Why you should learn Machine Learning justified in 5 minutes

(This is the 2nd article in the series of articles being written on Machine Learning where we explore, learn, and understand the fundamentals of machine learning in the simplest way possible. Here is the link to the previous article in the series- Machine Learning Simplified in 4 minutes )

Before diving deep into the technical concepts of machine learning, I felt it was essential to understand why machine learning is among one of the hottest topics in the industry today and why it might be really important to keep an eye on the developments in this area.

Why Learn Machine Learning Now?

What does the future look like? Advancements in machine learning are by far among the most significant developments in the technology of the 21st century apart from the rise of the Internet of Things [IOT]. What’s more interesting is that IoT devices too, need machine learning to become more functional and intelligent. The future does look bright but progress often comes with its own challenges. Our current knowledge of Artificial Intelligence is only moderate. There is still a lot to achieve and innovate but harvesting all the potential of AI is within the reach of our skillset. It is evident that machine learning will be extensively used in various domains of science and technology and as an Innovator and an Engineer, it is something that can't go ignored. Having command of this subject can surely help us build disruptive solutions to real life problems and multipurpose utilities to improve the quality of human life.

2.1 CURRENT TRENDS IN THE INDUSTRY

Much of the research attention today is in the field of Natural language processing and Computer vision. Most of the other technologies are rapidly evolving to support developments in Artificial Intelligence as well. Even some new technologies are emerging which could assist in faster development. Cloud computing comes under this category enabling even small-time developers to build sophisticated machine learning systems. Another emergent technology is Quantum Computing.

R&D departments have started using machine learning for their research activities as well. Machine learning is being widely used in various industries and will only expand further in the coming years.

The job opportunities are rapidly increasing and even the start-up culture is shifting with a lot of new companies emerging in this field. Tech giants like Google and Microsoft are investing heavily in research and development in this field. It only shows how much promise machine learning and AI holds for the future.

2.2 FROM SCI-FI TO REALITY

Most of the ideas that were only science fiction a few years ago are now becoming a reality. It will not be late before our inventions will surpass the imagination of science fiction itself.

Perhaps science fiction writers will have a tough time in future to write some new innovative stuff with everything they could imagine already being invented. Automated intelligent robots, smart security systems, self-producing factories, Intelligent virtual assistants, etc are some of the sci-fi technologies already being implemented in real life and more are going to follow.

2.3 PROJECTS FOR THE FUTURE

Here are a few projects that developers will work towards building in the future. Some of them are already under development and perfection will eventually be achieved with time. It has always been a question of when? And not If? These are among the most promising advances humans would want to achieve:

• The Virtual Doctor: IBM Watson is already better at diagnosing diseases than an average doctor. Machines will soon be able to provide health care on par with doctors, if not better than them. The key advancements that can achieve this are better computer vision algorithms and recommendation systems which will be able to provide personalized health care based on various medical parameters of the patient.
• The Artificial Writer: Yes! You heard it right. Machines are going to get creative. The existing technology itself is commendable but things are only going to get better. Soon machines could become as creative as humans in writing content.
• Self-Driving Vehicles: Autonomous cars, drones, planes, etc. are already here and more will be available for commercial purposes on a wide scale soon. This has been one of the most researched topics by Google. Computer vision and object tracking play a key role in the development of better and safer self-driving vehicles.
• The Virtual Teacher: Education is already being revolutionized with digital learning platforms and applications. Machine learning will further enhance in providing efficient education to all.
• Better Unsupervised Learning Methods: Sooner or later, this is bound to happen as there haven’t been many significant advances in this area. A better technique in this area will take machine learning algorithms a step ahead. If you are a researcher, remember to keep an eye on unsupervised learning.

2.4 CHALLENGES TO OVERCOME

While machines are getting more intelligent by the day, not everyone is happy. It has always been a speculation if the day would come when we would achieve technological singularity. What will be the consequences then? There is another question of concern. If machines learn to do everything by themselves and everything that humans could do, then what will humans do? With the rise in jobs in AI and deep learning, one may think humans are going to work in those fields but that is only temporary. What if sometime in future, an intelligent program is made, so intelligent that it can create new intelligent programs on its own (essentially creating a technological singularity)? What will humans do then? A more scary question would be what will machines create then? Another concern is the fact that people from other industries are rapidly losing jobs due to automation. Advancements in machine learning ultimately improve AI technology and are we taking AI seriously enough?

Scientists like Stephen Hawking and his colleagues accept that "The creation of the perfect AI will be the biggest event in human history but it could also be the last unless we learn to avoid the risks".

Perhaps the answer to the problems that machine learning could possibly pose lie in machine learning itself. Learning about something that is now an integral part of our daily life is quintessential irrespective of the merits and demerits of the technology. For that matter, knowing about it helps us in learning new ways to avoid the risks it can pose, both in our lifestyle and in our business. Facebook, Google, Amazon, and even LinkedIn along with other tech-giants are now heavily dependent on recommendation systems based on machine learning and related concepts. In fact, we are using products of machine learning everywhere without realizing it. The following image summarizes where exactly ML products are currently being developed.

(Infographic Image Source: forbes.com)

In a nutshell, machine learning, today is omnipresent in multiple domains and humankind will continue exploring and reap it's benefits to the maximum ignoring the uncertain consequences.

"Nevertheless, we are becoming more like machines in pursuit of making machines look more human, don't you think?"

The ultimate question I raise here is, How well do we know about the technology that is set to revolutionize the world as we know it? and are we a part of that revolution or just a spectator?

(Stay tuned for the next article where we will start with the technical concepts relating to various machine learning algorithms in the simplest way you can think of)

This article is a part of a series on Machine Learning by 'The Research Nest'

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