For centuries, we have seen that natural resources like land, gold, or oil have been the source of power in one civilisation after the other. But as we get close to completing the first two decades of this millennium, it has become apparent that data is the new natural resource. Whoever has more information is likely to wield more power, but the one who makes the best use of Data Analytics to make sense of that data can become more powerful scientifically, economically and even politically. From governments to large corporations, everyone is trying to collect, store and use data in large quantities, which is changing the way we live our lives. Machines like supercomputers are being fed humongous amount of data, and the insights obtained from Data Analytics are helping companies make better decisions, governments make citizens’ lives better, and also allowing the common man to make better use of different types of gadgets.

Computer programmers and scientists have also taken this journey a step further, by incorporating algorithms which help machines to work on data to think intelligently and learn how to provide better solutions. Artificial Intelligence is being supplemented by Machine Learning in several spheres of life, leading to surprising results earlier thought possible only on the pages of science fiction books. Every year brings in further improvements in the quality of our collective knowledge and 2018 looks to be no different. Let us take a quick look at the seven most significant trends we see so far in Machine Learning in 2018.

1. The Internet of Things (IoT) will leapfrog into the next level, with machines becoming more participative in both business and household ecosystems. Machine Learning will make IoT a two-way affair, in which the available data will be analysed by devices and better solutions provided without prompting.
2. Data Analytics will take on a new dimension by the inherent intelligence provided by Machine Learning. There will be a growth in the market for electronic Machine Learning applications.
3. Speech recognition and almost-human conversational ability will become an intrinsic part of several Data Analytics tool. The recent announcements of Google Assistant making calls on behalf of humans and even booking appointments for them tell us how far we have reached in teaching machines how to think like humans and respond to other humans.
4. The number of young and fit people doing labour intensive activities like mining and farming is reducing by the day. This provides an enormous potential for applying Data Analytics and Artificial Intelligence to teach farm and mining implements to replace humans without losing out on the human feel for such activities.
5. Healthcare is an area which sorely needs the benefits of artificial intelligence, and this is already underway as you read this. The great work done in genome sequencing which has helped combat diseases like cancer will be taken forward in 2018. Added to this is the enhanced quality of visual recognition which we have developed as part of facial recognition technology, and we can see this being used to spot flaws and anomalies in medical scans.
6. Machine Learning is set to become a significant differentiator for corporations. Earlier, companies used to spend on research and development to improve the products and services, but more and more companies will now shift the focus of their research to get the cutting edge and move ahead of competition, in areas like customer relationship management, targeted marketing, complaint resolution, and Data Analytics of historical data.
7. The whole world is focusing on better and faster software which will facilitate Machine Learning, but one fallout of this is that even the hardware industry will see a churn in 2018 and beyond. We will require smaller, faster and better chipsets along with more efficient stacks to run these smarter software and also be able to handle the enhanced Data Analytics requirements.