knowledge.
AI has a wide range of potential applications, including:
        It's important to note that the development and use of AI raise many ethical, legal, and societal concerns, such as the impact on jobs and the potential for misuse.

Mainly we are dividing AI in two parts:

  • Weak AI: Weak AI, also known as narrow AI, is a type of artificial intelligence that is designed to perform a specific task or set of tasks. It is not capable of general intelligence or consciousness, and it cannot perform tasks that are outside of its programming.
  • Strong AI: Strong AI, also known as artificial general intelligence (AGI), is a type of artificial intelligence that is capable of performing any intellectual task that a human can. It is designed to be able to learn and adapt to new tasks without being explicitly programmed.