What We’re Reading (Week Ending 20 July 2025) - 20 Jul 2025
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 20 July 2025):
1. Sweatshop data is over – Tamay Besiroglu, Matthew Barnett, Ege Erdil
Historically, the importance of data has been underrated in the field of AI. Decades ago, many assumed the key to AGI would come from devising the right “theory of intelligence”, which we could then implement by hand; the role of training data was sidelined.
Despite being trained on more compute than GPT-3, AlphaGo Zero could only play Go, while GPT-3 could write essays, code, translate languages, and assist with countless other tasks. The main difference was training data. AlphaGo Zero learned from Go games, whereas GPT-3 learned from natural language. This meant that while Google was playing games, OpenAI was able to seize the opportunity of a lifetime. What you train on matters.
We may soon witness a similar lesson if AI labs continue to scale up their models without similarly scaling up the quality of their training environments. Many have observed that pretraining is already saturating. GPT-4.5, while impressive in its own right, didn’t feel like a major generational leap in the way GPT-4 did over GPT-3.5.
The recent reinforcement learning with verifiable rewards (RLVR) paradigm seeks to revive progress by getting AIs to learn how to perform formally checkable reasoning inside contained environments. What we’ve seen so far is necessary for progress, but it is far from sufficient. Current methods will get us to the point where AIs can prove theorems and solve hard puzzles, but it won’t be enough to get models to deal with the open-ended nature of reality, where the quality of our actions cannot be so easily “verified” as either correct or incorrect.
To make progress, there’s no way around designing better rewards, and ultimately better RL environments.
2. Silk, Porcelain, Tea, Opium: 2000 Years of Trade Deficit with China – Tomas Pueyo
The West has had deficits with China for over 2,000 years, and they have had a massive impact on world history, from the opening of global trade routes, to the establishment of colonies, colonial policies, international wars, the emergence of nation-states, the politics of present-day China and the US…
…Romans loved luxury goods:
India, China and the Arabian peninsula take one hundred million sesterces1 from our empire per annum at a conservative estimate: that is what our luxuries and women cost us—Pliny the Elder, Natural History (77–79 AD).
Of these, silk was the biggest import from China. In 14 AD the Senate prohibited the wearing of silk by men!
To pay for it, Romans traded glassware, amber, wine, carpets, and other goods,2 but they didn’t make up for the value of what Romans bought from China. And in general, Chinese traders preferred money—mostly gold and silver—over other goods…
…Europeans obsessed about producing silk locally, but they didn’t know how to make it and didn’t have silkworms: China had protected its near-monopoly on silk for many centuries thanks to imperial orders to execute anybody caught trying to export silkworms or their eggs. The only way to succeed was by stealing them, and that’s precisely what two Christian monks did around 550 AD, risking their lives to smuggle silkworms hidden inside their canes.
This started silk production in the Eastern Roman Empire, which would slowly permeate through the rest of Europe.
This might have been the first time Chinese manufacturing prowess caused a trade imbalance in the West that required political intervention…
…Porcelain could only start reaching Europe in the 1500s,4 which is not a coincidence either: Porcelain was too heavy and fragile for overland routes, so it needed a maritime route to reach Europe. The Portuguese found a path to the Indies circumventing Africa just around 1500…
…Chinese porcelain was so much thinner, whiter and more translucent than local wares that European nobility really prized it…
…You know how nowadays Westerners design some products and then they send those designs to China for manufacture?
Porcelain is another example of China manufacturing products that Europeans craved, but again it didn’t need anything Europeans produced. Except for silver. So silver flowed from Europe to China. From 1500 to 1800, Bolivia and Mexico’s mines produced about 80% of the world’s silver; 30% of that eventually ended up in China!
Europeans hated that flow, as the silver disappeared as fast as it was produced, so they tried to stop it. Of course, the most incentivized were the countries who didn’t have access to either silver or trade with China. This is why the Italians tried to copy porcelain in the late 1500s with Medici porcelain, although they largely failed. By the early 1700s, Germans succeeded. A few years later, in 1712, the French Jesuit father Francois Xavier d’Entrecolles published the secrets of porcelain making in Europe, which he had read about and witnessed in China. In the following decades, the local production of porcelain increased and the import of Chinese porcelain fell…
…Tea’s ever-escalating trade imbalance with China became a serious economic problem, so much so that the British King George III sent an envoy to the Chinese Emperor to ask for more trade liberalization. These are excerpts of the Emperor’s response:
Our Celestial Empire possesses all things in prolific abundance and lacks no product within its own borders. There is therefore no need to import the manufactures of outside barbarians in exchange for our own produce. But as the tea, silk and porcelain which the Celestial Empire produces, are absolute necessities to European nations and to yourselves, we have permitted, as a signal mark of favor, that foreign merchants should be established at Canton, so that your wants might be supplied and your country thus participate in our beneficence.
So what did the British do to solve the trade imbalance? Two things. One is that the East India Company sent Scottish botanist Robert Fortune to China to purchase and export Chinese tea plants in the 1850s. This kick-started tea production in India, which grew over the following decades, reducing the share of Chinese tea consumed. Here we have, for the third time, a smuggling of Chinese production know-how to reduce trade imbalances…
…When the British conquered India8 in the late 1700s, they were very conscious about their trade imbalance with China, so they looked for any way to reduce it. They found the right tool in opium. They devised a plan to produce it in India and sell it in China. So the British drove local farmers in eastern India out of crop production and into poppies, from which opium is derived.
Then, the British introduced opium smoking in China…
…The Emperor Jiaqing noticed all this so he published an edict to stop it in 1810:
Opium has a harm. Opium is a poison, undermining our good customs and morality. Its use is prohibited by law.
But the government couldn’t enforce it. When the Chinese government finally cracked down on opium in 1839, the opium trade was paying for all the tea trade and then some, so the British reacted to protect the trade and attacked China; this was the First Opium War.
Britain won and bent China’s arm: It would be allowed to sell opium in China. It also took over Hong Kong.
There would be another Opium War, after which the British, and then other Westerners10 could reach far inland in China to sell opium. The deficit to China became a surplus. Over the following decades, opium addiction became widespread. By 1949, 4.4% of Chinese people were addicted. Local farmers replaced their crops with opium. Governments used opium taxes to finance themselves, and this lasted until the Communist Party had a strong enough chokehold on society and culture to finally ban opium.
This is what the Chinese call the century of humiliation, when China went from the richest and most advanced nation of the world to a dirt poor backwater.
3. The Codes AI Can’t Crack – Taras Grescoe
Since 2018, neural networks trained on cuneiform, the writing system of Mesopotamia, have been able to fill in lost verses from the story of Gilgamesh, the world’s earliest known epic poem. In 2023, a project known as the Vesuvius Challenge used 3D scanners and artificial intelligence to restore handwritten texts that hadn’t been read in 2,000 years, revealing previously unknown works by Epicurus and other philosophers. (The scrolls came from a luxurious villa in Herculaneum, buried during the same eruption of Mount Vesuvius that destroyed Pompeii. When scholars had previously tried to unroll them, the carbonized papyrus crumbled to dust.)
Yet despite these advances, a dozen or so ancient scripts — the writing systems used to transcribe spoken language — remain undeciphered. These include such mysteries as the one-of-a-kind Phaistos Disk, a spiral of 45 symbols found on a single sixteen-inch clay disk in a Minoan palace on Crete, and Proto-Elamite, a script used 5,000 years ago in what is now Iran, which may have consisted of a thousand distinct symbols. Some, like Cypro-Minoan — which transcribes a language spoken in the Late Bronze Age on Cyprus — are tantalizingly similar to early European scripts that have already been fully deciphered. Others, like the quipu of the Andes — intricately knotted ropes made of the wool of llamas, vicuñas, and alpacas — stretch our definitions of how speech can be transformed into writing…
…Cracking these ancient codes may seem like the kind of challenge AI is ideally suited to solve. After all, neural networks have already bested human champions at chess, as well as the most complex of all games, Go. They can detect cancer in medical images, predict protein structures, synthesize novel drugs, and converse fluently and persuasively in 200 languages. Given AI’s ability to find order in complex sets of data, surely assigning meaning to ancient symbols would be child’s play.
But if the example of Ithaca shows the promise of AI in the study of the past, these mystery scripts reveal its limitations. Artificial neural networks might prove a crucial tool, but true progress will come through collaboration between human neural networks: the intuitions and expertise stored in the heads of scholars, working in different disciplines in real-world settings…
…Ithaca was trained on ancient Greek, a language we’ve long known how to read, and whose entire corpus amounts to tens of thousands of inscriptions. The AI models that have filled in lost verses of Gilgamesh are trained on cuneiform, whose corpus is even larger: hundreds of thousands of cuneiform tablets can be found in the storerooms of the world’s museums, many of them still untranslated. The problem with mystery scripts like Linear A, Cypro-Minoan, Rongorongo, and Harappan is that the total number of known inscriptions can be counted in the thousands, and sometimes in the hundreds. Not only that, in most cases we have no idea what spoken language they’re meant to encode…
… Two of the greatest intellectual feats of the 20th century involved the decipherment of ancient writing systems. In 01952, when Michael Ventris, a young English architect, announced that he’d cracked the code of Linear B, a script used in Bronze Age Crete, newspapers likened the accomplishment to the scaling of Mount Everest. (Behind the scenes, the crucial grouping and classifying of characters on 180,000 index cards into common roots — the grunt work that would now be performed by AI — was done by Alice Kober, a chain-smoking instructor from Brooklyn College.)
The decipherment of the Maya script, which is capable of recording all human thought using bulbous jaguars, frogs, warriors’ heads, and other stylized glyphs, involved a decades-long collaboration between Yuri Knorozov, a Soviet epigrapher, and American scholars working on excavations in the jungles of Central America.
While the interpreting of Egyptian hieroglyphics is held up as a triumph of human ingenuity, the Linear B and Mayan codes were cracked without the help of a Rosetta Stone to point the way. With Linear B, the breakthrough came when Ventris broke with the established thinking, which held that it transcribed Etruscan — a script scholars can read aloud, but whose meaning still remains elusive — and realized that it corresponded to a form of archaic Greek spoken 500 years before Homer. In the case of ancient Mayan, long thought to be a cartoonish depiction of universal ideas, it was only when scholars acknowledged that it might transcribe the ancestors of the languages spoken by contemporary Maya people that the decipherment really began. Today, we can read 85% of the glyphs; it is even possible to translate Shakespeare’s Hamlet into ancient Mayan.
Collaborating across cultures and disciplines, and carrying out paradigm-shedding leaps of intuition, are not the strong points of existing artificial neural networks. But that doesn’t mean AI can’t play a role in decipherment of ancient writing systems. Miguel Valério, an epigrapher at the Autonomous University of Barcelona, has worked on Cypro-Minoan, the script used on Cyprus 3,500 years ago. Two hundred inscriptions, on golden jewelry, metal ingots, ivory plaques, and four broken clay tablets, have survived. Valério was suspicious of the scholarly orthodoxy, which attributed the great diversity in signs to the coexistence of three distinct forms of the language.
To test the theory that many of the signs were in fact allographs — that is, variants, like the capital letter “G” and “g,” its lower-case version — Valério worked with Michele Corazza, a computational linguist at the University of Bologna, to design a custom-built neural network they called Sign2Vecd. Because the model was unsupervised, it searched for patterns without applying human-imposed preconceptions to the data set.
“The machine learned how to cluster the signs,” says Valério, “but it didn’t do it simply on the basis of their resemblance, but also on the specific context of a sign in relation to other signs. It allowed us to create a three-dimensional plot of the results. We could see the signs floating in a sphere, and zoom in to see their relationship to each other, and whether they’d been written on clay or metal.”…
…A generation ago, most people were taught that writing was invented once, in Mesopotamia, about 5,500 years ago, as a tool of accountancy and state bureaucracy. From there, the standard thinking went, it spread to Egypt, and hieroglyphics were simplified into the alphabet that became the basis for recording most European languages…
…Monogenesis, the idea that the Ur-script diffused from Mesopotamia, has been replaced by the recognition that writing was invented independently in China, Egypt, Central America, and — though this remains controversial — in the Indus Valley, where 4,000 inscriptions been unearthed in sites that were home to one of the earliest large urban civilizations.
4. A 37,000-Year Chronicle of What Once Ailed Us – Carl Zimmer
On Wednesday, a team of scientists unveiled a new genetic chronicle, documenting the rise of 214 diseases across Europe and Asia over the past 37,000 years…
…The researchers examined the remains of 1,313 ancient individuals for the project. The large scale enabled the researchers to do more than just push back the earliest known occurrence of different diseases. They could also track the rise and fall of epidemics across centuries.
The oldest remains the researchers studied belonged to hunter-gatherers. Their bones and teeth contained a host of pathogens, such as hepatitis B, herpes virus and Helicobacter pylori, a stomach-dwelling bacterium.
“As far back as we go, humans have had infectious diseases,” said Eske Willerslev, a geneticist at the University of Copenhagen and an author of the new study…
…Initially, Dr. Willerslev and his colleagues assumed that they would see such diseases rise to prominence starting about 11,000 years ago. That’s when people started domesticating animals, from which new diseases could spread more easily…
…But the ancient DNA defied that expectation. The scientists found that plague and a number of other diseases jumped to people from animals thousands of years later, starting about 6,000 years ago. And those microbes did not jump into early farmers.
Instead, the new study points to nomadic tribes in Russia and Asia. Thousands of years after the dawn of agriculture, those nomads started rearing vast herds of cattle and other livestock.
Why diseases would have attacked those herders instead of earlier farmers, the scientists can’t say for sure. “We haven’t been able to come up with anything conclusive,” Dr. Willerslev said…
…The nomads expanded over the next few centuries across the steppes of Asia and eastern Europe. In that time, their pathogens thrived; the scientists frequently found several individuals in a single grave with DNA from plague or other diseases.
Those epidemics were so intense that they changed the genetic profile of the nomads. Last year, Dr. Willerslev and his colleagues found that the nomads experienced a spike in mutations that boosted their immune system and that may have helped them resist the diseases they contracted. But their active immune systems may have also attacked their own bodies, producing chronic diseases such as multiple sclerosis.
5. AI is killing the web. Can anything save it? – The Economist
Similarweb, which measures traffic to more than 100m web domains, estimates that worldwide search traffic (by humans) fell by about 15% in the year to June. Although some categories, such as hobbyists’ sites, are doing fine, others have been hit hard (see chart). Many of the most affected are just the kind that might have commonly answered search queries. Science and education sites have lost 10% of their visitors. Reference sites have lost 15%. Health sites have lost 31%.
For companies that sell advertising or subscriptions, lost visitors means lost revenue…
…Google has insisted that its use of others’ content is fair. But since it launched its AI overviews, the share of news-related searches resulting in no onward clicks has risen from 56% to 69%, estimates Similarweb. In other words, seven in ten people get their answer without visiting the page that supplied it…
…To keep the traffic and the money coming, many big content producers have negotiated licensing deals with AI companies, backed up by legal threats: what Robert Thomson, chief executive of News Corp, has dubbed “wooing and suing”. His company, which owns the Wall Street Journal and the New York Post, among other titles, has struck a deal with OpenAI. Two of its subsidiaries are suing Perplexity, another AI answer engine. The New York Times has done a deal with Amazon while suing OpenAI. Plenty of other transactions and lawsuits are going on…
…Reddit, an online forum, has licensed its user-generated content to Google for a reported $60m a year…
…The bigger problem, however, is that most of the internet’s hundreds of millions of domains are too small to either woo or sue the tech giants. Their content may be collectively essential to AI firms, but each site is individually dispensable. Even if they could join forces to bargain collectively, antitrust law would forbid it. They could block AI crawlers, and some do. But that means no search visibility at all…
…All of Cloudflare’s new customers will now be asked if they want to allow AI companies’ bots to scrape their site, and for what purpose. Cloudflare’s scale gives it a better chance than most of enabling something like a collective response by content sites that want to force AI firms to cough up. It is testing a pay-as-you-crawl system that would let sites charge bots an entry fee…
…An alternative is offered by Tollbit, which bills itself as a paywall for bots. It allows content sites to charge AI crawlers varying rates: for instance, a magazine could charge more for new stories than old ones. In the first quarter of this year Tollbit processed 15m micro-transactions of this sort, for 2,000 content producers including the Associated Press and Newsweek…
…One of Tollbit’s highest per-crawl rates is charged by a local newspaper.
Another model is being put forward by ProRata, a startup led by Bill Gross, a pioneer in the 1990s of the pay-as-you-click online ads that have powered much of the web ever since. He proposes that money from ads placed alongside AI-generated answers should be redistributed to sites in proportion to how much their content contributed to the answer. ProRata has its own answer engine, Gist.ai, which shares ad revenue with its 500-plus partners, which include the Financial Times and the Atlantic…
…As for the idea that Google is disseminating less human traffic than before, Mr Stein says the company has not noticed a dramatic decline in the number of outbound clicks, though it declines to make the number public. There are other reasons besides AI why people may be visiting sites less. Maybe they are scrolling social media. Maybe they are listening to podcasts.
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 Alphabet (the company behind AlphaGo Zero and Google). Holdings are subject to change at any time.
