Longreads
- In Quanta, the story of how mathematician and journalist Demian Goos tracked down a long-lost letter indicating that Georg Cantor plagiarized one of his most famous discoveries from Dedeking. One of the nice things about math is that it's apolitical—you're either right or wrong, regardless of who you are and how inconvenient your results might be to someone else. But the practice of collaborating on it and publishing results is political. Cantor was partly taking credit for someone else's work, but he was also sneaking in a way to publish it—the journal in which these results were published was run by Leopold Kronecker, who was personally annoyed with Dedekind over another paper. This is a great story about cheating among high-achievers. It has all of the ingredients: Cantor was talented, and it was plausible that he'd come up with something like this on his own. He had a reasonable excuse for leaving Dedekind's name off the paper. But if the two of them had published jointly, perhaps in a more obscure journal, history would have eventually given them credit. Instead, history eventually caught up with Cantor.
- Patrick and John Collison have released Stripe's 2026 annual letter. The main theme is that the world is getting faster and more extreme—more companies are being launched, they're growing faster, and the biggest are bigger than they've ever been. One reason is that historically, companies grew in their home market and then eventually expanded internationally, but the hurdle for operating in a new country, with a new currency, was a lot higher than for incremental expansion in their home market. But now, "The “domestic market” for a new generation of internet businesses is the internet itself." They're very bullish on agentic commerce, though that can be slightly qualified: the specific reason to expect it to be a big deal is that the more agents there are, the more agent-to-agent transactions there are, and these can be put together in arbitrarily complicated chains. Their definition of agentic commerce is also quite wide: anything from having your agent fill in a web check out form on your behalf for a pre-specified item to having an agent anticipate exactly what you need right before you need it and ordering it (the first part of which sounds a lot like Instagram ads wrapped in different verbiage).
- The University of Chicago Business Law Review has a piece from an anonymous contributor ( who is a "senior partner at a leading international law firm and an adjunct professor at a leading United States law school"), arguing that private equity-owned companies provide worse service at higher costs and make the economy more brittle. Which is a point plenty of other people have made before. But this piece also proposes a novel solution: that PE acquisition targets should have to put up some money in advance to pay for the cost of keeping the business around or remediating environmental damage, paying legal judgments and fines, etc. Limited liability is an incredibly useful social technology, but in the worst case it gives people a cheap call option that they might use irresponsibly. (For example, there's a company that buys up old natural gas wells, basically betting that the cost of plugging them or the fine for leaks will be low ($, Diff). Once they've made that bet, it makes sense for them to keep buying these assets—in a bad scenario, they're a zero no matter what, but in a better one they can be greater-than-zero by many more dollars. But that example also illustrates that this problem isn't unique to private equity, or to leverage, and that it applies differently to different industries. We should be very careful about writing over-broad rules to solve for industry-specific problems.
- Felix Stocker has a more economically coherent look at what AI will do to developer demand: lower cost per project means many, many more software projects, and more companies operating like Palantir rather than selling a standardized offering.
- Colin Gorrie tells a story, but every few paragraphs the language shifts a century back in time: we start with chatty bloggerese ("Not going to lie though: so far, it’s totally worth it.") then something a little trickier but still quite readable ("When I was firſt come to Wulfleet, I did not see the harbour, for I was weary and would ſooner go to the inn, that I might ſleep."), before we end up with a completely foreign tongue ("And þæt heo sægde wæs eall soþ."). A very fun exercise. It really is striking how many centuries of English literature remain accessible today. It's possible that LLMs will make this process even more fixed, and that for the rest of history, English will be written according to the rules that prevailed when we all generously shared so many tokens online. Or perhaps the evolutionary process will accelerate: if you can always translate something into a more readable form, will we still go to the trouble to parse Shakespeare?
- In this week's Capital Gains, a writeup of The Big Pair Trade. Shorting subprime-backed structured products through credit default swaps was a clever trade, but the even cleverer one was to buy the riskiest tranche, and turn the trade from a directional bet on housing to a cleaner bet on how correlated the real estate market had gotten.
- A Read.Haus reader asks if Bitcoin and AI are inversely correlated. Empirically, they are right now. Long-term, the answer is trickier. Both of them use datacenters and power as inputs, and some former Bitcoin miners turned out to be asset plays that were more valuable if they had different chips consuming that power. And the relationship between power use and underlying economics is different: crypto miners' energy demand is a function of crypto prices—bigger block rewards mean a higher breakeven price for running miners. In AI, power consumption drives the value creation, instead of following it. More training means better AI, more inference means it gets used in more contexts. But, in the longer-term view: agent-to-agent transactions will probably happen with stablecoins, and Bitcoin is a crypto-native reserve asset, so perhaps the story loops around to a more stable version of what it was in the heyday of Tether-driven liquidity creation: more credit expansion via stablecoins probably spills over into more demand for Bitcoin.
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Books
This Earthly Globe: A Venetian Geographer and the Quest to Map the World: For all their odd little failure modes, it's sometimes striking to think that large language models have such a comprehensive model of the world, created entirely from identifying and generalizing statistical patterns in text. But, in a way, it's a return to a very old tradition. In 1550, a Venetian publisher and public servant produced the first volume of Navigationi et Viaggi ("Navigations and Voyages"), the first comprehensive book about what you could see and where you could go throughout the entire world—it had accounts of trading voyages to Africa, it revived a more accurate translation of Marco Polo's memoir, details about what was happening back in Muscovy, and descriptions of North and South America.
You can't coherently write a history of geography, because every inhabited place has been implicitly mapped by whoever lives there. What you can write is a history of geography as it's practiced from one particular location: what would a 12-century Venetian think you'd see if you started in Constantinople and traveled east, and how would a 16-century traveler's view differ?
From a European perspective, these maps were gradually clouded by religious conflict. The rise of Islam put hostile land and naval powers between Europe and Asia, which meant that people were using some very old sources (Ptolemy, Herodotus) and otherwise relying on rumors. It's not as if the Ottoman Empire had a strong interest in sharing detailed maps and travel advice with their biggest rival in the Mediterranean.
They also had to deal with what's best described as an early example of a political deepfake: in the 12th century, the Eastern Roman Empire received a letter purporting to be from Prester John, who claimed to rule a vast and wealthy Christian kingdom somewhere in Central Asia. This letter got mixed up with news of the actual battle of Qatwan, in which the Seljuk Turks were defeated by Qara Khitai. Turks being known to be Muslim, and Qara Khitai being unfamiliar to Europeans, it didn't take much motivated reasoning for them to conclude that Prester John was real, and that if they launched yet another crusade, he'd surely show up with reinforcements. Which didn't happen, though a few centuries later the narrative had shifted from Central Asia to Africa, and European explorers did stumble on Ethiopia, which had been a Christian country since the 4th century.
Navigationi et Viaggi collected narratives from people who had often led more interesting lives than they personally preferred. al-Ḥasan ibn Muḥammad ibn Aḥmad al-Wazzān al-Zayyātī al-Fasī, for example, grew up in Muslim Granada, grew up in Fez, was kidnapped by Spanish pirates, and kept under house arrest by the Pope. He wrote extensively about North Africa (as it turns out, 16th century Fez had a lively red-light district). He eventually converted to Christianity, at least nominally, and took the name Leo Africanus. Marco Polo had a similarly tricky experience, where he traveled throughout Asia taking notes and striking deals, and ended up at the court of Kublai Khan, where he was simply too interesting and helpful to be given permission to get home. He did eventually manage to find his way home, and then ended up in another prison, in Genoa, where he collaborated with a novelist to publish his memoirs.
So the task for Giovanni Battista Ramusio, the author of the book, was to take an enormous store of information—memoirs, journals, private letters secretly leaked or stolen, nth-hand rumors, works that had gone through multiple rounds of translation, political screeds, stories written under varying kinds of duress, etc.—and weld them into a coherent narrative. Which is, interestingly enough, a task that starts out impossible but actually gets easier as the story gets more comprehensive. If Marco Polo's stories line up with other narratives about Central Asia, and if the hypothetical kingdom of Prester John was simply too big to miss, it had to be cut from the narrative. If the rhubarb described in a story about its point of origin sounds like the rhubarb that shows up in Venice, it's probably real. As you collect more comprehensive information about the world, even if it's mostly text, you get to a point where an internally-consistent story takes shape. And this book is a nice meta-book about how that process works. It’s a portrait of a very weird world, but one that’s in the process of becoming recognizable to us.
Open Thread
- Drop in any links or comments of interest to Diff readers.
- The US military has apparently judged itself capable of launching a two-front war against AI safety and Iran. Thoughts on either?
Diff Jobs
Companies in the Diff network are actively looking for talent. See a sampling of current open roles below:
- A pre-IPO, next-generation chemicals company that’s manufacturing the mission-critical inputs for a sustainable American reindustrialization is looking for a CFO to own the capital raising roadmap and allocation strategy end to end. Experience turning corporate strategy into a data-driven narrative and advising on late stage capital raises and/or IPOs preferred. (Remote, Houston)
- Ex-Citadel/D.E. Shaw team building AI-native infrastructure that turns lots of insurance data—structured and unstructured—into decision-grade plumbing that helps casualty risk and insurance liabilities move is looking for forward deployed data scientists to help clients optimize/underwrite/price their portfolios. Experience in consulting, banking, PE, etc. with a technical academic background (CS, Applied Math, Statistics) a plus. Traditional data scientists with a commercial bent also encouraged. (NYC)
- A leading AI transformation & PE investment firm (think private equity meets Palantir) that’s been focused on investing in and transforming businesses with AI long before ChatGPT (100+ successful portfolio company AI transformations since 2019) is hiring experienced forward deployed AI engineers to design, implement, test, and maintain cutting edge AI products that solve complex problems in a variety of sector areas. If you have 3+ years of experience across the development lifecycle and enjoy working with clients to solve concrete problems please reach out. Experience managing engineering teams is a plus. (Remote)
- Series A startup that powers 2 of the 3 frontier labs’ coding agents with the highest quality SFT and RLVR data pipelines is looking for growth/ops folks to help customers improve the underlying intelligence and usefulness of their models by scaling data quality and quantity. If you read axRiv, but also love playing strategy games, this one is for you. (SF)
- Ex-Bridgewater, Worldcoin founders using LLMs to generate investment signals, systematize fundamental analysis, and power the superintelligence for investing are looking for machine learning and full-stack software engineers (Typescript/React + Python) who want to build highly-scalable infrastructure that enables previously impossible machine learning results. Experience with large scale data pipelines, applied machine learning, etc. preferred. If you’re a sharp generalist with strong technical skills, please reach out. (SF, NYC)
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