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Hey friends, 

Merry Christmas.  Happy Holidays.  Are you ready for 2021?  Not that any of us have a choice.

I learned a new term today: Cucumber Time.  It means the periods in the calendar when there is a lull in meaningful news.  That's what we are in right now, as most things that drive news are on holiday. However, a more positive framing is that now is the time to read (and re-read) the timeless essays and the long-form pieces that you didn't have time for during a year of events. 

I'm reading You Can Be A Stockmarket Genius by Joel Greenblatt today.  A gift from a friend.

For that reason, I'm keeping DS short and sweet this week. 
 
Today's Contents:

  • Weekly Song: Build Me Up Buttercup
  • Obviously The Future: Making Predictions
  • Good Reads

Weekly Song: Build Me Up Buttercup

I love this oldie.  It's a 'sounds optimistic but the lyrics suggest the outcome probably ends up being a bit disappointing' sort of song.

It's with this attitude that we leave 2020 and venture on to 2021.  I'm not going to build you up: 2021 could be more volatile and more dramatic than 2020 was.  So, please, moderate your expectations and remember that, generally speaking, the quality of life on Earth is improving.  A fact for today?  In 1920, the average male life expectancy in the US was 53.6 years; by 2020, that had risen to 76.2 years.     
 

"Build Me Up Buttercup" by The Foundations

Why do you build me up (build me up) buttercup, baby
Just to let me down (let me down) and mess me around?
And then worst of all (worst of all) you never call, baby
When you say you will (say you will) but I love you still
I need you (I need you) more than anyone, darlin'
You know that I have from the start
So build me up (build me up) buttercup, don't break my heart

The 5 best holiday movies, ranked

Is it too late for these recommendations?  Maybe, but I'm going to list them anyway.  I like the classics:

5. A Christmas Story

4. A Christmas Carol.  It’s amazing that you can watch full movies on YouTube.  It's never too late for epiphanies and new beginnings. 

3. National Lampoon’s Christmas Vacation.  Chevy Chase is hilarious. 

2. The Grinch.  The original, obviously.  Dr. Seuss is the best.

1. It’s a Wonderful Life - Classic of classics.  'Every time a bell rings, an angel gets it's wings'

Making predictions and the challenge of expertise


New year, new predictions.  How do I think about prediction and forecasting?  The most important part is that you do it.  Do it consistently.  Not once a year when everyone is doing it, but on a regular basis.  My specific thoughts:  

  1. Always write it out.  Writing your thinking out makes it clearer, stronger, better.
  2. After writing it out, share it. Test it.  Refine it.  List out the ways you could be wrong.  Review it after the fact.  And then learn.  But the only way to do it is by doing the work.
  3. Most predictions you read (particularly year-end) are sales and marketing.  They are people selling or marketing a position they often have already put their money, time, and/or career behind.  View them through that lens.
  4. Predictions are only as valuable as what you are willing to do to act on them.  How you place a bet to capture value or upside is the hardest part and the most vital to get right. 
  5. Spend time deepening your knowledge but also examine the bias from your expertise and past experience.  What do you do when you know a sector inside and out and you are looking for something that might change?

This point on expertise is where I want to go deeper.

A couple of weeks ago, I attended a deep tech conference, which was full of insight and learning.  The final keynote was Peter Diamandis who founded the Singularity University.  His presentation, which you can find here, maintained the thesis that everything is changing at an exponential rate, and you have to go all-in on Artificial Intelligence.  He went through examples, e.g., there should be energy cheap and easy from the sun; everything will be connected; and, gene therapies will be approved and utilized in mass.  Near the end, he proclaimed that technology converts scarcity into abundance.  Which seems to make logical sense.  Of course, the level deeper is scarcity for who?  An abundance of what?

At this point, I'm buying the narrative.  Eating it all up.  And he keeps talking about all the things he's worked on and then...bam.  He lands on something I know well. 

On slide 77 out of 90, we get to the X-prize in 'Global Learning'.  See below.  It's, like, hold up.

What is going on here?  I spent a good several years as the head of a venture fund that invested in emerging market education and EdTech companies.  We had four portfolio companies in sub-Saharan Africa, and I had looked at over 100 'solve education in Africa' companies, including a few that had participated in the X-prize. 

Let's break down what is happening on the slide.  There was $15M of prize money.  Organizations spent an estimated $300M of resources to address the challenge.  The goal was to improve learning for 2,500 students in rural Tanzania.

Some basic math tells us the ROI was not great.  $300M divided by 2,500 means that $120,000 was spent per student in Tanzania, where the average GDP per capita is $985.  So there's that.  You could have sent each kids to a US boarding school... for several years.

Second, the stipulation that "1 House of Tablet Use = Full-time School."  Well, they don't give a lot of details about what that means, but I am 95% sure that it's mostly a reflection on the fact that children in school in rural Tanzania don't learn very much.  So if you don't learn much in full-time school, it's not too hard to not learn much during 60 minutes on an iPad.  

As much as people have tried to make 'if you give them all laptops and tablets with good content, they will learn' happen, it never comes to fruition. 

It was a great reminder of the level of belief that I should give to anything else from this presentation about the areas where I knew much, much less.

Joel Greenblatt had a similar story at the beginning of the book:

When I was fifteen, the only gambling establishment that would let me sneak in was the Hollywood Dog Track. This was a great thing because, during my illicit visit, I discovered a sur-fire route to big greyhound riches. In the third race, there was a dog who had run each of his previous six races in only thirty-two seconds. The odds on this dog - Lucky - were 99-1. None of the dogs up against Lucky in the third race had managed a time better than forty-four seconds in any previous race.

Of course, I bet what passed for a small fortune at the time on Lucky to WIN. If all those fools who bet on the other dogs wanted to give me their money, so be it. However, as Lucky struggled down the home stretch in last place, my opinion of the other gamblers slowly began to change. 

This was Lucky's first race at a longer distance. Apparently, as everyone else already knew, Lucky's spectacularly fast times in his previous races were achieved at much shorter distances. All the other dogs were experienced long-distance runners.

I learned a valuable lesson. Without a basic level of knowledge and understanding, you can't tell a great investment from a real dog. 


The tough part is when you know a sector super well and you are looking for the things that will change the game, alter the outcome, make it different this time. Maybe it will be different with AI?

Good Reads

Last week this link didn't work.  Corrected: Tom Goodwin wrote a thought-provoking piece.  

Everyone has read the sad article in Elle about Christie Smythe and Martin Shkreli.  The funny thing about these stories is how canned they are.  In the feature, there are posed photos of Christie Smith where it notes she is wearing a dress from a brand called The Vampires Wife.  Yes.  That's a real clothing outlet.  And, yes, it is exactly what you'd suspect. 

Greenhaven Road Investor Letters.  These are good. 

See you in the New Year. 

Thank you for reading.  Please always be in touch. 

Best,
Katelyn

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