Introduction to Artificial Intelligence(AI)

Original article was published on Artificial Intelligence on Medium

Introduction to Artificial Intelligence(AI)

Getting started with used definitions and types/stages of AI

Artificial Intelligence or simply AI has absolutely been the buzz in the most recent era of technology. Humankind has been experiencing the impact of AI in solving real-world problems where humans can’t interfere. Therefore, let’s get started to know more.

source: Google images

“Predicting future isn’t magic, it’s Artificial Intelligence” -Dave Waters

Before diving into the AI, we need to know the term intelligence.

What is intelligence?

Humans have innate intelligence, that governs every activity in the human body. This intelligence is what causes an oak tree to grow out of a little seed and an elephant to form from a single-celled organism, it’s really an amazing art of nature.

Origin of AI

Sources tell us intelligent robots and artificial beings first appeared in the ancient Greek myths of Antiquity. Aristotle’s development of the syllogism and its use of deductive reasoning was a key moment in mankind’s quest to understand its own intelligence.

Can machines think? — Alan Turing, 1950

But Alan Turing’s paper “Computing Machinery and Intelligence” (1950), and it’s subsequent Turing Test, established the fundamental goal and vision of artificial intelligence. Rest is history.

What is Artificial Intelligence?

“Artificial intelligence,” which has been much used since the 1970s, refers to the ability of computers to mimic human thought. Then it was defined as building machines that are intelligent but unable to answer what’s actually the artificial intelligence.

Artificial Intelligence is the intelligence exhibited by machines and the capability of a machine to imitate human behavior as like how human can take decisions based on surroundings same as machine can make its own decisions based on situations. It can be anything that makes machines to act more intelligently.

AI is the new electricity. It will transform every industry and create huge economic value — Andrew Ng

AI is a multi-disciplinary field

source: IBM

AI modeled after human brain. In fact, AI is a multi-disciplinary field it mean it is not limited to computer science but also the combination of electrical engineering, mathematics, statistics, Psychology, linguistics and philosophy.

Okay, we got to know what’s definition of AI

How to AI learn?

Is it possible to teach machines by taking them to school, giving home works and putting exams with cutoff marks? Here’s big no and non-conventional in the way humans learn.

The main quality of the artificial intelligence is learning and applying i.e. learning from external experiences and altering its perceptions based on them.

source: TowardsDatascience

According to IBM, AI learns by creating machine learning models based on provided inputs and desired outputs.

Data has a better idea, we need to know how to feed and train machines with the help of data sets with a process called as modelling. Better ways to train machines possibly explained with the help of machine learning and deep learning.

Types/Stages of Artificial Intelligence (AI)

source: edureka

There are three stages/types of AI. They are:

1. Artificial Narrow Intelligence or Narrow AI

2. Artificial General Intelligence or General AI

3. Artificial Super Intelligence or Super AI

Lets discuss in detail

  1. Artificial Narrow Intelligence or Weak or Narrow AI :-

Narrow AI is effective since 2015 and it is limited to one or two functional areas i.e. applied to a specific domain, are not self-aware or self-conscious, appear to be making decisions based on programmed algorithms and training data. All the responses from the machine are statistic/math in action. Narrow AI outperform humans in doing specific task like driving etc.

Examples: IBM Watson, Deep Blue Alexa, Siri, Smartphone apps, chess, recommendation engines . mage identification tools, speech recognition tools, self-driving systems, Google Translate, Spam filters, learning analytics Chatbots etc.

2. Artificial General Intelligence or Strong or General AI :-

General AI covers over more than one functional area, such as reasoning, problem-solving and abstract thinking. It is a combination of many AI strategies that learn from experience, learn new logic to solve new problems and can perform at a human level of intelligence. General AI has its popular applications at present which is in research stage.

Examples: Multipurpose systems with human level intelligence, reasoning, thinking and decision-making. Systems that synthesize diverse information and decide actions.

3. Artificial Super Intelligence or Conscious or Super AI :-

Super AI surpasses human intelligence it means systems characterizing self-training. It is better than human in every task. It is the most advanced and more conscious AI. We can’t imagine what consciousness it is.

Examples: Super intelligent AI agents, systems that are masters at every skill, subject or discipline and are faster than the smartest humans


The fact is artificial intelligence is going to change the entire world and we are just entered into General AI but not in its full form. In the future, we’ll face an AI revolution and it won’t be limited to software industries, but penetrating its roots deep into almost every sector.

I hope this will help you to understand the basics of AI. Thanks for reading.