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Machine learning and AI two different concepts why

Great to read this article. This is a summary of what I learnt from many books and magazines. Summary, I am going to present for you a quick guide. Let us come to the point...

The thoughts on AI...

Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”.

The theory in way back,

Very early European computers were conceived as “logical machines” and by reproducing capabilities such as basic arithmetic and memory, engineers saw their job, fundamentally, as attempting to create mechanical brains.

As progressing to new era the technology and understanding about our mind how it works caused creation of thoughts.

That thoughts now called as AI (Artificial Intelligence).
The artificial intelligence comes in two parts. One is Applied AI and the other one Generalised AI.
AI example
AI Example

When Applied AI
is far more common – systems designed to intelligently trade stocks and shares, or manoeuvre an autonomous vehicle would fall into this category.

The other category is...

Generalized AIs – systems or devices which can in theory handle any task – are less common, but this is where some of the most exciting advancements are happening today.

An Introduction to Machine Learning
#Sponsored (An affiliate relation with Udemy)
What is Machine Learning...

Machine Learning as the vehicle which is driving AI development forward with the speed it currently has. The father of Machine learning is Arthur Samuel in 1959.

In short, the concept of Machine learning is...

Rather than teaching computers everything they need to know about the world and how to do the tasks, instead it might be possible to teach them to learn themselves. This is basically called Machine Learning.

The second, more recently, was the emergence of the internet, and the huge increase in the amount of digital information being generated, stored, and made available for analysis.

Once these innovations were in place, engineers realized that rather than teaching computers and machines how to do everything, it would be far more efficient to code them to think like human beings, and then plug them into the internet to give them access to all of the information in the world.


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