What We’re Reading (Week Ending 24 March 2024) - 24 Mar 2024
Reading helps us learn about the world and it is a really important aspect of investing. The late Charlie Munger even went 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 24 March 2024):
1. The future of ‘communist capitalism’ in China – Martin Wolf
What is the economic future of China? This question raises many specific issues, notably China’s persistent macroeconomic imbalances, the threat of population decline and worsening relations with important parts of the outside world, above all, an increasingly hostile US. But underneath all of these lies a deeper one: is “communist capitalism”, that seemingly self-contradicting invention of Deng Xiaoping, inexorably fading away under Xi Jinping? Will China’s regime ossify and, in the end, collapse, as the Soviet Union did?…
…Much light on this issue is shed by China’s World View, a recently published book by David Daokui Li, a distinguished Harvard-trained professor of economics, who teaches at Tsinghua University. People interested in China, be they hawks or doves, should read Li’s valuable book carefully.
Perhaps its most startling observation is that “from 980 until 1840, the beginning of China’s modern history”, income per head declined. Ancient China was in a Malthusian trap. This picture is even worse than the one shown in the work of the late Angus Maddison. Even after 1840, this grim reality did not get much brighter. Only after Deng Xiaoping’s “reform and opening up” did it change.
By freeing the private economy, relying on market forces and opening up to the world economy, Deng created the conditions for an extraordinary transformation. Yet, by repressing demands for democracy in Tiananmen Square in 1989, he also reinforced communist party control. He invented a new political economy: today’s China is the result.
Is it also sustainable? Li’s book answers a clear “yes” to this question. In essence, he argues that China’s political system should be viewed not as Soviet, but as a modernised form of the traditional Chinese imperial state. This state is paternal. It is responsible for the people, but not accountable to them, except in one fundamental way: if it loses mass support, it will be overthrown. Its job is to provide stability and prosperity. But, in doing so, it does not try to run everything from the centre. That would be crazy in so vast a country: it decentralises to local levels. The communist party should, he argues, be seen fundamentally as the national party of China.
From this perspective, the Xi regime does not represent an abandonment of the goals of the Deng era, but rather an attempt to remedy some of the problems created by its reliance on “go-go” capitalism, namely, pervasive corruption, soaring inequality and environmental damage…
…When considering the prospects for China, one should not focus mainly on the list of obvious problems — falling property prices, excessive debt, excess savings, an ageing population and western hostility. All these can be dealt with by a country with China’s human resources and growth potential, even if with difficulty.
The bigger issue is whether, in the centralising, cautious and conservative era of Xi, Deng’s move from stagnation to explosive growth is doomed to reverse back into stagnation. If people come to believe that the dynamism of the recent past has been lost for good, then there is a risk of a downward spiral of disappointed hopes. But the force of 1.4bn people wanting a better life is extremely powerful. Will anything be allowed to halt it? The answer, I suspect, is still “no”.
2. Is diversification a blessing or curse? – Chin Hui Leong
DIVERSIFICATION is good or bad for you, depending on whom you ask. Warren Buffett, the legendary investor and businessman, once said that if you know what you’re doing, it makes little sense to diversify.
But Peter Lynch, a star mutual fund manager of the 1980s, had a different approach. He believed that the more stocks you own, the better your chances of finding a winner. Lynch was famous for holding up to 1,400 stocks in his portfolio.
Here’s the surprise: They both achieved remarkable success, despite their opposing positions. What does this mean for you as an investor? Should you diversify, or not?…
…As we delve deeper into diversification, we should not lose sight of its goal to reduce risk. This is where buying businesses from unrelated industries or geographies can go wrong. In fact, investors who diversify into areas where they lack expertise are taking more risk, not less. It makes little sense to do so, says Lynch. How well you know your stocks matters more than how many sectors or regions you spread your money across.
I agree with Lynch. Diversify only if you want to boost your chances of finding more winning stocks in your portfolio.
Here is a point you shouldn’t miss: you should always be looking to learn more about new businesses and industries. As you become more knowledgeable, you can grow your portfolio with more stocks you know well, but without exceeding your limits.
Remaining humble is key. Knowing the limits of your knowledge in any new area is how you keep yourself in check. As author Carl Richards once said, risk is what’s left when you think you’ve thought of everything…
…Here’s a simple rule of thumb to help you. If you’ve been following a new company for a year, invest no more than 1 per cent of your portfolio into the stock. If it’s five years, then up to 5 per cent. You can adjust the percentage to fit your risk appetite.
The point of this strategy is to have a reference point where you can match your risk level with your knowledge level…
…Finally, investing over time helps to spread your risk over years. Don’t worry about starting small in a stock. A winning stock is only known in hindsight. Here’s the point most people miss: if a stock is destined to be a winner, the stock price rise will happen over years, if not decades…
…Here’s the final conundrum: the mark of a successful portfolio is a concentrated portfolio. How can that be? Let’s say you invested $1,000 each into 10 stocks. Each stock will make up a tenth of this $10,000 portfolio.
After five years, the first one skyrockets, increasing by 10 times and is worth $10,000, while the last one goes to zero. The other eight stocks stay the same at $1,000. Do the math and you’ll end up with $18,000 in total. The big difference is, the winning stock will comprise more than 55 per cent of the five-year old portfolio…
…As you diversify to find more winners, the best of them will naturally rise to the top – thereby concentrating your portfolio in the right set of winning stocks. That’s more than any investor can wish for.
3. China has little choice but stimulus – Ethan Wu
The near universal reaction in the west to China’s refreshed 5 per cent gross domestic product growth target: good luck with that…
…The old growth drivers — property, infrastructure and manufacturing — all face major constraints. Property’s structural decline is well known; home prices and sales keep falling. Meanwhile, infrastructure is running into the limit of high debt levels. Chinese officials were dispatched last year to prod local governments to delever. It began with easy cost cuts: withholding wages from civil servants, delaying payments to vendors, slashing city services. But more recently, the deleveraging drive has been hitting infrastructure projects already under way, as Reuters reported in January:
Increasing its efforts to manage $13 trillion in municipal debt, the State Council in recent weeks issued a directive to local governments and state banks to delay or halt construction on projects with less than half the planned investment completed in 12 regions across the country, the sources said…
…Lastly, manufacturing. Since about 2020, the credit that once flowed to the property sector has been redirected to manufacturing, especially in politically favoured sectors such as solar and electric vehicles. The year-over-year growth rate of loans to Chinese industry has risen steadily, though the level is now declining..
…This pivot back to manufacturing is “radical”, says Adam Wolfe of Absolute Strategy Research, and it has generated important victories for China. Most notably, BYD is now the world’s biggest EV maker, and China the biggest auto exporter. But it has also created an enormous oversupply of manufactured goods, which, when combined with limp demand at home, is crushing industrial margins and fuelling deflation…
…China’s manufacturing trade surplus is already huge, perhaps 2 per cent of world GDP. As Gavekal’s Yanmei Xie wrote in the FT last month, western countries sensibly fear China dumping cheap goods into export markets. A cheap renminbi heightens the threat; trade retaliation is widely anticipated. If that is right, export-led growth probably can’t be China’s escape valve.
This glum picture suggests that China may soon be forced into stimulus. Assuming the GDP target is at least somewhat binding, no sector of the Chinese economy stands ready to get growth to 5 per cent. A pick-up in consumption could do it, but we’ve heard no convincing story for why anxious consumers would suddenly become gripped by animal spirits…
…The unclear stimulus outlook has left the bulk of investors nervous, but equity outflows have at least stopped. The stock market has rallied 14 per cent since early February, but only because of ample support from the state. Value trade or value trap?
What keeps us sceptical is the fact that Chinese stocks are not loads cheaper than global stocks. After the rally, the CSI 300 trades at 13x forward earnings, versus 14x for the MSCI all-country world ex-US index. To us the risks in China stocks are much clearer than the reward.
4. Exxon Barges in on Hess Deal – Matt Levine
I, on the other hand, used to be a convertible bond investment banker, so I have somewhat more than the usual familiarity with them. I could tell you, for instance, that it is common in the US for a convertible to be done as a Rule 144A offering, meaning that the bonds are sold to large “qualified institutional buyers” (QIBs) in a private placement and then can’t be resold to retail investors. Doing a 144A deal is generally faster and cheaper than doing a public deal that is registered with the US Securities and Exchange Commission, and retail investors don’t really buy convertibles anyway.
But eventually the institutional buyers of a 144A deal will want to be able to convert their bonds into regular, publicly traded stock, so there needs to be some mechanism for turning “144A” convertibles into “registered” ones. I am old enough that, when I started as a converts banker, the way to do this was to file a registration statement with the SEC, but the modern approach is pretty much that you wait six months or a year and the convertible becomes freely tradeable as a legal matter.
As a practical matter, though, the way this works is that the bonds, when they are originally issued, have a “restrictive legend” on them saying that they can be sold only to institutional buyers, and after a year the company sends a notice to its transfer agent saying “you can take that legend off the bonds now.” And when the bonds have the legend, they can’t be freely traded; once the legend is off, they can be. Here I am pretending, as one does, that “the bonds” are pieces of paper with a legend stamped on them, but of course they are actually entries in an electronic database; what really happens is that the original bonds have a “restricted CUSIP” (the identification number that every security has), telling transfer agents and depositaries and brokers and everyone else that they can only be sold to QIBs, and then after a year the company gets them a new “unrestricted CUSIP” and they trade freely. This is not hard — it’s a phone call or an email, maybe a legal opinion — but the company has to do it…
…So for instance here is the indenture for Avid Bioservices Inc.’s 1.25% exchangeable senior notes due 2026, a convertible bond it issued in 2021.4 Section 4.06(e) of the indenture, the 94-page contract governing the bonds, says:
If, and for so long as, the restrictive legend on the Notes specified in Section 2.05(c) has not been removed, the Notes are assigned a restricted CUSIP or the Notes are not otherwise freely tradable … as of the 370th day after the last date of original issuance of the Notes, the Company shall pay Additional Interest on the Notes at a rate equal to 0.50% per annum of the principal amount of Notes outstanding until the restrictive legend on the Notes has been removed. …
…Avid forgot, for two years, to take the restrictive legend off of its convertible. This was very understandable: Its obligation to remove the restricted legend was boring and technical and buried in Section 4.06(e) of a bond indenture that surely nobody read. It could only remove the legend a year after it issued the bonds, after everyone had stopped paying attention. And, as Avid points out, it “did not receive any notices and was not otherwise made aware” of this provision in, sure, a contract that it signed, but a very long and boring contract. (And, to be fair, the holders forgot too!) And because it completely forgot about its obligation to remove the legend, Avid also forgot to pay the 0.5% penalty interest rate for two years. And because it forgot to pay the extra interest, it created a non-curable default on the bonds: The holders can demand all of their money back, with interest, immediately, with no chance for Avid to fix the problem by removing the legend and paying the overdue interest…
…This is a bad oopsie by Avid, which probably should have put a reminder in its calendar to unrestrict the CUSIP. But it’s a clever trade by whoever this holder was: The old bonds are far out-of-the-money (that is, they’re not going to convert into stock), and Bloomberg tells me that they were trading in the high 70s as recently as a month ago (the high 80s more recently). If you had noticed Avid’s extremely technical oopsie, you could have bought the bonds at, say, 80 cents on the dollar, sent them a letter saying “we gotcha hahahaha,” and made a quick 20 points, plus interest. The holder owns “at least 25%” of the bonds (the amount required to accelerate), and there are $143.75 million of bonds outstanding; 20 points on 25% of $143.75 million is $7.2 million. Plus interest.
5. Sora, Groq, and Virtual Reality – Ben Thompson
Groq was founded in 2016 by Jonathan Ross, who created Google’s first Tensor Processing Unit; Ross’s thesis was that chips should take their cue from software-defined networking: instead of specialized hardware for routing data, a software-defined network uses commodity hardware with a software layer to handle the complexity of routing. Indeed, Groq’s paper explaining their technology is entitled “A Software-defined Tensor Streaming Multiprocessor for Large-scale Machine Learning.”
To that end Groq started with the compiler, the software that translates code into machine language that can be understood by chips; the goal was to be able to reduce machine-learning algorithms into a format that could be executed on dramatically simpler processors that could operate at very high speed, without expensive memory calls and prediction misses that make modern processors relatively slow.
The end result is that Groq’s chips are purely deterministic: instead of the high-bandwidth memory (HBM) used for modern GPUs or Dynamic Random Access Memory (DRAM) used in computers, both of which need to be refreshed regularly to function (which introduces latency and uncertainty about the location of data at a specific moment in time), Groq uses SRAM — Static Random Access Memory. SRAM stores data in what is called a bistable latching circuitry; this, unlike the transistor/capacitor architecture undergirding DRAM (and by extension, HBM), stores data in a stable state, which means that Groq always knows exactly where every piece of data is at any particular moment in time. This allows the Groq compiler to, in an ideal situation, pre-define every memory call, enabling extremely rapid computation with a relatively simple architecture.
It turns out that running inference on transformer-based models is an extremely ideal situation, because the computing itself is extremely deterministic. An LLM like GPT-4 processes text through a series of layers which have a predetermined set of operations, which is perfectly suited to Groq’s compiler. Meanwhile, token-based generation is a purely serial operation: every single token generated depends on knowing the previous token; there is zero parallelism for any one specific answer, which means the speed of token calculation is at an absolute premium…
…One of the arguments I have made as to why OpenAI CEO Sam Altman may be exploring hardware is that the closer an AI comes to being human, the more grating and ultimately gating are the little inconveniences that get in the way of actually interacting with said AI. It is one thing to have to walk to your desk to use a PC, or even reach into your pocket for a smartphone: you are, at all times, clearly interacting with a device. Having to open an app or wait for text in the context of a human-like AI is far more painful: it breaks the illusion in a much more profound, and ultimately disappointing, way. Groq suggests a path to keeping the illusion intact.
It is striking that Groq is a deterministic system running deterministic software that, in the end, produces probabilistic output. I explained deterministic versus probabilistic computing in ChatGPT Gets a Computer:
Computers are deterministic: if circuit X is open, then the proposition represented by X is true; 1 plus 1 is always 2; clicking “back” on your browser will exit this page. There are, of course, a huge number of abstractions and massive amounts of logic between an individual transistor and any action we might take with a computer — and an effectively infinite number of places for bugs — but the appropriate mental model for a computer is that they do exactly what they are told (indeed, a bug is not the computer making a mistake, but rather a manifestation of the programmer telling the computer to do the wrong thing).
I’ve already mentioned Bing Chat and ChatGPT; on March 14 Anthropic released another AI assistant named Claude: while the announcement doesn’t say so explicitly, I assume the name is in honor of the aforementioned Claude Shannon. This is certainly a noble sentiment — Shannon’s contributions to information theory broadly extend far beyond what Dixon laid out above — but it also feels misplaced: while technically speaking everything an AI assistant is doing is ultimately composed of 1s and 0s, the manner in which they operate is emergent from their training, not proscribed, which leads to the experience feeling fundamentally different from logical computers — something nearly human — which takes us back to hallucinations; Sydney was interesting, but what about homework?
The idea behind ChatGPT Gets a Computer is that large language models seem to operate somewhat similarly to the human brain, which is incredible and also imprecise, and just as we need a computer to do exact computations, so does ChatGPT. A regular computer, though, is actually the opposite of Groq: you get deterministic answers from hardware that is, thanks to the design of modern processors and memory, more probabilistic than you might think, running software that assumes the processor will handle endless memory calls and branch prediction.
In the end, though, we are back where we started: a computer would know where the bow and stern are on a ship, while a transformer-based model like Sora made a bad guess. The former calculates reality; the latter a virtual reality.
Imagine, though, Sora running on Groq (which is absolutely doable): could we have generated videos in real-time? Even if we could not, we are certainly much closer than you might have expected. And where, you might ask, would we consume those videos? How about on a head-mounted display like the Apple Vision Pro or Meta Quest? Virtual reality (my new definition) for virtual reality (the old definition).
Disclaimer: None of the information or analysis presented is intended to form the basis for any offer or recommendation. We currently have a vested interest in Apple and Meta Platforms. Holdings are subject to change at any time.
