It's [A]l[I]ve

If 2016 was the year of VR, then 2017 is the year of AI.

- Mithun Mohandas

Primarily pictured in movies as that evil entity which threatens all of mankind, the future of Artificial Intelligence (AI) seems a long way from what we see today. Current AI are simply decision makers, very good decision makers, with millions and millions of data inputs being factored to generate elaborate binary trees which form the brains. And with hardware pushing the boundaries, we’re enabling these AI to become smarter at an unprecedented pace. The growth of AI has been so rapid, that some of the smartest minds on the planet have rung the alarm bells. So how do these simple decision making AIs pose such a threat to mankind? To understand that, we need to have a look at the state of AI so far.

A primer on Machine Learning

Machine Learning has been around for ages, and in the simplest sense it is about building machines that can learn without being explicitly programmed. It boils down to creating a set of conditions for pattern recognition and then the computer is fed a lot of data using which it hones these preset conditions to increase levels of accuracy. The data sets are also monitored during the learning phase to ensure that the right kind of conditions are learnt by the system. This is the training phase where the data that’s fed to the system is handpicked. Once the training phase is over, we provide a few data sets to see how well the system has trained itself, this being the validation test. Based on the validation set, the system might need to be tweaked again to ensure accuracy. And lastly, we have testing, wherein real world data sets are given to see if the classification performed is up to human standard. The system is then put into production.