Artificial Intelligence | The Pillar of the Post-Digital Era.

Artificial Intelligence | The Pillar of the Post-Digital Era.

What is Artificial Intelligence?

Artificial Intelligence is a term often used nowadays, people are very much familiar with this word. Artificial means something created by man and Intelligence means the ability to acquire and apply knowledge.

You’ve seen nowadays machines can perform lots of human tasks that a we can perform. The machine can pretty much see and recognize objects, the distance between the objects, and do certain tasks that are require at any specific moment.

Machines can hear, understand, and respond. Also machines can perform many human tasks which are intended to make human life effortless.

Does this mean Machines have Brain now ???

No, machine is and has been dumb since its creation. The intention of AI is to make the machines think for themselves, by using means such as algorithms, trial & error, and repeated attempts of the task to make the outcome more closer to the intended result.

AI is a bundle of Machine Learning, Deep Learning, and Neural Networks. All these technologies made Artificial Intelligence possible.

It grants machine to think and take decisions like humans. Due to this machines can learn and solve the problems on their own.

Artificial Intelligence work patterns & Classification.

AI is classified on basis of how they work, and is basically classified into three types :

  • Strong AI or Deep AI.
  • Weak AI or Narrow AI.
  • Artificial Superintelligence

Strong AI.

Strong AI is the concept of a machine with general intelligence that mimics human intelligence and/or behavior, with the ability to learn and apply its intelligence to solve any problem.

It can think, understand, and act in the same way as humans.

AI researchers and scientists have not yet achieved Strong AI. To succeed, they would need to find a way to make machines conscious & programming a full set of cognitive abilities.

Weak AI.

Weak AI or Narrow AI is the only type of Artificial Intelligence we have successfully created to date.

Narrow AI is a goal-oriented, designed to perform singular tasks – i.e. facial recognition, speech recognition/voice assistants, driving a car, or searching the internet – and is very intelligent at completing a specific task it is programmed to do.

While these machines may seem intelligent, they operate under a narrow set of limitations, which is why this type is commonly referred to as weak AI.

Narrow AI doesn’t mimic or replicate human intelligence, it merely simulates human behavior based on a narrow range of parameters and contexts. 

Artificial Superintelligence.

Artificial superintelligence (ASI), is a hypothetical AI that doesn’t just mimic or understand human intelligence and behavior but it is where machines become self-aware and surpass the capacity of human intelligence and ability.

Two Major AI techniques.

  1. Logic and Rules-Based Approach.
  2. Machine learning (Pattern-Based approach).

Logic and Rules-Based Approach.

A rule-based system uses rules as the knowledge representation. These rules are coded into the system in the form of if-then-else statements.

The main idea of a rule-based system is to capture the knowledge of a human expert in a specialized domain and embody it within a computer system. That its No more, no less. Hence, knowledge is encoded as rules.

Machine learning (Pattern-Based Approach).

In contrast to rule-based systems, learning systems have a very ambitious goal.

The vision of AI research, which turns out to be more of a hope than a concrete vision. It is to implement general AI through the learning capability of these systems. Hence, the hope is that a learning system is in a principle unlimited in its ability to simulate intelligence.

How AI works?

AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data.

AI is a broad field of study that includes many theories, methods and technologies, as well as the following major subfields:

  • Machine Learning.
  • Deep Learning.
  • Neural Networks.
  • Computer Vision.
  • Natural Language Processing
  • Machine Learning.
    • Machine learning is an application of Artificial Intelligence (AI) that provides system the ability to automatically learn and improve from experience without being explicitly programmed. 
  • Deep Learning.
    • Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called as artificial neural networks.
  • Neural network
    • The concept of the Neural Network was inspired by human biology and the way neurons of the human brain function together to understand inputs from human senses. 
  • Computer Vision.
    • Computer vision is an interdisciplinary scientific field that deals with how computers can gain a high-level understanding of digital images or videos.
  • Natural Language Processing.
    • Natural language processing is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language.

Additionally, several technologies are enabled and supports AI:

  • Graphical Processing Units.
  • The Internet of Things. 
  • Advanced Algorithms.
  • APIs, or Application Programming Interfaces.

With the Integration of all these technologies together is how AI works.

Applications of Artificial Intelligence.

AI Applications.
  • AI in Gaming.
    • AI is be used for gaming purposes. The AI machines can play strategic games like chess, where the machine needs to think of a large number of possible places.
  •  AI in Finance.
    • AI and finance industries are the best matches for each other. The finance industry is implementing automation, chatbots, adaptive intelligence, algorithm trading, and machine learning into financial processes.
  • AI in Social Media.
    • Social Media sites such as Facebook, Twitter, and Snapchat contain billions of user profiles, which need to be stored and managed in a very efficient way. AI can organize and manage massive amounts of data. AI can analyze lots of data to identify the latest trends, hashtags, and requirements of different users.
  •  AI in Automotive Industry.
    • Some Automotive industries are using AI to provide virtual assistants to their usage for better performance. Such as Tesla has introduced TeslaBot, an intelligent virtual assistant.
  •  AI in Robotics.
    • Humanoid Robots are the best examples for AI in robotics, recently the intelligent Humanoid robot named Erica and Sophia has been developed which can talk and behave like humans.
  •  AI in Education.
    • AI can automate grading so that the tutor can have more time to teach. AI chatbot can communicate with students as a teaching assistant.

Pros and Cons.

 AI doesn’t get tired and wear out easily. High cost.
Digital assistance helps in day to day chores.No human replication.
Rational decision maker.No improvement with Experience.
Can reduce no of labors needed.Creativity is not the key for AI.
Digital Assistants.Unemployment.
Comparison table for AI.

Limits of Artificial Intelligence.

  1. Many things are still beyond the realms of AI.
  2. No Abstract reasoning.
  3. Sometimes hard to interpret systems.


In above article we tried to deliver the best knowledge regarding AI. What is AI?, How it works?, Applications, Pros and cons. we’ve tried to explain everything in a simple way. AI is the pillar of post-digital era. The DARQ technology also consists of AI.

The term smart for gadgets is used only because of AI, because machine is dumb, with the help of AI, Machines can think, process tasks like human.

AI is a buzzing technology. Even outside the tech world. People are getting more familiar with this term.

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