Skip to main content


For some, rain is captivating. Some others say rain is nostalgic. I had always maintained that rain was inspiring, but that day was different. Despite the sky opening its floodgates over my flat and its surroundings at the scenic Fort Kochi, I was anything but inspired. I was on my couch, with my netbook by my side and had finished typing my latest piece of fiction. It was three years ago that I had, rather inadvertently, discovered that I could actually write prose. After a few unsuccessful trysts with some leading magazines, I resorted to social media for publishing my works. Likes, comments and shares made me quite famous. In fact, my works do have some following in the cyberspace.

As I said before, I had finished typing a new story, but the problem I was facing was that I couldn’t find an appropriate title for my work. A thousand seconds and half a dozen titles flashed through, but none gave me any satisfaction. As I was still pondering over it, my phone rang. Unknown number.


‘Hi sir. Read your last work that you had posted on facebook. Frankly, it was brilliant. I loved it.’
Oh thank you very much. As you might know, that was not my first work.’

‘I have gone through every of your stories, but none touched me to the core the way this did. Clearly this one was a cut above the rest.’

‘Nice to hear that. By the way, you are?’

‘I would appreciate if you would not ask that.’

‘Excuse me?’

‘Just consider me as one of your readers. Isn’t that enough?’

‘But what’s wrong with me knowing your name?’

‘It’s not about being wrong, sir. Only that it is unnecessary. We both are total strangers. You write stories and I read them. After reading a story I couldn’t resist from calling you. My name is not of significance here. Hope you understand my point.’

‘But if you wouldn’t tell me your name, I might waste time thinking over the mysterious caller, right? Isn’t it better if you could tell me?’

‘I have reservations about what you said, sir.’

‘Enlighten me.’

‘Well, if I didn’t tell my name, you might think about it for a while but eventually you’ll forget. On the other hand, consider the scenario of me telling you my name. I am Mr. Z for instance. In that case, whenever you come across a person named Z, my thoughts also could come to your mind. That is, you’ll think about this stranger all through your life. I felt I could make that not happen by simply not revealing an irrelevant bit of information. Okay, sir?’

‘Hmm. As you wish. Good day, gentleman.’

And I ended the rather eccentric conversation. Nevertheless, all of what he said was not bluff. I thought about a Hollywood movie that I had watched some time ago. In that movie, the protagonist was always shown wearing a mask. His real face never revealed, and I must accept this gave the hero a certain level of awe. Vikas Swarup, the celebrated author of the Slumdog Millionaire once echoed similar sentiments. Through a character in his novel Six Suspects, he stated that women in lingerie were a lot more appealing than nude ones.

Riding by this new wave of thoughts, I had another shot at my untitled work. After reading from the very beginning to the last period, I felt my work was complete in all sense. A title seemed out of place. As if the extra bit of information would kill the essence of the story.  And I posted the story without any titles. In under two minutes, the first ‘like’ was registered. I withheld my urge to check the name of who had liked. With a click, I logged out of the world that made me what I was. The downpour had not ceased. I found the rain seducing.


Popular posts from this blog

Machine Unlearning #0 (Intro)

You might be familiar with the term Machine Learning. Worry not if you have not, cause I have tried to give a gist of the concept here. The term has been in the limelight of late and has been tossed around rather liberally to denote anything related to artificial intelligence, robotics, and data mining. Machine Learning, as the name suggests, could simply mean the field of study of enabling the “machines” (computers) to “learn” from past experiences and make informed decisions in the future.   Wait a minute! Learning from past experiences is something humans do, right? Exactly! The computer folks want computers to behave more and more like us. As if there aren't enough of us already. As the machines are becoming more like us, we are becoming more like them. Introspection time! Most of us wake up every morning like clockwork! Then we rush through the morning routines - get dressed, wade through the traffic, and reach our offices or schools or wherever people expect us to be. We spe

The High State

 Before The Judgement I believe I must begin by addressing the pressing question - Was planning a vacation in the midst of a pandemic a recommended move?  No. Yet we went ahead with it. Here is why.  We (Nithya & I) were newly married, and our vividly planned vacation at the island of Langkawi was stolen away from us by the virus. Our stay in Delhi was coming to an end due to job-related moves, and we felt it would be a waste not to utilize this opportunity in exploring at least one of the tourist hot spots easily accessible from the national capital region. Let us end this section by answering another question - Are the reasons listed above good enough to risk a vacation during a pandemic? No. We had taken a calculated risk. Arrival at Manali There are two phases to this - planning and execution. We had not started planning with Manali in mind. There were numerous choices - starting from Jaipur and Amritsar to Nainital, Shimla, and Manali. After a bit of reading and deliberations,

Machine Unlearning #1 (Classification)

You can’t conclude a discussion on Machine Learning without mentioning classification. Classification is a machine learning technique where the machine is trained to predict the label of the given input data. Alright, let’s cut the jargon and get some real-world examples. Oranges and Bananas. Let’s assume that we have a box of fruits that contain some oranges and some bananas. You are asked to pick one fruit at random and tell if it is an orange or a banana. Pretty basic, right? For us, it is straightforward. We would know the answer at first sight. But, how would a computer be able to tell the difference? In classification, the machine would first be trained on some pre-labeled data. It would be shown an orange and we would tell it that the fruit is an orange. The machine would study the orange and remember its features - orange color and round shape. Then it would be shown a banana and the process is repeated. What are these features? A feature is anything that helps us uniquely labe