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“AI doesn’t have to be evil to destroy humanity — if AI has a goal and humanity just happens to come in the way, it will destroy humanity as a matter of course without even thinking about it, no hard feelings.”
Elon Musk, Technology Entrepreneur, and Investor.
Artificial Intelligence in simple words is to make robots/computers think, learn, act and react like we humans do.
Artificial Intelligence aims to enable computers to have their own brains, something which we would not have to program explicitly but the computers will program(learn) and reprogram(relearn) on their own like we do.
Now where have we seen such computers?
- Jarvis from Ironman-Sometimes you gotta run before you can walk.
- T-101 from Terminator-Hasta La Vista Baby.
- Transformers-More than meets the eye. Transformers-Robots in disguise.
- Will Smith in I-Robot, Rajnikanth in Robot, the list goes on.
Now although these examples may seem way too exaggerated(also imaginary), that is the ultimate destination, the place where we are eventually aiming to be. Whether we will be able to achieve it or not? Only time will tell.
As of now, researchers and technological experts from all across the globe are taking baby steps towards achieving this ultimate goal.
Now where does Machine Learning come into this? What exactly is Machine Learning? Read on ….
The learn part in Artificial Intelligence is where Machine Learning kicks in. The term is self-explanatory: It is the process of making machines learn on their own.
Let’s clear up one ambiguity before we head into how Machine Learning evolved.
People often get confused between three terms: Artificial Intelligence, Machine Learning and Data Science.
These are three different but interrelated terms.
I guess I’ve already explained the first two.
So you can imagine Machine Learning as a subset of Artificial Intelligence.
Can you imagine how Data Science will fit into this picture?
This is exactly how it fits in.
Data Science is the art of gathering, mining, processing, extracting, organizing, etc, etc data. Basically anything you do with data falls into Data Science.
Fun fact: Anything you do with extremely large scale of data is known as Big Data.
You might wonder what role data has to play in machine learning or Artificial Intelligence in itself.
The simplest explanation for this is:
Q. How did you learn in school?
A. Through Textbooks(Voila) which is nothing but data in textual form.
Q. How did you learn to see?
A. Through the magic of sight (Data in image/video form).
Q. How did you learn to listen/speak?
A. The question is the answer over here. By listening/speaking (Data in audio form).
You learn with the huge amounts of data available to you. You learn with experience which in itself is nothing but data in your memory.
Let’s roll back a few decades.
You are a baby. You go into the kitchen. You touch a hot plate. What do you do? Well… apart from start crying.
You learn that you do not touch a hot plate. Never!!! Although you had no idea about what a hot plate is, or were never before told not to touch it(not that you would understand anyway), you learnt it from an experience. Not to mention you’ll probably start screaming the next time you’re anywhere near a hot plate.
This extends to other experiences you have as a child.
You try to do something. You make mistakes. You learn from your mistakes. You get good at doing that something. This, in essence, is the basic building block(the atom) of any machine learning algorithm. Or any learning for that matter.
Now, as you can see here, the computer is getting good at one specific task.
There are two variations to Artificial Intelligence.
Narrow AI is what we talked about. Getting good at something specific. Spam filters, Facebook’s face tagging, YouTube’s recommendation system or even Self Driving cars for that matter are Narrow AI. They are focused on one particular task and excel at that task far better in comparison to most humans.
General AI on the other hand has to cope up with any task that is thrown at it much like a human. The various examples we mentioned at the start- Jarvis, Terminator, Transformers, and the humanoid robots are all able to do any task that is asked of them (or in cases, willed by them). It ranges from giving advice to the most popular superhero on the planet to well, plan to takeover the planet itself.
They possess the cognitive intelligence and are be able to understand and interact with the surrounding environment, much like a human but also possess extremely high data crunching capabilities(in human terms- a much higher knowledge and sense of the surroundings – kind of like Spider Man’s spider sense).
To get a better understanding of how Machine Learning evolved over time, visit the below link where it is illustrated in much detail.
Surprised at how far back the roots of Machine Learning go?
Now, you may wonder that such species of robots would become superior to humans. And with the amount of processing power at their arsenal, they may also pose a considerable threat to the human race. You are not alone.
There are countless movies which are based off this theme:
Terminator, I-Robot, Robot, Avengers: Age of Ultron are a few of the popular ones. Quite enjoyable watches as well.
But no need to be worried.
The General Artificial Intelligence is, at the moment leaps and bounds away.
That is the end goal technologists and researchers around the world are racing towards, but we are far, far away from the finish line.
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