Skip to main content


When I had first heard of Thappad, the premise had felt interesting to me. I did wait for its release, but then the Covid situation took its toll.
When the movie had its digital premiere on Amazon Prime on May 1st, I had made sure I caught the movie the very first day. Lately, I seldom share my thoughts on movies I watch, anyway, this is my two cents on it.

Spoiler Alert.

I saw a lot of discussion revolving around the slap and how it ended in their separation. Some of the viewers, while admitting the intensity of his action, found it a bit hard to digest that they had to separate because of this one moment of aggression.

What I felt is that it was not the slap alone that resulted in separation. The fact that he never acknowledged his mistake, and never really apologize for the same until the very end is something that hurt Amu as deeply as the public humiliation inflicted on her by the slap. Instead, initially, he tried to play it down by taking her out to dinners and buying her expensive gifts. Even at the restaurant, he's more focused on his phone and never paying any serious attention to what she has to say. It's like how his boss told him that he never hit him even though he was mad at him, not at her. That's because at least in his mind, he thought of her as lesser rather than equal. All Amu wanted was respect.

The movie also has hints that show us he thinks lowly of women. There is this one scene where he is driving and is pissed off at something. He takes out the anger by honking at a car and then wondering why they (women) drive at all. In another scene, when Amu casually says she's considering learning to drive, he mocks her saying she should first learn to make parathas properly. These are clues that he's misogynistic at heart.

Even if he had a change of heart in the end, a few good words wouldn't suffice to get her back. He needs to work towards it and show he has changed. To quote him, he needs to earn her. Especially since during the divorce case, he had even considered buying out the baby or forcing his friends who had attended the party to deny the incident.

The movie does not put all the blame on him anyway. He is only a part of an unhealthy society that is passive to toxic masculinity. The movie points fingers towards them too.

While watching the movie, I had no idea it was from the director who gave us hard-hitting movies like Article 15 or Mulk. One of the main factors which had caught my attention was the fact that Tapsee was the lead. From getting coconuts thrown at her, she has indeed come a long way to become one of the most evolved actors on screen today. Besides her choice of movies, the right stand taken by her off-screen (standing up against the Hindi imposition at IFFI is an example) are strong factors that make me a big fan. It would be good to see her doing a Malayalam movie some day. I'm pretty sure our filmmakers would have something solid to offer her.


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