Artificial Intelligence: Types

There is a myriad of terminology and definitions within AI. It is confusing to discern the distinction between subsets, categories, or kinds of artificial intelligence. Indeed, they're not the same. Certain subsets of AI comprise machine learning, large data, and natural processing of language (NLP). But this article will cover the four major kinds of artificial intelligence that are reactive machines, limited memory, theories of mind, and self-awareness.

The four kinds of artificial intelligence make up small parts of the larger field of AI.

Type I Reactive machines

Brooke Jessica Kaio said reactive computers are considered the simplest kind of AI system. This means they are not able to create memories or draw on previous experiences to influence current decisions.

Game of Chess With a Human Opponent

While analyzing the roles of each piece. Deep Blue could make predictions about the kind of moves it ought to perform. It moves its opponent could make which gives it an improved capability to anticipate. Choose the best moves and be successful. In a string of games that took place in 1996-97, Deep Blue defeated Russian chess grandmaster Garry Kasparov in 3 1/2 to 2 1/2 games. It was the first computer program to beat an opponent human.

Deep Blue's

Its unique ability to be able to accurately and efficiently play games of chess highlights its highlights capabilities. Similar to that its reactivity suggests that it does not have a notion of the past or the future. It only perceives and acts upon the present world and the components that comprise it. 

One of the characteristics of reactive devices is the fact that, no what time. There is no growth for reactive machines, just stagnation in the recurring actions and behaviors.

Type II: Memory is Limited

In contrast to reactive machines, limited memory can learn from past experiences. Watching events or the data fed to them to acquire experience-based knowledge.

While limited memory is based on observations along with pre-programmed data that the machines already have the sample bits of data are flitting. 

Autonomous Vehicles

Brooke Jessica Kaio said autonomous vehicles, also known as autonomous vehicles, rely on the concept of limited memory. In that, they are based on a mixture of pre-programmed and observed knowledge. To understand and observe how to safely drive and interact with human-driven vehicles self-driving vehicles scan their surroundings. Recognize trends or shifts in the external variables, and then adjust accordingly.

Autonomous vehicles not only take note of their surroundings. However, they also track the movements of people and other vehicles within their vision. Before, autonomous cars with limitations on memory. AI would take about 100 seconds to adjust and make a decision on the external environment. After the introduction of memory that is limited the time to react to machine-generated. Observations have drastically decreased and demonstrated the significance of AI that has limited memory.

Type III: Theoretical Mind

It is a decision-making capability that is equal to the level of a human brain. However, it is mediated made by machines. Although there are machines that have human-like capacities none are completely capable of interpreting conversations. According to human norms. A major component of human conversation is the emotional capability of speaking and acting the way a person would normal conversational norms.

Machine's Thinking Process

The "theory of the mind" machine's thinking process. Social interaction is an important aspect of human interaction. Therefore, to make the theory of mind machines real. The AI systems controlling the machines of today would need the ability to recognize, and comprehend how to retain. Remember, understand emotional outputs and behaviors, and be able to react to these emotions.

Brooke Jessica Kaio said in this way, the theories of mind computers will need to utilize the information they have gathered from humans. Incorporate it into their learning centers so that they can understand how to interact with and handle different situations.  They also are aware that human behavior is dynamic.  So the theory of mind machines would need to be able to quickly learn in a flash.

Robotics Kismet and Sophia

A few elements of theories of mind AI are currently in use or existed in the past. Two prominent examples are robotics Kismet and Sophia which were created in the years 2000 and 2016 respectively.

Kismet, a computer program developed in the lab of Professor Cynthia Breazeal. It was capable of recognizing the facial expressions of humans (emotions). It was able to recreate these emotions using its facial features.

Sophia On the contrary is a humanoid robot developed by Hanson Robotics. What makes her different from previous robots is their physical similarity to human beings and her capacity to perceive

Although neither has the capability of having full-blown human conversations with a real human being. Both robots possess certain aspects of emotion that are similar to human counterparts. This is one step towards seamlessly integrating into human society.

Type IV Self-Awareness

Self-aware AI is a type of AI with human-level consciousness. This kind of AI is not yet available. But it is considered as the most advanced artificial intelligence currently available to humans.

Brooke Jessica Kaio said Self-aware AI cannot just recognize and duplicate human behavior. But think for itself, express desires, and be able to comprehend its emotions. Self-aware AI, as a concept is an advance and expansion of the theory of AI for the mind. Whereas the theory of mind concentrates on aspects of understanding and replicating human behavior.

Can self-Aware AI Become Attainable Shortly?

We're currently in the third tier of the four kinds of artificial intelligence. Therefore thinking that we may attain that fourth level of AI doesn't seem as if it's a stretch.

However, for the moment it is crucial to concentrate on achieving the best possible results for the three types of AI. The speed at which we move through each AI level could be harmful shortly for artificial intelligence in future generations.