Machine Learning & its implications

The term Machine learning & AI is closely related & it’s not wrong to say that the abstraction level between these two words is fairly thin line & they can be interchangeably used. Talking about Artificial Intelligence, people still think of the 1991 blockbuster Terminator, where a machine will come from the future & destroy all the mankind. If that is true, then we should stop testing with the gamma rays, because it can generate a Hulk. Also we should stop looking into the space, where there might be aliens which can invade into our planet & destroy all of us.

So, coming back to the reality, ML (Machine Learning) & AI (Artificial Intelligence) are the branches of the computer science. In particular, ML is closely related to data mining, rather than AI. So, talking of Data Mining, a simple example is Spam E-mails. There is a huge chunk of data & your program & algorithm is written in such a way that the machine will automatically learn which mails need to go the spam box, & which are appropriate to be delivered into the inbox. That is a basic example of ML or can be regarded as ML version 1 but nowadays ML has expanded itself hugely that we are using it in the regular life.

In Facebook, when we are tagging friends or objects, it is clearly an example of ML. Image Detection, Fraud Detection, Text & Speech systems are also can be termed as Machine Learning. These powerful capabilities can be applied to a wide range of fields. From Healthcare, retails to logistics as well as to the self driving vehicles, ML is everywhere. It is rapidly becoming an expected feature. Just as we expect, the company websites that works on the mobile devices, or perhaps on an app. The day will soon come when it will be expected that the technology will be personalized, insightful & self correcting.