Machine Learning -An insight into future

When Google’s AlphaGo crushed hope of millions by convincingly beating Lee Sedol in a Chinese board game GO three month back, suddenly the mankind felt the power of the beast inside the machine created by human beings itself. First time in the history a computer Go program had defeated a world champion leaving the human champion speechless.

So far there has been a great limitation in the traditional computer programming language to teach computers how to perform each task thus limiting the extension of intelligence in solving the more complex tasks. In such a situation Machine Learning comes to rescue.

Machine Learning is a sub-set of artificial intelligence where computer algorithms are used to autonomously learn from data and information. In machine learning computers don't have to be explicitly programmed but can change and improve their algorithms by themselves.

 Machine learning systems automatically learn programs from data. Machine learning is used in Web search, spam filters, credit scoring, fraud detection, stock trading, improving health care delivery, driverless cars and many other applications.

If we go back to the history of Machine Learning then we find even in 1950 Alan Turing created a “Turing test” to check if computer has real intelligence. In order to pass the test, a computer must be able to fool a human into believing it also to be human.

In 1957 Frank Rosenblatt designed the first neural network for computers which was called Perceptron having capability of simulating the thought processes of the human brain. During the 90’s machine learning changed its approach from being knowledge driven to data driven. Who can forget the famous win of IBM’s Deep Blue over chess champion Garry Kasparov in 1997 and now a great achievement by Alpha Go in beating another world champion Lee Sedol in 2016.

Drivers of Machine Learning:

Two key things which are driving the machine learning solutions are Raw Data and Data models. Machine learning enables data based decision systems to learn from new data to deliver reliable and consistent outcomes. New technologies viz. Big data and the IOT have given new wings to traditional machine learning practices.

Emerging trends in Machine learning

Soon people across globe will witness a tremendous growth of smart applications and main stream use of Artificial Intelligence. It is bound to proliferate the smartphone market and enter the territories of drones and self-driving cars. More domain specific and machine learning enabled technologies are bound to emerge this year. All the big names in technology viz. Google, Facebook, Microsoft etc. are putting their might behind in this domain to be relevant to emerging business scenarios.

 Some of the interesting application areas are:

The classrooms of the future will learn about each student, helping them master the critical skills. Teachers will be able to predict strength and challenge areas of each student and suggest them the measures to overcome those challenges.

Buying locally than on online will be in fashion again. Retailers will use the immediacy of the physical store and proximity to customers to create experiences that cannot be replicated by online-only retail. Digital experience will be magnifies by bringing web right to where the shopper can physically touch it.

Computers will help doctors understand how a tumor affects a patient down to their DNA, and present a collective set of medications shown to best attack the cancer, while reducing the time it takes to find the right treatment for a patient from weeks and months to days and minutes.

Smarter cities will become sentient cities, understanding in real time how billions of events occur as computers learn to understand what people need, what they like, what they do, and how they move from place to place. Mobile devices and social engagement will enable citizens to strike up a relationship with their city leaders so their voices will be heard not only on election day, but every day.

The darker side of Machine Learning:

Automated lifestyle emerging because of Machine learning systems will erode the human capabilities to fight odds to overcome obstacles. Too much dependence on Machine can remove the need of human interdependencies which is the core of civilization. Do we really want that? Though visionaries like Bill Gates are excited about the rise of artificial intelligence but also acknowledged the possibilities of unique challenges because of the possible greater–than-human capabilities of future machines.

Within a decade, Robots are expected to takeover tasks like driving and warehouse work as well machines which can outpace humans in certain areas of knowledge. A challenge of keeping the control of these machines with humans is not as easy as it looks. A must read by Martin Ford “The rise of the Robots” paints a realistic picture of the possibilities emerging from this new field of Machine learning.

Conclusion:

Whether we like it or not, advancements in Machine learning will keep on mesmerizing the human race. In the process lot of established norms will be obliterated and new ones will emerge. Lot of employment related issues are bound to haunt us ( As per a recent report a leading manufacturer of technology products Foxconn has replaced 60,000 workers with robots in its factory in Kunshan, China) while possibilities of extending the cutting edge solutions in healthcare even in remotest areas of globe excites us. This is a journey where both humans and machines have to co-exist, hopefully peacefully.