Age of Machine Learning – Next big wave for IT professionals

If you are a 90’s kid then you know how big a role this era plays in the history of humankind when it comes to achievement in technology.

Ask why?

Did you really forget that Keanu Reeves starter AI-based movie The Matrix was released in 1999? This is the same year when life-changing technology “dot com” emerged in our world. It’s really tempting for any tech professional to discuss the fascinating idea of “Horror or Paradise” presented by Matrix. However, that’s not the focus of this article.

Yet isn’t it true that everything starts with imagination?

In 90’s idea of inventing the human-like machine, the brain started taking shape. It began in 1050 when the “Turing Test” was performed by Alan Turing. To pass the test computer must fool humans into believing that it is also human. This idea was of having human-like machines were beautifully picked up by The Matrix. And yes, it was the beginning of the machine learning era.

In the year 1990, the work on machines started to shift from knowledge-driven to data-driven. Tech scientists began to create programs for computers to analyse a large amount of data, draw results and learn from results. Technology expert and author of 18 books wrote an amazing article on stages of machine learning from 1950 to till date.

As yet we are sceptical if we are able to create high-end Machines like the fictional Matrix. However, we are really progressive in building some really better machines for example first Robot US Citizen – Sophia.

Introduction to Machine Learning

Nowadays, when we don’t understand anything we just Google it. It’s a very natural habit. However often we get complicated answers. So let’s just try to simplify the complicated answer for the most Google question “What is ML” for better understanding. Machine Learning and AI are making a buzz in the tech world for decades yet these terms are relatively new to many out there.

What If We say Machine Learning is a part of AI?  we wouldn’t be making any mistakes. How about we take a closure look to clarify? Primarily Machine Learning is nothing but building machines which are able to process huge amount of data on their own and learn from it to think and act like a human without any supervision. You must be thinking like, It’s sounding like building a transformer.

Well yes, it’s more or less like that in layman’s language. In simple words let’s call it a building Machine who has a brain. In order to build a brain-like logical machine we first need to understand how the human brain works. It became easy as in the past few decades we decoded how the human brain functions through its neural network. We came to an understanding that, it is easy to teach computers how to learn than to teach them how to just perform. And that was the first major breakthrough in Machine Learning history.

It is very similar to teaching a new-born human baby to make a fine citizen. Of course in the case of the machine, the catch is we don’t want citizens we want machines to perform the given task effectively. The second breakthrough was the invention of the internet AKA the World Wide Web in the year 1989. Sir Tim Berners-Lee graduate of Oxford University and British computer scientist succeeded in opening our doors to the virtual world.

With this unthinkable invention, it became very easy to store massive information data which is not at all possible for the human brain.

Future of Machine Learning

Let’s hop-on to take a sneak peek into the near future of Machine Learning. It wouldn’t be a brave statement “Machine Learning future is undying”. This technology is growing at a breakneck pace almost every day. Take a look around and you will see that you are surrounded by machines that are actually logical like humans’ brains. The laptop on which you are reading this article right now is a machine and the mobile on your desk is a machine.

The smart speakers from Amazon – Alexa in your house are an example of a logical machine. The role of future tech is huge with the trend like remote monitoring of the sick, work from home, and our new normal online shopping. We are moving towards an era of the automotive industry, automotive homes basically automotive society. And to make that happen obviously we need more and more machines those are able to perform tasks without supervision.

We cannot unseen that Tesla CEO Elon Musk already succeeded in launching Full Self-Driving (FSD) feature in its Autopilot system on Oct 20, 2020, which is just last month. Musk is aiming for a wide release of FSD by the end of the year. So if you don’t see a driver in the driver seat you shouldn’t be surprised. It’s the magic of Machine Learning and AI.

Industries that have huge scope for Machine Learning

Frankly, every industry has scope for Machine Learning and it’s not limited to any particular sector. Investment sector, banking and finance, information technology, media & entertainment, gaming, healthcare, and the automotive industry you name it.

Somehow every industry is making Machine Learning a part of it. However, there are some industries where researchers are working toward revolutionizing the world for the future through Machine Learning. Let us discuss them in detail. In the automotive industry it’s not only Tesla but also companies like Google, Mercedes Benz, Nissan, etc. are taking part in this race. Robotics is one more industry that has shown significant interest in ML since 1954 when George Devol invented the programmable robot Unimate.

Healthcare is among those industries that generate huge data and continuously work on research. Considering that effective machine learning implementation is going to be the need of the hour in Healthcare. In informational Technology, quantum computing is going to have a huge scope as there are a lot of advancements to achieve.

Conclusion

ML has particularly taken the centre-stage as more and more brands have to realize that the possibilities are endless. According to research 2020 is the breakthrough year for Machine Learning. CRN predicted that the revenue generated by ML is expected to reach $156.5 billion worldwide this year, according to market researcher IDC, up 12.3% from 2019.

Considering all the facts until now Machine learning future looks prominent and it’s not going to fade away so soon. So, as an IT professional if you are thinking to take step ahead for ML Certification then needless to say It is right choice and time.