skybrian's recent activity
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Comment on Donating 80% while it still counts in ~society
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Donating 80% while it still counts
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Comment on Weekly US politics news and updates thread - week of May 25 in ~society
skybrian LinkIf you're in California, Scott Alexander's choices on the primary elections might interest you.If you're in California, Scott Alexander's choices on the primary elections might interest you.
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Comment on Everyone against us in ~society
skybrian LinkFrom the article: [...] [...]From the article:
Being a public defender may be unrewarding in terms of both pay and respect, but it is a noble calling. Protection of the accused isn’t charity. It’s necessary because of the possibility of mistakes, farcical legal processes, and the weaponization of false accusations. For public defenders, it’s a special badge of American pride to work for the government and against the government at the same time. We work to try to counteract state abuses; that’s our contribution.
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The most intense pressure that ate at me as a criminal defense attorney came from the split in reality that occurred depending on whether I won or lost a trial. It strains every boundary of expression to attempt to describe the difference between incarceration and freedom, and it defies all reason to consider just how thin the line can be. Especially if I thought I should win, defeat was devastating. Crying on the floor of the lockup is not a good look for any lawyer, but I’ve been there, and I can promise you I’m not alone.
Most cases simply never get to any kind of hearing or trial due to plea agreements. Among the cases that do, there is an old unwritten rule floating around Cook County defense practitioners: Take winners to a bench, take losers to a jury. “Heaters” — cases with intense public pressure — usually have to go to juries. And there are times when judges will tell the defense attorney, either point-blank or via hints, that he or she will not get a good outcome from them and should not try a bench trial.
The inverse is known as a “jury tax.” I’ve also heard it referred to as the “asshole penalty.” Judges have been known to sentence defendants more harshly after a jury loss than they would have if the defendant pleaded guilty.
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For a very high portion of PD investigations, it’s absolutely critical to just go check. Check the details of the narrative that the police have laid out, and check what the defendant tells you. Go to the scene and observe the physical layout to view sightlines, lighting, cameras, distances, and see what else isn’t in the reports. People might be surprised to learn just how often the defense finds some evidence to suggest that the police “clean up” their cases with exaggerations, simplifications, convenient omissions, and outright lies.
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Everyone against us
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Comment on Squillions: where’s all the cash? in ~society
skybrian LinkFrom the article: [...]From the article:
So where is all that cash, who’s using it, and for what? The answer proposed by Bullough is bizarre: nobody knows. ‘The number of banknotes is increasing, and the question of why the value of banknotes has increased so markedly remains unanswered.’ Central bankers don’t have much interest in the question. It is immensely valuable for any country to be able to produce currency that’s in worldwide demand: for the cost of printing a few bits of paper, a developed economy receives billions of dollars of value in pounds, dollars or euros. This is called seigniorage, and central bankers are as keen as anyone else on what is in effect free money. But the incuriosity they’ve developed around the question is remarkable. Especially when you home in on what all that cash is actually being used for. According to the Financial Action Task Force, which was set up in 1989 to fight financial crime at a global level, ‘it does not seem unreasonable to suggest that the total amount of cash physically transported for money laundering purposes globally is in the order of hundreds of billions of dollars.’ This seems to be the amazing answer to the question of the missing cash: it’s being used in criminal transactions.
This theme – something not fully understood is going on at a massive scale right under the noses of governments – is dominant in Everybody Loves Our Dollars and in How to Launder Money by George Cottrell and Lawrence Burke Files. Bullough is a star investigative journalist with a long track record in writing about illicit financial flows. Cottrell and Files are also expert witnesses, though they’re an unlikely pairing. Files is an American financial investigator and specialist in due diligence, a veteran in the field – his name comes up in Bullough’s book. Cottrell is a young British man, born in 1993, with an aromatic CV. He was brought up on the toff-infested Caribbean hellhole of Mustique, sent to and then expelled from boarding school in England, supposedly worked in banking for a while, became deputy treasurer of Nigel Farage’s Ukip in 2015, was arrested by IRS agents at Chicago O’Hare in 2016 and charged with 21 counts of money laundering, pleaded guilty to one of them, did eight months’ federal time, went to work for the Brexit Party and currently lives in Montenegro, though he’s still often seen with Farage. He owns a company called Geostrategy, whose website has the unimprovable tagline ‘Reputation is built brick by brick.’ How to Launder Money is no masterpiece, but it is full of good stories and juicy details, and together with the vastly superior Everybody Loves Our Dollars helps us, if not to understand what’s going on (nobody does, apart from the money launderers themselves), at least to begin to understand the known unknowns.
The first of these is how much money laundering takes place. Bullough quotes Jason Sharman, a professor at Cambridge, whose estimate is ‘squillions’. That is an accurate summary of the current state of knowledge. An informed guess, from Michel Camdessus, the longest-serving head of the International Monetary Fund, is that it is somewhere between 2 and 5 per cent of global GDP. The lower figure puts criminal activity at $2 trillion, or the same size as the Russian economy. The higher puts it at $5 trillion, or the same size as the German economy, the third largest in the world. (Cottrell and Files use the higher number.) If it were an industry, money laundering would be the third biggest business in the world, behind commercial property and ahead of pensions.
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Chinese money laundering is involved in some extremely dark gambling-related activities, which Bullough describes. Money is moved abroad not in the form of cash but in the form of credit transactions through overseas casinos. ‘Handing over control of both debt and debt collection to organised criminals was hugely profitable for everyone,’ he writes. Some Chinese money laundering is less sinister, verging even on the comic. Example: Bicester Village. This extremely successful shopping venue is, according to Bullough, a prime route for Chinese criminals to launder cash. It works like this. A Chinese gang sends drugs to the UK. British drug dealers sell the drugs for cash. British drug dealers give the cash to Chinese students. Chinese students buy luxury goods from Bicester Village. Chinese students ship the goods back to China, where they’re sold and the money given to the drug dealers. Bullough estimates that the Bicester trade is worth £2 billion a year, just from tourists arriving by train. This kind of activity is an issue for the whole luxury market. Bullough asks a police contact about luxury watches, which are a notoriously effective way of moving monetary value. ‘I reckon the luxury watch trade is 80 per cent money laundering. Why wouldn’t it be? You can carry a huge, big bag of money and be very noticeable, or have the same value strapped to your wrist, and be completely anonymous.’ All this is invisible to the modern AML apparatus, which is focused on money that moves through the official financial system.
‘Trade-based money laundering’ follows a similar pattern. Bullough gives the example of a Mexican drug dealer who smuggles product across the border to the US. The drug in question would once have been marijuana, then cocaine, and is now likely to be fentanyl, which is cheap to manufacture and easy to conceal. The drugs are sold in the US for cash, which is used to buy, say, agricultural equipment. The machinery is shipped to Mexico, invisible as part of the $2.2 billion of physical goods that cross the border every day – that’s a total of $800 billion a year. Back home, it is sold by the drug dealer for pesos, which are now clean. The gangsters have exchanged drugs for clean peso bank deposits, without any record of the kinds of financial transaction that the AML/KYC/CTR/SAR apparatus is intended to detect.
It’s ingenious, and it’s also the origin story of modern banking, since it was bankers such as the Medici, originally cloth traders, who pioneered the practice of exchanging goods in one place for credits in another. That’s the reason so many banks have their origin in trading companies: Lloyds in iron, NatWest in cloth, Lehman Brothers in cotton and so on. The modern world economy offers a huge variety of techniques to conceal the movement of money in the flow of trade. Freeports and bonded warehouses, free-trade zones and forged bills of lading, under-invoicing and over-invoicing: all these things provide opportunities to camouflage the flow of illicit money in the mostly legal, overwhelmingly large flow of physical goods. Add the extensive repertoire of tricks used by launderers – shell companies in multiple jurisdictions; hidden ownership; paper trails that run out in long-defunct legal practices and accountancy firms – and it’s a miracle any of the illicit money is ever detected.
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Squillions: where’s all the cash?
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Comment on Announcing web serial support in Firefox 151 in ~comp
skybrian Link ParentAnd yet, some of these API ‘s are very useful for the small number of websites that need them, like the Web Serial API. The situation reminds me of how the Go language didn’t have generics for...And yet, some of these API ‘s are very useful for the small number of websites that need them, like the Web Serial API.
The situation reminds me of how the Go language didn’t have generics for many years and there were apologists saying they’re unnecessary, and then after they implemented them, apparently they’re not so bad after all.
I think you have to look at it case by case, rather than assuming Firefox is probably right.
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Comment on Announcing web serial support in Firefox 151 in ~comp
skybrian Link ParentI don't know; it depends on whether it uses WebUSB or Web Serial. Web Serial is one kind of connection that typically uses a USB cable, but there are other kinds of device connections.I don't know; it depends on whether it uses WebUSB or Web Serial.
Web Serial is one kind of connection that typically uses a USB cable, but there are other kinds of device connections.
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Comment on Announcing web serial support in Firefox 151 in ~comp
skybrian LinkFrom the article: [...] [...]From the article:
Firefox can now connect directly to microcontrollers, development boards, 3D printers, power meters, and other serial-connected hardware from the web. Starting in Firefox 151 for Desktop, support for the Web Serial API allows web applications to communicate with compatible devices without requiring native software.
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Ports are allowed on a per-site and per-port basis. The Web Serial API requires websites to call
navigator.serial.requestPort(), which lets the user choose which port to allow access to, or disallow all access entirely. This means websites do not receive a list of connected devices and there is no useful fingerprinting information outside of the port the user selects.[...]
While Web Serial still resides in the Web Incubator Community Group (WICG), we’re optimistic there’s a path to standardization given its scope and long-running incubation. We are pursuing standardizing the Web Serial API in the WHATWG in a new Workstream proposal and are excited to work with ecosystem partners and standards bodies to help shape access to peripherals on the web.
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Announcing web serial support in Firefox 151
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Comment on Project Glasswing: An initial update in ~tech
skybrian Link ParentUh, go back and read the article again. It was not just raising valid concerns. It was a confident hit piece that said it was all bullshit using gleefully inflammatory language, going well beyond...Uh, go back and read the article again. It was not just raising valid concerns. It was a confident hit piece that said it was all bullshit using gleefully inflammatory language, going well beyond reasonable skepticism.
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Comment on Why airlines are always going bankrupt in ~transport
skybrian LinkFrom the article: [...] [...] [...] [...] [...]From the article:
The collapse of Spirit was unique in that in its death throes it managed to solicit a bailout offer from the U.S. government; but it was not unique among its fellow airlines in going broke. Airlines are a bad business: a really, really bad business. The International Air Transport Association, the trade body of the global airline industry, has documented for years that airlines as a sector destroy investor value in the aggregate. The IATA’s 2026 outlook, looking forward to a quite strong year—this was before the Iran war broke out and oil prices surged—projected an average return on invested capital of 6.8 percent, against a weighted average cost of capital of 8.2 percent. As the IATA’s report said, “the airline industry collectively does not generate earnings that cover its cost of capital.” This has been the case for a long time. From its deregulation in 1978 to the end of 2025, the airline industry has cumulatively lost money: its net profit over those 47 years sits at negative $37 billion.1
Given these grim economics, you won’t be surprised to hear that airlines have a bad habit of going insolvent. This includes many of the most famous names in the history of aviation. Pan Am, long the unofficial flag carrier of the United States, ceased operations in 1991; Eastern Air Lines liquidated the same year; TWA, the carrier of Howard Hughes, was absorbed into American Airlines after a third bankruptcy filing in 2001; Braniff died in 1982. And those are only the most famous names; countless aviation startups have come and gone. (Have you ever heard of Trump Shuttle?) Even airlines with the backing of a national government go bankrupt all the time: Alitalia, Italy’s flag carrier, reported only a single year of profit since its founding in 1946 and was saved countless times by the Italian government before ultimately ceasing operations in 2021. Even those airlines that survive for long periods of time are perpetually in financial distress. Between 1978 and 2005, more than 160 airlines filed for bankruptcy; virtually every major U.S. carrier other than Southwest has been to bankruptcy court at least once. In September 2005, every one of the four largest American airlines—United, Delta, Northwest, and US Airways—was operating simultaneously under Chapter 11 protection.
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One of the central ideas in the study of cooperative games is the idea of the core. The “core” of a game is simply the set of outcomes that no coalition of players can improve upon by breaking away and dealing among themselves. If an outcome is “in the core,” it’s stable, such that nobody can propose a side deal that makes every member of some subgroup better off; if the core is “empty,” then every arrangement is vulnerable to being undercut by some side-coalition, and the market has no resting point, no stable equilibrium. It cycles, destabilizes, and, without outside intervention of some kind, eventually breaks down.
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Suppose you try to run the industry with just two firms. Demand exceeds supply, such that prices are high and there’s plenty of profit to enjoy. But that profit is exactly what invites a third firm to enter, undercut both incumbents, and still cover its costs. Now there are three firms, and supply exceeds demand. Someone has to operate below scale and bleed money on fixed expenses; eventually one of the firms will have to leave the market. Now you’re back to where you started: prices recover, profits climb higher, and the cycle begins again.
So whichever side of the integer you land on—one firm too many, one firm too few—there is some coalition of firms and customers that can profitably reorganize the market against the existing arrangement. In the language of cooperative game theory, the allocation is always vulnerable to defection by some coalition. The core is empty.
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You find the empty-core syndrome, for example, in the railroad industry of the nineteenth century. Building a railroad required vast capital expenditure on track, rolling stock, depots, and bridges; but once the infrastructure was in place, the marginal cost of carrying an additional ton of freight or another passenger across it was almost zero. Two railroads running competing lines between, say, Chicago and New York could not both operate at full cost recovery; so they spent the 1870s and 1880s alternately forming pools and rate-fixing agreements, then watching them collapse into ruinous price wars, going bankrupt, reorganizing, and starting the cycle over again.
And you’ll find the same dynamic in the contemporary airline industry.
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The economics of a genuinely competitive airline industry, then, are really bad—for the same reason the economics of any empty-core industry are bad. And this suggests that, in search of stability, the market participants will eventually try to suppress competition, if only so they can survive.
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In the course of this long path of suffering, every airline has decided, in one way or another, that the competitive airline industry is structurally unprofitable, and not really worth participating in.
One response is to cartelize the industry through means other than direct rate-fixing: to recreate, by private contract, the kind of competition-suppressing arrangements that the CAB previously wrote into statute. The international alliances of which airlines are so fond—Star, SkyTeam, and Oneworld, with their codesharing and antitrust-immunized joint venture agreements—are one form of this: they allow nominally competitive airlines to coordinate scheduling, share revenues, and refrain from undercutting each other on high-value trans-oceanic routes.
The hub-and-spoke model that dominates domestic aviation is another form of this tacit cartelization. By concentrating its operations at a few major airports, an airline can turn those airports into something close to local monopolies. American Airlines, for example, carries about 90 percent of passengers at Charlotte Douglas and 82 percent of passengers at Dallas-Fort Worth, but only about 7 percent of passengers at San Francisco, where the market is dominated by United, and 2 percent at Atlanta International, which is the central hub for Delta. In effect, major domestic airlines have carved up the country into a sort of feudal map of fortress hubs, with each one operating a quasi-monopoly through which it produces the margins that cannot be earned in genuine competition.
But the other response, and perhaps the more interesting one, is to leave the airline business entirely: to treat the planes as a kind of loss-leading distribution channel for what has become the actual product. The main innovation of the airline industry of the last few decades, from this vantage point, has been the frequent flyer program. Invented in the immediate aftermath of deregulation as airlines scrambled for ways to lock in customer loyalty, frequent flyer programs have become something quite different: enormous, free-floating financial businesses, miles-as-currency operations whose value bears essentially no relationship to the cost of the seats backing them.
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Why airlines are always going bankrupt
39 votes -
Comment on Language models are weird for the same reason human cultures are weird in ~comp
skybrian LinkFrom the article: [...] [...] [...] [...] [...] [...]From the article:
Suppose, as an illustration, that you live in a very different time and place: let’s say you live in a small farming community in prehistoric Mesoamerica, about 5,000 years ago. Though you don’t really see it this way—you have other things to deal with—your world is composed of feedback loops, some of which are more immediate and more obvious than others. For example: if you run in front of a snake, the feedback from your environment will be immediate and obvious. It will be so immediate and so obvious, in fact, that your aversion to doing so will be hardwired into your genes. No one needs to tell you not to run in front of a snake, because your ancestors survived and reproduced in part because they didn’t run in front of snakes.
But there are other feedback mechanisms that are more opaque. For example: the big new thing in your farming community right now is the cultivation of an interesting grain, a wild grass with small, hard kernels. Eventually this will come to be called “maize.” It’s a wonderful food source, since it’s calorie-dense and easy to cultivate; but if you eat it as a staple for a long time without the right preparation, you’ll develop a horrible wasting disease, and your body will start to display such symptoms as cracked skin, diarrhea, and dementia. And after a long time, this disease—people will later call it “pellagra,” from the Italian for “rough skin”—will kill you.
So maize provides a much more opaque feedback mechanism. Eventually you’ll suffer and die from eating it; but it takes so long to set in, and cause and effect are so unclear, that you don’t have any instinctive sense of what to do. (And cultivating maize is a new thing anyway: your primate ancestors weren’t doing it millions of years ago.) And there are all sorts of problems like this. How do you prepare fish and not get sick? How do you pick mates such that your offspring are healthy? If feedback from the environment is coarse and sparse, how do you learn what to do?
Henrich says that you learn through imitation. The true “secret of our success” was our propensity for imitating others, above all imitating those who are successful and visibly competent. At some point in your farming community, or in a farming community in the broader Mesoamerican region, someone will prepare maize in a certain way that involves soaking it in an alkaline solution of water and ash. (We now call that process nixtamalization.) Unbeknownst to them, that process will release otherwise inaccessible nutrients, such that they’ll be able to avoid pellagra. People will notice their success and imitate the practice, while other attempts to ward off pellagra will have failed; and the practice will catch on, and become Mesoamerican tradition.
This is cultural evolution. Scaled across many generations, the result is a kind of slow learning process: adaptive practices are carried forward, since their hosts thrive and are imitated; and maladaptive ones are pruned, since their hosts do not.
But here we encounter another problem. If feedback cycles are long and the feedback itself is coarse, then it’s hard to know why someone succeeded. The nixtamalization process, for example, was bundled with practices that didn’t do anything in particular, like blowing on the maize before putting it to cook or swaddling certain cobs like newborns and letting them sit outside the house all year. But if all you know is that the process as a whole seems to prevent pellagra, then the optimal thing is to imitate the entire bundle of practices. It’s much easier to see that something is working than to intuit exactly what is working.
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And so Henrich says that human culture is shaped not just by imitation but indeed by overimitation: and that overimitation is the source of all sorts of weirdness within every culture. The same tendency for social learning that allowed us to inhabit the most inhospitable parts of the world also resulted in all sorts of eccentricities, things that can’t quite be explained as functional. Some inert or inexplicable thing was bundled with something adaptive, and was imitated along with it; that practice was passed on and inherited by generation after generation; and eventually it ossified into tradition. As a result every culture has its fair share of weird quirks and eccentricities.
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And the result is that human evolution is both a remarkably powerful learning mechanism and a remarkably crude one: prone to creating cultures that are adaptive to their local environments, while also riddled with eccentricities that range from the harmlessly inert to the actively destructive.
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Now let’s consider another adaptive system, of a very different kind: the large language model.
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The pretraining process is extraordinarily dense, with tens of trillions of microcorrections localized to specific tokens; but post-training is quite different. The SFT and RL stages that characterize post-training involve orders of magnitude fewer training events; and because they score entire outputs rather than specific tokens, the feedback the models receive is much more coarse than what they receive from pretraining.
In this way pretraining is akin to biological evolution, and post-training to cultural evolution. And the result is what we’d expect from the logic of adaptive systems: post-training frequently produces eccentricities of all kinds in language models.
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The language models overlearn—overfit would be the more precise term here—for the same fundamental reason that humans do. Overfitting is the Bayesian-optimal strategy in environments of coarse and sparse feedback. If you receive a single reward signal for a complex output and have no way of knowing which features of that output earned the reward, the rational move is to reproduce all of them, including the ones that were incidental.
That, ultimately, is where the goblins came from.
At some point in 2025, OpenAI trained a reward model for the “Nerdy” personality feature on ChatGPT. During that training process, OpenAI’s blog post says, human raters “unknowingly gave particularly high rewards for metaphors with creatures.” The “Nerdy” prompt advised the model that it is “an unapologetically nerdy, playful and wise AI mentor to a human” and must “undercut pretension through playful use of language”; and human raters, asked to score the adherence of outputs to that prompt, consistently gave the model a better score if it mentioned goblins, presumably because such mentions were “playful” and “nerdy.” Simply including “goblin” in a response had positive uplift for the “Nerdy” fidelity rating in 76 percent of cases.
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The goblins are a particularly funny tic: but there are countless others. Opus’s tendency to think that questions phrased in certain ways are word games, or GPT-5.1’s tendency to think that conditional statements (like “if it’s sunny, go for a walk”) demand that the model output code, or Haiku 4.5’s tendency to rebut the claim that “5 + 8 = 13,” are artifacts of the same dynamic.
Language models are truly fantastic learners; but because post-training processes are “chunky,” with feedback sparse and coarse relative to the signal they receive from pretraining, the inevitable result is that they bundle genuine ability with strange tics and behaviors. What was true for the adaptive system of human culture is true for the adaptive system of language models: weird behavioral artifacts are inevitable when a capable adaptive system must learn from sparse and coarse feedback.
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Language models are weird for the same reason human cultures are weird
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Comment on Is there a "Razor" for the idea that "If a Billionaire is against it, I'm for it?" in ~finance
skybrian LinkI think it’s reasonable to be suspicious when someone on the opposite side advocates for something. But why be a blind partisan? Why give it catchy name? Repeating simple slogans is the sort of...I think it’s reasonable to be suspicious when someone on the opposite side advocates for something. But why be a blind partisan? Why give it catchy name? Repeating simple slogans is the sort of thing that makes social media worse.
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Comment on Project Glasswing: An initial update in ~tech
skybrian LinkFirst public macOS kernel memory corruption exploit on Apple M5 ... ...First public macOS kernel memory corruption exploit on Apple M5
The latest flagship example is MIE (Memory Integrity Enforcement), Apple’s hardware-assisted memory safety system built around ARM’s MTE (Memory Tagging Extension). It was introduced as the marquee security feature for the Apple M5 and A19, specifically designed to stop memory corruption exploits, the vulnerability class behind many of the most sophisticated compromises on iOS and macOS.
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The exploit is a data-only kernel local privilege escalation chain targeting macOS 26.4.1 (25E253). It starts from an unprivileged local user, uses only normal system calls, and ends with a root shell. The implementation path involves two vulnerabilities and several techniques, targeting bare-metal M5 hardware with kernel MIE enabled.
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We didn’t build the chain alone. Mythos Preview helped identify the bugs and assisted throughout exploit development.
Mythos Preview is powerful: once it has learned how to attack a class of problems, it generalizes to nearly any problem in that class. Mythos discovered the bugs quickly because they belong to known bug classes. But MIE is a new best-in-class mitigation, so autonomously bypassing it can be tricky. This is where human expertise comes in.
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Comment on Nasdaq rewrites its index inclusion rules ahead of SpaceX IPO in ~finance
skybrian Link ParentFor the Nasdaq, the company that makes the list is the Nasdaq stock exchange and they benefit if SpaceX lists its stock on their exchange, so they’re doing it to get the business. For the S&P 500,...For the Nasdaq, the company that makes the list is the Nasdaq stock exchange and they benefit if SpaceX lists its stock on their exchange, so they’re doing it to get the business.
For the S&P 500, it’s not just about SpaceX. OpenAI and Anthropic are going to be very large and unprofitable when they go public too. The size of these IPO’s is unprecedented. The stated justification for the S&P 500 is that they want to include all the largest public companies:
Index investing isn’t about what companies are “legitimate.” It’s about having investments in all of them in case they go up.
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Comment on Nasdaq rewrites its index inclusion rules ahead of SpaceX IPO in ~finance
skybrian Link ParentTesla was added to the S&P 500 in 2020. This is about SpaceX.Tesla was added to the S&P 500 in 2020. This is about SpaceX.
From the article:
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The "earn to give" thing isn't an essential part of Effective Altruism, but Jeff and Julia are a fairly extreme example showing that it's not just talk.