Pre-trained models

On Sunday evening, we were driving to a relative’s place in Mahalakshmi Layout when I almost missed a turn. And then I was about to miss another turn and my wife said “how bad are you with directions? You don’t even know where to turn!”.

“Well, this is your area”, I told her (she grew up in Rajajinagar). “I had very little clue of this part of town till I married you, so it’s no surprise I don’t know how to go to your cousin’s place”.

“But they moved into this house like six months ago, and every time we’ve gone there together. So if I know the route, why can’t you”, she retorted.

This gave me a trigger to go off on a rant on pre-trained models, and I’m going to inflict that on you now.

For a long time, I didn’t understand what the big deal was on pre-trained machine learning models. “If it’s trained on some other data, how will it even work with my data”, I wondered. And then recently I started using GPT4 and other similar large language models. And I started reading blogposts on how with very little finetuning these models can do “gymnastics”.

Having grown up in North Bangalore, my wife has a “pretrained model” of that part of town in her head. This means she has sufficient domain knowledge, even if she doesn’t have any specific knowledge. Now, with a small amount of new specific information (the way to her cousins’s new house, for example), it is easy for her to fit in the specific information to her generic knowledge and get a clear idea on how to get there.

(PS: I’m not at all suggesting that my wife’s intelligence is artificial here)

On the other hand, my domain knowledge of North Bangalore is rather weak, despite having lived there for two years. For the longest time, Mallewaram was a Chakravyuha – I would know how to go there, but not how to get back. Given this lack of domain knowledge, the little information on the way to my wife’s cousin’s new house is not sufficient for me to find my way there.

It is similar with machines. LLMs and other pre-trained models have sufficient “generic domain knowledge” in lots of things, thanks to the large amounts of data they’ve been trained on. As a consequence, if you can train them on fairly small samples of specific data, they are able to generalise around this specific data and learn around them.

More pertinently, in real life, depending upon our “generic domain knowledge” of different domains, the amount of information that you and I will need to learn a certain amount about a certain domain can be very very different.

Everything is context-sensitive!

Lifting and arithmetic

At a party we hosted recently, we ended up talking a lot about lifting heavy weights in the gym. In the middle of the conversation, my wife wondered loudly as to why “so many intelligent people are into weightlifting nowadays”. A few theories got postulated in the following few minutes but I’m not going to talk about that here.

Anecdotally, this is true. The two people I hold responsible for getting me lift heavy weights are both people I consider rather intelligent. I discuss weights and lifting with quite a few other friends as well. Nassim Taleb, for a long time, kept tweeting about deadlifts, though now he has dialled back on strength training.

In 2012 or 2013 I had written about how hard it was to maintain a good diet and exercise regime. While I had stopped being really fat in 2009, my weight had started creeping up again and my triglyceride numbers hadn’t been good. I had found it hard to stick to a diet, and found the gym rather boring.

In response, one old friend (one of the intelligent people I mentioned above) sent me Mark Rippetoe’s Starting Strength (and a few other articles on cutting carbs, and high-fat diets). Starting Strength, in a way, brought back geekery into the gym, which had until then been taken over by “gym bros” doing bicep curls and staring into mirrors.

It’s been a long time since I read it, but it’s fascinating – I remember reading it and thinking it reminded me of IIT-JEE physics. He draws free body diagrams to explain why you should maintain a straight bar path. He talks about “moment arms” to explain why the bar should be over your mid-foot while deadlifting (ok this book we did discuss at the party in response to my wife’s question).

However, two incidents that happened last week gave me an idea on why “intelligent people” are drawn to lifting heavy barbells. It’s about challenging yourself to the right extent.

The gym that I go to (a rather kickass gym) has regular classes that most members attend. These classes focus on functional fitness (among other things, everyone is made to squat and press and deadlift), but I’ve for long found that these classes bore me so I just do my own thing (squats, press / bench and deadlift, on most days). Occasionally, though, like last Friday, I decide to “do the class”. And on these occasions, I remember why I don’t like the class.

The problem with the gym class is that I get bored. Most of the time, the exercises you are doing are of the sort where you lift well below capacity on each lift, but you do a lot of lifts. They train you not just for strength but also for endurance and metabolic conditioning. The problem with that for me is that because every single repetition is not challenging, I get bored. “Why do i need to do so much”, I think. Last Friday I exited the class midway, bored.

My daughter is having school holidays, and one of the things we have figured is that while she has grasped all her maths concepts rather soundly (the montessori system does a good job of that), she has completely failed to mug her tables. If I ask her what is “7 times 4” (for example), she takes half a minute, adds  7 four times and tells me.

Last Monday, I printed out (using Excel) all combinations of single digit multiplications and told her she “better mug it by Friday”. She completely refused to do it. There was no headway in her “learning”. I resorted to occasionally asking her simple arithmetic questions and making her answer immediately. While waiting to cross the road while on a walk, “what is six times eight?”. While waiting for the baker to give us bread “you gave him ?100 and the bread costs ?40. How much change should he give you?”. And so on.

She would occasionally answer but again her boredom was inherent. The concept learning had been challenging for her and she had learnt it. But this “repetitive practice” was boring and she would refuse to do it.

Then, last Friday, I decided to take it up a notch. I suddenly asked “what is four and a half times eight?” (she’s done fractions in school). This was a gamechanger.

Suddenly, by dialling up the challenge, she got interested, and with some prodding gave me the correct answer. An hour earlier, she had struggled for a minute to tell me what 8 times 7 is. However, when I asked her “what is eight times seven and a half?” she responded in a few seconds, “eight times seven is fifty six..” (and then proceeded to complete the solution).

Having exited my gym class midway just that morning, I was now able to make sense of everything. Practicing simple arithmetic for her is like light weight lifting for me. “Each rep” is not challenging in either case, and so we get bored and don’t want to do it. Dial up the challenge a little bit, such as bringing in fractions or making the weights very heavy, and now every rep is a challenge. The whole thing becomes more fun.

And if you are of the type that easily gets bored and wants to do things where each unit is challenging, barbell training is an obvious way to exercise. and “intelligent” people are more likely to get bored of routine stuff. And so they are taking to lifting heavy weights.

I guess my wife has her answer now.

 

Sugar and Tobacco

This is NOT a blogpost about cash crops in the West Indies. This is more about biology.

I had my first cigarette when I was 21. I was about to graduate from my undergrad, and had decided to “experiment” a bit. Friends who were already smokers warned me that the thing is addictive, and that I need to be careful.

I still remember that cigarette, a Wills Classic Milds shared with a classmate who was a very occasional smoker. I remember feeling high, and weak in the knees in a way I had never felt before (I was yet to taste alcohol, but when I did a couple of months later, it was underwhelming compared to tobacco). It was extremely pleasurable, but I remembered what my smoker friends had told me. It was addictive shit.

That day I made a decision that I’ll smoke a maximum of one cigarette per calendar year, something I’ve lived up to. It’s never been more than one, though in some years (especially in the early years), the 1 was made up of several fractions.

The thing with tobacco is that it is addictive. The high is incredibly high (for a non-smoker like me), but when that passes you have withdrawal symptoms. And you crave for more. If you don’t have friends like me who have warned you about the addictive nature of it, you can get addicted (alcohol doesn’t react that way – beyond a few drinks you don’t want to drink more. And I don’t have annual limits on alcohol consumption).

A few prescription drugs act the same way – most notably (in my experience) antidepressants. They are biologically addictive and when you stop having them, the body starts having strong withdrawal symptoms. So you need to be careful in terms of getting on to antidepressants because getting off them is not easy.

Caffeine is the same as well – and I continue to be addicted to it. Two days without coffee and I get the same kind of withdrawal symptoms I had the last time I was getting off antidepressants.

And thinking about it, it’s the same with sugar (or any other high carb foods). When you consume too much sugar (or carbs), the body needs to produce a lot of insulin to be able to deal with it. The insulin thus produced is like a demon / genie (based on the sort of myths you favour) – once it has devoured the excess sugar, it devours the “regular blood sugar” as well, leading to a massive sugar crash.

It was possibly my psychiatrist who pointed this out in a consultation a few months back (and so I officially have a medical prescription that says “follow a low carb diet”) – that these sugar crashes are what lead to bouts of  low mood and depression, and that the way to keep my mood good is to not have sugar crashes, which means not eating much sugar.

Similarly, she told me that the reason I sometimes wake up in the middle of the night ravenously hungry and unable to sleep back is likely due to a sugar crash. And so I need to have a low-carb dinner. I found this the hard way last night when I had noodles for dinner (my blood sugar levels are especially sensitive to pulverised grains  (including the supposedly “healthy” ones like ragi, jowar, etc.) –  whole rice is fine for me, but not rice flour), and found myself awake at 4 am and unable to sleep. As it happened, I resisted the temptation to eat then and slowly fell back asleep at 6 (luckily today was not a “gym day”).

As if this morning’s sugar crash wasn’t enough, after lunch today I ate some sweets that a colleague had got to office. Sugar crash duly happened an hour later, and how did I react? By reaching for the same sweets. Yet another crash happened as I got home – and  I reached for some sweets my wife had got today. I’m writing this awaiting another sugar crash.

Thanks to the functioning of insulin, sugar can behave like tobacco. You eat and feel good, and then the crash happens. And you eat more. Spike again, crash again. And so on and so forth.

When I examine my own periods of putting on weight or becoming mildly depressed (now that I think of it, they are correlated), it’s because I get into this eating cycle. Eating more carbs means I get more hungry. And I eat more. Which makes my hungrier. And that goes on.

The only way is to wilfully break the chain – by skipping meals or having very low-carb meals. Once you’ve done this for a considerable period of time (I managed this easily between last Thursday and last evening), your body feels less hungrier, and you get on to a sort of virtuous cycle. And you progressively get better.

And then it takes one noodles meal or a sweet offer to get back into the vicious cycle. Some people have famously “quit smoking hundreds of times”. I’ve also “gone on a low cab diet hundreds of times”.

Cliquebusting

Last evening we hosted a party at home. Like all parties we host, we used Graph Theory to plan this one. This time, however, we used graph theory in a very different way to how we normally use it – our intent was to avoid large cliques. And, looking back, I think it worked.

First, some back story. For some 3-4 months now we’ve been planning to have a party at home. There has been no real occasion accompanying it – we’ve just wanted to have a party for the heck of it, and to meet a few people.

The moment we started planning, my wife declared “you are the relatively more extrovert among the two of us, so organising this is your responsibility”. I duly put NED. She even wrote a newsletter about it.

The gamechanger was this podcast episode I listened to last month.

The episode, like a lot of podcast episodes, is related to this book that the guest has written. Something went off in my head as I listened to this episode on my way to work one day.

The biggest “bingo” moment was that this was going to be a strictly 2-hour party (well, we did 2.5 hours last night). In other words, “limited liability”!!

One of my biggest issues about having parties at my house is that sometimes guests tend to linger on, and there is no “defined end time”. For someone with limited social skills, this can be far more important than you think.

The next bingo was that this would be a “cocktail” party (meaning, no main course food). Again that massively brought down the cost of hosting – no planning menus, no messy food that would make the floor dirty, no hassles of cleaning up, and (most importantly) you could stick to your 2 / 2.5 hour limit without any “blockers”.

Listen to the whole episode. There are other tips and tricks, some of which I had internalised ahead of yesterday’s party. And then came the matter of the guest list.

I’ve always used graph theory (coincidentally my favourite subject from my undergrad) while planning parties. Typical use cases have been to ensure that the graph is connected (everyone knows at least one other person) and that there are no “cut vertices” (you don’t want the graph to get disconnected if one person doesn’t turn up).

This time we used it in another way – we wanted the graph to be connected but not too connected! The idea was that if there are small groups of guests who know each other too well, then they will spend the entirety of the party hanging out with each other, and not add value to the rest of the group.

Related to this was the fact that we had pre-decided that this party is not going to be a one-off, and we will host regularly. This made it easier to leave out people – we could always invite them the next time. Again, it is important that the party was “occasion-less” – if it is a birthday party or graduation party or wedding party or some such, people might feel offended that you left them out. Here, because we know we are going to do this regularly, we know “everyone’s number will come sometime”.

I remember the day we make the guest list. “If we invite X and Y, we cannot invite Z since she knows both X and Y too well”. “OK let’s leave out Z then”. “Take this guy’s name off the list, else there will be too many people from this hostel”. “I’ve met these two together several times, so we can call exactly one of them”. And so on.

With the benefit of hindsight, it went well. Everyone who said they will turn up turned up. There were fourteen adults (including us), which meant that there were at least three groups of conversation at any point in time – the “anti two pizza rule” I’ve written about. So a lot of people spoke to a lot of other people, and it was easy to move across groups.

I had promised to serve wine and kODbaLe, and kept it – kODbaLe is a fantastic party food in that it is large enough that you don’t eat too many in the course of an evening, and it doesn’t mess up your fingers. So no need of plates, and very little use of tissues. The wine was served in paper cups.

I wasn’t very good at keeping up timelines – maybe I drank too much wine. The party was supposed to end at 7:30, but it was 7:45 when I banged a spoon on a plate to get everyone’s attention and inform them that the party was over. In another ten minutes, everyone had left.

Blackjack and ADHD

My mornings feel like I’m playing blackjack. A few months back, I had a bit of a health scare (elevated blood sugar levels), and since finding good low-carb food in/around office is a challenge, after that I’ve been taking my own lunch box.

It’s a fairly elaborate lunch, which one colleague calls as “looking rather European”. It started with grilled paneer and grilled vegetables, but has now grown to a massive glass Ikea box with grilled paneer, boiled eggs, grilled vegetables (some pre-blanched / steamed before grilling), roasted and crushed nuts and (of late) kimchi.

And despite my cook occasionally helping me out with some mise-en-place, there are a lot of things to do every morning. Some of the processes involved are:

  • keeping water for boiling, for eggs
  • putting eggs carefully into the boiling water (without breaking), and setting a timer for 7 minutes. If I’m not wearing my Apple Watch, I need to also run around to find my phone
  • Putting water in the steamer for steaming vegetables
  • Putting the hard veggies (carrot, beans, broccoli) into the steamer and closing the pot.
  • Taking out the veggies from the steamer before they are too soggy
  • Slicing paneer
  • Grilling paneer on the frying pan with salt and pepper and olive oil
  • Grilling veggies on the frying pan with salt and pepper and olive oil (including the steamed veggies)
  • Pre-heating the air fryer
  • Adding almonds into the air fryer; shaking the fryer once in the middle, transferring almonds to the pestle and mortar
  • Putting cashews into the air fryer
  • Taking out cashews when they have just browned and putting into the pestle and mortar
  • Putting eggs in cold water after seven minutes are up
  • Peeling and slicing eggs, and seasoning with salt and pepper
  • Crushing cashews and almonds and adding them to grilled vegetables

I don’t think I’ve ever timed myself. However, pretty much every morning I get into a frenzy trying to finish all of this, and then take my daughter to school on time. Maybe some days I take twenty minutes. Maybe I take thirty. I don’t even know. Life is such a blur.

As you can imagine, the above process can be heavily parallelised. And while my menu is standardised, the process is not. Which means I’m trying to both experiment and measure at the same time. While cooking four different processes at exactly the same time.

Sometimes, life feels like playing blackjack. You would have flipped the paneer over in the frying pan maybe for one last time. And then you think “I can peel this egg before the paneer is done”. Before you know it the paneer is black. You are not wearing your watch, so you go in search of the phone – to put the timer for the egg. In that time the veggies are burnt.

I don’t even know why I sometimes put myself through this. Maybe this is yet another tradeoff between physical and mental health. For now, physical seems to be winning.

Maybe a sustainable long term strategy is to forego lunch as well (nowadays I don’t eat breakfast unless I’ve gone to the gym in the morning), and transition to an “OMAD” (one meal a day) lifestyle.  Or maybe I should find myself some nice lunch I can take to office which doesn’t involve so many parallel steps.

Until I figure something out, I’ll continue running in the mornings.

Why I never became a pundit

It’s been nearly a decade since i started writing in the mainstream media. Ahead of the Karnataka elections in 2013, I had published on this blog a series of quantitative analyses of the election, when R Sukumar (then editor-in-chief of Mint) picked it up and asked me if I could write for his paper on the topic – quantitative analysis of elections.

And so Election Metrics (what my pieces in Mint – they were analysis and not editorials, which meant it wasn’t a strict “column” per se, but I got paid well) was born. I wrote for Mint until the end of 2018, when my then contract ran out and Sukumar’s successor chose not to renew.

Having thus “cracked print”, I decided that the next frontier had to be video. I wanted to be on TV, as a pundit. That didn’t come easily. The 2014 national elections (when Modi first became PM) came and went, and I spent the counting day in the Mint newsroom, far from any television camera. I tried to get my way in to IPL auction analysis, but to no avail.

Finally, in 2018, on the day of the Karnataka elections, I got one guy I knew from way back to arrange for a TV appearance, and went on “News9” (a Bangalore-focussed English news channel) to talk about exit polls.

“I saw the video you had put on Facebook”, my friend Ranga said when he met me a few days later, “and you were waxing all eloquent about sample sizes and standard errors”. On that day I had been given space to make my arguments clear, and I had unleashed the sort of stuff you don’t normally see on news TV. Three days later, I got invited on the day of counting, enjoyed myself far less, and that, so far, has been the end of my career in punditry.

Barring a stray invitation from The Republic aside, my career in TV punditry has never gotten close to getting started after that. Of late I haven’t bothered, but in the past it has frequently rankled, that I’ve never been able to “crack TV”. And today I figured out why.

On my way to work this morning I was listening to this podcast featuring noted quant / factor investors Jim O’Shaughnessy and Cliff Asness. It was this nice episode where they spoke about pretty much everything – from FTX and AMC to psychedelics. But as you might expect with two quant investors in a room, they spent a lot of time talking about quantitative investing.

And then somewhere they started  talking about their respective TV appearances. O’Shaughnessy started talking about how in the early days of his fund, he used to make a lot of appearances on Bloomberg and CNBC, but of late he has pretty much stopped going.

He said something to the effect of: “I am a quant. I cannot give soundbites. I talk in terms of stories and theories. In the 80s, the channels used to give me a minute or two to speak – that was the agreement under which I appeared on them. But on my last appearance, I barely got 10 seconds to speak. They wanted soundbites, but as a quant I cannot give soundbites”.

And then Asness agreed, saying pretty much the same thing. That it was okay to go on television in the time when you got a reasonable amount of time to speak, and build a theory, and explain stuff, but now that television has come down to soundbites and oneliners, he is especially unsuited to it. And so he has stopped going.

There it was – if you are the sort who is driven by theories, and you need space to explain, doing so over voice is not efficient. You would rather write, where there is room for constructing an argument and making your point. If you were to speak, unless you had a lot of time (remember that speaking involves a fair amount of redundancy, unlike writing), it would be impossible to talk theories and arguments.

And I realise I have internalised this in life as well – at work for example, I write long emails (in a previous job, colleagues used to call them “blogposts”) and documents. I try to avoid complicated voice discussions – for with my laborious style I can never win them. Better to just write a note after it is over.

Computer science and psychology

This morning, when I got back from the gym, my wife and daughter were playing 20 questions, with my wife having just taught my daughter the game.

Given that this was the first time they were playing, they started with guessing “2 digit numbers”. And when I came in, they were asking questions such as “is this number divisible by 6” etc.

To me this was obviously inefficient. “Binary search is O(log n)“, I realised in my head, and decided this is a good time to teach my daughter binary search.

So for the next game, I volunteered to guess, and started with “is the number \ge 55“? And went on to “is the number \ge 77“, and got to the number in my wife’s mind (74) in exactly  7 guesses (and you might guess that \lceil log_2 90 \rceil (90 is the number of 2 digit numbers) is 7).

And so we moved on. Next, I “kept” 41, and my wife went through a rather random series of guesses (including “is it divisible by 4” fairly early on) to get in 8 tries. By this time I had been feeling massively proud, of putting to good use my computer science knowledge in real life.

“See, you keep saying that I’m not a good engineer. See how I’m using skills that I learnt in my engineering to do well in this game”, I exclaimed. My wife didn’t react.

It was finally my daughter’s turn to keep a number in mind, and my turn to guess.

“Is the number \ge 55?”
“Yes”

“Is the number \ge 77?”
“Yes”

“Is the number \ge 88?”
“Yes”

My wife started grinning. I ignored it and continued with my “process”, and I got to the right answer (99) in 6 tries. “You are stupid and know nothing”, said my wife. “As soon as she said it’s greater than 88, I knew it is 99. You might be good at computer science but I’m good at psychology”.

She had a point. And then I started thinking – basically the binary search method works under the assumption that the numbers are all uniformly distributed. Clearly, my wife had some superior information to me, which made 99 far more probable than any number between 89 and 98. And s0 when the answer to “Is the number \ge 88?”turned out to by “yes”, she made an educated guess that it’s 99.

And since I’m used to writing algorithms, and  teaching dumb computers to solve problems, I used a process that didn’t make use of any educated guesses! And thus took far many more steps to get to the answer.

When the numbers don’t follow a uniform distribution, binary search works differently. You don’t start with the middle number – instead, you start with the weighted median of all the numbers! And then go on to the weighted median of whichever half you end up in. And so on and so forth until you find the number in the counterparty’s mind. That is the most optimal algo.

Then again, how do you figure out what the prior distribution of numbers is? For that, I guess knowing some psychology helps.

 

Hanging out with the lads

One of my favourite podcasts this year has been The Rest is History with Tom Holland and Dominic Sandbrook. It is simultaneously insanely informative and insanely funny, and I’ve been listening to it as regularly as I can this year.

A few months back, a prequel to The Lord Of The Rings called “Rings of Power” came out on Amazon. To commemorate that, Rest is History did a few episodes on JRR Tolkien. It’s a fascinating profile, but one line especially stood out.

Holland was talking about how Tolkien found himself a steady girlfriend when he was 13 (and got himself excommunicated from the church in the process – he was Catholic and she was Protestant, I think). And then he said “that part of his life having been settled, he now focussed on other things, such as hanging out with the lads”.

I find this to be a rather profound line. “Hanging out with the lads”. And having found myself a steady girlfriend for the first time relatively late in life (when I was nearly 27), I can look back at my life and think of the value of this phrase.

When you are single, among other things, you become a “life detector” (this phrase comes from one friend, who used it to describe another, saying “she is a life detector. She puts blade on anything that moves”). Especially if, as a youngster, you have watched good but illogical movies such as Dil To Pagal Hai.

You may not realise it until you are no longer single, but being single takes a toll on your mental health. Because you are subconsciously searching for a statistically significant other, you mind has less time and space for other things. And you miss out on more enjoyable things in life.

Such as “hanging out with the lads”.

I have written (forgot where, and too lazy to find the link now) about how being no longer single was fantastic in terms of simply appreciating other women. You could say they were nice, or beautiful, or intelligent, or whatever, and it would be a simply honest comment without any “ulterior motives”. More importantly, you could very simply tell her that, without worrying whether she will like you back, what caste she belongs to (if you were into that kind of stuff) and so on.

I listened to the podcast on Tolkien when it came out a few months ago, but got reminded of it over the weekend. I spent most of my weekend in IIMB, at our 15th year batch reunion (ok, it’s been 16 years since we graduated but our party was postponed by a year due to Covid). As part of the reunion (and unlike our 10th reunion in 2016), we had a real “L^2 party” (check here to see what L^2 parties used to be (for me) back in the day).

So effectively, this Saturday I was at my first ever L^2 party after I had graduated from IIMB. In other words, I was at my first ever L^2 party where I was NOT single (my wife wasn’t there, though. Pretty much no one from our batch brought spice or kids along).

However, despite the near 17-year gap from the last L^2 I had attended, I could feel a different feeling. I found myself far more willing to “hang out with the lads” than I had been in 2004-6. I had a lot of fairly strong conversations during the time. I held random people and danced (thankfully the music got better after a while).

Through the entire party I was at some kind of perfect peace with myself. Yeah, you might find it strange that a 40-year-old guy is writing like this, but whatever. Early on, I sent a video of the party to my wife. She sent back a video of our daughter trying to imitate the way I was “dancing”.

And it was not just the party. I spent a day and a half at IIMB, hanging out with the “lads” (which included a few women from our batch), having random conversations about random things, just laughing a lot and exchanging stories. Nobody spoke about work. There was very little small talk. Some conversations actually went deep. It was a great time.

With the full benefit of hindsight, I had as much fun as I did in this period (ok i might be drawing random connections, but what the hell)  because I was secure in the fact that I am in a steady relationship, and have a family. And it took me a long time to realise this, well after I had stopped being single.

 

 

 

 

Eating Alone

In the last 2 weeks, about 4 times I had lunch in my office cafeteria. After a small health scare in early October (high HbA1c), I carry my own (self-made) lunch to office every day now (since I can’t reliably find low carb food around). On these days, I took my lunch to the cafeteria and ate along with colleagues, some of whom had brought there own lunches and others bought from the on-site caterer.

This, to me, however, is highly unusual behaviour. First of all, taking lunch to office is highly unusual – something that till recently I considered an “uncle thing to do”. Of course, now that I’m 40, doing “uncle things” is par for the course.

More importantly, eating lunch in the cafeteria is even more unusual behaviour for me. And in the last couple of days, most days I’ve sat there because a colleague who sits near me and brings lunch as well has called me on his way to the cafeteria.

A long time ago, an old friend had recommended to me this book called “never eat alone“. I remember reading it, but don’t remember anything of its contents (and its average goodreads rating of 3.8 suggests my opinion is not isolated). From what I remember, it was about networking and things like that.

However, as far as I am concerned, especially when it comes to lunch on a working day, I actually prefer to eat alone (whether it is at my desk or at a nearby restaurant). Maybe it is because my first “job” (it was actually an internship, but not my first ever internship) was in London, on a trading floor of an investment bank.

On trading floors, lunch at desk is the done thing. In fact, I remember being told off once or twice in my internship for taking too long a lunch break. “You can take your long break after trading hours. For lunch, though, you just go, grab and come and eat at the desk”, I had been told. And despite never again working in an environment like that (barring 4-5 weeks in New York in 2010-11), this habit has struck with me for life.

There are several reasons why I like to eat alone, either at a restaurant or at my desk. Most importantly, there is a time zone mismatch – on most days I either don’t eat breakfast, or would have gone to the gym in the morning. Either ways, by 12-1230, I’m famished and hungry. Most others in India eat lunch only beyond 1.

Then, there is the coordination problem. Yes, if everyone gets lunchboxes (or is okay to but at the cafeteria) and goes to the cafeteria, then it is fine. Else you simply can’t agree on where to go and some of you end up compromising. And a suboptimal lunch means highly suboptimal second half of the day.

Then, there is control over one’s time. Sometimes you can get stuck in long conversations, or hurry up because the other person has an impending meeting. In either case, you can’t enjoy your lunch.

Finally, when you have been having a hectic work day, you want to chill out and relax and do your own thing. It helps to just introspect, and be in control of your own mind and thoughts and distractions while you are eating, rather than losing control of your stimulations to someone else.

Of course it can work the other day as well – cafeteria lunches can mean the possibility of random catchups and gossip and “chit chat” (one reason I’ve done a few of those in the last few weeks), but in the balance, it’s good to have control over your own schedule.

So I don’t really get the point of why people think it’s a shame to eat alone, or thing something is wrong with you if you’re eating alone. I know of people who have foregone meals only because they couldn’t find anyone to go eat with. And I simply don’t understand any of this!

Quiz Time

This morning was Mahaquizzer, KQA’s (used to be) annual national solo written championships. When I had seen the invite a few days back, I had somehow registered in my head that the quiz was between 11:00 am and 12:30 pm.

The website says,

Reporting time for participants will be 10:00 AM

The quiz will be held across all cities from 10:30 am – 12:00 pm

But in my head I had it as 10:30 registration and quiz starting at 11:00. And so around 10, I went in for a long shower. And came out and just for the heck of it, picked my phone to confirm what time the event was. And panicked.

It was 10:55 by the time I reached the venue and started doing the quiz. This meant that rather  than the allotted 90 minutes, I only had 65 minutes to answer the 150 questions. I got into my “speed zone” (I used to be good at solving problems really really fast – that’s how I did very well in CAT etc.) and started working my way through the paper.

It was ~ 11:55 by the time I got done with my first parse of the paper, which meant there was little time for me to revise. And so for a lot of questions I ended up paying far less attention than I should have. And I left some 5-10 questions unattempted (more because I didn’t have a good answer rather than due to lack of time itself).

When the answers were given out presently, I figured I ended up making 67 out of 150. There were a few bad misses. My intuitive thought then was that had I had the full 90 minutes, I could have done better in some 5-10 questions and maybe ended up with 75 out of 150. My misreading of the time had cost me 5-10 points (and I’ll know in a few days how many places in the national rnanking).

Thinking about this, I headed out for lunch with 3 other quizzers (all of whom scored much more than me this morning). Through the lunch, we discussed all the questions. It turned out that for a bunch of questions, some of these people had over-analysed and over-thought, and ended up getting the wrong answer. Because I was doing the quiz in some insane speed mode, I didn’t have the luxury to over-analyse – I had written down the simplest and most intuitive answers I could think of.

Suddenly, by the end of the lunch (by which time we had analysed the full paper), I wasn’t sure any more on how much more I would have got had I had more time. Yes, there were 5-10 questions that would have definitely benefited from my paying more attention. On the other hand, there was another bunch of questions where more attention might have actually been damaging – I would have ended up over-analysing and turned my correct answers into wrong ones.

So I  will never really know how much more (or less) I might have got had I had the full quota of time this morning.

And now that I think of it – it is the case with my blogposts also sometimes. Most of the times I just want to bang it out and publish it, so I get into one zone and start writing. And it will be a stream of thought that will go on to this page, where you will read it .

However, when I try to write more leisurely, I make a right royal mess of it. I over-analyse, over-edit, spend needless time worrying about things I shouldn’t be worrying about, etc. In my own opinion, the best blogposts are those I have written in a “mad speed zone”. Editing can only make my writing worse.

PS: Because I was quizzing today (in the afternoon I attended Asiasweep along with Kodhi. Doing a quiz with Kodhi is always a lot of fun because we end up laughing about random things through the quiz). I deliberately decided to skip my ADHD medication for the day. And that worked out well, since I was able to make all sorts of random connections and work out the answers.

In quizzing, a little bit of hallucination can be a good thing!