Artificial Intelligence vs Machine Learning vs Data Science

Artificial Intelligence, Machine Learning, and Data Science are amongst a few terms that have become extremely popular amongst professionals in almost all the fields. It will be a matter of surprise if any professional has not ever heard of even one of these terms.

With the beginning of FOURTH INDUSTRIAL REVOLUTION — a technological revolution that is blurring the lines between the physical, digital, and biological spheres — it is now essential to have a better understanding of the terminology of fast-changing tech.

Is it easy to have a complete understanding of each of these terms?

We are assuming that you have no prior knowledge of any of these terms. Our goal is to dive deep into each of these concepts and spotlight the characteristics that make each of these distinct.

What is Artificial Intelligence (AI)?

“Artificial” can be anything that is made by humans and is not natural. And what do you understand by the word “Intelligence”? It is the ability to understand, think ,and learn. Therefore, artificial intelligence is a broad area of computer science that makes machines seem like they have human intelligence.

The goal of AI is to mimic the human brain and create systems that can function intelligently and independently. AI can manifest itself in many different ways.

If you have ever asked Alexa to order your food or browse Netflix movie suggestions, you are interacting with AI without realizing it.

AI is designed so that you do not realize that there is a machine calling the shots. In the near future, AI is expected to become a little less artificial and a lot more intelligent.

The definition of the word “Intelligence” is important here. Let’s define intelligence in two more ways. “Intelligence” is the ability to make the right decision given a set of inputs and a variety of possible actions, or it is a set of properties of the mind — the ability to plan, solve problems, and reason.

What Does Intelligent Behavior Exhibit?

  • Problem Solving — process of finding solutions to complex issues.
  • Reasoning — the act of thinking about something in a logical way.
  • Planning — the process of making plans for something.
  • Decision Making — the process of making important decisions.
  • Making Inferences — to conclude or judge from evidence.
  • Learning — acquisition of knowledge through study, experience or being taught.

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