Sunday Snapshots (12th July, 2020)

Collaborations, Adaptive walks and random jumps, Neural networks, Walmart's unique strengths, Hot metal typesetting, and Hamilton

Hey everyone,

Greetings from Evanston!

As a reminder, I’m Sid Jha, and I’ve written this newsletter every Sunday since May 2019. I write about the best books and academic papers, unique business stories, and a few niche parts of the internet. I try to share perspectives that build on my own unique life experiences growing up in India and South East Asia, training as an Industrial Engineer, and writing a weekly newsletter.

Sharing two collaborations from this week:

  • A guest post that I co-wrote with my friend and mentor Ross Gordon on his amazing newsletter, Gridology, about career building activities. We wrote about how to decide what to focus on, share personal examples (including my cold email to him from 3 years ago), and what we can learn from The Karate Kid.

  • An interview with Rishi Taparia about his perspective as an investment banker graduating into the 2008 financial crisis, what graduating seniors can expect, his shift towards venture capital and tech, and how to look at your career as a long term game. Rishi is my favorite person I’ve met in 2020 and writes his own weekly newsletter, Tippets by Taps, about commerce, technology, and the future of work that everyone should subscribe to.

In this issue of Snapshots, I want to explore:

  • Adaptive walks, random jumps, and how to achieve global maximums in your relationships, career, and investments

  • Learning about Convolutional Neural Networks in an interactive way

  • How Walmart is leveraging its unique strengths with drive-in theaters

  • Hot metal typesetting, HBO’s Watchmen, and the font on Air Force One

  • And Hamilton

Book of the week

I wrote about The Origin of Wealth by Eric Beinhocker a few months ago. In this book about economics and how our current framework of how the world works is too deterministic are nuggets of advice about life that I came back to this week.

The one nugget that stands out to me the most is the idea of adaptive walks and random jumps.

Let’s say you are at the bottom of a mountain range and your goal is to get to the highest point, but you can only see the terrain that is in your immediate vicinity and you cannot see where that highest point is. You can think about this mountain as your career, your relationships, your investments, or your personal development. The peak of this mountain range represents some ideal state in one of these categories of your life – you don’t necessary know what’s your best in these categories but you can think logically about your next best move.

Given this, how do you start your climb?

You start by looking for whatever the closest point to you is that is higher than your current position. Once you’re there, you look for a position that is higher than that. You keep repeating this iterative algorithm, known as an adaptive walk.

But there’s a problem here.

What if you get stuck on a peak while being the highest point in the immediate vicinity, isn’t the highest point in the mountain range overall? In order words, what if it’s a local maxima and not a global maxima?

The way to prevent this from happening is to take random jumps every now and then. These jumps will typically fail, but a few times, you’ll end up on a mountain that’s higher than the one you jumped from. Imagine this as making a big career change, allocating a portion of your portfolio into a risky IPO, asking out someone, or starting a newsletter 😅.

The optimal strategy is to be on an adaptive walk most of the time and to take random jumps when you find your elevation hasn’t increased in a while. It combine practicality with measured risk taking that maximizes outcomes.

I would love to hear about what random jumps you’ve taken in your life. Send me a message by replying to this email.

Long read of the week

I really enjoyed going through this website from Polo Club of Data Science at Georgia Tech that explained how Convolutional Neural Networks work. It is not an understatement to say that these algorithms run our world so it’s important to understand them. The way that this website explains technical jargon like max pooling, ReLu, and bias is exceptional.

Tip: Schedule a 30 minute block on your calendar this upcoming week and check out this website.

Business move of the week

Walmart and drive-in theaters

If you were to look back through the issues of Snapshots over the last year, you’ll find two themes that come up frequently:

  1. Businesses should focus on their strengths

  2. Every strength will have a corresponding weakness.

This move by Walmart to have drive-in theaters in its parking lots would be exhibit A for these themes.

Walmart sees Amazon in the rear view mirror with its monopolistic stronghold on online retail. It’s unsuccessfully tried to pump up its e-commerce business line through acquisitions like Jet.com. What it needs to do is to leverage its strengths.

One of those strengths? 90% percent of Americans live within 10 miles of a Walmart store. Another strength? Walmart is known for its expansive open parking lots.

Combine these strengths with the implosion of movie theaters because of COVID-19 and a ting of nostalgia for the good old days, and you’ve got a perfect lead generation tool for Walmart that cannot be replicated by Amazon. People who come to watch would likely be willing to increase some of their spending at Walmart if they are going to go to the parking lot anyways.

An idea to take this further? Add unlimited drive-in privileges to the upcoming Walmart+ service. It’s like a niche MoviePass-like offering, but with a real mechanism to make money through shoppers buying things at Walmart. A mechanism that doesn’t try to replicate Amazon’s streaming services but tries to leverage Walmart’s unique strengths.

If you know someone involved with Walmart+, I’d love for you to forward this to them and get their feedback.

Odds and ends of the week

🗞️ Hot Metal Typesetting: Get ready to nerd out on how newspapers were printed before the advent of the computer. Big lead blocks were moved physically at an extremely fast rate to get the daily paper ready. You can see the conflict in the craftsmen about the impending extinction of these craft.

⚛️ Making of Watchmen: HBO’s Watchmen series is one of those rare artifacts that not only do justice to, but improve upon the original source material. This video about how it accomplishes that was fascinating. I’ve been trying to learn more about cinematography and what lessons I can learn from it about keeping an audience’s attention. This breakdown helped me do that for Watchmen.

🤯 Font on Air Force One: This fact is one of the coolest random things I’ve learned this year.

Movie of the week

I finally gave into peer pressure and watched Hamilton after its release on Disney+ last week. It’s pretty good – the tell-tale sign was me not getting bored even once during its almost 3 hour run time – and I’ve heard from people who watched the play in person that it does a great job of replicating the in-person experience.

If you haven’t seen it yet or just want to relive the experience, check it out on Disney+.


That wraps up this week’s newsletter. If you want to discuss any of the ideas mentioned above or have any books/papers/links you think would be interesting to share on a future edition of Sunday Snapshots, please reach out to me by replying to this email or sending me a direct message on Twitter at @sidharthajha.

Until next Sunday,
Sid