AI Or ML, Who Has The Upper Hand?

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So many coming of age movies have been developed where there is showcasing of advanced technology which has not been developed yet in the real world. This reel world imaginations seem so cool that we almost wish these technologies existed in real world too.

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One such coming of age technology is Artificial Intelligence. We cannot stress enough how important this word has become in today’s world. With AI there is another word that follows it, ML.

Now we come to the debate, which is more important or bigger?

Much speculations have been going around among students but to clear the air I bring you this article. An exclusive on AI VS ML.

Firstly, to get it out of the way, ML is simply an application of AI. It is a part of Artificial Intelligence and a different slice of the cake but not a different cake entirely.

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 Inspecting Artificial Intelligence, we can break it into two parts: Artificial and Intelligence. The major characteristic separating humans from other animals is the intelligence. When we build something, which is able to think and understand it is artificial intelligence.

Applying AI to a system which makes it able to learn on itself without any programming is termed as machine learning.

To understand the difference better, I present to you an extensive difference table.

     Artificial Intelligence                                       Machine Learning

Ability to acquire
knowledge and apply it.
Ability to develop a skill and achieve greater levels from the initial knowledge acquired.
Aims to increase rate of success. Aims at increasing the accuracy.
It resembles a
computer program that performs smart work.
A machine that takes input as data and
graduates itself from that data.
Involves applying
human intelligence to
solve complex
problems.
Involves getting data for a certain task and
honing its skills to improve performance.
Decision making Learning
Developing a system
that mimics humans.
Developing self-learning algorithms.
Wisdom Knowledge
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To simplify things machine learning is simply giving machine a teaching set of data and then it is asked to answer specific questions based on the set, just like teaching a child. You provide a set of pictures and make him/her learn what is the object in the photograph. Then the child is asked to identify the pictures. For example: A dog picture, an umbrella, etc. You then add to the pictures to confuse the child and increase the level of complexity. Each correct identification is stored in his/her mind and the wrong ones are corrected and tested again. Similarly, the machine behaves and this process is called machine learning. When it starts to add to its teaching set the new photos, it is learning and getting smarter. This learning process is possible through AI application in the machines. Just as the child uses its brain to develop itself, the machine uses its algorithms and develops itself.

So it is only AI vs ML in the learning world and not in the application world. We need to mix one with the other to attain great productions.

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When we look at the future of AI and Machine Learning, it is definitely bright. With their application in fields like data security, personal security, healthcare, fraud detection, marketing personalization and various other business aspects, millions and billions of dollars are expected to be invested in this field of technology.

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