Types Of Artificial Intelligence (AI)

Artificial intelligence is the science of building intelligent machines from vast volumes of data. This data can be structured, semi-structured or unstructured in nature. AI systems learn from past experiences and perform human-like tasks. There are various types of AI to consider. 

Artificial intelligence enhances the speed decision and effectiveness of human efforts. AI uses sophisticated algorithms and methods to build machines that can make decisions on their own. 

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Deep Learning and Machine Learning are the two subsets of artificial intelligence. So you need both machine learning algorithms and deep learning networks to build intelligent systems. AI is now being widely used in almost every sector of business such as transportation, healthcare, banking, retail, entertainment and e-commerce. 

Now, let’s look at the different types of artificial intelligence. AI can be classified based on capabilities and functionalities.

Based on capabilities: 

There are three types of artificial intelligence (AI). They are 

• Narrow AI 
• General AI 
• Super AI 

Based on functionalities.

We have four types of artificial intelligence (AI)

• Reactive Machine 
• Limited Memory 
• Theory of Mind 
• Self Awareness 

Let’s look at them one by one. First, we will look at the different types of artificial intelligence (AI) based on capabilities.

Narrow AI

Narrow AI also known as Weak AI focuses on one narrow task and cannot perform beyond its limitations. It is widely used in NLP.  It aims at a single subset of cognitive abilities and advances in that Spectrum applications of narrow AI are becoming increasingly common in our day-to-day lives as machine learning and deep learning methods continue to evolve.

Apple Siri is a simple example of a narrow AI that operates with a limited predefined range of functions. Siri often has challenges with tasks outside. Its range of abilities. 

IBM Watson supercomputer is another example of narrow AI which applies cognitive computing, machine learning and natural language processing to process information and answer your questions. IBM Watson once outperformed human contestant Ken Jennings to become the champion on the popular game show Jeopardy. Other examples of narrow AI includes Google Translate, image recognition software, recommendation systems, spam filtering and Google’s page ranking algorithm.

General AI

General Artificial Intelligence or General AI. General AI also known as strong AI has the ability to understand and learn any intellectual tasks that a human can. General artificial intelligence has received a 1 billion dollar investment from Microsoft through Open AI. It allows the machine to apply Knowledge and Skills in different contexts. 

AI researchers and scientists have not achieved strong AI so far. To succeed they would need to find a way to make machines conscious and programming a full set of abilities. 

Fujitsu built the K Computer, which is one of the fastest computers in the world. It is one of the most notable attempts at achieving strong AI. it took 40 minutes to simulate a single second of neural activity. So it is difficult to determine whether or not strong AI will be achieved in the near future. 

Tianhe-2 is a superconductor created by China’s National University of Defense Technology. It currently holds the record for CPS at 33.86 petaFLOP. Although it sounds exciting. The human brain is estimated to be capable of one exaFLOP. CPS means Characters Per Second that a system can process. 

Super AI

Super AI exceeds human intelligence and can perform any task better than a human. The concept of artificial superintelligence sees AI evolve to be knowing human emotions and experiences that it doesn’t just understand them. It evokes emotions, needs, beliefs and desires of its own. Its existence is still hypothetical some of the key characteristics of super. I include the ability to think, solve puzzles, make judgments and decisions on its own. 

Next, we will see the different types of artificial intelligence based on functionalities. 

Reactive Machine 

A Reactive Machine is the basic form of AI that does not store memories or use past experiences to determine future actions. It works only with present data the simply perceive the world and react to it. Reactive Machines are given certain tasks and don’t have capabilities beyond those duties.

IBM’s Deep Blue which defeated chess Grandmaster Garry Kasparov is a reactive machine that sees the pieces on a chessboard and reacts to them it cannot refer to any of its prior experiences and cannot improve with practice.

Deep Blue can identify the pieces on a chessboard and know how each moves it can make predictions about what moves might be next for it and its opponent it can choose the most optimal moves from among the possibilities. Deep Blue knows everything before the present moment. All it does is look at the pieces on the chessboard as it stands right now and choose from possible next moves. 

Limited Memory 

Limited Memory AI learns from past data to make decisions. The memory of such systems is short-lived, while they can use this data for a specific period of time. They cannot add it to a library of their experiences. This kind of technology is used for self-driving vehicles. They observe how other vehicles are moving around them in the present and as time passes. That ongoing collected data gets added to the static data within the air machine such as lean markers and traffic lights. They’re included when the vehicle decides to change lanes to avoid cutting off another driver or being hit by a nearby vehicle. Mitsubishi Electric is a company that has been figuring out how to improve such technology for applications like self-driving cars. 

Theory of Mind

Theory of Mind represents a very advanced class of technology and exists as a concept. This kind of AI requires a thorough understanding that the people and the things within an environment can also feelings and behaviours. It should be able to understand people’s emotions sentiment and thoughts. 

Even though a lot of improvements are there in this field. This kind of AI is not complete yet. One real-world example of theory of mind AI is Kismet – a robot head made in the late 90s by a Massachusetts Institute of Technology researcher. Kismet can make human emotions and recognize them. Both abilities are key advancements in the theory of Mind AI, but Kismet can’t follow cases or convey attention to humans.

Sophia from Hanson Robotics is another example, where the theory of mind AI has implemented cameras within Sophia’s eyes combined with computer algorithms allow her to see. She can follow faces sustained eye contact and recognize individuals since able to process speech and have conversations using natural language subsystem. 

Self Awareness 

Self Awareness AI only exist hypothetically, such systems understand that internal traits states and conditions and perceive human emotions. These machines will be smarter than the human mind.

This types of AI will not only be able to understand and evoke emotions in those it interacts with but also have emotions, needs and beliefs of it soon while we are probably far away from creating machines that are self-aware. We should focus our efforts towards understanding memory learning and the ability to base decisions on past experiences.

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