- You are browsing on your Facebook webpage and you see a lovely advertisement of fancy shoes. You stop browsing and gaze at it for few seconds. In few hours, you find similar advertisement on your cell phone or in your email inbox.
- You are on tour and travelling by your car to scenic location near Mahableshwar. You click some lovely pictures using your cell phone. In some time, your social media account asks you a question “How did you find the ranges near Pratapgadh? Or how was your dining experience with “xyz” hotel near Pratapgadh?” Oops.. your GPS was on..!!
- You are “in” for a traffic jam and your Google Maps tell you to divert, just before you land into that jam..
- You are in a grocery shop and buy dozens of cookies and the next thing that happens is that you get dozens of recommendations of different cookies from the same/similar Mall.
Well, who is watching us? Who is keeping an eye over the likes and dislikes of us, our preferences, our budgets and our habits? Welcome to the world of Big Data and Machine learning!
Huge computers worldwide, which are maintained by giants such as Google / IBM / HP / Amazon, are storing large amount of data. The data which they collect from a extremely complicated network of computers, cell phones, cameras and GPS devices. These are huge storages which generate big data. Someone should be able to use it, and process it for something tangible/lucrative/useful. Well, machines do that job. Machines process the data, keeping an eye on the owner of the device, from whom the data is originating. These machines slowly gather the information about the person, not only in terms of the restaurants they visit, but also the clothes they wear, the places they tour and other likes and dislikes such as brands of shoes, perfumes they wear and so on. They link this data to the brands, restaurants and tourists locations of interest; and in this way, the advertisements start flowing in.
Does this sound like humans? Well, yes. Just as humans learn through experience, the machines also learn through the improvised data. For example, a small kid, initially crawls and falls on a slippery floor. But slowly, it learns how to be careful on the floor. This is because, in its brain (database), “slippery floor” gets added in and the next time, this improved database helps him avoid skidding. In the same way, a machine starts learning using the data it has. For example, it learns that I use “Nike” sports shoes. It will show me similar advertisements. But slowly, looking into my shopping preferences, it finds that I also use “Adidas” brand for my outdoor sports activity. It will learn this and upgrade my preferences and the data that it shows, will include both “Nike” and “Adidas” brands. This is machine learning.. Humans learn by experience and Machines learn by acquiring more data.
Therefore, Machine learning is a data analytics technique that teaches computers to do what comes naturally to humans (and animals). Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. The algorithms adaptively improve their performance, as the number of samples available for learning increases. This is a giant business model, in which the telephone companies, computer industry, network subscribers, consumer industries and cell-phone industries come together to mobilise the global economy.
This is not enough. Big enterprises are making these machines more and more versatile through creation of smarter algorithms and faster decision-taking-algorithms. Slowly, these machines are becoming intelligent by learning “Deep”. Just like a kid, once knows enough to survive, starts learning specialised skills, such as making a career in automobiles, textiles, accounts or finance; so does a machine. Deep learning is a specialized form of machine learning. This makes the computers become more intelligent and take decisions in split seconds, which is much faster than humans. This is fantastic, in one way, and has a huge flip-side too. We see this a bit later. However, till then, imagine someone showing exactly same “imagination” as yours .. or “creativity” as yours. Would you like it? And even if you don’t, can you control this technology, which is coming? We will see soon..!