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Introduction to Artificial Intelligence

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Introduction to Artificial Intelligence

Hammad Ul Haq's photo
Hammad Ul Haq
·May 13, 2022·

7 min read

Table of contents

What is Artificial Intelligence?

Artificial Intelligence is a technique of enabling a computer to think intelligently like the human mind. AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. The outcome of these studies develops intelligent software and systems. In simple words, AI is trying to enable computers to think and act like humans. The main purpose of AI is to create smart machines efficient for performing tasks that typically require human intelligence and reduce the man's effort to As stated simply, AI is trying to make computers think and act like humans.


Need for Artificial Intelligence

Artificial Intelligence is the simulation of the human process by computer systems. These processes include learning, reasoning, and self-correction. We need Artificial Intelligence (AI) because the work that we need to do is increasing day-to-day. So, it’s a good idea to automate the routine work. This saves the workforce of the organization and also increases productivity. Additionally, through this Artificial Intelligence, the company can also get skilled persons for the development of the company. Moreover, companies today think that they want to mechanize all the regular and routine work. And they think they can automate those regular works through a simple program Because, with the development of data science, automation becomes more common. The application of this AI is majorly seen in the website chat portal. You people when you come to the websites probably see the welcome message. Then actual conversation usually starts.

History of Artificial Intelligence

Artificial Intelligence is not a new word and not a new technology for researchers. This technology is much older than you would imagine. Following are some milestones in the history of AI which defines the journey from the AI generation to till date development.


Credit goes to awaisbajwa

Maturation of Artificial Intelligence (1943-1952)

The first work which is now recognized as AI was done by Warren McCulloch and Walter pits in 1943. They proposed a model of artificial neurons. In 1949 Donald Hebb demonstrated an updating rule for modifying the connection strength between neurons. His rule is now called Hebbian learning. Alan Turing was an English mathematician who pioneered Machine learning in 1950. Alan Turing publishes "Computing Machinery and Intelligence" in which he proposed a test. The test can check the machine's ability to exhibit intelligent behavior equivalent to human intelligence, called a Turing test.

The birth of Artificial Intelligence (1952-1956)

In 1955 An Allen Newell and Herbert A. Simon created the "first artificial intelligence program "Which was named "Logic Theorist". This program had proved 38 of 52 Mathematics theorems and found new and more elegant proofs for some theorems. The year 1956: The word "Artificial Intelligence" was first adopted by American Computer scientist John McCarthy at the Dartmouth Conference. For the first time, AI was coined as an academic field.

The golden years-Early enthusiasm (1956-1974)

In 1966: The researchers emphasized developing algorithms that can solve mathematical problems. Joseph Weizenbaum created the first chatbot in 1966, which was named ELIZA. The year 1972: The first intelligent humanoid robot was built in Japan and was named WABOT-1. The first AI winter (1974-1980)

The duration between the years 1974 to 1980 was the first AI winter duration. AI winter refers to the time period when computer scientists dealt with a severe shortage of funding from the government for AI researchers. During AI winters, an interest in publicity on artificial intelligence was decreased.

A boom of AI (1980-1987)

After AI's winter duration, AI came back with an "Expert System". Expert systems were programmed that emulate the decision-making ability of a human expert. In the Year 1980, the first national conference of the American Association of Artificial Intelligence was held at Stanford University.

The second AI winter (1987-1993)

The duration between the years 1987 to 1993 was the second AI Winter duration. Again, Investors and the government stopped funding AI research due to high costs but not efficient results. The expert system such as XCON was very cost-effective.

The emergence of intelligent agents (1993-2011)

IBM Deep Blue beats world chess champion, Gary Kasparov, and became the first computer to beat a world chess champion. In this era for the first time, AI entered the home in the form of Roomba, a vacuum cleaner. AI came into the Business world in the year 2006. Companies like Facebook, Twitter, and Netflix also started using AI. In the year 2011, IBM's Watson won jeopardy, a quiz show, where it had to solve complex questions as well as riddles. Watson had proved that it could understand natural language and can solve tricky questions quickly. Google has launched an Android app feature "Google now", which was able to provide information to the user as a prediction. In the year 2014, Chatbot "Eugene Goostman" won a competition in the infamous "Turing test." In the Year 2018, The "Project Debater" from IBM debated on complex topics with two master debaters and also performed extremely well. Google has demonstrated an AI program "Duplex" which was a virtual assistant which had taken hairdresser appointments on call, and the lady on the other side didn't notice that she was talking with the machine. Now AI has developed to a remarkable level. The concept of Deep learning, big data, and data science are now trending like a boom. Nowadays companies like Google, Facebook, IBM, and Amazon are working with AI and creating amazing devices. The future of Artificial Intelligence is inspiring and will come with high intelligence.

Branches Of Artificial Intelligence

1_h_yloQIVEY2vaca31HN8HA.png Artificial Intelligence can be used to solve real-world problems by implementing the following processes/ techniques:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Robotics
  • Expert Systems
  • Fuzzy Logic

    Machine Learning

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

understanding-different-types-of-machine-learning.png Under Machine Learning there are three categories:

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning

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

    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. Twitter uses NLP to filter out terroristic language in their tweets, Amazon uses NLP to understand customer reviews and improve user experience. This video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP.


    Robotics is a branch of Artificial Intelligence that focuses on different branches and applications of robots. AI Robots are artificial agents acting in a real-world environment to produce results by taking accountable actions. 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 is used in the medical field to solve complex problems that involve decision-making. They are also used in automatic gearboxes, vehicle environment control, and so on.

    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 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.

    Future of AI

    That's not to make light of AI's potential impact on our future. In a recent survey, more than 72% of Americans expressed worry about a future in which machines perform many human jobs. Additionally, tech billionaire Elon Musk, long an advocate for the regulation of artificial intelligence, recently called AI more dangerous than nukes.

The least scary future I can think of is one where we have at least democratized AI…[also] when there’s an evil dictator, that human is going to die. But for an AI, there would be no death. It would live forever. And then you’d have an immortal dictator from which we can never escape Elon Musk

Jobs in AI

As we enter 2022, the AI job market is on fire. Data Science, Machine Learning, data engineering, and similar AI Roles continue to occupy the top spot by many measures, such as salary, desirability, and job prospects. This is all down to demand lead growth. Not only is the AI job market on fire but we believe it will continue to burn brightly. Here’s a look at 6 charts that explain why the AI job market is doing so well. C1.png

Chart Credit: Pitchbook 2021, Q3, Emerging Tech Report


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