455: Rolex Pricing, Jensen & Nvidia, China Chip Ban 1.5, Costco, Google Maps to Optimize Cities, Bicycle for the Mind, and Beckham

"most fields are legible to an interested outsider"

The owner of an idea is not he who imagines it, but he who executes it.

—M.J. DeMarco

Who needs legs when you're thinking that hard 💚 🥃

🛀💭 🧠🧐 Is there anything that I could never understand no matter how long and how well it was explained to me?

I’m not referring to gaining the ability to *do* that thing well, I just mean would I be able to understand what’s going on at the high level. And it has to be something that is known and knowable by some people — I’m not looking for loophole answers like understanding the inner workings of 75,000-dimension matrices inside transformer models or the answer to the Riemann hypothesis or the P versus NP problem or made-up gibberish like post-modern deconstructionism!

The first thing that comes to mind is quantum mechanics, but I’m not sure it qualifies. That really depends on the definition of “high-level understanding”.

I think I could understand it with enough effort and a good teacher (where’s Feynman when you need him?). To be clear: I don’t mean to have an intuitive understanding of quantum physics, that’s impossible. I’m talking about understanding it like a physicist, even if I can’t do all the math myself. To have an idea of what the experiments and the math show and why we think what we think about it.

There are many things where the details are impossibly complex — like biology or cryptography — but if I zoom out, I can understand the broad strokes of what’s going on when the AES encryption algorithm is generating a cipher or when a cell converts ATP to ADP or AMP.

What I find most interesting about this thought experiment is how freeing it is!

As a kid, so many things intimidated me.

I used to believe that I could never understand XYZ without spending years studying it at a university. And since I knew I wasn’t going to do that for cosmology / psychology / biology / finance / mechanical engineering / semiconductors / design / etc, it seemed like there would always be large fields of human knowledge that would remain opaque.

Like magic that only an inner circle of the initiated could understand. 🧙‍♂️

However, as I followed my curiosity and started reading books on various subjects, fell down rabbit holes online, listened to long-form interviews and presentations, etc, I realized that most fields are legible to an interested outsider if the goal is to understand the big ideas that carry most of the freight.

Good ol’ Pareto to the rescue!

But let’s not forget the Dunning-Kruger danger zone. ⚠️

Knowing a few things about a field can be dangerous if you think you know more than you do or lose sight of the nuances contained in what you don’t know.

But as long as you stay humble and well-calibrated, there is a great deal of richness to be found in exploring new fields AND combining what you learn with what you know from other fields.

A lot of the most interesting stuff in life can be found at the very bleeding edge of a field *or* at the intersection of multiple fields that don’t typically intersect.

🤔 🪂 I know what the expression means, but a gold parachute would actually kill you.

☀️⏰ I’m thinking of getting a “sunrise” alarm clock. I think I’d prefer being woken up slowly by light rather than by sound… Let me know if you have a recommendation for a good model.

A deal-breaker for me: I need to be able to turn off all lights from it during the night. No clock, no ambiance glow, nothing!

🗓️🛫 Next week, I’ll be traveling to the US to spend some time in person with the wonderful OSV team. There will be a short break in the newsletter.

💚 🥃 🐇 I know you’ve been sitting on the fence for a while, meaning to support this project but putting it off to a later time.

Well, *now* is the time! Your support makes a big difference and every new signup makes my day (I email each one individually):

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Drop me a line if you’re interested in sponsoring the newsletter.

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🏦 💰 Liberty Capital 💳 💴

⌚︎ 50 years of Rolex price increases 📈 💵

Friend-of-the-show Sleepwell Capital:

Average yearly price increases of 6-8%. This is what pricing power looks like.

These are retail prices at Authorized Dealers, not what they trade for in secondary market (eg Daytona goes for 2x retail)

Submariner saw the highest price increases at 8% CAGR, Day-Date the lowest at 6%. Difference mainly being low starting base

A Submariner cost only $180 in 1971, while a Presidential Day-Date (18K Gold) cost $1850 in 1973. 

Over the next 10 years, Rolex Gold watches rose significantly in price (5X or 17% p/yr), mainly to position as a luxury brand given the Quartz crisis (competition from Japan)

Source of the pricing data.

🇺🇸✋🇨🇳 The China Chip Ban gets updated to V1.5 🐜

Surprising no one:

The updated rules significantly expand the U.S. government’s authority to determine what products U.S. companies can and can’t sell in the name of national security. Shipments of high-end AI chips, including those developed by Nvidia and Intel for the Chinese market, are banned without a license. And “gray zone” chips just below those thresholds will now require notification to the government, which can then deny their sales.

Even high-end gaming chips are now more closely monitored:

[The update to the rules] Creates a notification requirement for a small number of high-end gaming chips to increase visibility into shipments and prevent their misuse to undermine U.S. national security

Lennart Heim has a nice visualization of the change, and how it blocks one of the scaling paths for China:

The US just published its revised export controls on AI chips, moving away from the 'chip-to-chip' interconnect bandwidth threshold to a threshold on computational performance (OP/s), including its derived performance density (OP/s per mm²).

There were loopholes in the initial controls. At first glance, these new measures seem to address those. The prior 'escape/scaling path' allowed continued scaling computational performance while bounding the interconnect.

This seems to make the A800 and H800 chips that Nvidia made specifically for China verboten.

Nvidia is saying that the short-term impact on its results won’t be too significant because demand is so high everywhere else too, but there’s no doubt that China is a very large market, and losing more of it for the long term has to meaningfully change the company’s addressable market.

And even if China is somehow re-opened to Nvidia later, by then it will likely be a lot less dependent on CUDA and Nvidia platforms.

😎 Interview: Jensen Huang, Nvidia CEO and Co-Founder 🔥

Friends-of-the-show Ben and David (💚 🥃 ) are on fire these days! Their latest very special episode is a great interview with Jensen.

For all the details on the company’s history, check out their 3-part series on Nvidia.

Jensen is a very clear thinker so it’s a pleasure to listen to him talk about how he made certain decisions:

Here’s a highlight:

Ben: So is the lesson for founders out there when you have conviction on something like the RIVA 128 or CUDA, go bet the company on it. This keeps working for you. It seems like your lesson learned from this is yes, keep pushing all the chips in because so far it’s worked every time. How do you think about that?

Jensen: No, no. When [I] push your chips in I know it’s going to work. The reason why we taped out a perfect chip is because we emulated the whole chip before we taped it out. We developed the entire software stack. We ran QA on all the drivers and all the software. We ran all the games we had. We ran every VGA application we had.

When you push your chips in, what you’re really doing is, when you bet the farm you’re saying, I’m going to take everything in the future, all the risky things, and I pull in in advance. That is probably the lesson. To this day, everything that we can prefetch, everything in the future that we can simulate today, we prefetch it.

What may seem like a high-risk gamble from the outside can be a calculated risk with a lot of emphasis on the calculated part and on reducing the risk part as much as possible.

It was a big bet that they *had* to make — they wouldn’t have chosen to run out of money at the time — but once you have to do it, the way that they did it was very smart, and they learned a bunch of lessons that they use to this day.

I also loved this part (it’s a bit long, but it’s good):

Jensen: Nvidia’s not built like a military. It’s not built like the armed forces, where you have generals and colonels. We’re not set up like that. We’re not set up in a command and control and information distribution system from the top down.

We’re really built much more like a computing stack. The lowest layer is our architecture, then there’s our chip, then there’s our software, and on top of it there are all these different modules. Each one of these layers of modules are people.

The architecture of the company (to me) is a computer with a computing stack, with people managing different parts of the system. Who reports to whom, your title is not related to anywhere you are in the stack. It just happens to be who is the best at running that module on that function on that layer, is in-charge. That person is the pilot in command. That’s one characteristic. [...]

your organization should be the architecture of the machinery of building the product. That’s what a company is. And yet, everybody’s company looks exactly the same, but they all build different things. How does that make any sense? Do you see what I’m saying? [...]

It’s not sensible to me that if you look at the org charts of most companies, it all looks like this. [...]

None of that stuff makes any sense to me. It just depends on what is it that we’re trying to build and what is the architecture of the company that best suits to go build it? [...]

In terms of information systems and how you enable collaboration, we’re wired up like a neural network. The way that we say this is that there’s a phrase in the company called ‘mission is the boss.’ We figure out what is the mission of what is the mission, and we go wire up the best skills, the best teams, and the best resources to achieve that mission. It cuts across the entire organization in a way that doesn’t make any sense, but it looks a little bit like a neural network.

This reminds me a bit of how Steve Jobs’ greatest product may be Apple as a company.

They were doing things very differently from their competitors for a long time (in ways that have now been emulated by many of them).

Things like having a functional organization, not having separate R&D but integrating it into product development, having DRIs (Direct Responsible Individuals) for every aspect of hardware and software so that someone “owns” a thing to avoid having diffuse responsibility, etc.

All that stuff matters because your products and services are a reflection of the organization that made them. It’s the old saying about how “you ship your org chart”.

🆙🪽 James Pethokoukis: Forget about left and right, how about up and down? 🚀 ♾️ 🔁

I really enjoyed this conversation between Jim O’Shaughnessy (💚 🥃 🎩) and James Pethokoukis.

• 🎧 James Pethokoukis — The Conservative Futurist (EP.183)

As an aside: I think calling his book “The Conservative Futurist” will limit its reach (and James seems to imply that his publisher had something to do with that) because it reinforces the obsolete and over-simplified notion that everything falls on a one-dimensional line.

But the conversation and James’ ideas are very inspiring and a good reminder that there are exciting futures worth fighting for and that problems can be solved.

🛒 📦 Number of Costco stores around the world 🌎

It’s really not that many locations considering that they did $242 billion in sales in the past year.

If my napkin math is right, that’s over $280m per location on average (to be fair, some of the revenue is from online orders — imagine how much more they could sell if they had a decent app!).

For an amazing overview of Costco’s history and business model, I recommend two podcasts by friends-of-the-show:

• David Senra: #304 : Sol Price (The Founder Who Taught Jim Sinegal, Sam Walton, Jeff Bezos, Bernie Marcus)

• Acquired: The Complete History & Strategy of Costco

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🧪🔬 Liberty Labs 🧬 🔭

Understanding Nvidia’s DLSS 3.5: Real-Time AI Upscaling 🤯

Very cool, very clever.

🚦 Google Maps data used to optimize traffic lights🚦

Now *that* is an idea I can get 10,000% behind.

It seems like a no-brainer that with the mountains of traffic data that we have plus all kinds of wonderful AI algorithms, we should be able to optimize traffic flows much better and save everybody some time and fuel.

The project analyzes data from Maps users using AI algorithms and has initially led to timing tweaks at 70 intersections. By Google’s preliminary accounting of traffic before and after adjustments tested last year and this year, its AI-powered recommendations for timing out the busy lights cut as many as 30 percent of stops and 10 percent of emissions for 30 million cars a month.

We’re not talking about rocket science either:

Some of Google’s recommendations are as simple as adding two more seconds during specific hours to the time between the start of one green light and when the next one down the road turns green, allowing more vehicles to pass through both intersections without stopping. More complicated suggestions can involve two steps, tuning both the duration of a particular light and the offset between that light and an adjacent one.

City engineers log into an online Google dashboard to view the recommendations, which they can copy over to their lighting control programs and apply in minutes remotely, or for non-networked lights, by stopping by an intersection’s control box in person.

How about a massive roll-out everywhere? We need this!

🚲🧠 A Bicycle for the Mind (classic Steve Jobs metaphor)

The context of this classic chart is something that Steve Jobs said in an interview in 1990. If you’re not familiar with it, you have to see this.

h/t Jaso Crawford

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🎨 🎭 Liberty Studio 👩‍🎨 🎥

⚽️ ‘Beckham’ documentary (Netflix, 2023) 📸 🟥 😱

I don’t follow sports. I vaguely knew who David Beckham was before watching this.

But after listening to a recent episode of the Not Investment Advice podcast where they discussed the mini-series, I had to check it out.

The meta-aspects of high-level sports and what it takes to succeed are very interesting to me and so much of it transfers to other fields (I love Michael Jordan’s Last Dance).

So far, two episodes in, this is pretty good.

I didn’t know anything about the red card controversy, so I wasn’t expecting just how vicious everyone got about it — and at a time when news cycles could last for months!

Beckham’s mental fortitude is impressive, but you can also tell that this really got to him.

It’s easy to imagine ourselves in his shoes and think “oh yeah, I’d just have ignored it and waited for it to pass”, but in practice, we haven’t evolved for this kind of social situation. Being constantly in the spotlight, getting death threats and kidnapping threats for your kids, and being screamed at by thousands of people live on TV, day after day, 24/7.

And this happened to a 23-year-old kid!

Another interesting dichotomy is how his coach on the England team didn’t have his back and blamed him publicly, while the manager of United created a bubble for the team for them to focus, concentrate, and feel protected from the world. Very different approaches…

Update: Last night I watched the 3rd episode, and I think it was my favorite so far. One more to go, but I can already recommend the mini-series.