Author: SK

Tamil

I’m not great at languages. The two languages I can speak fluently in – Kannada and English – I learnt them both before I was four.

I learnt Hindi in school but speak a mix of highly sanskritised Hindi (textbook Hindi) and bombay Hindi (from movies) with a thick kannada accent. As for other languages, the less I say the better.

I spent four years studying in Tamil Nadu so sometimes people assume I know Tamil (it also has to do with my name and face, I guess!). The truth, however, is that by the time I graduated from IIT Madras, I had barely learnt to distinguish between Tamil and Telugu – the two “new” languages i had been massively exposed to during my time there.

Basically I didn’t bother learning Tamil when I lived in madras in 2000-4 because I didn’t really need to. Most people on campus spoke at least basic English. Most outsiders I interacted with were shopkeepers, restaurant waiters and auto drivers, all of whom could speak broken English at least. And since I’m inherently not good at picking up languages, I just didn’t bother.

Before we started out Tamil Nadu trip yesterday my wife (who happens to be good at languages) was wondering how I would fare on this front. “Let’s see how you can put your four years of living in TN to good use”, she said. I told her I hoped to mostly get by with English, and broken Tamil.

After yesterdays lunch she had been impressed. “Not bad. With just words for one and two you managed to manage the conversation”. “Yeah that’s how I managed in chennai”, I replied.

High expectations having thus been set, I’ve had to try and live up to them later on in the trip. My biggest issue is that I end up speaking “assembly language”. I know the words but not the word forms or grammar, and so what I speak can sound funny.

“Instead of asking the shopkeeper what that is, you ended up asking where that is”, my wife informed me yesterday. I had at least got the message across. This kind of faux pas, largely because I can’t speak prepositions and other word forms, continued.

This morning we were at an Adyar ananda Bhavan (a chennai based Tamil Nadu style food chain restaurant) for breakfast. I confidently decided the waiter there might know English and started speaking in English. To our horror, for the rest of the breakfast he spoke to us in Hindi! “If you don’t know Tamil but look Indian you must be Hindi types”, he must have decided.

We tried to talk to him henceforth in our broken Tamil, but he had made his decision. Hindi it was for us.

Then, in the afternoon, at lunch in a “mess” in karaikudi, I was again struggling to speak Tamil with the waitress (to link back to yesterdays post – she was a middle aged woman. Again a cohort I don’t normally see among bangalore waiters). Suddenly I ended up speaking a few Hindi words!

I quickly realised what had happened – Tamil and Hindi are both languages I can’t think in. For both, I “think in Kannada” and translate to the respective language before speaking. And somewhere my wiring had gone wrong today and instead of translating to Tamil I translated to Hindi.

Later on in the conversation she said something quickly. I caught a few words but couldn’t catch the prepositions and ended up entirely misunderstanding her. Apparently she said “the sambar is hot”. And I replied “no, I don’t need hot rice. Pour the sambar on this only”.

And so it’s been going.

Tamil Nadu Day 1

Today and tomorrow are a series of parent teacher meetings at my daughter’s school. Consequently, the school is closed for the children (since teachers are busy meeting parents all day).

Having observed this pattern last year we decided it’s a good time to an extended weekend holiday, and quickly booked the first available Thursday slot and headed out.

I’m writing this from Madurai. The taj gateway here is a fantastic hotel, with a magnificent view of Madurai city. In the evening, there were wonderful sounds from the birds here. We saw lots of peacocks and a mongoose, and my daughter inferred that “there must be lots of snakes here”.

This is my first time ever in this part of Tamil Nadu. Although I went to college in chennai, I didn’t travel much around. So the only parts of Tamil Nadu I’d seen before were the areas around Chennai (Kanchi, mahabs, etc), the hill stations of Ooty and Kodaikanal and one trip to Palani when I was very very young.

As a family we like driving holidays. It gives us flexibility in terms of itineraries, and all we need to fix are the hotels. Also, we can travel at our own pace, deciding to stop or slow down or see some interesting thing on the way.

My first surprise today was the terrain. Maybe I don’t pay enough attention to “physical maps”, so had missed that central Tamil Nadu is hilly! I mean I know krishnagiri is hilly (once our bus from chennai to bangalore was unable to climb a slope there and we’d been made to get off and walk a short distance). I know yercaud exists near Salem. But I hadn’t expected so many low hills along the way.

And so while driving I was thinking – when you drive (rather than take a bus or train) you pay attention to your surroundings and the terrain and the people around and all that. And you notice the road signs – the ones saying “ghat section. Go slow” were hilarious given the magnitude of the said ghats (mountains and passes ).

The second surprise was the highways – most of our drive today (from Silk Board to very near Madurai) was along the north south corridor (now NH44, earlier NH7). The number of barricades across the road in Tamil Nadu was not funny.

Wherever there was a cut in the road for cross traffic, there were barricades, so that traffic had to slow down to a snails pace to get around them. In some places it seemed downright dangerous, since you couldn’t see (thanks to bends, trucks ahead, etc) the suddenly approaching barricades.

I find them rather bizarre – I’ve never come across them on any highways in Karnataka. I haven’t seen them on the same NH44 north of bangalore (in AP). It’s only in Tamil Nadu. And these are supposed to be national highways! And this was my fastag bill for the day!

The biggest surprise of the day, though, was the role of women I observed in the economy here.

I remember when I moved back from Gurgaon to bangalore in 2009, that in Gurgaon many jobs that are done by women in bangalore are done by men (bank clerks, gas agency operators, street vendors, etc). Now I find that Tamil Nadu takes this to another level.

Pretty much all the fastag booths we passed today were manned by women. Almost all the waiters in the place we had lunch at today were women (to be fair, it was called Selvi (Tamil for young woman) Mess) – not seen this in bangalore. And on multiple occasions I saw middle aged women in saris riding along the highways on Luna’s / TVS50s, some carrying heavy loads on their bikes. Oh – and the 50cc scooter category again seems Tamil Nadu specific – in bangalore most people have activas or similar scooters. Nothing smaller.

Food has been excelllent so far on the tour. Selvi mess was great – simple rice and biryani with meat side dishes. Back in 2013 when I went to Lucknow, a friend had said “don’t waste your appetite eating chicken”. The same applies in this part of Tamil Nadu as well – the mutton is far better.

Dinner was at this “bun parotta” place here in Madurai. Again unassuming and quick (we were in and out in 20 minutes). There I saw an interesting concept – you would be served on plantain leaves and at the end of the meal you had to clear away your own leaves (and residues) and put it in the bin.

I know Tamil Nadu is a bit ahead of other Indian states with it comes to countering caste oppression but I’m curious to know the origins of this “clear your own leaf” concept. Maybe it’s a Covid thing also!

This is a packed trip and tomorrow we move to the nearby Chettinad region, seeing Chettinad mansions and stuff. Hopefully I’ll keep you posted!

Food recommendations (including for breakfast in Madurai, if you can tell me in the next 10 hours) are welcome!

Status and money

Over the last week or so, I’ve been discussing this post by Robin Hanson with just about anyone. The first paragraph is the one that caught my attention.

Having a romantic partner is useful in many ways. You won’t be as lonely, you can ask them for advice, you can do activities together, and you can share transport and even a household with them. But if you look carefully, you will notice that many people don’t choose such partners mainly for their promise in such roles. They instead seek high status partners, who make them look good by association. Partners who are hot, funny, rich, powerful, etc.

Nevertheless, I urge you to read the whole thing. Hanson goes on to talk about status in several other fields, such as politics or in organisations.

Broadly paraphrasing (you should still read the whole thing), he says that people want to be associated with people with high status, or people who add status to them. So politicians who can project higher status will get elected. Organisations will appoint people who can further increase the status of the organisation.

I was thinking about this today from the point of view of last night’s post, where I had compared my life in my (current) full time job to that of a consultant, which I had been for nine years prior.

Sometimes it is common for us to comment, or gossip, that someone  got hired purely on the strength of their reputation, and that their abilities are not extraordinary. Sometimes, reputations can be self-fulfilling – if you can somehow get the reputation of being good at something, more people will start with the Bayesian prior that you’re good at that, and as long as you don’t suck at that thing, the prior will continue to hold. And so more people will think you’re good at it, and so on.

So when I think of my own career, basically I realise the way to go is to get into a position that my sheer presence adds status to the organisation I’m associated with. That way, they will be more forgiving of the work that I do (or don’t do). At the same time, from my own perspective, the organisation also needs to (at least marginally) add to my status – at some level I may not want to join a club that wants me as a member.

I remember back in the day when I was consulting – one of my clients, during the negotiations prior to the engagement, had wanted me to put on LinkedIn that I was working for them. Now when I think of it from the point of view of Hanson’s post, this was the client leveraging my then reputation in data to further their own status.

This is what I need to bring to my employers as well (I have no clue if I do already with my current ones – though I’m not so popular within my (data science) domain in india). The target, if I were to think of it, is to get into that self-fulfilling space when it comes to status – that people want me just because I’m me and bring along a certain (positive) status.

Now that I’ve identified the target, I need to figure out how to get there. I know in his famous podcast, Naval said that we should optimise for wealth (a positive sum game) rather than for status (a zero sum game). But Hanson’s post, and my analysis of it, suggests that status can also lead to wealth. I need to figure out the tradeoff now!

Coasean notes

I’m well over two and a half years into my current job, easily making this my longest unbroken spell of employment ever. This is a random set of pertinent observations, more a set of notes to myself rather than for any reader, regarding how the job has been playing out.

  • The Nature of The Firm is real. For nine years, as a consultant, I enjoyed market pricing (adjusting for illiquidity and and other distortions) for all the work that I did, but also suffered from the transaction costs that Coase writes about in his famous paper.

    This meant that unless the work was reasonably well defined, or of a certain minimum size, I wouldn’t take it up – the transaction costs involved in doing the deal would far outweigh any benefits that my counterparty and I would achieve from the deal. This meant I added less value than I could have to my clients

  • “Going deep” has its benefits. If I look at some of the work that I’ve done in the last few months here, and compared that to my work in my first year here, there is an absolutely marked difference. The difference is the two years of compounded extreme domain knowledge (about the company and its business).

    From that perspective, consulting can sometimes suffer from a limitation of domain knowledge

  • Countering the above point is that I’ve “been internalised” after two plus years here. The things that excited me at the time I joined don’t excite me any more. There are times when I get what I think are interesting insights, and then just don’t bother about showing them to anyone, based on the historical reaction to such insights.

    A fresh consultant, on the other hand, would share more, and would thus get more done

  • The biggest advantage of being “in house” is the data – I have access to pretty much ALL data in the company, and if I don’t have access to something, there is a good chance that the data doesn’t exist. This means I’m able to craft better hypotheses and do better analysis, compared to the time when I relied on clients to share specific datasets with me (pretty much nobody opened up full live access to their database to me)
  • In a way I also miss the novelty of being a consultant – because you work with a company for a short period of time, you are bringing in new ideas and insights in that period of time, and people pay you attention for it. As an in-house employee, you become a part of the furniture. And a lot of the time, it is a good thing if nobody notices you
  • Lack of friction in terms of taking up work means average quality of work can suffer. If you are very particular about the kind of work you want to do, it’s good if you can be a consultant – the friction means it’s easier to say no there.
  • As a consultant, by definition, I was a “hybrid worker”, working by myself for long periods of time and then visiting the client for meetings and discussions. That had worked out brilliantly well for me.

    However, I realise “that hybrid” is different from “this hybrid” (the job), since here people have access to my calendar and are able to schedule meetings even at times when I’m not in office. Rather, since my company has a multiple-headquarter setup, I even prefer to take meetings with colleagues not in Bangalore on days when I’m at home.

  • The biggest difference between monogamy (one employer) and polyamory (two or more “clients”) is that in the latter, no one owns your time. Because they know that they are “one of several” (even if at some point in time they are “one of one” it doesn’t matter, since that’s a special case), they can’t take your time for granted. And that gives you immensely more control over your time.

    This was possibly the hardest part for me getting back to a full time job – the lack of control over my time since I had now sold ALL of it to one company.

  • The flip side of this is that, at least for someone like me, not having to keep selling myself constantly is a brilliant feeling. Though, there is some amount of “within the company selling” that has to happen from time to time.
  • Apart from control over my time, the thing I miss the most about my consulting life are the “semi work meetings” – these are meetings with prospective clients, people who can lead you to prospective clients, old clients, etc. Where there is a tinge of work to the meeting, but you also catch up on several other things.

    Now that I’m in a job, and one that is entirely internal facing, there is no concept of “pseudo work meetings”. It is either proper work meetings (or “water cooler conversations”) with colleagues, or proper socialisation with others. That means I’m meeting far fewer people on average, nowadays

  • I admit that having become a sort of a “company man“, I’ve started taking myself more seriously than I would like to. Of late I’ve started making a conscious effort to dial this back a little bit, and I think it’s already making me happier.
  • Oh, and game theory rocks. Not a day goes by without me thinking about “saama daana bhEda danDa“

I can go on and on and on, but I think this is enough for now. If I have more, I’ll write another post.

Bad Data Analysis

This is a post tangentially related to work, so I must point out that all views here are my own, and not views of my employer or anyone else I’m associated with

The good thing about data analysis is that it’s inherently easy to do. The bad thing about data analysis is also that it’s inherently easy to do – with increasing data democratisation in companies, it is easier than ever than pulling some data related to your hypothesis, building a few pivot tables and charts on Excel and then presenting your results.

Why is this a bad thing, you may ask – the reason is that it is rather easy to do bad data analysis. I’m never tired of telling people who ask me “what does the data say?”, “what do you want it to say? I can make it say that”. This is not a rhetorical statement. As the old saying goes, you can “take data down into the basement and torture it until it confesses to your hypothesis”.

So, for example, when I hire analysts, I don’t check as much for the ability to pull and analyse data (those can be taught) as I do for their logical thinking skills. When they do a piece of data analysis, are they able to say that it makes sense or not? Can they identify that some correlations data shows are spurious? Are they taking ratios along the correct axis (eg. “2% of Indians are below the poverty line”, versus “20% of the world’s poor is in India”)? Are they controlling for instrumental variables?

This is the real skill in analytics – are you able to draw logical and sensible conclusions from what the data says? It is no coincidence that half my team at my current job has been formally trained in economics.

One of the externalities of being a head of analytics is that you come across a lot of bad data analysis – you are yourself responsible for some of it, your team is responsible for some more and given the ease of analysing data, there is a lot from everyone else as well.

And it becomes part of your job to comment on this analysis, to draw sense from it, and to say if it makes sense or not. In most cases, the analysis itself will be immaculate – well written queries and logic / code. The problem, almost all the time, is in the logic used.

I was reading this post by Nabeel Qureshi on puzzles. There, he quotes a book on chess puzzles, and talks about the differences between how experts approach a problem compared to novices.

The lesson I found the most striking is this: there’s a direct correlation between how skilled you are as a chess player, and how much time you spend falsifying your ideas. The authors find that grandmasters spend longer falsifying their idea for a move than they do coming up with the move in the first place, whereas amateur players tend to identify a solution and then play it shortly after without trying their hardest to falsify it first. (Often amateurs, find reasons for playing the move — ‘hope chess’.)

Call this the ‘falsification ratio’: the ratio of time you spend trying to falsify your idea to the time you took coming up with it in the first place. For grandmasters, this is 4:1 — they’ll spend 1 minute finding the right move, and another 4 minutes trying to falsify it, whereas for amateurs this is something like 0.5:1 — 1 minute finding the move, 30 seconds making a cursory effort to falsify it.

It is the same in data analysis. If I think about the amount of time I spend in analysing data, a very very large percentage of it (can’t put a number since I don’t track my time) goes in “falsifying it”. “Does this correlation make sense?”; “Have I taken care of all the confounding variables?”; “Does the result hold if I take a different sample or cut of data?”. “Has the data I’m using been collected properly?”; “Are there any biases in the data that might be affecting the result?”; And so on.

It is not an easy job. One small adjustment here or there, and the entire recommendations might flip. Despite being rigorous with the whole process, you can leave in some inaccuracy. And sometimes what your data shows may not conform to the counterparty (who has much better domain knowledge)’s biases – and so you have a much harder job selling it.

And once again – when someone says “we have used data, so we have been rigorous about the process”, it is more likely that they are more wrong.

Dislike of the like button

When you read histories or profiles of Facebook (the “original” product), there are two inflexion points that are likely to get mentioned. One is the news feed, where updates from all your friends are shown in “random” order on your wall (along with a bunch of ads). The other is the “like” button.

The like button was transformative in that it allowed people to express their acknowledgement of a post without really having to write a word. It was the lazy person’s best friend. One bit to show that they have “put attendance” or “shown support” or just acknowledged that they had been there.

More importantly, from Facebook’s perspective, this gave them tremendous data (at low cost to the users) in terms of what people wanted to see more or less of on their newsfeeds. Their algorithms quickly started working on this, and people’s feeds got tuned. Engagement went up. Ad sales went up. Everything was good.

And then the like button started appearing everywhere. I remember Twitter changing one button – from something else to “like”. LinkedIn introduced it, too. Soon, there were several versions of the like button representing different kinds of emotions. I don’t even understand what most of these buttons mean.

It was only a matter of time that this button would make its way to WhatsApp. It’s been there for a few years now but I haven’t really taken to using it. And now I’m thinking it’s actually a problem.

The problem with the like button (or any other such emojis) on WhatsApp is that it is a conversation stopper. Literally. It is basically a message that cannot be replied to, or acknowledged (you can’t like a like). So once one of the parties puts the emoji, there is nothing more to be done, but to move on.

Long ago, conversations would go like this:

“Hey man, happy birthday”.
“Thanks a lot. how are you doing? how’s the job / wife / kid? ”
Conversation continues….

Or

“Hey, check out this link”
Either no response, or “Thanks, I’ll check it out”, or (best case) “Very very interesting. This is my take on this. And see this other article”

Now all this is history. You say Happy Birthday, and people react right there with some emoji. You send them a link. They react with a thumbs up sign on the same message. There is nothing else to do. There is no conversation.

I’ve started regarding the like emoji on WhatsApp as rude (the only exception is the laughing emoji, to react to jokes, and that is ONLY to be used in groups). If someone reacts with an emoji (especially the thumbs up, or folded hands), I take that as “ok fine, I don’t want to talk to you” sign.

Maybe I’m becoming old.

 

IQ and mental health

It’s possible that I’ve written about this before, but I’m too lazy to check. I just saw this tweet by Baal about what he calls the “Aaron Swartz syndrome” (of brilliant people lost to mental illness because they put too much pressure on themselves).

(and yay, tweets are publicly visible again)

Baal’s tweet here is about a mutual classmate who we lost over a decade ago.  And this tweet triggered off a thought that I’ve had regarding pattern recognition, and which I might have written about earlier.

Fundamentally, what makes us intelligent is our ability to see patterns. Before the advent of modern “advanced linear algebra”, the difference between giving instructions to a human and to a computer was that the latter had to be incredibly specific. The human, on the other hand, could get approximate instructions, and then quickly see patterns in what they were observing, and get the job done.

Even a lot of “advanced linear algebra” works the same way. You give it a bunch of data, and it uses some mathematical transformations to “learn patterns” about the data, and then looks for these patterns in hitherto unseen data to make predictions. So what makes “artificial intelligence” intelligent is that it can use maths to divine patterns.

I remember taking this Mensa test when in college. It was all about pattern recognition. Four images given, and you need to figure the best fifth image to complete the sequence. That sorts. And Mensa claims to be a “club for the insanely intelligent”, and they use pattern recognition as a means to identify the more intelligent humans.

I can go on but I think I’ve provided sufficient evidence arguments on how intelligence is basically about pattern recognition. The more intelligent you are the better you are at identifying patterns.

Now what does it have to do with mental health?

The answer lies in false positives.

The problem with being good at pattern recognition is that sometimes you can tend to overdo it. You start seeing patterns that don’t really exist. I must mention here that I got over my extremely long-term and fairly deep depression back in 2012 when I was asked to deliver a few lectures on logical reasoning – explaining to my lecturees that correlation does not imply causation convinced me of the same, and I started feelingbetter.

So – because you are good at pattern recognition, you end up seeing too many patterns. I remember this from business school – I saw a bunch of people eating lunch together and thought I’ll go eat with them. And then I noticed a pattern among the set of people (something silly to the effect of “they are all from Section A, and taking this marketing elective”) that didn’t apply to me. And suddenly I decided I didn’t belong there and didn’t go to sit with them.

On that day I remember this happening multiple times, and I finally ate my lunch alone. Now thinking back, this was silly of me – and I had voluntarily brought upon myself unpleasant thoughts (“I don’t belong in this group”) and loneliness.

This is just one example – such things regularly happened through the decade of the 2000s. I would see demons (patterns, basically) where none existed. I would overthink decisions like crazy. I would bring loneliness upon myself. I would make random correlations, that would only serve to depress (“oh, my lucky shirt hasn’t dried, so I won’t be able to do well in today’s exam” types).

Generalising – what you see is that the better you are at seeing patterns, the more the spurious patterns you see (in advanced linear algebra, we call this “overfitting”). And these spurious patterns end up affecting you, and clouding your judgment. And making you less capable of leading life.

I keep thinking, and saying, that my engineering class has been especially badly affected by mental illness. In the class of 30 odd, we’ve lost two people to suicide already (including the person Baal mentioned in his tweet), and know of several others who had mental illness severe enough to either drop out, or take semesters off.

And given that the class was largely made up people from the extreme right tail of the distribution in a highly competitive entrance exam, I’m coming to believe that correlation exists – all of us being superior pattern recognisers, have been prone to recognising spurious patterns, and many have fallen prey to mental illness, to different extents.

PS: I found one blogpost I’ve written about this topic

 

Notes from a wedding reception

One of the impacts of the Covid-19 pandemic was to reduce the size of weddings. For a brief period of two or three years, the so-called “big fat indian wedding” got significantly slimmer.

It had started with the lockdowns and some insane government-imposed regulations on the size of weddings. I remember attending even some close relatives’ weddings over Zoom during 2020 and 2021.

And then there was the bandwagon. Because during that time people had been used to not being invited for weddings of people they knew (a few years back my wife’s French flatmate had been shocked to know that we had invited my wife’s aunt’s friends to our wedding. And this was before we told him that we’d also invited the priest of the temple across the road, and the guy who ran a chaat stall down the road), some people continued to have small weddings.

As a consequence, it had been a good four years since we had attended a “random” wedding – the wedding of someone we didn’t know too well. And as we were getting ready to go to my wife’s school friend’s brother’s wedding reception, she remarked that “somehow these receptions of people you don’t know too well are more fun than those of close friends or relatives”. Having gone to the wedding and come back, I attest that statement.

A few pertinent observations, in no particular order:

  • The “density of a queue” is a function of the level of trust in society. In a high-trust society, where you expect everyone to follow the queue, people can have personal space in the queue. In a low trust society, when you are concerned about someone overtaking you in the queue, you stand close to the person in front of you. By recursion, this leads to a rather dense queue.
  • Unfortunately, by the time of my own wedding in 2010, I hadn’t figured out why lines at wedding receptions were so long (apart from the fact that we had invited the priest across the road and the guy who supplied coffee powder to my father-in-law). And then later found that the culprit was the “panning shot” – a video taken by the videographer where he pans across the set of people posing with the couple for the photo.

    It is 2023, the panning shot still causes hold-ups. Now, I expect generative AI to solve this problem for good. All you need are a bunch of still photographers at a few strategic angles, and then the AI can fill in the panning shot, thus saving the time of everyone at the reception.

  • For a while I had stood alone in the queue, as my wife and daughter had gone somewhere with my wife’s close friend (whose brother was getting married today). I had a bouquet in hand, and the density of the queue meant that I had to be conscious of it getting squished. And the uncle in front of me in the line kept walking backwards randomly. Soon I decided to let the thorns on the roses in the bouquet do the work
  • Of late we’ve had so many bad experiences with food at functions (and remember that we’ve largely gone to close relatives’ and friends’ events, so we haven’t been able to crib loudly as well) that we recently took a policy decision to have our meals at home and then go to the events. As Murphy’s Law would dictate, the food today looked rather good (and my wife, who had the chaat there as an after-dinner snack, confirmed it was)
  • At my own reception in 2010, I remember my (then new) wife and I feeling happy when large groups came to greet us – that meant the queue would dissolve that much quicker. From today’s experience I’m not sure that’s the case. The advantage is one panning shot for the entire group. The disadvantage is the amount of time it takes to get the group organised into a coherent formation for the photo
  • Reception queues, if anything, have become slower thanks to people’s impatience to wait for the official pictures. Inevitably in every largish group, there is someone who hands their phone to the official photographers asking for a photo using that. In some seemingly low-trust groups, multiple people hand over their phones to the official photographer asking for the picture to be taken with THAT
  • Wedding receptions are good places for peoplewatching, especially when you are in the queue.

    And not knowing too many people at the wedding means there are more new people to watch

  • One downside of not knowing too many people at the wedding means you are doubtful if the groom or bride recognise you (especially if you are the invitee of one of their close relatives). You will be hoping the parent or sibling who invited you is around to do the intro. I’ve had a few awkward moments

OK that is one wedding reception I’ve attended in almost four years, and I’ve written a lot. I’ll stop.

Modern Ganeshas

Om Ganeshaaya Namaha

There is this theory I have heard – just that I have forgotten the source – that Ganesha was not originally part of the Hindu pantheon, but was a local god who was coopted into the fold later on. In fact, the same is said of his “brothers” Karthikeya and Ayyappa, and it is interesting that all these cooptions happened as sons of Shiva.

Back to Ganesha, the story goes that he is “vighneshwara” not because he removes obstacles (“vighnas”) but because he is the “obstacle god” (direct translation of vighneshwara). The full funda is – the locals who had Ganesha as their god allowed him to become part of the Hindu pantheon (and thus themselves becoming Hindus) under the express condition that he be worshipped in advance of any of the other gods in the Hindu pantheon.

Now, as even most non-practising Hindus will know, pretty much every Hindu ritual starts with a worship of Ganesha. It doesn’t matter which other god you are trying to worship, you always start with a prayer to Ganesha (unless, of course, if you are a radical Vaishnavite – in which case, Ganesha, as a son of Shiva, is taboo).

The polite explanation of this is “Ganesha is such a great god, and a remover of obstacles, you better worship him first so that the rest of your worship goes without obstacles”.

The more realist (and impolite, and controversial) explanation (again I’ve forgotten the source) is that if you started a worship without worshipping Ganesha at first, the locals who had “contributed” him to the pantheon would get pissed off and ransack your worship. And so the Ganesha worship at the beginning of every worship (and invocation ceremony) originally started as a form of blackmail, and then became part of culture. Eventually, it became lip service to Ganesha.

Earlier this year, I was watching the Australian Open. The finals ended, and it was time for the prizes. And at the beginning of the prize distribution, the announcer (Todd Woodbridge) said (paraphrasing) “we begin with a worship to the native peoples of Australia on whose lands we now stand”. It was similar to some episode of Masterchef Australia 2-3 years  back, which again started with the same “invocation”.

OK I actually found the video of Woodbridge from this year:

 

In this particular case, what has happened is that Australia has (finally) learnt about racism, and is now going overboard to identify all forms of overt or covert racism, past and present. The modern Ganesha-worshippers are the people whose job it is to point out every instance of overt or covert racism. If you don’t worship this Ganesha (talking about the “native peoples whose lands we stand upon”), the Ganesha-worshippers will come for you and maybe disturb the rest of your worship.

Ultimately, like the original Ganesha worship, this has turned into lip service.

“Modern Ganeshas” are not restricted to Australia. I just read this hilarious tweet (new Twitter rules means I have to copy paste here):

Have been on college tours in the Northeast. Every admissions officer and student volunteer starts with (1) a declaration of their pronouns, and (2) an acknowledgement of the stolen native lands their college is placed upon.

This is similar modern Ganesha worship, but practiced in the US. Lip service paid so that the “modern Ganesha worshippers” don’t come and disturb your worship.

When Colin Kaepernick knelt down during the playing of the (US) national anthem, he made a powerful statement. But then, when people started randomly taking the knee at the beginning of events (especially immediately after George Floyd’s murder), it turned into “modern Ganesha worship” (lip service so that the worthies don’t get offended).

And no political “wing” or party has a monopoly on modern Ganesha worship. In some places, ceremonies routinely start with praise being conferred on some “dear leader”. Literal Ganesha worship can also help in modern times, since that still has its guardians. You can include recitals of (whichever nation’s) national anthems, or readings from the constitution into this list.

The less memetically fit of these worships will fade away (or burn out, in case of a change in government). The more memetically fit of these worships will remain, but over a period of time turn into Ganesha worship – a token done out of habit and practice rather than due to fear of any contemporary reprisal.

Algo trading and ice cream

I refuse to share ice cream with my daughter, just like I used to refuse to share peanuts with my father. This refusal to share in both cases primarily has to do with the differential speed of consumption.

With my father and peanuts, it was a matter of ability – as someone who had grown up on a peanut farm (and thus he was a fan of Jimmy Carter), he was an expert at shelling peanuts. The Bangalore-born me was much less expert, and so before I knew it he would have finished the lot of it.

With my daughter and ice cream, it is a matter of willingness – she likes to finish it quickly, in big spoons. I like to savour it over a long time – at home,  I use a rather small spoon and eat it slowly. Nowadays I’ve been trying to cut down sugars and so when I eat them I try to get the maximum benefit out of them and thus eat slowly. However, even as a child I would eat my desserts slowly, trying to “extract maximum benefits”.

So last night we were having ice cream (individual small tubs of course). Daughter finished hers quickly and came to me, to see that my tub was still half full (and I was blogging as I was eating it).

“Appa, why do you like to turn your ice cream into milkshake?”, she asked.

“I don’t”, I said, “I just try to get the maximum value out of it, and thus I eat it slowly”.

“But then if you take too long to eat, then it turns into milkshake which is much less enjoyable than ice cream”, she countered. She had a valid point.

And then I realised this is exactly the problem I worked on during my stint as an investment banking quant in 2009-11. I was working on algo trading, specifically execution of large block deals.

The tradeoff there was that if you traded too quickly, you would end up moving the market and thus trading at an unfavourable price. On the other hand, if you traded too slowly, the natural volatility of the stock would mean that the market might move against you. And so you had to balance the two and trade.

I won’t go into the details on how we solved it (my erstwhile bank might not like it), but it suffices to say here that it is similar to eating ice cream.

If you eat too quickly, you run the risk of not getting sufficient “benefit” out of the ice cream at hand. If you eat too slowly, then there is the risk that the ice cream itself will melt and thus be less enjoyable for you.

I tried explaining this analogy to my daughter last night, but she didn’t get it. I guess she is too young to understand risk, volatility, market impact and the like.

And so I’m inflicting this on you!