Why You Should Reject That Gift?

Here’s a story that resonated with me recently, posting it here.

When Buddha Rejects a Gift

When Buddha was walking through a village teaching, a rude and angry person who belonged to another group of believers walks in. He starts insulting Gautama and says, “You have no right teaching others. You are as stupid as everyone else.” He shouted, “You are nothing but a fake.”

Looking at his anger, Buddha simply gave a gentle smile and asked, “Tell me, if you buy a gift for someone and if that person does not take it, to whom does the gift belong to?”

This question pushed the person to surprise and he answers, “It belongs to me because I bought the gift.” Gautama smiled and said, “That’s right. It is exactly same with your anger and frustration. If you become angry with me and if I do not get insulted then the anger falls back on you. All you have done is hurt yourself.”

This is it. We should know what to reject and what to accept in the life. In this case, Buddha simply rejected the insult and now the gift belongs to a man in the form of frustration, anger, displeasure.

via this

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Why do Three-Toed Sloths Come Down From Their Trees to Defecate?

Our bodies are most robust and most fragile at the same time. Recently completed the excellent book Evolution gone wrong the curious case why our body fails us? by Alex Bezzerides

Well written and extremely fun to read. Filled with many funny but insightful why questions. Here’s a small sample from the book on pooing sloths?

Why do three-toed sloths come down from their trees to defecate?

On the surface, this behavior is baffling. Why risk the chance of encountering a predator? Why not just let it fly from the branches? In class, my students work together to develop hypotheses and design hypothetical experiments to test their hypotheses. Are sloths fertilizing their trees in a targeted manner? Is it some way of marking their territory? Is it an atypical type of mate attraction?

Acutely observant scientists solved the mystery only recently with a great deal of patience.

They first observed that sloths have algae growing in their fur, which gives the sloths a green tint. The algae help the sloths blend in with the forest canopy, but the story goes beyond organic camouflage.

The sloth scientists noted sloths feeding on their homegrown algae and in doing so, supplementing their otherwise nutrient-poor diet. Eating their own fur algae is admittedly weird, but it gets even stranger than that.

A population of moths lives in the fur of each three-toed sloth. The moth population increases the nitrogen content of the fur and thus promotes the growth of the algae the sloths snack on.

When the sloths make their weekly treks to the bottoms of trees, the female moths lay their eggs in the fresh sloth dung. The tidy sloths cover up their mess with some leaf litter, and after the eggs hatch, the moth caterpillars dine on the sloth poop, grow up, become adults, and fly to the canopy layer to colonize sloths just as their parents did.

Sloths risk their lives to make a dung nursery for the moths on whom they depend for fertilizer to grow the algae they not only use as camo but also eat from their own fur for an extra shot of nutrition. Bam! Mystery solved. We can finally let the sloths poop in peace. Next question.

I hope this sloth-and-moth story has made the point that ultimate questions are fascinating to consider. They push researchers in completely different directions compared with proximate questions. The answers to ultimate questions are also often wildly unexpected.

This is what the book delivers answers to the ultimate questions on human anatomy? Do give it a read if you get a chance?

Do you have other interesting books to recommend, please let me know in the comments below?

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Modelling Uncertainty: When will I get delivery of my Car?

Covid 19 has affected everyone. Direct effects of these were felt by everyone and indirect effects will be felt for some time.

One of the second-order effects was the chip shortage and the consequent delay in car manufacturing and deliveries.

Let’s start from the beginning, In December 2021, after sitting on the fence and no longer batting my better half nugs, we booked our car.

The selection, shortlisting and elimination took a few weeks and then after a round of test drives, finally booked KIA Sonet G1.0T HTX iMT.

Being the most value for money (VFM) variant and the best transmission combination variant, this had a waiting of 19-20 weeks.

The first 10 weeks of waiting were easy to pass, looking at youtube videos of accessories, modifications, road trips etc but as we entered the double-digit phase of the waiting weeks, everyone was anxious to know when are we getting our car?

A couple of calls to the CSR only solicited, please wait you are on the 6th person in line. That’s what has happened so far till we entered the month of Feb.

Frustrated with the wait and the uncertainty, there is one thing left that the engineer in me was dying to try. Put some numbers to this uncertainty.

The uncertainty increased as we had a planned vacation in April, so my better half was anxious if there will be a clash in delivery and our travel plans

So turned to Montecarlo to predict what are the chances of getting the car in mid-Feb, end Feb, mid-Mar or beyond.

Here’s how I did it.

import numpy as np
import scipy.stats as st

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

%matplotlib inline

Data Collection

Turned to google and the internet and got the data for last year’s KIA Sonet monthly deliveries in India. This is 2021 data on which we will base our predictions.

sales_data = np.asarray([8859,7997,8498,7724,6627,5963,7675,7752,4454,5443,4719,3578])
plt.bar(range(len(sales_data)),sales_data);
Not an encouraging sign, limited and declining production numbers

We will use a 90% confidence interval for the normal distribution and a rough guesstimate of the number of KIA dealers in India

ci_90 = 3.29

#Rough no of KIA delaers
nodelears = 250

# No of monte carlo simulations
nos = 1000000

Time to Make Some Assumptions

After this data collection, there were other things that I have to estimate

  • Percentage of people opting for the petrol variant. Low and High
  • Percentage of people opting for IMT transmission. Low and High
  • Percentage of people buying the HTX variant. HTX is the most value-for-money variant. Mostly derived this number based on our discussions with the sales person and youtube videos and a cursory look at social media posts
# This is our rough consesus estimate with 90% confidence
# % of people oping for petrol
petrol_low = 0.6
petrol_high = 0.7

# IMT transmission
# % of people buying imt transmission
imt_low = .30
imt_high = .40

# HTX Variant probability 
# % of people buying the Sonet HTX variant
variant_low = 0.40
variant_high = 0.50

Converting all this data collected into normal distributions

petrol = st.norm(loc=(petrol_low+petrol_high)/2, scale=(petrol_high-petrol_low)/ci_90)
imt = st.norm(loc=(imt_high+imt_low)/2, scale=(imt_high-imt_low)/ci_90)
variant = st.norm(loc=(variant_high+variant_low)/2, scale=(variant_high-variant_low)/ci_90)

# Generating the data for 1000000 simulations

petrol_results = petrol.rvs(nos)
imt_result = imt.rvs(nos)
variant_result = variant.rvs(nos)

Now using the historical data and the simulation numbers of Kia Sonet deliveries to predict the next 3 month mean deliveries

sales=np.random.choice(sales_data, (nos,3)).mean(1)
sns.displot(sales, kind="kde");
Encouraging sign or were we too optimistic about our assumptions?
# Storing everything into a dataframe for easy statistics
data = pd.DataFrame({
"sales":sales,
"petrol":petrol_results,
"imt":imt_result,
"variant":variant_result})

print(data.describe())

                sales          petrol             imt         variant
count  1000000.000000  1000000.000000  1000000.000000  1000000.000000
mean      6607.339004        0.650043        0.349980        0.449967
std        962.995620        0.030412        0.030419        0.030376
min       3578.000000        0.507467        0.202519        0.312613
25%       5960.000000        0.629536        0.329489        0.429458
50%       6646.666667        0.650035        0.349975        0.449975
75%       7325.666667        0.670540        0.370531        0.470449
max       8859.000000        0.796902        0.496014        0.588184

Computing final number

Once we have this data, now using this we calculate Nocars that our dealership can get

Nocars is a number of deliveries that a dealership will get for the variant, transmission and engine we are interested in.

data["nocars"] = (data.sales*data.petrol*data.imt*data.variant)/nodelears
print(data.nocars.describe())

count    1000000.000000
mean           2.705510
std            0.512645
min            1.070139
25%            2.344456
50%            2.686584
75%            3.044903
max            5.662677

Inference

As seen in the above column, the dealership will receive less than 3 cars delivered per month 75% of the time. Not looking good for us we were the 6th person in line.

plt.axvline(x= data.nocars.mean(), c='g');
plt.hist(data.nocars, bins=100);
Less than 3 deliveries per month for the dealership for our chosen variant. 😦
pesimistic = data.nocars.quantile(q=0.25)
mean = data.nocars.mean()
optimistic = data.nocars.quantile(q=0.75)

timea = ["feb-beg", "feb-end", "mid-mar", "end-mar", "mid-apr", "end-apr"]
multiplier =[0.5, 0.75, 1, 2,2.8,3]

print("Time", "\t", "Pessimistic", "\t", "Mean", "\t", "Optimistic")
for t,m in zip(timea,multiplier):
    print(t, "\t",round(m*pesimistic, 0),"\t",round(m*mean, 0),"\t",round(m*optimistic, 0))

Time 	 Pessimistic 	 Mean 	 Optimistic
feb-beg 	 1.0 	 1.0 	 2.0
feb-end 	 2.0 	 2.0 	 2.0
mid-mar 	 2.0 	 3.0 	 3.0
end-mar 	 5.0 	 5.0 	 6.0
mid-apr 	 7.0 	 8.0 	 9.0
end-apr 	 7.0 	 8.0 	 9.0

Probability

Probability of number of Petrol Sonets IMT transmission HTX variants the dealership can get in a given month, based on past data

for i in range(1,6):
    print(i, round(data[data.nocars>i]["nocars"].count()/nos*100,2), "%" )

1 100.0 %
2 92.0 %
3 27.69 %
4 0.85 %
5 0.0 %

Bottom line, very slim chance of getting the car by end of March, most probable date was the end of April, which came to the promised delivery date.

What has this exercise taught me?

A lot.

Putting a number to that uncertainty was a huge deal for me and with this exercise, I dispelled all hope that I will get the car in March as verbally promised by the dealership. Also, these calculations gave me a little insight into how Covid continues to affect us way beyond the initial days.


I have used Montecarlo in my work for modelling material, geometry, and BC uncertainties in gas turbine engines but this was the first time I tried using it on something so close to my own life and circumstances.

It was a fun exercise.

Update:

Someone doing this analysis today can use the data provided by the company

According to the company, 25% of Sonet buyers chose the iMT variants, while 22% opted for the automatic transmission. 26% of customers prefer the top variants, while diesel variants accounted for 41% of the overall Sonet sales.

According to Kia, the two most popular colours for the Sonet are Glacier White Pearl and Aurora Black Pearl. These account for 44% of the overall dispatches.

source

Why Many Doctors Recommend a High-Fiber Diet?

This might be simplistic, but a good explanation of why you should eat more fiber?

Whatever our small intestine does, it always obeys one basic rule: onward, ever onward!

This is achieved by the peristaltic reflex. The man who first discovered this mechanism did so by isolating a piece of gut and blowing air into it through a small tube and the friendly gut blew right back.

This is why many doctors recommend a high-fiber diet to encourage digestion: indigestible fiber presses against the gut wall, which becomes intrigued and presses back.

These gut gymnastics speed up the passage of food through the system and make sure the gut remains supple.

From the excellent book Gut by Giulia Enders

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20 Slots

Here’s a video of Warren Buffett talking about choices. Applicable to investing as well in all other areas of life.

I keep coming back to this, timeless advice.

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True power is ….

Here’s a quote from Warren Buffets that’s on my mind.

You will continue to suffer if you have an emotional reaction to everything that is said to you.

True power is sitting back and observing things with magic.

True power is restraint.

If words control you that means everyone else can control you.”

-Warren Buffett

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The Man Who Boiled Urine to Get Gold.

Ever since we moved our dinner out of our TV room, dinner time has been a constant source of enjoyment. Sometimes kids tell their stories and sometimes I tell them stories that I have read from the recent books I have been reading.

Last month told an interesting story to kids from the Book Elemental by Tim James. I was hoping to post it here on this blog but my Son beat me to it. He likes these stories and wastes no time in sharing them if they are interesting on his blog. Do read this. You will love the story.

The man who boiled urine for gold.
Click on the image to read.

Its a story of a late seventh-century German experimenter named Henning Brandt who proved everyday substances had elements locked inside them and most of the stuff we thought pure was not so.

Do give it a read. The Man Who Boiled Urine.

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Starting and Finishing

This is a repost from the excellent Seth Godin’s blog. I keep coming back to this post.

Sometimes the rule is:

You don’t have to finish, but you do have to start.

And sometimes the rule is:

You don’t have to start, but if you do, you have to finish.

When building a personal habit, it might make sense to embrace the first rule. You don’t have to run all the way, every day, but you do have to get out of the house and start running.

And when making promises to a group where trust matters, the second rule definitely applies.

Seth’s Blog

Simplicity Can Be Lucrative

Who hasn’t played with Legos or its many varied copycat replicas? My kids have a lot of fun with them. Many of our fun memories are around these toys. Even today I see my friends kids getting so engrossed with this. As soon as these simple plastic bits and bobs are laid out for them, they are in their own world.

So when I stumbled on this little historical note on lego’s history I couldn’t resist posting it here.

Infinite Builds: Modular Lego Bricks

Ole Kirk Christiansen, a carpenter, founded The Lego Group in 1932.

At the time, he was out of work because of the Depression and decided to build wooden toys in Denmark. In 1947, Ole got samples of a plastic brick invented and patented (“self locking building bricks”) by Mr. Hilary “Harry” Fisher Page in Britain, and began creating the automatic binding bricks that we know today as Lego bricks, a name that originated in 1953. Ole’s 1958 Lego patent (#3005282) states, “the principle object of the invention is to provide for a vast variety of combinations of the bricks for making toy structures of many different kinds and shapes.” And that was the magic of Lego—vast variety from simplicity. Anything imaginable could be built.

All kids could unleash their creativity on the world with simple, modular, relational blocks.

Today, Lego, with headquarters in Billund, Denmark, is the sixth largest toy company in the world, with over 5,000 employees andrevenue of $7.8 billon Danish Kroner.

Simplicity can be lucrative.

The Most Important Lesson

Covid 19 has changed the world, accelerated tech adoption, made things possible we didn’t think was possible. Fastest vaccine development ever! But what were our biggest lessons from this? Thankfully as covid subsides we should all ponder on its important question.

But as explained in the below passage from Morgan Housely, we would be better off taking a 30k foot view than selecting the first specific thing that comes to mind.

A good lesson from the dot-com bust was the perils of overconfidence. But the lesson most people took away was “the stock market becomes overvalued when it trades at a P/E ratio over 30.” It was hyperspecific, so many of the same investors who lost their shirts in 2002 got up and walked straight into the housing bubble, where they lost again.

The most important lessons from a big event are usually the broad, 30,000-foot takeaways. They’re more likely to apply to the next iteration of crisis.

Morgan Housely

Terrified to do anything…..

Sometimes Twitter is a gem. Only social media that I follow. Here’s one thought that has remained with me since I read it.

If you went back in time before your birth you’d be terrified to do anything, because you’d know that even the smallest nudges to the present can have major impacts on the future.

Applied to today, a reminder that how you live each day really does matter. It changes the future.

via this

Room For Error

Photo by Pixabay on Pexels.com

The recent market declines and my stock WhatsApp groups falling silent reminded me of this piece that I had saved on my desktop, written by Morgan Housely

Many bets fail not because they were wrong, but because they were mostly right in a situation that required things to be exactly right. Room for error – often called the margin of safety – is one of the most underappreciated forces in business.

It comes in many forms:
A frugal budget, flexible thinking, and a loose timeline – anything that lets you live happily with a range of outcomes.

It’s different from being conservative.

Conservative is avoiding a certain level of risk. Margin of safety is raising the odds of success at a given level of risk by increasing your chances of survival.

Its magic is that the higher your margin of safety, the smaller your edge needs to be to have a favourable outcome. And small edges are where big payoffs tend to live, since most people don’t have the patience to wait around for them.

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Will Tech Giants of Today Last?

In a recent Daily Journal Annual Meeting, Charlie Munger was asked

Question: Do the great tech giant franchises of our day, specifically Microsoft, Apple, and Alphabet, have the same long-term durability that Coca-Cola had 30 to 40 years ago?

Charlie Munger: It’s a lot easier to predict who flourished in the past because we know what happened in the past. But now I want to compare what’s gonna happen in the future. Of course, that’s harder.

It’s very hard for me to imagine—that doesn’t mean it couldn’t happen—but I would expect Microsoft, Apple, and Alphabet to be strong 50 years from now—really strong, still strong. But if you’d asked me when I was young what was gonna happen to the department stores that went broke or the newspapers which were broke, and so on, I wouldn’t have predicted that either. I think it’s hard to predict how your world is going to change if you’re going to talk about 70, 80, 90 years.

Just imagine, they wiped out the shareholders of General Motors, they wiped out the shareholders at Kodak. Who in the hell would have predicted that? This technological change can destroy a lot of people. It’s hard to predict for sure in advance.

Thermodynamics, Life and Universe

Thermodynamics was my favourite subject when I was in college. The subject felt close to something I can relate to. I did not know why I like it better than others, I liked fluid dynamics too but thermodynamics was always my top one. Reading the book Einsteins Fridge did rekindled that love of that subject.

Here’s a quote from the book.

At its heart are three concepts energy, entropy, and temperature. Without an understanding of these and the laws they obey, all science physics, chemistry, and biology would be incoherent. The laws of thermodynamics govern everything from the behavior of atoms to that of living cells, from the engines that power our world to the black hole at the center of our galaxy.

Thermodynamics explains why we must eat and breathe, how the lights come on, and how the universe will end.

From the book

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It’s Not What You Want…

Photo by Pixabay on Pexels.com

Johannes Gensfleisch was a German inventor, printer, publisher, and goldsmith who introduced printing to Europe with his mechanical movable-type printing press. His work started the Printing Revolution in Europe and is regarded as a milestone of the second millennium.

Here’s a story from the book From Gutenberg to Google: The History of Our Future Hardcover by Tom Wheeler on what he might have felt after inventing the movable type and how it would be Guternber day.

It is worthwhile pausing at this point to savor Gutenberg’s success.

Imagine the exultation and celebration that must have gripped Johannes Gutenberg as his first printed book was bound!

More than a decade in development, Gutenberg’s understanding that a page of information was the sum of its parts had required a “secret art” to both discover a revolutionary new process and find the means of adjusting a seemingly endless number of variables into harmonious production.

Now it was done. Success had been achieved in twenty-eight pages of Latin grammar instruction.

The Western world had never before seen the rapid production of hundreds of perfect-quality pages, each one identical to the others. It was a moment to be savored, a decade-long quest with a transformative result.

Unfortunately, the exultation would be short-lived.

Other mass-market documents flowed from Gutenberg’s printing shop. The earliest dated work was a papal indulgence of 1454. Having spent more than a decade perfecting his technique, however, Gutenberg, it would appear, was not satisfied with such run-of-the-mill products. He wanted a monument. Today we call that monument the Gutenberg Bible.

It would be his downfall.

The Gutenberg Bible, Tim Hartford says in his book called Adapt: Why Success Always Starts With Failure., was a failure. It’s a pretty strange example of failure since it was the first book printed with movable type which started 500 years of mass communication. What we do now is pretty much the result of Gutenberg bible.

Believe it or not, the Gutenberg Bible was a total flop for Johannes Gutenberg, the father of the printing press. He went bankrupt trying to make money printing this book. Just like with any new technology, it was very expensive to print books. It was actually so expensive that you might as well hand write them rather then print them. The business model which eventually worked out a bit after Gutenberg’s time was printing leaflets for the church. These early leaflets for the church kept the early printing industry afloat.

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Precision versus Approximation

In the book How Long is a Piece of String by Eastaway Rob

How can you tell the difference between a mathematician and an engineer? Ask them what pi is. Mathematician: “It is a ratio describing the circumference of a circle to its diameter, a transcendental number which begins 3.14 and continues for an infinite number of digits.”

Engineer: “It’s about 3, but let’s call it 10 just to be on the safe side.”

Happy PI day!!

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