Astral Codex Ten

Microsoft

23 min read

Microsoft

Article

Microsoft is a recurring brand in the Astral Codex Ten archive, appearing 6 times across 6 issues between September 22, 2022 and March 03, 2026. The archive places it in contexts such as “The last big antitrust case involved Microsoft”; “before Microsoft and Amazon were a thing”; “globally respected corporations like Microsoft and Coca-Cola”. It most often appears alongside Amazon, Amazon, effective altruism.

Metadata

  • Category: Brands
  • Mention count: 6
  • Issue count: 6
  • First seen: September 22, 2022
  • Last seen: March 03, 2026

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

Highlights From The Comments On Billionaire Replaceability
September 22, 2022 · Original source
The last big antitrust case involved Microsoft. When IBM got sick of antitrust fights, they decided to outsource the operating system for their PCs. This was like throwing a monopoly bouquet at a wedding and Bill Gates was the bridesmaid who jumped highest and snatched the prize. His plan was to leverage this operating system monopoly into an internet monopoly, and the scheme was working before the Clinton administration sued. The reason I am writing this on Substack and not some Microsoft comment board is because of an antitrust lawsuit.
I’m still not sure about this line of thought. How is this situation? Do we think Mark Zuckerberg wouldn’t have founded Facebook, or Bill Gates Microsoft, if he could only get $1 billion? Can people really tell the difference between $10 billion and $100 billion? Has Jeff Bezos even spent $10 billion?
The Question Of Separatism
May 19, 2023 · Original source
When people argue against separatism, they often tout the benefits of being large. A Canada that would be split in two would mean smaller markets, and a weaker political counterweight to the United States. (Not to be mean to Canadian readers, but this argument seems delusional to me — I don’t think Americans currently see Canada as a political counterweight of any significance.) It would certainly be less prestigious. Large size, Jacobs says, is associated with power, and we admire power. We love slogans like “unity makes strength.” But after the medium-sized country of Sweden-Norway became the two smaller countries of Sweden and Norway, they both did well. Small size is less powerful, but it has its own advantages, such as nimbleness and ability to fail non-catastrophically. Small size also allows more diversity in cultural and economic matters, and here Jacobs waxes philosophical, pointing out that favoring diversity over uniformity is a recent, post-Enlightenment idea that has not yet been fully embraced in politics. We can see analogs everywhere. Europe, split into numerous small countries from the Middle Ages onward, became far more advanced than China, which has been unified more often than not. The city-states of ancient Greece and Renaissance Italy are seen as golden ages of Western civilization, even if they weren’t part of larger political units and therefore constantly went to war with one another. In business, large companies are impressive and powerful, but people always complain that Google or Microsoft have become stagnant and that the best place to work is tiny startups of about 2 cofounders and 4 employees. In biology, humans are more successful than numerous larger animals, and in terms of raw numbers, small animals like rats or insects are the most successful of all. Jacobs’s point isn’t that smaller is always better. Her point is that the converse statement, “bigger is always better,” is false — despite how intuitive it feels for political entities. Just like we don’t view a small nation like Switzerland or Singapore as a failure of unity, we (and in particular, Canadians) shouldn’t see the secession of a place like Quebec, if it’s done peacefully and democratically, as a failure either. Still, some people in online reviews of the book complain that this argument is a bit thin, especially considering that it serves as the foundation for the later chapters (which are more directly about late 1970s Quebec politics). Sure, small is beautiful, but large states are great for stability, peace, markets, whatever. If the potential benefits of small national size are Jacobs’s strongest argument, then we can breathe a sigh of relief and go back to agreeing that separatism is bad. Pointing out the widespread bias in favor of unified political entities does seem valuable to me, but okay, fair enough. Does Jacobs have deeper reasons why separatism might be a good idea in general? Yes, and for this we go back to the second half of Cities and the Wealth of Nations. Why Nations and Empires Fail Our breathing rate is regulated through a feedback mechanism. Too much carbon dioxide in the blood, or too little oxygen, and the brain stem commands the diaphragm to accelerate breathing. Once the levels are back to normal, the brain stem receives this feedback and slows breathing down again. Now, Jacobs asks, imagine an impossible creature: ten people, all doing their own thing, but whose breathing is somehow regulated by a single brain stem. The feedback the brain stem receives is a consolidated average of everyone’s carbon dioxide and oxygen levels, and the breathing rate the stem decides on is applied to all ten people, regardless of whether they’re sleeping or playing tennis. This, to put it mildly, wouldn’t work. This creature is an analogy, representing a nation. The ten people are its individual cities, and the breathing rate is the cities’ economies. If it sounds like a stupid analogy, that’s because it is: “I have had to propose a preposterous situation,” writes Jacobs, “because systems as structurally flawed as this don’t exist in nature; they wouldn’t last.” Nor do they exist in machines we design; they wouldn’t work. But “nations, from this point of view, don’t work either, yet do exist.” The feedback mechanism that fails to work properly in a nation is currency. A currency always fluctuates according to the exports and imports of the area where it circulates. Let me use the Republic of Venice and its ducat as a toy example, because the coins look nice: Whenever Venice produces something (like salt) and sells it abroad, foreigners need ducats to buy the exports, so the demand for ducats increases. When Venice buys something from abroad, it needs to use foreign currencies, so the demand for ducats decreases. Add up everything that Venice exports and imports, and you get either a trade surplus (more exports than imports) or a trade deficit (more imports than exports), which determines the value of the ducat relative to other currencies. In both cases, a negative feedback loop restores balance over time, just like our brain stem does with carbon dioxide levels. A trade surplus, and therefore a strong ducat, means that when foreigners want Venetian salt, it’s expensive. So Venice’s exports decrease, while imports increase, since Venetians can use their valuable ducats to buy stuff cheaply from abroad. Conversely, a trade deficit makes exports a bargain for foreigners and imports expensive for Venetians. This feedback loop is great. It’s exactly what a city needs to trigger the crucial import replacement process. When exports decrease and a trade deficit begins (maybe because Constantinople found a cheaper source of salt somewhere else), the weak ducat means that Venice is less able to afford the resources and manufactured goods it used to import. The people of Venice don’t want to have less of those goods, though, so they figure out ways to produce some themselves — that is, they do import replacement. Later they will be able to export the output of the newly expanding industries too, strengthening the ducat and continuing the cycle. Currencies, Jacobs explains, function as automatic tariffs (to protect local industry from foreign imports) and automatic export subsidies (to encourage local industry to export). They are “automatic” because of the feedback mechanism. Just like an accelerated breathing rate, they take effect exactly when they are needed — and no longer. … Or so they should, except that import replacement, as we discussed, is a city process. Whereas most currencies are national or supranational. National currencies work well for city-states, like the Republic of Venice or today’s Singapore. But in large nations, which, remember, are not the fundamental unit of economic life, they mess everything up. Take a city like Detroit. When Detroit’s exports (primarily cars) decrease, Detroit gets no feedback about this, because its currency is the United States dollar, and the United States dollar’s value depends on much more than Detroit. It depends on other cities whose foreign exports might be increasing at the moment. And on rural regions that are selling resources like oil abroad. Also, trade between Detroit and other cities that use the United States dollar — i.e., American cities — is structurally unable to provide any feedback whatsoever. So Detroit doesn’t get the signal that it should buy less stuff from other cities and replace the missing imports with local production. Instead, it just declines. Jacobs hypothesizes that this issue of national currencies is at the root of every large country’s economic troubles. It is why nations and empires always centralize everything into one large city, whether that’s Paris, London, Tokyo, or Toronto, or ancient Rome: that city, being the largest, is simply the only one for which national-level currency feedback works fine. The rest of the nation or empire, then, declines. But of course, nations and empires don’t accept this. They care about the economic well-being of their peripheral regions, sometimes out of genuine concern for the people there, sometimes out of fear that they rebel or hold independence referendums. So nations and empires will embark on every possible solution to reverse the decline. All of their solutions will look like good ideas at first, and yet fail at helping the peripheral regions. Worse, these solutions will weaken the cities, thereby destroying the only real wealth of the country and bringing untold hardship for everyone. Eventually the nation or empire will disintegrate, as nations and empires always do, and always will. Jacobs calls these false solutions transactions of decline. She identifies three types, and, content warning, you might not like some of them depending on your political sensibilities. Sustained military production is a transaction of decline. Permanent military bases and garrison towns are a special kind of settlement: they import a lot and export nothing. Superficially, producing weapons and supplies for the military seems like a good deal for some cities — Jacobs gives the example of Seattle, which, before Microsoft and Amazon were a thing, depended mostly on making military aircraft. But because nobody in a military base ever tries to replace those weapons and supplies with their own production, the trade is sterile in terms of economic development. In a sense, the wealth is slowly “drained” from cities. Large empires are especially prone to this: eventually all of their wealth is destined to the military just to keep the empire together.
Inline links: https://substackcdn.com/image/fetch/$s_!YeXj!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6fe681e6-b571-4f4c-aa90-313f77fc1dbb_750x359.png
Sustained military production is a transaction of decline. Permanent military bases and garrison towns are a special kind of settlement: they import a lot and export nothing. Superficially, producing weapons and supplies for the military seems like a good deal for some cities — Jacobs gives the example of Seattle, which, before Microsoft and Amazon were a thing, depended mostly on making military aircraft. But because nobody in a military base ever tries to replace those weapons and supplies with their own production, the trade is sterile in terms of economic development. In a sense, the wealth is slowly “drained” from cities. Large empires are especially prone to this: eventually all of their wealth is destined to the military just to keep the empire together.
Assistant Dictator Book Club: America Against America
June 07, 2023 · Original source
On one side is the good America that Wang admires. This is the America that grew from a bunch of tiny colonies under attack by Indians and Redcoats into a technological and economic superpower. It won World War II and the Cold War, and outlasted Maoism in China. It built the Panama Canal, the interstate highways, and the Space Shuttle, but also globally respected corporations like Microsoft and Coca-Cola. Its people are effortlessly patriotic, self-assured, and committed to their Constitution and ideals. Its government runs on meritocracy and everyone respects talent regardless of its social class.
Americans (especially within a libertarian or neoliberal tradition) tend to think of these as two sides of the same coin. Freedom leads to innovation. The downside of a society where Bill Gates can drop out of Harvard and create Microsoft without anyone’s permission, is a society where someone can drop out of high school and create a drug gang. We’re committed to the Constitution because it guarantees us the right to build a good life however we envision that term.
Your Book Review: The Laws of Trading
July 21, 2023 · Original source
We need a framework for thinking about these trades. Lebron’s first law states that we must know ourselves and our motivations for trading before we trade. We tell ourselves many stories, but someone with intellectual honesty – the person with the most alignment between their motivations and actions – will take money from the person who didn’t go through the work to understand their own motivations. There is a reason that Citadel and other hedge funds pay millions of dollars to trade with retail. They know why they are trading: to maximize profit. And the dilettante who “trades for fun” will be eaten alive by a firm with a much better model of a) the world and b) the dilettante themself. Why did I write this book review? To test my intellectual mettle. I could easily have posted this book review elsewhere, but no, I wanted to see how I stack up against other ACX Book Review contest participants. Similarly, this is often the reason people get into trading. One motivation that Lebron explicitly calls out is intellectual validation. You can toil in obscurity for years as an academic. But in trading, there is a quick feedback loop. If your P&L showed $10M last year and the guy sitting next to you showed $8M, you have demonstrated who is “cleverer” and established a clear hierarchy. What lessons here transfer to our daily lives? Like Paul Graham, Lebron encourages us to keep our identities small. He gives the standard decision-making advice to write down your framework and reasoning for why you made a decision at a specific point in time, in order to avoid biases after the fact. This section of the book contained good general advice, but nothing that will be particularly new for the median ACX reader. 2: Adverse Selection You’re never happy with the amount you traded. Now we start to get into the good stuff. Financial markets are an information aggregation mechanism, relying on multiple parties’ beliefs and recursive Bayesian updates of an individual actor’s beliefs based on the beliefs of others2. Market mechanics demonstrate Bayesian beliefs in action. The following quote is quite long, so skip over it if you don’t want to dive deep into the psychology of making a market. I retained it in full because this is quite literally the best description I’ve ever seen of the Bayesian dance between two market makers: “You are a market maker in South African mining companies. Through years of effort and continual improvement, you have built a trading model for the company Veldt Resources. You walk into work one day, ready to set up your trading for the day. It's a stock that doesn't trade much, and usually there are only two market makers: you and another (we'll call her Jo). She's sharp, and she competes well to trade against customer orders that come in. Your model has Veldt valued at 54.35 ZAR (South African rand). You're going to start quoting the stock, so you're about to turn on your machine making a market 54.25 - 54.45 (1000x)3. Before you turn on, you check the current market and notice that Jo has already turned on and she's making her market 53.50 - 54.00 (2000x). If you were to turn on your machine, your market would cross her market, and you would buy 1000 shares from her for 54.00. You now need to make a decision. Whose model do you believe more, yours or Jo's? If you believe yours, you should turn on your machine, trade at 54.00, and expect to make money. If you believe Jo's model, you should adjust your own model parameters to match her market and turn on, making a similar market to hers. What to do? As with many dichotomies, this is a false one. And as with many decision processes, Bayesian reasoning lights the way… …Jo presumably believes Veldt is worth around 53.75 (the average of her bid and offer). But how confident is she in her belief? The width of her market can give you a clue. It's 0.50 ZAR, whereas yours was going to be 0.20 ZAR wide. All other things equal, you should think that Jo only has 40% (0.20/0.50) of the confidence in her fair value as you do in yours. On some absolute scale of confidence, you can say you had a belief-strength of 100 in your fair value of 54.35 (before seeing Jo's market), and Jo has a belief-strength of 40 in her fair value of 53.75 (before seeing yours). And it turns out the weighted average of these two beliefs is quite a reasonable way to combine them: 100/140 * 54.35 + 40/140 * 53.75 = 54.18. Your updated fair value, having seen Jo's market, is thus 54.18 ZAR. This procedure is a quick, heuristic, and reduced version of Bayesian belief-updating, and a good reference on the subject is A.L. Barker's 1995 paper. After updating, you now believe that the stock is worth 54.18. Assuming your trading costs, risk limits, and return requirements are satisfied, buying 1000 shares for 54.00 is a good trade. Naively, you might just put out a 54.00 bid for 1000 shares, trade with half the 2000 share offer, and hope to collect your expected-value ZAR. In practice, however, you might be able to make even more. If Jo is making a 0.50 wide market, maybe she'd be willing to sell lower than 54.00. It's conceivable that if you put out a 53.90 bid for 1000 shares, Jo will sell at that price, and you collect an extra 100 ZAR! Of course, Jo could react differently. She could see your bid and use that information to change her market, in much the same way you did before turning on. These are difficult decisions, ones where experience with the product and the market make a big difference in being able to eke out a little extra edge. Let's play it safe however and pay 54.00 for 1000 shares. You trade, and Jo reacts by immediately canceling her market. This is not an uncommon occurrence in illiquid stocks, especially in emerging markets, so you're not too surprised. You wait a couple of minutes, mentally visualizing Jo in front of her six monitors, evaluating her trade and her model. Finally, she turns back on. Her new market is 53.50 - 54.05 (10000x)! You reason that Jo has seen that someone (you) disagrees with her valuation of the stock. Jo is a good Bayesian like you, and so she has incorporated that information into her model and updated her beliefs about the fair value of the stock. Her updated belief is that she now wants to sell even more stock, at a marginally higher price. Clearly, she almost entirely discounts the information you've communicated to her with your trade. How should you react? It seems fairly clear that, assuming Jo is not a crazy or incompetent market maker (usually a fair assumption), your trade was a bad one. You bought 1000 shares, when in retrospect, you would have wanted to buy much less, probably zero. Imagine instead that Jo had turned back on with a market of 54.00 - 54.50 (1000x). Her reaction now clearly indicates the information you gave her with your trade is valuable, and she has adjusted her beliefs accordingly. Your trade was probably a good one. Don't you wish you had bought all 2000 shares on offer? No matter what Jo's reaction is, you will be unhappy with your trade. Note that Jo will be unhappy too, since retrospectively she should have either made her initial market bigger or smaller. Welcome to the joyous world of trading!” Whether or not you make money, you have regrets! If you profited, you could have made more. If you lost money, you shouldn’t have made the trade at all. Like death and taxes, you can’t avoid adverse selection. Lebron continues to highlight a few areas of trading that have adverse selection problems. First, IPOs. If you buy the stock in an IPO, you expect the share price to “pop” on the first day of trading. However, if others also have this expectation, the round will be oversubscribed. You can only get the quantity of shares that you bid for when the market doesn’t think the shares will go up. So if you are able to get the shares that you want, the IPO is likely a dud. See also: Venture Capital fundraising. Second, powerful entities that change the rules of the game while you’re playing. Exchanges nullify “erroneous” trades. Brokerages limit buying. Anyone who tried to buy GameStop stock on Robinhood on January 28, 2021, knows this form of adverse selection all too well. Lebron also highlights “special trades”, in which you should throw the “normal rules” out of the window. This advice generalizes to other areas of life: “The normal rules do not apply. If you remove yourself from our usual routine, if you think hard and clearly about the specific situation, maybe you can do something good. Perhaps even great. Others will be paralyzed by inaction, but perhaps you won’t be. Crises can be opportunities.” 3: Risk Take only the risks you’re being paid to take. Hedge the others. In trading, as in life, you can make the right call in expected value terms but still lose due to randomness. Some of that randomness is avoidable. Some of it is not — and can be accounted for by hedging. Here, Lebron encourages us to rely on multiple risk measures and actively seek to understand the risks that we might be subject to. That’s all well and good in the world of finance, with derivatives contracts. But how might this apply in other areas of life? If you work for a publicly traded company and are compensated in stock, sell your shares as soon as you receive them. This is not because I don’t expect the share price of Microsoft/Meta/Apple/etc. to go up. The stock may very well outperform the market. But you are not being compensated for the added risk that you take on here. Your employment prospects at Microsoft/Meta/Apple/etc. are highly correlated with the share price. When the share price is down is when layoffs happen. Former Enron employees can chime in here. Similarly, it makes sense to hedge anything that is outside of your control. Let’s say you’ve decided the crypto bear market of 2023 is a great time to start a new crypto company. Your success depends on things within your control, such as: Your idea
Inline links: pay millions of dollars to trade with retail, keep our identities small, 2, market makers, 3
Son Of Bride Of Bay Area House Party
December 12, 2023 · Original source
It has been three weeks since Sam Altman was fired, but the conversation won’t move on. “What did Ilya see?” asks your Uber driver, on the way to the airport. “What wasn’t he consistently candid about?” ask people on the street, as you walk your dog. “What was Adam D’Angelo’s angle?” asks the cop, as he writes you a ticket. “Was the Microsoft move just a bluff?” asks the robber at gunpoint, as he ransacks your apartment.
“I heard Q-star broke AES-192 encryption, Ilya used it to read Sam’s credit card transactions, and he found Sam spent all the Microsoft money on Aella’s OnlyFans,” says a woman, in a hushed whisper.
Mantic Monday: Groundhog Day
March 03, 2026 · Original source
Framed this way, the Pentagon’s actions sound devastating. Anthropic relies on compute to train and run its AIs. Most of this compute is in data centers owned by Amazon, Google, and Microsoft. At least Amazon and Microsoft have contracts with the US military. If they had to drop Anthropic, it would make it impossible for the company to stay a frontier AI lab.
The lawyers who weighed in seem to think that Anthropic’s interpretation of the law is correct, and Secretary Hegseth’s interpretation confused. In some situations, this might be cold comfort - how much does it help to be right about the law when the government is wrong? But in this case, it probably helps a lot. Amazon, Google, and Microsoft are all big Anthropic investors - each owns about a 10% stake - and have multi-billion dollar AI compute contracts. Together, the three tech giants must have at least $100 billion riding on Anthropic’s success. They also have good administration connections and great lobbyists, and even Hegseth isn’t stupid enough to pick fights with them all at once. So probably they send their lobbyists to have a talk with Hegseth about what the “supply chain risk” designation actually entails, Hegseth enforces the letter of the law, and Anthropic is barely affected. At least this is the story the prediction markets are going with: