welcome back!
So far we have seen what is an AI and its history of development
Starting from the early stages of AI,  people wanted to build an Artificial General Intelligence.
That is, creating a system that has the intelligence level comparable to humans
But we are unable to achieve in building such an advanced system
The most successful AI programs in the industry today, falls under the category of Artificial Narrow Intelligence.
Google Search engine is an example of Narrow AI
There is a major difference between a traditional software program and an Artificial Intelligence program
A traditional software program can do only the tasks that it has been programmed to do.
But, an artificial intelligence program can learn from your input data.
It can use the learned information to solve a similar kind of problem in the future,
whereas, a traditional program cannot solve any unknown problem.
There are many techniques to create intelligent programs.
We will see all those techniques in a separate tutorial series.
The most succesful and popular among them is Machine Learning!
People started to develop many algorithms under this topic way back from 1980s
All these techniques are the most popular and used to solve certain problems under certain conditions.
The most successful and popular technique of this machine learning is the Artificial Neural Networks.
Artificial neural networks are decade old models
But over a period of time, artificial neural network has been refined a lot in terms of its architecture
and has evolved to solve certain specific problems.
Today this artificial neural network is used a lot in the industry in the form of Deep learning.
Deep learning is also a part of machine learning.
But these are deep neural networks that can learn deeper insights from the data.
They learn to solve very minute and important details in any problem.
This deep learning is just a complex neural network.
The neural network architectures shown on the screen are the popular ones used in the industry today.
These deep neural nets are currently used in almost all big companies like Google, Facebook, Amazon, etc
These are currently the most promising model to build a successful AI system in a limited domain.
Here it's all about computing, the more processing power you have
the less time it takes to solve a problem and more effective the solution.
People have been using Graphics cards for gaming purposes.
These graphics cards are very good in computing floating point numbers which are required by the AI programs.
A GPU can compute floating point calculations at the rate of 10 -100x higher than a CPU.
A Neural network can learn as much as it can with the help of quality data
and as fast as it can with the help of computing speed. Both of them are available today.
So many things which were not possible before have been made possible now.
The Price of GPUs has also decreased.
Hence, it is possible for you to develop an artificial intelligence program just by
sitting in your home with a decent PC configuration!
Just look around us. Unknowingly we interact with many AI applications
Today most of the AI programs we interact with are  limited domain expert systems that perform only certain tasks very smartly.
We use Google search every day.
Google is using a lot of Deep learning programs in all its products.
Recently Google started using RankBrain which is a deep learning program.
We use Google translate applications. .
Certain architectures like Recurrent Neural Networks are used in these applications
Voice recognition technology has developed a lot in AI.
Today an AI can understand your language and respond to your queries by voice in your language
The technology that enables computers to understand the natural language of humans
and respond to the it is called Natural Language Processing.
This is one of the hot areas where AI research has huge potential applications.
Image processing by AI programs has been a huge success.
You take a picture, upload it to Facebook
and Facebook immediately recognizes the faces of the people in the photo.
Facebook uses an AI program called DeepFace.
Facebook claims this deep face program has near human level accuracy.
That is, if a human can recognize a face in a complex image with an accuracy of 97.53%,
the DeepFace program can recognize faces with an accuracy of 97.25%
Today, In many airports these AI programs decide which plane should land on a runway
given the airspace information to avoid a collisgiven the airspace information to avoid a collisionion
They decide which path to choose to reduce travel time and make efficient use of fuel.
Medical field also finds  great application for AI.
IBMs Watson computers are used to study and help scientists in cancer research.
You shop in FlipKart, Amazon, and other on-line marketplaces.
Once you purchase an item, the suggested future product recommendations are mostly done by an AI.
Amazon developed a deep learning program called DSSTNE.
They have recently open-sourced this program.
So it is possible for us to download this program and develop a custom recommendation based applications!
Today many people who trade in stock markets use these AI programs and trades more efficiently than ever.
These AI programs are available for $100.
You need to buy the program and just link your bank account to these programs.
This program will decide which stocks to buy and which ones not to buy.
We use email programs every day.
Have you ever noticed that spam messages in your Inbox have reduced considerably than what it was a few years back?
Who marked these emails as Spam? Obviously, a human can't do this for all people in the world.
It would be extremely difficult for a traditional computer program to categorize a mail as Spam.
So an artificially intelligent computer program should have done this.
Yes, it's an AI program that learns over a period of time what a Spam mail would mean and what might be contained in it.
It reads every mail and tries to identify the intention of the sender and analyzes everything related to the mail and classifies it as a Spam.
To do this, these programs have taken a lot of data and learned from it. As part of this learning,
you have also taught these programs by marking a mail as Spam.
Self Driving cars take data from Radar, and other sensors and an AI program interprets the readings and
creates a 3-dimensional map around the car and can safely drive the car on the road.
Today AI programs find applications in your Computer Antivirus software,
the Apps on your mobile phones,
Games and in all other areas.
If these neural networks were not there, we would not have reached this stage.
In this Fourth Industrial revolution series, we are going to take a deeper look at this deep neural networks.
Fine. This technology is interesting, this is the future and everything is OK.
But if I want to enter into this field today, what are the prerequisites and what can I do tomorrow?
That is what we are going to explore in part 4.
So please watch part -4 video.
Thanks for watching
See you again!
