What are the 7 most relevant types of artificial intelligence?

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It is worth making a brief list of the types of artificial intelligence, so that you can have a broad overview of this technology and use the most appropriate one.

H3. Artificial General Intelligence (AGI – Artificial General Intelligence)
This type of AI is capable of performing any task with the same effectiveness as a person, as it is a cognitive AI capable of imitating human intelligence .

Its purpose is to replicate attitudes and then resolve various issues, which is why it is called a deeper intelligence.

AGI is still largely theoretical, but it is one of the most widely used because of its ability to perform any human activity.

H3. Artificial Narrow Intelligence ( ANI)
Also known as weak artificial intelligence , it is designed to perform israel whatsapp resource a specific task. Its main function is to focus on a single task. ANI is an artificial intelligence with a reactive character, limited memory and oriented .

Furthermore, they are based on introducing a series of actions for a single purpose, but they do not have the ability to generalize or perform functions outside their predefined scope. A close example are virtual assistants such as Alexa and Siri.

H3. Artificial Super Intelligence (ASI)
Super AI, also known as superintelligent AI, should be able to do different activities better than a human, however, it is still unknown whether it can reach that level of complexity.

For this reason, this type of artificial intelligence would have the ability to reason , think, be conscious, autonomous and creative, and practically solve problems.

This theory raises significant philosophical and ethical questions due to its potential impact on society and human existence.

It has currently been the subject of active research and debate, but its creation is more a theoretical and future concept than an immediate reality.

To continue with the following types of AI we will describe them according to their functionality:

H3. Logic-based AI
It uses logical rules to make decisions, as this system employs predefined points and human knowledge to generate results.

Furthermore, it is a human-like machine reasoning method for making inferences and deductions based on interacting data.