Understanding Different Types of Artificial Intelligence with Examples

If I were to name a technology that completely revolutionized the 21st century, it would be Artificial Intelligence. AI is a part of our everyday life and that’s why I think it’s important we understand the different concepts of Artificial Intelligence. This article on Types Of Artificial Intelligence will help you understand the different stages and categories of AI.

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The following topics will be covered in this article:

What Is Artificial Intelligence?

In 1956, the term Artificial Intelligence was defined by John McCarthy. He defined AI as:

‘The science and engineering of making intelligent machines.’

Artificial Intelligence can also be defined as the development of computer systems that are capable of performing tasks that require human intelligence, such as decision making, object detection, solving complex problems and so on. To know how AI is creating designs like humans, Enroll in our AI for Designers Course today!

Now let’s understand the different stages or the types of learning in Artificial Intelligence.

Stages Of Artificial Intelligence

While I was doing my research I found a lot of articles that stated that Artificial General Intelligence, Artificial Narrow Intelligence, and Artificial Super Intelligence are the different types of AI. To be more precise, Artificial Intelligence has three stages.

Types Of Learning In Artificial Intelligence

1. Artificial Narrow Intelligence
2. Artificial General Intelligence
3. Artificial Super Intelligence

These are the three stages through which AI can evolve, rather than the 3 types of Artificial Intelligence.

Let’s understand each stage in depth.

Artificial intelligence→ Capabilities Based

Artificial Narrow Intelligence (ANI)

Also known as Weak AI, ANI is the stage of Artificial Intelligence involving machines that can perform only a narrowly defined set of specific tasks. At this stage, the machine does not possess any thinking ability, it just performs a set of pre-defined functions.

Artificial Narrow Intelligence

Examples of Weak AI include Siri, Alexa, Self-driving cars, Alpha-Go, Sophia the humanoid and so on. Almost all the AI-based systems built till this date fall under the category of Weak AI.

Artificial General Intelligence (AGI)

Also known as Strong AI, AGI is the stage in the evolution of Artificial Intelligence wherein machines will possess the ability to think and make decisions just like us humans.

There are currently no existing examples of Strong AI, however, it is believed that we will soon be able to create machines that are as smart as humans.

Artificial General Intelligence

Strong AI is considered a threat to human existence by many scientists, including Stephen Hawking who stated that:

“The development of full artificial intelligence could spell the end of the human race…. It would take off on its own, and re-design itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded.”

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Artificial Super Intelligence (ASI)

Artificial Super Intelligence is the stage of Artificial Intelligence when the capability of computers will surpass human beings. ASI is currently a hypothetical situation as depicted in movies and science fiction books, where machines have taken over the world.

Artificial Super Intelligence

I believe that machines are not very far from reaching this stage taking into considerations our current pace.

“The pace of progress in artificial intelligence (I’m not referring to narrow AI) is incredibly fast. Unless you have direct exposure to groups like Deepmind, you have no idea how fast—it is growing at a pace close to exponential. The risk of something seriously dangerous happening is in the five-year timeframe. 10 years at most.” —Elon Musk quoted.

So, these were the different stages of intelligence that a machine can acquire. Now let’s understand the types of AI, based on their functionality.

Artificial intelligence→ Functionality  Based

Types Of AI

Based on the functionality of AI-based systems, AI can be categorized into the following types:

1. Reactive Machines AI
2. Limited Memory AI
3. Theory Of Mind AI
4. Self-aware AI

Reactive Machine AI

This type of AI includes machines that operate solely based on the present data, taking into account only the current situation. Reactive AI machines cannot form inferences from the data to evaluate their future actions. They can perform a narrowed range of pre-defined tasks.

Reactive Machine AI

An example of Reactive AI is the famous IBM Chess program that beat the world champion, Garry Kasparov.

Limited Memory AI

Like the name suggests Limited Memory AI, can make informed and improved decisions by studying the past data from its memory. Such an AI has a short-lived or a temporary memory that can be used to store past experiences and hence evaluate future actions.

Limited Memory AI 

Self-driving cars are Limited Memory AI, that uses the data collected in the recent past to make immediate decisions. For example, self-driving cars use sensors to identify civilians crossing the road, steep roads, traffic signals and so on to make better driving decisions. This helps to prevent any future accidents.

Theory Of Mind AI

The Theory Of Mind AI is a more advanced type of Artificial Intelligence. This category of machines is speculated to play a major role in psychology. This type of AI will focus mainly on emotional intelligence so that human believes and thoughts can be better comprehended.

Theory of Mind AI

The Theory of Mind AI has not yet been fully developed but rigorous research is happening in this area.

Self-Aware AI

Let’s just pray that we don’t reach the state of AI, where machines have their own consciousness and become self-aware. This type of AI is a little far fetched given the present circumstances. However, in the future, achieving a stage of superintelligence might be possible.

Self-Aware AI 

Geniuses like Elon Musk and Stephen Hawkings have consistently warned us about the evolution of AI. Let me know your thoughts on this in the comment section.

AI is a very vast field that covers many domains like Machine Learning, Deep Learning and so on. In the below section I’ve covered the various fields of AI.

Practical application of AI technologies in computer vision 

Computer vision id no less than a human vision the only difference is that human use there retinas , optic nerves and visual cortex for vision rathan that computer uses cameras, data and algorithms for vision. For better understanding we can say that computer vision is a branch of computer science that only deals with developing systems that are able of process, interpret and then perceive pictures/videos like humans do. .  

Application 

• To recoganise objects 

Detection of objects is a technique of computer vision that can identify the objects , locate the objects, and also categorize the objects. For example , this technique can be used to identify the traffic signals on the road also to recoganise the faces of individuals  in crowd. In the context of AI in Cyber Security, object detection allows computers to see the world around them and enhances security measures by accurately identifying potential threats.

Computer vision can be used in various fields like 

• Agriculture – to detect weed growth or nutrients deficit or any kind of disease present in plants/crops 
• To recoganize patterns/edges – computer vision can discover pattern in data always well as computer vision can easily find the edges of the pictures.
• Facial recognition – facial recognition basically means to recognize the variety of objects or humans with there different skin color or facial expression.

Practical application of AI technologies in Robotics

Artificial intelligence in robotics is one of the biggest achievements of 21th century, it has changed the ways of robots performance, In this modern era artificial intelligence and robotics has integrated with each other.  Artificial intelligence has enhanced the capabilities of robots over the years.

Application 

• Artificial intelligence provide robotics a computer vision from which robots are able to detect objects easily , recognize the image and vides or human beings.
• One more way in which artificial intelligence is used in robotics is in the form of edge computing ,that is to process the massive amount of data before sending it to cloud to store 
• Artificial intelligence systems in  robots are used in the form of chat bots in customer care service
• Artifical intelligence system in robots are used for the packaging purpose in many packaging industries.

Practical application of AI technologies in Expert system

 We have human experts in every field but still we need artificial intelligence expert why? 

Well there are many things that can affect the decision made by humans like emotions, memory loss, expertise in particular domain and so on. But the decisions made by AI in customer service, or in other applications can not get affected by emotions and expertise.if given the right data input AI will give the right decision 99 percent of the time it has no memory limitations and also high security.

Application

• Expert system are used in financial sector in order to identify any kind of fraud or suspicious activity.
• Expert systems are used in medical feilds to detect dieseas like cancer. For example

         CaDet          (cancer decision support tool), 

         MYCIN        ( for identification of bacteria)

         DENDRAL  ( used for chemical analysis)

• Expert system are used in educational sectors to help students solve the question using the data.

Branches Of Artifical Intelligence

Artificial Intelligence can be used to solve real-world problems by implementing the following processes/ techniques:

1. Machine Learning
2. Deep Learning
3. Natural Language Processing
4. Robotics
5. Expert Systems
6. Fuzzy Logic

Domains Of AI – Types Of  AI- Edureka

Machine Learning

Machine Learning is the science of getting machines to interpret, process and analyze data in order to solve real-world problems.

Machine Learning – Types Of AI – Edureka

Under Machine Learning there are three categories:

1. Supervised Learning
2. Unsupervised Learning
3. Reinforcement Learning

To learn more about Machine Learning, you can go through the following blogs:

1. Machine Learning Tutorial for Beginners
2. What is Machine Learning? Machine Learning For Beginners

Deep Learning

Deep Learning is the process of implementing Neural Networks on high dimensional data to gain insights and form solutions. Deep Learning is an advanced field of Machine Learning that can be used to solve more advanced problems.

Deep Learning – Types Of AI – Edureka

Deep Learning is the logic behind the face verification algorithm on Facebook, self-driving cars, virtual assistants like Siri, Alexa and so on.

To learn more about Deep Learning you can go through the following blogs:

1. What is Deep Learning? Getting Started With Deep Learning
2. Deep Learning Tutorial: Artificial Intelligence Using Deep Learning

Natural Language Processing

Natural Language Processing (NLP) refers to the science of drawing insights from natural human language in order to communicate with machines and grow businesses.

Natural Language Processing – Types Of AI – Edureka

Twitter uses NLP to filter out terroristic language in their tweets, Amazon uses NLP to understand customer reviews and improve user experience.

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Here’s a video to get you started with Natural Language Processing.

Robotics

Robotics is a branch of Artificial Intelligence which focuses on different branches and application of robots. AI Robots are artificial agents acting in a real-world environment to produce results by taking accountable actions.

Robotics – Types Of AI – Edureka

Sophia the humanoid is a good example of AI in robotics.

Fuzzy Logic

Fuzzy logic is a computing approach based on the principles of “degrees of truth” instead of the usual modern computer logic i.e. boolean in nature.

Fuzzy Logic – Types Of AI – Edureka

Fuzzy logic is used in the medical fields to solve complex problems that involve decision making. They are also used in automatic gearboxes, vehicle environment control and so on.

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Expert Systems

An expert system is an AI-based computer system that learns and reciprocates the decision-making ability of a human expert.

Expert Systems – Types Of AI – Edureka

Expert systems use if-then logical notations to solve complex problems. It does not rely on conventional procedural programming. Expert systems are mainly used in information management, medical facilities, loan analysis, virus detection and so on.

Conclusion

Artificial intelligence has revolutionized in 21th century and has become integral part of our day to day life, it has made our life easier than before. Artificial intelligence is emerging in every industry like educational sector, financial sector, health sector or argricultire sector. From Narrow AI’s specialized tasks to the theoretical prospects of General and Superintelligence, AI continues to reshape industries and daily life alike. When choosing between AI coding assistants, consider the features and benefits of Tabnine vs GitHub Copilot for your projects.

Frequently asked questions

1.What is an AI model?

AI model is a program that has been designed on certain data set so that it can recoganize any kind of patterns and make decision without any kind of human intervention. AI models use different kind of algorithms to achieve the task, different kinds of AI models are specified for different tasks and there decision making logic is most useful.  

2. What are the seven types of Artificial intelligence ?

7 types of artificial intelligence are:

• Narrow AI
• Artificial General Intelligence
• Artificial Super Intelligence
• Reactive Machine AI
• Limited Memory AI
• Theory of Mind AI
• Self-Aware AI

3. What is the most common type of AI ?

Narrow AI and Limited memory AI are the most common types of AI used nowdays 

4. Who is the father of AI ?

John McCarthy is known to be the father of AI.

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