Machine learning will disrupt several industries

This morning Harini Calamur shared a note on how machine learning is transforming the way research is done. So true! In fact machine learning will disrupt several industries including - legal, medicine, education and banking!

Machine Learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a "Field of study that gives computers the ability to learn without being explicitly programmed".

Of course, you need to program the machine to start learning and from that point forward, I guess, it is independent. While our quest to replicate the human brain remains unfulfilled so far, the advances in AI since 1959 have been significant. 

In the legal space, you now have technology that abstracts contracts, sorts millions of documents prior to review, it's called TAR, and emerging technology that promises to negotiate contracts automatically. 

Scientists can upload all their research material into an AI platform and the result strings all documents in a logical sequence, helping them utilize their limited study time better. 

The learning and development domain has largely remained unchanged since the innovation of computer based learning. Surely, there are new bells and whistles that have developed around learning management systems, however given that every person, that has access to education, spends nearly 1/3 of their productive life in a classroom, that's not enough. AI has the power to adapt learning to suit to an individual's context, learning styles and environment. There is an urgent need to exploit AI for learning. 

The banking industry is always at the forefront of adopting new technology. That's because it's highly competitive and dynamic. Machine learning can help banks manage risks better, define more personalized products and analyse big data efficiently. 

The AI space is heating up with several hundred start-up's, billions in funding and brave experiments. It is my hope that the sub-space of machine learning will flourish too!