What We’re Reading (Week Ending 13 September 2020)

What We’re Reading (Week Ending 13 September 2020) -

Reading helps us learn about the world and it is a really important aspect of investing. The legendary Charlie Munger even goes so far as to say that “I don’t think you can get to be a really good investor over a broad range without doing a massive amount of reading.” We (the co-founders of Compounder Fund) read widely across a range of topics, including investing, business, technology, and the world in general. We want to regularly share the best articles we’ve come across recently. Here they are (for the week ending 13 September 2020):

1. The S-1 Club | Unity is Manifesting the Metaverse – MDA Gabriele

We’d be remiss if we didn’t discuss Unity’s role as a “founder” of the Metaverse, a term coined in Neal Stephenson’s Snow Crash, and further popularized by media analystMatthew Ball.

The Metaverse describes a state of interoperability across digital platforms in the virtual world. To date, virtual worlds have been built as walled gardens with their own laws of physics, currencies, and customs. The Metaverse connects walled gardens the way physical networking infrastructure connected internal networks nearly 50 years ago to create the Internet. The Metaverse also powers real-world interactions by enabling multiple people to experience the same event at once and collaborate in highly immersive environments. Fans of Ready Player One will recall the ragers held in The Oasis.

Where does Unity fit in such a world?

One perspective comes from Unity’s nemesis, Epic Games. As mentioned in Company History, Epic is the creator of the directly competitive Unreal engine. In a conversation with the LA Times, CEO Tim Sweeney described what the Metaverse will enable:

“Just as every company a few decades ago created a webpage, and then at some point every company created a Facebook page, I think we’re approaching the point where every company will have a real-time live 3D presence, through partnerships with game companies or through games like Fortnite and Minecraft and Roblox. That’s starting to happen now. It’s going to be a much bigger thing than these previous generational shifts. Not only will it be a boon for game developers, but it will be the beginning of tearing down the barriers not just between platforms but between games.”

If you ascribe to Sweeney’s view, then the upside for engines like Unity and Unreal is extraordinary. Rather than merely powering game development, Unity has the potential to serve as the foundational layer — the rails — of a new, shared synthetic reality.

2. Will Money Printing Cause Inflation? – Michael Batnick

If we’ve learned anything since the government’s response to the last crisis, it’s that quantitative easing or money printing or whatever you want to call it, does not necessarily plant the seeds for higher prices in the future. If you have any faith in how markets work, then look to our borrowing costs as a clue. If investors were really worried about the size of the federal deficit, than the costs for funding it wouldn’t be at a record low.

One of the reasons that people worry so much about the size of the deficit is because they think of the government like a household. But unlike a household, the government can create more money. Unlike a household the government can keep borrowing. And unlike a household, the bill never comes due.

3. WeChat and TikTok Taking China Censorship Global, Study Says – Jamie Tarabay

ByteDance Ltd.’s TikTok often buries or hides words that reflect political movements, gender and sexual orientation or religion in most countries where it operates, the Australian Strategic Policy Institute said in a report released Tuesday. Most of the content censored on WeChat supported pro-democracy activists in Hong Kong, as well as messages from the U.S. and U.K. embassies regarding a new national security law enacted by Beijing at the end of June that has provoked protests across the city.

TikTok, which began as a place where teens lip-sync to music, has become a forum for political protest including the Black Lives Matter movement, said Fergus Ryan, one of the authors. Hashtags related to LGBTQ+ issues were also suppressed in several languages, according to the report. Other topics censored in the past included criticism of Russian President Vladimir Putin.

4. Understanding Stakeholder Value: Where Do Profits Come From? – Sean Stannard-Stockton

In our 2017 post PRICING POWER: DELIGHTING CUSTOMERS VS MORTGAGING YOUR MOAT, we explained how companies that seek to capture as much of the surplus value as possible for themselves and leave as little as possible in the hands of their customers, do not have nearly the opportunity to maximize long term shareholder profits as those companies that relentless try to increase consumer surplus.

A company that is “mortgaging its moat” as described in the post, is one that seeks to extract as much of the consumer surplus as possible from their customers and capture the value as profit for themselves. This is what a monopoly is all about. Monopoly conditions disconnect sellers from needing to worry about competition and allows them to set pricing at the level that wins the maximum amount of profits while minimizing consumer surplus. Under these conditions, there is some end point at which the company has extracted every dollar of consumer surplus for themselves and 1) they are unable to extract any more, while 2) consumers are willing to try any other even barely viable alternative just to attempt to exit the exploitative relationship they are in with the seller.

Conversely, a company that is “delighting customers” is one that, because they relentless drive up the value of their products and services by creating so much additional consumer surplus, gets no push back from consumers when they raise prices. Under these conditions, there is no theoretical limit to the amount of consumer surplus a company can create nor on the value they can capture as producer surplus (profits) via raising prices.

5. Reed Hastings Had Us All Staying Home Before We Had To – Maureen Dowd

Has the pandemic altered Mr. Hastings’s perception of the competition?

It’s the “sideways threats” that bite companies, he said. “If you think of Kodak and Fuji, competing in film for 100 years, but then ultimately it turns out to be Instagram.”

Speaking of which, I wondered if he thinks that Mark Zuckerberg, Sheryl Sandberg and Jack Dorsey have done enough as far as election meddling and disinformation threats?

“Every new technology has real issues that have to be thought through and, you know, we’re in that phase for social media,” he said, adding: “The car, many people think is a great invention for human freedom, but it also has killed a lot of people over time. Film got used by Hitler for terrible purposes.”

He continued: “So I find Mark and Sheryl to be sincere in trying to think these things through.”

6. Taming the Tail: Adventures in Improving AI Economics – Martin Casado and Matt Bornstein

Many of the difficulties in building efficient AI companies happen when facing long-tailed distributions of data, which are well-documented in many natural and computational systems.

While formal definitions of the concept can be pretty dense, the intuition behind it is relatively simple: If you choose a data point from a long-tailed distribution at random, it’s very likely (for the purpose of this post, let’s say at least 50% and possibly much higher) to be in the tail.

Take the example of internet search terms. Popular keywords in the “head” and “middle” of the distribution (shown in blue below) account for less than 30% of all terms. The remaining 70% of keywords lie in the “tail,” seeing less than 100 searches per month. If you assume it takes the same amount of work to process a query regardless of where it sits in the distribution, then in a heavy-tailed system the majority of work will be in the tail – where the value per query is relatively low…

… The long tail – and the work it creates – turn out to be a major cause of the economic challenges of building AI businesses.

The most immediate impact is on the raw cost of data and compute resources. These costs are often far higher for ML than for traditional software, since so much data, so many experiments, and so many parameters are required to achieve accurate results. Anecdotally, development costs – and failure rates – for AI applications can be 3-5x higher than in typical software products.

However, a narrow focus on cloud costs misses two more pernicious potential impacts of the long tail. First, the long tail can contribute to high variable costs beyond infrastructure. If, for example, the questions sent to a chatbot vary greatly from customer to customer – i.e. a large fraction of the queries are in the tail – then building an accurate system will likely require substantial work per customer. Unfortunately, depending on the distribution of the solution space, this work and the associated COGS (cost of goods sold) may be hard to engineer away.

Even worse, AI businesses working on long-tailed problems can actually show diseconomies of scale – meaning the economics get worse over time relative to competitors. Data has a cost to collect, process, and maintain. While this cost tends to decrease over time relative to data volume, the marginal benefit of additional data points declines much faster. In fact, this relationship appears to be exponential – at some point, developers may need 10x more data to achieve a 2x subjective improvement. While it’s tempting to wish for an AI analog to Moore’s Law that will dramatically improve processing performance and drive down costs, that doesn’t seem to be taking place (algorithmic improvements notwithstanding).

7. Airbnb’s resurgence – Felix Salmon

Estimates from Edison Trends show Marriott and other hotel chains seeing much lower spending than at this time last year. At Airbnb, by contrast, spending is hitting new all-time highs.

Airbnb spending is running a whopping 75% higher than this time [September 2020] last year, says the research shop, based on a panel of spending data including more than 65,000 Airbnb transactions.

That means Airbnb’s revenues have comfortably surpassed Marriott’s, for the first time.

Ser Jing & Jeremy
thegoodinvestors@gmail.com