A (very) Brief Introduction to AI & Data Science in the Industry 4.0 – DataDrivenInvestor

A quick guide on the scope of AI & Data Science with respect to Industry 4.0

Image by Gerd Altmann from Pixabay

In the rapidly evolving digital world, it is crucial that young people are prepared for a future where artificial intelligence (AI) & Data Science will likely play an ever-increasing role in their work lives. In the next few years, AI & Data Science will likely make a significant impact on many aspects of our society, including our work lives. AI & Data Science will revolutionize the workforce and change how we think about jobs and careers. It may also enable innovations that help to improve life for everyone on the planet.

Now, if you want to learn about the future and the present, then you always need to know the past because that’s very important and if you look at the technological revolutions, right? And I’m sure all of you must have listened to this and all of you may know about it, but I just want to spend a minute about this to say there has been sort of, you know, four technological revolutions that have changed the way we think or the way technology has improved and each one of these technological improvements or revolutions have sort of jumped or leapfrogged the technology for the entire human generation.

Industry 1.0

The first one is Industry 1.0, which is basically the steam engine. So the steam engine basically helped until that point, the people who produced and the people who consume had to be close to each other. The steam engine was the first time when you know, the people who produced and the people who actually consumed at a very fast pace because the steam engine is basically the engine or the train that pulled the train and it could take goods too far off places.

Industry 2.0

The second one was the invention of electricity that revolutionized because now you could work 24*7 technically, right? And also this mass production, so people could actually do a lot of mass production like telephones, bulbs, etc.

Industry 3.0

The third one was the electronic revolution. This is when the personal computers, your internet, your cell phones, all of that was basically invented or you can say created and that basically led to a humungous amount of data that was created. So people started thinking, you know, “How do I start collecting this data so that I can get some a lot of value into it? How do I start now generating more data in a very automated way?” And all of that has led to something called Industry 4.0.

Industry 4.0

This is where the concept of Artificial Intelligence, this Data Science, the Internet of Things and all come into the picture. This is where you know this data that’s been generated, “how do I make sense out of it?” For example, if I have data of somebody’s buying patterns, how do I make sure next time he or she logs in that I can do a recommendation to say, “Hey, buy this product, or if they have a particular service, let’s say in your broadband, so the next time you call, how do I make sure based on the usage pattern, where I can say, Hey, this person needs a better service or a lower service.” So all of that is basically the concept of using AI or data science and then generating automated data using the Internet of Things is what is at a high level is called the Industrial Revolution.

So I have a quick example.

Credit: REUTERS/Kimimasa Mayama
Credit: AP

Now, I just want to talk about the Industrial Revolution 4.0 a little bit so that you understand what it is and why it is.

Now, I wanted to share a video and this is how much of the data is generated in a minute and it will give you the format of data generated in one minute on the internet, one minute on the internet. After watching this video, you will feel like, “it is tremendous.” So it is a tremendous amount of data in one minute on the internet. Now think of 24*7 internet because when we are sleeping, somebody else is generating the data and when they are sleeping, we are generating the data.

People say that Industrial Revolution started in 2007 and that led to the entire AI and everything, and we will see now.

Let’s see what happened (Globally) in 2007.

  • At the beginning of 2007, on January 30th in the Moscone Center in San Francisco, a guy with the turtleneck and the jeans, and I’m sure everybody recognized that guy called Steve Jobs introduced to the world, something called iPhone. This was the first time the world saw a phone completely different. Until that point, they were so-called smartphones, then came the iPhone and the computing power of the iPhone was more than the computing power of Apollo 13 that went to the Moon, but that was not the main thing about iPhone. Yes, the computing power was higher but it created a revolution. How? It created this concept called apps. It created this concept where every information can be accessed, you have that information at your fingertips and you don’t have to go to 200 sites to get it. One small app can basically get some information to you, so that is what happened.
  • Then in 2007, Facebook was launched, but in 2006 actually, it was started in a dorm in Harvard, and then in 2007 it came up to the world.
  • In 2007, actually, a company called Twitter was started.
  • In 2007, one of the most important software, what today we call it for AI and Big Data called Hadoop, which is now used by 80% of the companies in order for their big data strategy.
  • The second-biggest software, I’m sure most of you must have heard it or some of you may not have heard it, what makes cloud possible started in 2007 called VMware. VMware with what makes virtualization today available in the cloud, and that virtualization is what makes cloud the most attractive in terms of the technologies that have come out.
  • In 2007, one of the other companies, which you must have heard of called GitHub and it started in 2007 and it is the largest repository of software in the world.
  • In 2007, basically, Google bought a small video company, which today we call it as YouTube.
  • In 2007, three design students went to a conference in San Francisco and they had carried three air pillows because they saw that all the hotels were filled, so they actually leased out the three air pillows and they got an idea, Wow, if I can do that, why can’t I use some people homes to do it? And so that’s how Airbnb was started.
  • In 2007, Google started an alternative operating system to Apple, and they called it Android and today 85% of the world’s phones run in this operating system called Android.
  • In 2007, Amazon actually released its first e-reader and as we know it today, it’s called Kindle.
  • In 2007, IBM actually went live in terms of, you know, their processing power.
  • In 2007, if you look at the curve of solar energy, just look at 2007 alone, the capacity just went up because of the technology.
  • In 2007, the cost of sequencing the human genome because of all these improvements, as you can see, it just dropped. It started with a billion-dollar or a million dollars and $100 million dollars in some cases and today, less than, you know, $100-$150, you can get your entire genome of your body sequenced.
  • 2007 was the first time Intel used non-silicon-based material for their chips, for their ICs because that’s how only they could keep up Moore’s law.
  • In 2007, Michael Dell, who had resigned from his job as the chief executive of Dell two years back, took the company private and came back as the chief executive.
  • 2008 was the first time we have public data for cloud computing, which means to say obviously, you’re going to have 2007 data in 2008. So that’s when the public cloud started.
  • In 2007, Google actually released something called Street View. In India, it is not there, but if you are familiar with that, just go to Street View and basically, it’s not just your Google Maps, but it’ll tell you how the street looks like.
  • 2007 is when the first time Netflix switched from its DVDs into streaming. So they said DVDs don’t work anymore. They said they went into streaming because they saw that the cloud, everything had come up so much and said this is when I have to switch into streaming.
  • 2007 was the first time a cyberattack happened on a sovereign country, and Russia was responsible for it for Estonia. Obviously, today’s situation is, you know, everybody knows what’s happening, but 2007 was the first time Russia actually had recorded an official cyber attack. The country’s first cyberattack from country to country in Estonia.

Let’s see what happened in India in 2007.

  • Jio (India’s largest 4G network) started in 2007.
  • In 2007, two kids said, you know what, if amazon can do it globally, we can do it in India and today we know it as Flipkart.
  • In 2007, probably one of the biggest fashion sites in India called Myntra started.
  • InMobi, which is, you know, basically the mobile ads company started in 2007.


Now, what is always all about this artificial intelligence? What does that mean to be artificial intelligence and what are the jobs available? But before that, I wanted to say one of the big applications of artificial intelligence is called NLP natural language processing. So basically this video talks about how in real-time you can do a conversion from language A to language B, listen to it. So basically, as you can see, in real-time when people are speaking from English to Chinese or Japanese I think. So this is the power of AI.

Data Science

If you are interested in basically, you know, to get into pure data science, what does that mean? If you’re learning in and interested in, you know, basically getting information from the data, understanding that then data science basically has three components.

  • The second is called visualization and it is basically, “how do I display the data using the software to do that?”
  • Third, one is the actual algorithms and the model, which is called machine learning statistics and deep learning.

Computational Data Science

However, if you’re interested so much about, you know, for example, cloud technologies, “how do I actually get the data? How do I actually modify data? How do I actually set up the data?” Then it is called computational data science, which is basically a bit of computer science and engineering and then you also have to learn machine learning, science and programming.

What do you require for anybody to be a good data scientist?

For that, basically, there are two things.

What do you need to succeed in Data Science?

I come up with this called TALENT and it is divided into,

What types of jobs are available out there in Data Science?

One of the things that if you look at data science is, the good news for data science is can be used anywhere, any domain. It can be in finance, it can be in healthcare. In every industry, there’s a need for data scientists, there’s a need for people both, you know, business and data science knowledge, with pure data science knowledge, with pure engineering knowledge.

Data Science is being used everywhere. How?

I would like to share a video and please listen to it.

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