An intelligent system is a system that has been designed to perform a task that would normally require human intelligence, such as understanding natural language or recognizing objects. There are three main types of intelligent systems:
1. Artificial intelligence (AI) systems are designed to simulate human intelligence, and can be used for tasks such as decision making, pattern recognition, and natural language processing.
2. Expert systems are designed to imitate the decision-making process of humans experts in a particular field, and can be used for tasks such as diagnosis, troubleshooting, and planning.
3. Cognitive architectures are artificial intelligence systems that are designed to replicate the structure and function of the human mind, and can be used for tasks such as learning, problem solving, and perception.
Artificial narrow intelligence (ANI), which has a narrow range of abilities;

Artificial general intelligence (AGI), which has a broad range of abilities; and
Superintelligent AI, which has abilities that far surpass those of humans.
Artificial Narrow Intelligence (ANI) is a term used to describe artificial intelligence that is limited to a single task or range of tasks. ANI systems are sometimes known as weak AI or narrow AI. Some examples of ANI include facial recognition software, spam filters and virtual assistants such as Siri or Alexa. These systems are generally designed to perform one specific task and are not capable of performing other tasks outside their area of expertise.
While ANI systems are not as advanced as AGI or super intelligent AI, they can still be very useful for businesses and organizations. For example, facial recognition software can be used for security purposes, while spam filters can help reduce the amount of junk mail that people receive. Virtual assistants can also be used to help with tasks such as scheduling appointments or sending emails.
Overall, ANI systems have a number of advantages over more advanced forms of AI. They are usually cheaper and easier to develop than AGI or super intelligent AI, and they often require less data in order to function properly. Additionally, ANI systems tend to be more efficient than their more advanced counterparts since they are only focused on one specific task.
However, there are also some disadvantages associated with ANI systems. One major downside is that these systems often lack flexibility and can not adapt to new situations outside their area of expertise. Additionally, because ANI systems tend to be reliant on large amounts of data, they can be susceptible to bias if the data used to train them is not representative of the real world .
Artificial general intelligence (AGI), which is on par with human capabilities; or
The three types of intelligent systems are artificial general intelligence (AGI), machine learning, and deep learning.
Artificial general intelligence (AGI) is a type of AI that is on par with human capabilities. It can learn or understand any intellectual task that a human being can. Machine learning is a subset of AI that focuses on the ability of machines to learn from data without being explicitly programmed. Deep learning is a newer approach to machine learning that uses neural networks to learn from data in an unsupervised way.
“There are different types of intelligent systems, but the basis for each one is to make decisions or process information in ways that simulate or exceed human intelligence