artificial intelligence

Artificial Intelligence- What is AI, Types of AI, All about AI

   What is Artificial intelligence?

Artificial intelligence (AI), is the ability of a digital computer or computer-controlled robot to  perform tasks that normally require human intelligence. 


We can also describe  AI   as machines (or computers) that copies ‘Think and Apply’ functions that humans associate with the human mind, such as identifying things, knowledge grasping and problem-solving.

 Here are the topics that is to say we are going to cover in further for more clear vision:

What are the types of Artificial intelligence?
What is narrow/weak AI?
 What is general/strong AI ?
What is Super AI?
How Artificial intelligence works?
What are the main components of artificial intelligence?
What is Machine learning?
What is a neural network in artificial intelligence?
What is deep learning?
What is problem-solving?
Perception in artificial intelligence.
What is natural language processing?
History of Artificial Intelligence

Also Read : iOS 14 updates – all about latest widgets, features, full user guide 

      So let’s get started to learn all the exciting study stuff about AI….. 

    What are the types of Artificial Intelligence?

artificial intelligence

     There are  2 types of artificial intelligence (AI) based on

     ability and based on  functionality as follow,


all types of AI















1. Narrow artificial intelligence (weak AI)

What is Narrow AI?

The ANI is also called “Weak” AI. Narrow AI is goal-oriented AI and designed to perform singular tasks. In simple words these are artificial intelligence systems that are specified to manage a single or limited task.

Applications related Narrow AI are becoming most common in machine learning(ML) and continually integrating into modern society.  However Narrow AI works within a pre-determined and pre-defined range.

Above all we call it “Weak AI” because these machines are nowhere close to having human-like behavior. For instance  using ANI machines can’t think for themselves they just perform limited tasks for what they originally designed for.

ANI Examples :
One of the most famous integrated forms of Narrow AI is Apple’s Siri and Google assistant.
Facial recognition tools to tag in pictures
Customer service bots.
 Google’s page-ranking  technology  is also based on ANI.

2. General artificial intelligence( strong AI)

What is general AI?

This also known as ” Strong or Deep AI ” allows a machine to apply knowledge and intelligence as per we humans do.

In other words, AGI can successfully perform any intellectual job that a human brain can. Moreover  General AI  is the concept of a machine with general intelligence that mimics human intelligence.

So AGI originally based on human intelligence, with the ability to learn and apply its intelligence to resolve any problem.

Consequently AGI can think itself, understand the relative situations, and act in a way that is very similar to a human in any given situation.

Above all the main goal of AI, computers that copy human thinking and apply processes, is famously known as artificial general intelligence.

Recently, the main approach to AGI is called “ whole brain emulation ,” where a human brain’s memory and mental state transferred onto a computer.

However Strong AI uses a theory of mind level AI, the theory of mind level AI is not about duplication or task based, it’s only about training machines to truly understand humans.

3. Super artificial intelligence 

What is super AI?

super artificial intelligence

The Super Artificial Intelligence is a higher level of Intelligence of Systems at which machines could cross human intelligence, and they are able to execute any job one step ahead than humans with cognitive properties.

So the development of  Artificial Super intelligence  will probably mark the miracle of AI research. It is an upper version of general AI.

Meanwhile using super artificial intelligence systems, machines will be way better than humans, machines will be exceptionally better at everything they do because of their potential of greater memory storing, faster data processing and analysis, and decision-making capabilities.

Above all  Super AI  is still a hypothetical theory of Artificial Intelligence. Development of such systems in real life is still a human life changing task.

How Artificial intelligence works?

As we know the human brain has been called one of the most complicated things in science and the universe.
likewise, Artificial intelligence is the technology of making  machines brain  as humans.
Therefore AI makes it possible for machines to adjust to new inputs, think smartly, learn from experience, and perform tasks regarding past experience.

In conclusion, as reading further the concept of AI working will be perfectly clear to you reader trust me.

What are the main components of artificial intelligence?

Let’s go through some important factors of Artificial Intelligence as follow,

artificial intelligence

I.  Machine learning (ML)

What is Machine learning?

The ML is a subset of Artificial intelligence which is the study of computer algorithms that improve itself automatically through experience while practicing and learning.

 During  ML  algorithms build on training data. In Machine learning, computers learn how they can perform particular tasks without being explicitly programmed to do. Likewise humans, AI needs to learn a task before doing it.

Similarly our human brain restores all the data so that it can use that data to make faster and right decisions when next encounter of similar information.

Similarly, a computer algorithm, or a problem-solving protocol, generates a model of thinking with parameters from external data past input. It’s a process made to resolve future problems easily.

In conclusion there is no doubt that  machine learning  is an important part to enhance our everyday lifestyle.

Machine learning Examples:
 Weather forecasting  and mobile face recognition to unlock the phone is built on ML technology.

II. Deep learning

What is deep learning(DL)?

The term Deep learning is a subset of artificial intelligence, also a machine learning technique that teaches computers to do what comes naturally to humans mind and they learn by past example.

Meanwhile early DL was in the context of artificial neural networks but in 2013 titled ” Deep Learning , Self-Taught Learning and Unsupervised Feature Learning”. Moreover in deep learning use of multiple layers that progressively work together to extract a single output from many inputs”.

Examples of Deep learning:
So Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, signal recognition also speech recognition like ” Hey  Siri  ” to enabling phone search on, are nowadays famous examples.

 III. Neural network

What is a Neural Network(NN)?

As we all know that a normal human brain has more than 100 billion neurons that connect the entire human body through the neuron cells and collect the information from that body part and tell the brain about the problem over there.

 Above all  Neural networks  enable deep learning. Whenever humans have a new experience brain links between neurons are formed to store it and represent that memory, your brain creates a mapping between the actions and the outcomes.

similarly, In artificial intelligence, we have a ‘neural network’ which works like neurons. Therefore NN are set layers of highly interconnected processing elements that store transformations of the data to generate its own understanding capability.

Examples of Neural network:
In the case of recognizing handwriting or person recognition or animal recognition Artificial intelligence has neural networking.

 IV. Natural language processing

What is Natural language processing(NLP)?

The term NLP is a subset of Artificial Intelligence (AI) that makes human language (like English) intelligible and understandable to machines. So NLP makes the computer perform tasks with the natural languages that we humans use. NLP works best in the field of symbolic AI.

 Example of NLP:
Natural Language Processing helps to recognize and  predict the disease  based on electronic health records and the patient’s own speech.

 Alexa  and Google are the best examples of an intelligent voice-driven interface, they use NLP to respond to our questions and perform tasks like find a particular shop, tell me the weather forecast, tell me today’s news, or turn on/off the lights at home.

V. Problem-solving

What is problem-solving?

In AI Problems are the difficulties that come across the system. A solution is needed to solve that particular error. In other words a problem-solving technique is a result-driven technique and always focuses on satisfying the goals.

The process of solving a problem consists of five steps:

Defining The Problem
Analysing The Problem
Identification Of Solution
Choosing a Solution
Implementation of solution

simple offline games like sudoku and chess where a built program plays with us.

VI.  Perception in artificial intelligence

Perception in machines is the process of analyzing senses, visions, sounds, smell, and other human-like things. The main goal of machine perception is to give machines the power to see and feel the world as we humans do. However ML algorithms and techniques that help robots to learn from sensory data, to react and take decisions accordingly.

Example of perception in AI:
activity recognition used in workout games, place or object recognition used in google photos classification.

History of Artificial Intelligence

First of all, let me tell you Artificial Intelligence is not a new word and not a new technology.

Year 1943: In 1943 Warren McCulloch
and Walter pits proposed a model of artificial neurons.
Year 1950: Alan Turing an English mathematician and pioneered Machine learning in 1950. Alan Turing publishes “Computing Machinery and Intelligence”.
Year 1956: The term artificial intelligence was coined in 1956 by John McCarthy.
Year 1966:Joseph Weizenbaum created the first chatbot in 1966, which was named ELIZA.
Year 1972: The first intelligent humanoid robot was built in Japan and was named as WABOT-1.
Year 2006: AI came into the Business world. Companies like Facebook, Twitter, and Netflix also started using AI.

Now AI has developed to a remarkable level. However the concept of Deep learning, experiential learning, neural network, Machine learning, natural language learning, big data and data science are now trending on the top and there is much more new to see in this new decade 2021.


About Author


I am a Software Engineer. I am passionate about to read, to go deep and be always informative about latest technologies. So, I am writing here to give all readers accurate and deep information about important technologies nowadays and keep all updated. Contact:

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