AI (vs) Machine Learning (vs) Deep Learning

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What is AI?

AI stands for?Artificial Intelligence. As the name proposes, it is man-made Intelligence. AI is a technique/ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.

The idea and concepts of AI came into existence around the 1950s — 1970s. It is a very old concept. But, Why has it gained so much popularity recently? — It’s because, in the earlier days, we didn’t have the amount of data needed to predict things via computers but, now, we have got a huge amount of data (around more than 44 Zettabytes) in the world. In addition to that, nowadays, we also got a high-end computer with large storage, which are very suitable for AI. So, it is the perfect time to use this data and let the computers predict things.

In 2021, More or less around 88% of the industrial enterprises are considering AI adoption for their growth in business.

Uses of AI:

1. With AI, It is possible for machines to learn from their experience, and they predict things when we give them a new input.?Isn’t that like a human? We also learn from our past and try to improve ourselves in any given new situation.
2. Artificial Intelligence(AI) can be trained to accomplish specific tasks by processing a large amount of data and recognizing the patterns in the data.

We use AI in many fields today. Some examples are, Google Assistant, Siri or Alexa.

What is Machine Learning?

Machine Learning is a branch/Subset of AI.

Why did Machine Learning start in the first place?

Machine Learning came into existence in the late 80s-90s. There were some problems faced by AI and Neuroscience Researchers like, “How to make a more robust(advanced) version of AI system?” and “How to make a design model of a brain through AI?”.

That is when Machine Learning came in! So, In Machine Learning, with the properties of AI, it is more focused on building an algorithm and models to perform a task just like humans depending, upon the statistics and probability data of the tasks. Hence, Machine Learning makes computers act and make data-driven decisions to carry out a certain task.

“Machine Learning is a subset of AI technique that use statistical methods to enable machines to improve with experience.”

What is Deep Learning?

Deep Learning is a type of machine learning based on artificial neural networks.

What are Artificial Neural networks?

We know that, there are brain cells called neurons in our brain and to design an algorithm/model that functions like the brain (for example: Learning a large amount of data), the concept of artificial neural networks is formed.

How Deep Learning Works?

In Deep Learning, there are many neural nodes connected with each other and analysing the data through multiple levels of abstraction. Thereby allowing the system to learn complex functions mapping with any specified algorithm. So, No one knows, what is actually happening inside the neural network and why it works so perfectly.

The summary of its work is that We give a large amount of data to the neural network. After Analyzing the data through multiple levels of abstraction, it gives out a perfect output for the specific problem.

Conclusion:

In this article, I tried to explain the small differences in concept between AI, Machine Learning and Deep Learning. In conclusion, we can say that AI is the bigger picture, Machine Learning is one of the subsets of AI and Deep Learning is a particular kind of Machine Learning based on neural networks.

Hope you found this Article helpful!

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