File: A Falcon 9 rocket stands in the launch position at Space Launch Complex 40 (SLC-40) at Cape Canaveral Space Force Station ahead of the planned liftoff of the Starlink 6-61 mission on Oct. 22, 2024. Image: Adam Bernstein/Spaceflight Now
The expansion of SpaceX’s Starlink network of internet relay satellites will continue Monday with a Memorial Day launch from Cape Canaveral Space Force Station.
The Starlink 10-47 mission will add another 29 Starlink V2 Mini Optimized satellites to the low Earth orbit megaconstellation, which consists of more than 10,000 spacecraft. This will be SpaceX’s 60th orbital flight of the year, consisting of 59 Falcon 9 rockets and one Falcon Heavy rocket.
Liftoff from Space Launch Complex 40 is scheduled at 7:48 a.m. EDT (1148 UTC). The rocket will fly on a north-easterly trajectory upon leaving the pad.
Spaceflight Now will have live coverage beginning about an hour prior to liftoff.
On Sunday, the 45th Weather Squadron forecast a 85 percent chance for favorable weather during the launch window. Meteorologists said they’re watching a small chance for interference from cumulus clouds.
“The start of the window will still have a chance of showers forming in the Atlantic and moving onshore making the Cumulus Cloud Rule the primary concern of violation on launch day,” the Space Force meteorologists said in a forecast issued on Sunday.
SpaceX will launch the mission using the Falcon 9 first stage B1078, making its 28th flight. Its previous missions included NASA’s Crew-6, USSF-124, SES’ O3b mPOWER-B, BlueBird 1-5, Nusantara Lima (PSN N5), and 22 Starlink deliveries.
Nearly 8.5 minutes after liftoff, B1078 will target a landing on the drone ship, ‘A Shortfall of Gravitas,’ positioned in the Atlantic Ocean off the coast of South Carolina This will be the 151st landing for this vessel and the 614th booster landing to date for SpaceX.
Meanwhile, the second stage will shutdown eight minutes and 39 seconds into flight and enter a coast phase, before short second burn at T+52 minutes. If all goes according to plan, the stack of Starlink satellites will deploy 61 minutes and 26 seconds after launch.
The past few days I’ve been listening to Charlotte Cornfield’s recent album, Hurts Like Hell:
It hasn’t (yet) grabbed me as much as some earlier ones but I like her tunes and simple stories.
§ For the first half of the week I was still in Essex making some slow progress on sorting through the old family home. Ahead of time I’d thought that, by the time we left, we might reach the point we’d looked through everything, but I reckoned without the slow process of paperwork. We want to check every document, to work out what needs to be kept, or found a new home, or thrown away. And this is a house with five chock-full four-drawer filing cabinets, among many, many other containers of paper.
So much of it is stuff that wouldn’t exist these days, from the days before email (and Dad never did email). Messages that would now be an email buried somewhere ignorable in an archive, forms that would now have been completed online. And so many ways to organise paperwork: ring binders, box files, cardboard folders, hanging files, plastic sleeves; paperclips, staples, bulldog clips, paper fasteners, treasury tags.
Progress is slow and emotional. I don’t know if it’s easier or harder that neither me or my sister have children, so there’s no one to pass family history on to. If we had kids maybe we’d think, “We don’t need this receipt for our great aunt and uncle’s bathroom renovation 50 years ago, but maybe it’d be interesting to the kids, just keep it. Keep it all!” On the other hand, I don’t feel the need to keep much myself, and there’s very little I dither over.
In fact, every time I come home from this, I want to shed more of my own stuff. What’s the point of it? This is a bit Marie Kondo (I think) but if something isn’t useful and its presence doesn’t actively give you pleasure, why keep it on the shelf, or in a drawer, until someone has to throw it away when you die? Easier said than done of course. So many things fall into the space of, “I wouldn’t buy this now, but seeing as I’ve already got it, might as well keep it ‘just in case’.”
I’ve done a pass of my own little filing cabinet. Chucked some things. Scanned others and then chucked them. Kept the necessaries. Added a few books to the small pile already destined for the charity shop.
The weight of it all.
§ When I went to scan my papers, macOS told me the scanning software will stop working in a future version. ScanSnap Home, for my little old ScanSnap S1300i sheet-fed scanner, hasn’t managed to update itself for a while and it looks like the version for ARM Macs doesn’t support this scanner.
Thankfully, good old VueScan – which I have an oldish copy of – can operate it, which had never occurred to me. And NAPS2 provides a free, simpler PDF-generating-only alternative. Neither will allow me to simply press the scanner’s hardware button to scan unfortunately. I’m trying to be thankful for these alternatives rather than annoyed at the lack of longer term official support.
§ Being in Essex meant I was able to pop into London for Interesting at the Conway Hall. As ever, it was lovely. Good short talks, a full hall, lots of friends. I saw so many familiar faces, which is even nicer these days, given how few I ever see in between such events. My heart swelled.
The only bad part was having no good, positive answer to, “What are you up to?” (or D’s good variation, “What are you making?”). Only a long, rambling answer describing the past couple of years, which could involve me crying, so it was best to reply, “Not much!”
§ Having got a UniFi Express 7 to handle our WiFi a couple of weeks back, the signal still didn’t stretch much better to the opposite end of the house. So we got another one to extend things – when you get subsequent ones the original acts as the parent and a mesh network is set up with the others as children.
Despite UniFi stuff being popular among techy folk, I had been slightly apprehensive that the extreme configurability and detailed dashboard screens would mean they’d be hard to set up. But somehow UniFi have managed to make something that is not only suitable for people who love to tweak every last detail, but also Just Works: the new unit was automatically set up as a child in a mesh network, all the defaults are (as far as I understand them) sensible, and much of the data makes it easier to work out what to do. I can see the signal strength each device (phones, EV charger, etc.) has, I can walk round the house generating a rough heatmap of signal strength everywhere… it’s all so much nicer than the awful software most hardware comes with.
Mapping signals with WiFiman. Click through for a little more info.
I’m still not sure I’ve got the new node in the best position (both for coverage and for us to live with) but it’s an improvement.
§ I forgot to say last week that I finished re-reading Neuromancer. I think I’ve previously read it a couple of times, long ago, and it was still good, still mostly felt fresh and interesting. After I started reading I remembered that Apple are making a TV series of it, which is possibly what had subconsciously brought it to mind. The casting looks good, and close to how I imagined characters, so 🤞
§ We watched The Testament of Ann Lee (Mona Fastvold, 2025) which was pretty good but, as both Adrian and Aanand said, the voiceover spoils things a bit, putting too much at an emotional distance, and doing the opposite of “show, don’t tell”.
And I watched Jerichow (Christian Petzold, 2008). I always like Petzold’s films – for me they often don’t quite 100% work but there’s more than enough that’s interesting in the characters and their relationships to keep me coming back. I’d have liked this more if the ending – which some Letterboxd folks seem to love – wasn’t so… neatly wrapped? tight? cute? I almost groaned.
Of the other kids in school, my classmates and friends at Abraham Lincoln elementary in Revere, most had never been on an airplane. This was the late 70s, when the cost of tickets put air travel out of reach for much of middle class America.
Of the kids who had been on planes, myself among them, a surprisingly large number of us had vacationed on Bermuda — that hook-shaped island in the Atlantic, about two hours flying time from Boston.
People assume Bermuda is a lot further south than it actually is. It sits roughly on the same latitude as Atlanta, and only 650 miles off the coast of the Carolinas. The island’s proximity, together with its mild weather, pink sand beaches and picturesque stucco cottages, drew tens of thousands of New Englanders every year.
The Caribbean was a much further away and a lot more expensive. Hawaii was out of the question. Florida was the obvious go-to, but Bermuda had an exotic-ness to it that Orlando or Tampa didn’t. It was a little bit of Europe — in an unintimidating, fussily British sort of way — without the long flight and pricey airfare.
All the local travel agencies hyped Bermuda, and the Sunday paper was full of easy and affordable package deals.
We signed on for one of those packages in the early spring of 1979, when I was in seventh grade. My parents, my sister, my grandmother and one of my uncles all made the trip. None of us had ever been outside the United States.
American Airlines flew a daily DC-10 on the route from Boston. Not to be outdone, Delta flew a similarly sized L-1011.
Our flight was on American. At the time, the airline’s DC-10s had a cockpit camera that allowed you to watch the pilots during takeoff and landing. Projected onto the bulkhead screens, the black-and-white visuals were blurry and unsteady, but for a 13 year-old airplane nerd like me, it was thrilling to watch. I remember the captain, who for sure is long dead by now, turning his head to the side and saying to us all, “Here’s a handsome profile shot for ya.”
I’m not sure what, in retrospect, is more remarkable, the cockpit camera (unthinkable today) or the fact that two different airlines were operating 260-seat widebodies on a two-hour hop.
It’s not like that anymore.
Over time, Bermuda lost its crown as New Englanders’ premiere sun-spot. Those DC-10s and L-1011s gave way to narrowbody planes. Northwest Airlines ran a 727 for a while. Delta used a 767-200, then downsized to an Airbus A319. Delta suspended the route during the COVID pandemic, and never brought it back.
The cruise ships still make their runs, usually in the spring and fall, and they remain popular. But if you’re going by air, today your options are JetBlue or a tiny upstart called BermudAir, both using small jets.
What happened is simple enough: the cost of flying fell and the choice of destinations grew. The vacation market fragmented. It became significantly cheaper to fly, with more carriers going to more and more places.
Below, on the apron in Bermuda, is our DC-10 as it prepared for departure back in ’79. In the photo up top you can see my mother (in pink), my sister (yellow), and my grandmother (gray), climbing the airstairs for the flight home.
Speaking with the great sociologist Mark Granovetter gave me the opportunity to tell the joke "“Economists study how people make choices; sociologists study why people don’t have choices," since Moral Economics is about the controversial markets over which society struggles with which choices should be allowed and which should be banned.
Stanford's Center for the History of Capitalism sponsored the conversation, and here it is on YouTube, but it's just a podcast, there's audio of our conversation, but no video.
SpaceX launched the first test flight of its upgraded Starship rocket and Super Heavy booster Friday, with mostly positive results.
The powerful rocket, propelled by 33 methane-fueled main engines, climbed away from SpaceX's Starbase launch facility in South Texas at 5:30 pm CDT (6:30 pm EDT; 22:30 UTC) Friday. Within a few seconds, the 408-foot-tall (124-meter) rocket, the largest ever built, cleared the launch tower and turned onto an eastward heading over the Gulf of Mexico.
Starship splashed down on target in the Indian Ocean a little more than an hour later to conclude the first flight of the latest version of SpaceX's stainless steel mega-rocket. Starship V3 fared better on its debut than the first flights of Starship V1 and V2 in 2023 and 2025. Both past versions of Starship broke apart during launch on their inaugural flights.
President Donald J. Trump’s proposed triumphal arch would sit at a rotary on the Virginia side of the Arlington Memorial Bridge between Arlington National Cemetery and the Lincoln Memorial in Washington, D.C.
The proposed arch obscures the Lincoln Memorial, built to honor the president who steered the country safely through the Civil War, but perfectly frames Arlington House, the mansion built by enslaved Americans and once owned by Confederate General Robert E. Lee. The arch does not frame the nation’s honored dead, but frames instead the home of the man who led the armies of the Confederacy that killed them.
Secretary of War Edwin Stanton approved the land that had been Lee’s plantation as a national burying ground for soldiers on June 15, 1864. After 32 years in the U.S. Army, Lee resigned his commission and took over command of the Army of Northern Virginia in 1862, fighting across the state.
In early 1864 the U.S. government bought Lee’s property at public auction after Lee defaulted on property taxes, and months later it became the logical place to establish a national cemetery after the U.S. Army under General U.S. Grant began its spring 1864 offensive to crush the Confederate forces once and for all.
As the army advanced the Wilderness Campaign, grinding through the Battle of the Wilderness, the Battle of Spotsylvania Court House, Cold Harbor, and on to the siege of Petersburg, the dead piled up.
The Army buried the dead and sent the wounded back to Washington, D.C. Journalist Noah Brooks wrote: “Maimed and wounded…. arrived by hundreds as long as the waves of sorrow came streaming back from the fields of slaughter…. They came groping, hobbling, and faltering, so faint and so longing for rest that one’s heart bled at the piteous sight.” For many, that rest was forever. In the era before antibiotics and modern medicine, the soldiers died in the summer heat.
Cemeteries in the city quickly became overwhelmed and Quartermaster General Montgomery Meigs proposed to Stanton that the government begin burials at the Lee property. The National Republican newspaper called it, along with the establishment of a village of formerly enslaved Americans, “righteous uses of the estate of the rebel General Lee.”
By August 1864 the government had buried the bodies of twenty-six U.S. soldiers around the perimeter of Mrs. Lee’s rose garden, and it continued to bury bodies around the house to make sure Lee would never again be able to live there. By the end of the war, more than 16,000 Civil War soldiers were buried at Arlington National Cemetery.
It was there, on May 30, 1868, that the first official Memorial Day ceremony took place. In those days the observance was called “Decoration Day” and was widely celebrated after the war as people put flowers on the graves of the war dead. At the 1868 event, the newly organized Grand Army of the Republic honored the occasion with a speech by then-congressman James Garfield, who had served as a major general and seen action across the war, including at the battles of Shiloh and Chickamauga.
Garfield, who would later be elected president and lose his life to an assassin, told his comrades that the men buried at Arlington had “summed up and perfected, by one supreme act, the highest virtues of men and citizens. For love of country they accepted death, and thus…made immortal their patriotism and their virtue.“
They had fought, he said, to defend the fundamental principle of the United States. Before the war, Garfield said, “[t]he faith of our people in the stability and permanence of their institutions was like their faith in the eternal course of nature. Peace, liberty, and personal security were blessings as common and universal as sunshine and showers and fruitful seasons; and all sprang from a single source, the old American principle that all owe due submission and obedience to the lawfully expressed will of the majority. This is not one of the doctrines of our political system—it is the system itself. It is our political firmament, in which all other truths are set, as stars in Heaven…. Against this principle the whole weight of the rebellion was thrown. Its overthrow would have brought…ruin.”
And so, he said, “[t]he Nation was summoned to arms by every high motive which can inspire men. Two centuries of freedom had made its people unfit no for despotism. They must save their Government or miserably perish.”
For those who had died to defend the nation, he asked: “What other spot so fitting for their last resting place as this under the shadow of the Capitol saved by their valor?”
“Seven years ago, this was the home of one who lifted his sword against the life of his country, and who became the great Imperator of the rebellion. The soil beneath our feet was watered by the tears of slaves, in whose hearts the sight of yonder proud Capitol awakened no pride and inspired no hope…. But, thanks be to God, this arena of rebellion and slavery is a scene of violence and crime no longer! This will be forever the sacred mountain of our Capital….
“Hither our children’s children shall come to pay their tribute of grateful homage. For this are we met to-day.”
Garfield’s grand words obscured the extraordinary human cost of the war to defend the U.S. government. Almost seven years before, on July 14, 1861, at the very beginning of the conflict, Major Sullivan Ballou of Providence, Rhode Island, wrote his final letter to “My Very Dear Wife,” Sarah. Ballou anticipated the First Battle of Bull Run, the first major battle of the war, and wanted to explain why he was willing to give up his life for his country, and what it would cost.
“If it is necessary that I should fall on the battle-field for my country, I am ready,” he wrote. “I have no misgivings about, or lack of confidence in, the cause in which I am engaged, and my courage does not halt or falter. I know how strongly American civilization now leans upon the triumph of government, and how great a debt we owe to those who went before us through the blood and suffering of the Revolution, and I am willing, perfectly willing to lay down all my joys in this life to help maintain this government, and to pay that debt.”
“Sarah, my love for you is deathless. It seems to bind me with mighty cables, that nothing but Omnipotence can break; and yet, my love of country comes over me like a strong wind, and bears me irresistibly on with all those chains, to the battlefield.
“The memories of all the blissful moments I have spent with you come crowding over me, and I feel most deeply grateful to God and you, that I have enjoyed them so long. And how hard it is for me to give them up, and burn to ashes the hopes of future years, when, God willing, we might still have lived and loved together, and seen our boys grow up to honorable manhood around us.”
Ballou fell at the Battle of Bull Run. Sarah never remarried.
I’m posting our Wednesday conversation as this week’s video. Transcript below.
. . .
TRANSCRIPT: Paul Krugman in Conversation with Heather Cox Richardson
(recorded 5/20/26)
Heather Cox Richardson: How are you doing, Professor Krugman? I know you’re on vacation.
Paul Krugman: Yeah. As I wrote the other day, I’m in Europe, which means I don’t have to think about Trump 100% of the time, only about 90%. So that’s a little bit of release psychologically.
HCR: It’s really astonishing, isn’t it? But hopefully we don’t talk entirely about him today. I’m actually interested and would love to hear what you have to say about artificial intelligence, not itself as an entity, but as a factor in the economy. Because boy, it sure looks to me like we are way overinvested in AI. I think the growth on the stock market is basically AI companies. We know now that there’s more construction in AI data centers than there is in commercial real estate. And I’m wondering, can we just talk about that and you walk us through what this looks like? Because everybody keeps saying, “Oh, it’s a bubble like the housing bubble or like the dot-com bubble.” And I’m looking at it and saying…
PK: Obviously, history is mostly what we have to go on. There have been many bubbles like this. There’s some broad similarities to dot-com, which was also a telecommunication thing. It also looks like the canal bubble in England, which was earlier. Most of the bubbles were pretty clearly bubbles at the time and that was certainly true for dot-com which I sort of still remember in real time. But with AI, I’m finding that the contrasts with the late 90s bubble are really illuminating. Obviously it’s again technology with lots of investment. There’s an enormous enthusiasm of a kind, but in other ways, it’s quite different.
HCR: Well, let’s start with this. What exactly is a bubble?
PK: Yeah, it’s always a question, but a bubble more or less means that people are investing in something that has no realistic chance of paying off—not socially but just commercially, to an extent that justifies the amount of money being thrown at it. Crucially, a bubble is something that people do because everyone else is doing it. So, Robert Shiller, the great bubble theorist of modern economics, said that a bubble is a natural Ponzi scheme. It’s something where you get in and you make money because other people get in, and people keep on coming in because everybody before them made money. But in the end, it’s a game where the money isn’t really there. It all depends on fresh crops of suckers coming in. And at some point you run out of suckers. So that is a Ponzi scheme, especially when someone like a Bernie Madoff does it deliberately in a bubble. It also happens naturally. Nobody is orchestrating it but nonetheless the logic of it is the same as a Ponzi scheme. So basically, it’s a lot like pornography where you know it when you see it.
But it’s not just the fact that people are wrong but that people are wrong in a way that should have been predictable and where it’s really something that is sustained by the momentum, by the fact that other people keep on coming in until they don’t.
HCR: Okay, so when historians talk about this, they example they often use is tulips. It’s something that you can explain to people as a reference because it’s kind of a cool story. When you take it out of the economic system that we understand now, it’s easier to see.
PK: Yeah, I mean, I’m not really fond of the tulips analogy but sort of the first thing that people think of as being something like a modern bubble was the tulip mania in the Netherlands. 17th century Netherlands was not quite the first modern economy because they weren’t quite modern, but they were on the way. They were commercialized. They were banking. And people were speculating in tulip bulbs, which were in fact valuable investments, but it got crazy. The prices went up because people were buying and buying and then prices went up further.
And so, you can see the financial logic there, but I’m not really fond of this example because there wasn’t a whole lot of real investment. People weren’t building tulip infrastructure. But I guess in terms of the psychology, the market logic, it was not that different from railroad shares or dot com shares. So, yeah.
And it is telling you, the fact that this is the Holland of Rembrandt and not only wasn’t there an internet, there weren’t even telephones, and yet the psychological logic was the same. And that’s kind of telling you that in some ways there’s a kind of universality about bubbles.
HCR: So when we look at AI now, am I correct that there are two super companies in which the majority of AI money is invested?
PK: Yeah. There’s OpenAI and there’s Anthropic and who are the big players but it’s an industry. It’s not just that these are the two biggest AI models. So you’re either talking to ChatGPT or to Claude which are the two leaders but then Google has its own model which is Gemini and then Elon Musk has a really bad one, Grok. And then there’s a bunch of Chinese versions, where they’ve taken a very different strategy. So it’s a little bit more complicated than that. And then there’s this network.
So in a lot of ways, you want to think of this whole AI boom bubble as being a little bit like the California gold rush, another historical parallel. The people who are selling Anthropic and OpenAI are like miners, prospectors looking for gold. And what we know in California in the 1840s was that the people looking for gold mostly ended up bust but the people who made money were basically the Levi Strausses who didn’t make money by finding gold. They made money by selling equipment, by selling jeans and picks and shovels and also brothels and liquor to the prospectors.
The equivalents of that now are companies like Nvidia which is selling the specialized chips that go into AI and there’s a bunch of other companies making a lot of money basically renting out computational capacity. So now we’re starting to see at least a little bit of money being made by Anthropic. All of my friends are playing with Claude and I just can’t get myself to do it. The big thing seems to be vibe coding, which lets you do programming without knowing how to program. And so Anthropic is actually making some money because people are subscribing to that service. But at this point, most of the money being made is from people basically selling equipment, selling the suppliers to this thing.
And so the question from a kind financial economic point of view is whether there will ever be enough revenue, whether people actually end up paying enough for AI, this thing that we call AI, to justify all of the money being thrown at the industry. And history would suggest there’s a very good chance that the most likely outcome is no. The most likely outcome is that it will end up being a waste. But again, history doesn’t always repeat so maybe this pays off but I don’t think that explains the enthusiasm.
HCR: Well, it’s interesting because one of the things that you’re seeing lately is the changing model for paying AI. That is, most of the use of AI currently is subsidized really quite heavily for every dollar of computing power that people use. It’s subsidized between $3 and $25 at the minimum. And the idea that people are actually going to pay the extraordinary costs that certainly right now it would warrant…it doesn’t seem like it’s going to happen.
PK: Well there’s a question. Let me play devil’s advocate here for a second. When the dot-com bubble happened and people were offering all these services on the Internet where people weren’t willing to pay remotely enough to justify the money that was being thrown at it. But what eventually happened was that a few companies managed to create walled gardens. They managed to create enclaves. Essentially, Facebook is a walled garden where people pay for ads or watch ads or whatever. Google basically ended up being a kind of walled garden. The search was free, but Google was making money out of pushing targeted ads. We used to joke about Amazon. I’m old enough to remember when Amazon was famously unprofitable and was never going to be profitable. But it turns out that, well, in the end, Jeff Bezos built a moat with all of the infrastructure, the distribution centers. And so now Amazon is a huge moneymaker and evil. But that’s another story. And what’s happening with AI is, to a certain extent, they’re building walled gardens from the beginning.
So I know people who’ve been using Claude or have been playing with Claude, I think would be a better description, and the results have been terrible. And it turns out that the results are terrible unless you pay and buy a higher tier of service. Now even there it’s not remotely enough to justify the expense [of investments] but clearly Anthropic is trying to create a situation in which people get hooked on vibe coding and then end up addicted and they’re going to end up shelling out large amounts of money to have the the version of Claude that works. And with something like that you can already see the outlines, at least, of how the industry intends to make money.
Now, history suggests that usually there are only a few winners. Although one thing that’s also different from the dot-com bubble, is that in the dot-com bubble, there were hundreds of players trying to succeed, and in the end, just a few highly profitable corporations survived. This is not like that. This industry, at least on the U.S. side, is just a handful of players. So the chance that one or two or maybe three big AI models will end up becoming highly profitable monopolies, it’s not that remote.
So, as I say, things tend to be somewhat different. I mean, we don’t want to start talking about what AI is exactly, but I think there are inherent weaknesses of it. I mean, it’s a technology where you cannot predict exactly what the tools will do, and you cannot know when they’re going to betray you; when they’re going to deliver hallucinations instead of actual-actual true results. That’s weird. I don’t know if there’s anything like that and you have to wonder, just how much will our society be willing to rely on technology that every once in a while just decides to go crazy or basically turn into Frankenstein’s monster on you. So that would be my guess, but it’s not as if there’s no possible way these guys could make money.
HCR: Well, but there is something interesting in it as well, and I think you’ve identified that many of the things that we’re identifying as bubbles actually start with a product that people want. They don’t have to create their own markets. And the other piece of that is I certainly have heard people say exactly what you’re saying, that there will be a fallout where we’ll get a few good ideas out of where we are. And then you can have your walled gardens around those things. But it’s rare.
I mean, I can think of an occasion for it when we got the Union Pacific Railroad in the 1860s, because Congress recognizes that people actually would like to get to California. But if you actually wait for there to be enough of a market in the plains to get those railroads going all the way to California, you’re going to be waiting a very long time. So they put the money up to create a market for those railroads. But then very quickly you get all these branch roads that lead to nowhere and end up feeding that railroad boom in the 1870s that collapses.
So it does feel to me like this is something different. You’re not getting those walled gardens right now where people say, “Yeah, I really want to get into that and I’m willing to pay for it,” the way we were with iPhones, for example, or the way we were with the internet. I remember the first time I turned on the internet I was teaching at MIT and they made us take seminars so that we understood this new technology and I can still remember going home and saying, “Oh my god. My world just changed because I can do all this research.” This is the very early days but you look at the AI stuff and, I started using it pretty heavily just to see what it would do and I have become completely against it because so far I haven’t seen anything that isn’t crap. And I was agnostic. I’m usually pro-technology.
Now, I am willing to admit that there are places where it is probably a good thing, like checking engineering plans in construction plans, for example. We know that there are ways in which mixing cement can be much more efficient if you use AI [for calculations]. But right now, I don’t see it taking off.
PK: Well, you and I are not typical, of course. I think there’s an important distinction here but what I actually am using a little bit of AI for is actually producing transcripts of videos. You run a video through AI to produce a transcript which is often hilarious in detail but you can fix that. You wouldn’t believe what AI was making of the words, “vibecession.” But anyway, it can do certain things. I also find that with economic history, often there are a lot of papers that have tables and charts and I can feed them into a sort of low grade AI model as a PDF and get the numbers out instead of having to type the numbers from the old papers. So there are uses even for someone like me.
I mean, in a lot of ways AI is kind of awesome in how much it manages to produce intelligible if sometimes dishonest responses to plain language questions. That is awesome given where we used to be, even if it’s not totally reliable. But the main thing is that a lot of AI—and certainly what is likely to be the paying uses of AI—is not coming from individuals. It’s not coming from me or you or some middle manager deciding, “Hey, maybe I can use AI to do this better, or maybe I’m just going to have some fun with it.” (Slightly scary but I do know people who are developing relationships with Chat GPT.) But it’s mostly coming from people working at businesses and large organizations who are being told, “You must use AI.” And this is something I’ve never seen before. This is kind of coercive technology adoption where the big money is telling workers that you must use this technology.
And one thing you’ll remember from the early days of the internet, it was joyful. People loved the internet. People hate AI. We’re now having a regular pattern at college commencements of speakers who start talking about AI and all of the students start booing because everybody hates this. And the question is, how far can you go with a technology that everybody hates? So that’s one of the things that is unprecedented.
You think of the people whose jobs were displaced by power looms, the Luddites. Okay, they hated the technology because they didn’t like what it was doing to their jobs but people hate using AI and they hate the fact that other people are using it. But they are to a large extent being dragooned into doing it and I’m not sure that I can think of a historical example like that. It doesn’t seem like it’s a very sustainable path forward.
HCR: So, Henry Ford would have something to say about trying to force people to take on new technologies. I actually saw an Edsel a few years ago. I’d never seen one. I’d always just heard about how much they were rejected. And I saw it and I’m like, “That’s it? They just didn’t like the front grill?” And yeah, people just didn’t like the front grill and they wouldn’t go with it. But that brings up another question for me. You’re hearing a lot and there were stories out just today about companies cutting thousands of jobs because people were being replaced by AI. And I have a question for you about that. I actually then want to end with, what does this look like for the entire society? But it certainly looks to me that as the economy slows down, that it’s certainly possible that companies are letting workers go saying it’s AI. And what they’re really doing is they’re reducing their forces. Is it right that AI is possibly simply being a cover for people who wanted to downsize anyway?
PK: Well, there’s some of both. I mean, if you’re a company that wants to, in effect, increase the workload on a smaller number of workers, then AI is a great cover story. You can say, “Oh, we’re doing this because of the wonders of modern technology.”
And by the way, we expect you to, in effect, put in 10 hour days.
We keep getting stories of companies that lay off a lot of workers saying that AI can do it better and then it turns out it can’t. And I don’t think these are just stories. If we’re saying that AI is just doing routine stuff. Some of my friends who actually work on this, like Henry Farrell, say that AI is a social technology. It’s basically agglomerating what lots of people have said. And it’s delivering back to you what a lot of people who know something about a subject would say if asked the question you asked. And it’s not understanding. There’s no mind there. But it is delivering a kind of aggregated, standard response. And a lot of jobs are like that. If you’re talking to the help desk at a call center somewhere thousands of miles away, the person that you’re talking to, if it is an actual person, may very well be there with a three-ring binder looking for what they’re supposed to say. And AI can replace that job. AI is basically doing much the same. A lot of people are doing fairly routinized, standardized work. It’s just the common opinion of common opinion responses to things as a way of doing their jobs. So that’s real.
So it’s not just that AI is an excuse, but again, it’s an excuse. I mean, we always see this, right? To the extent that businesses care either what their workers feel or what their customers feel, stuff happening provides external excuses.
This is the story of greedflation, that companies may raise prices when there’s an energy crisis, not because their actual costs have gone up, but because with everybody raising prices, who will notice if I get greedy? So there’s something like that on AI and jobs as well. But I don’t know. I mean, again there are enough stories now of companies that have laid off all of their experienced professionals for AI, and it turns out, well, the experienced professionals could actually deal with questions that were not routine, and they didn’t hallucinate, and so they’re finding that they made a mistake.
But it’s amazing how little we know about how this works. I don’t remember there being so much uncertainty about what you could actually do with the internet. And of course, I don’t have any memory of what people thought you could do with railroads. But I think this is kind of unprecedented as this massive technology that we’re investing trillions of dollars in and still nobody quite knows how it works or what it will do.
HCR: Well, I want to end with my real question. That is, if I’m correct, and these people I’m reading are correct about it looking like a real bubble, what does it look like if that bubble bursts? This is the reason I use the comparison of the 19th century railroads, or you could do the 1920s with cars, and the investment in AI in data centers, in hiring practices, certainly in investments, certainly in NVIDIA and all these different places that are tied into that specific technology.
Now, I’ve heard from a lot of people, you included, that we’re going to get some good technologies out of it no matter what happens. And I agree with that. We always do. But with all the pressures that are on the American economy right now, I’m worried. And should I be?
PK: Yeah. Let me give you sort of good news and definitely bad news. The good news, and I say sort of for a reason, is that on the face of it, if you just look at the scale of the AI investment, it looks like that’s driving all of our economic growth. But it turns out that an awful lot of the AI spending is actually imported tech gear. It’s actually imported chips and computer equipment and so on. So if the AI bubble bursts, a large part of the burst would be falling imports. It would be a big shock to the domestic economy but not nearly as much as you might think. There’s been a back and forth about how much economic growth has been AI and how much the high import intensity of the stuff. So in some ways this is a shock to the world economy and not so much to the U.S. economy, specifically. So I guess that’s kind of good news, though not so good for other countries. But, you know, Taiwan has experienced an enormous economic growth because of all the chips they’re selling to U.S. AI companies. So a lot of the bad news will end up showing up in Taiwan rather than in the U.S.
The bad news: this would have been true of railroads, as well, but the dot-com bubble in terms of the actual really big money laid out was telecoms rather than dot-coms. It was the telecommunications companies investing especially in fiber optics, laying down tremendous amounts of fiber optic cable which stayed unused for a long time. There was lots of dark fiber after the dot-com bubble burst but it was still there. Fiber optic cable doesn’t depreciate rapidly. It was still there in the ground and eventually got used. So it was a lot of useful investments.
As I understand it, these data centers that are being built, the investment in chips, the investment in software, this stuff will depreciate physically pretty fast. It will become outmoded pretty fast. So I think there’s likely to be a much higher proportion of just wasted investment that never finds a use out of this boom than there was out of the last tech boom. So, not so great.
And by the way, the Chinese are taking a very different approach. They’re building much more limited models that just don’t use as much information but get a high fraction of the performance and use a lot less energy. If the world ends up going to that model of AI instead of the all-encompassing ones then we will have just wasted the money. We will have spent a lot of money on building super impressive stuff that nobody actually wants to use.
Obviously the railroads still had railroads. You could use the tracks later on. You could use dark fiber. I think the original boom that looks something like this was, in fact, the British Canal boom around 1800. All of those left usable legacies. And this one might not.
HCR: Wow. Fascinating. Absolutely fascinating. Thank you. It’s always a pleasure to talk to you.
Welcome to the reading list, a weekly roundup of news and links related to buildings, infrastructure and industrial technology. This week we look at squatter removal services, Apple finding uses for defective chips, process heat use in California, the brewing Colorado River crisis, and more. Roughly 2/3rds of the reading list is paywalled, so for full access become a paid subscriber.
War in Iran
Iran wants to charge US tech companies for use of the undersea cables that pass through the Strait of Hormuz. [Ars Technica] And Iran is starting a Bitcoin-backed ship insurance service [Bloomberg]
The hundreds of ships stuck in the Persian Gulf are starting to get damaged by all the barnacles and jellyfish that they’re accumulating. “...the Gulf’s shallow sandy seabed and warm waters have put ships at anchor or adrift there at risk of sand and sea creatures clogging up gratings that protect the vessel’s internal pipework. Seafarers are also struggling to get hold of critical parts when systems have broken down.” [FT]
An interesting example of the complexity of petroleum and petrochemical supply chains: a cooking oil shortage in India is driving up gas prices in California. “India, the most populous country, uses LPG as its primary cooking fuel. Cut off from Middle Eastern LPG, which represented over 90% of India’s total imports of the fuel before the Iran war, New Delhi has directed refiners to maximize LPG output. To comply, refiners have cut production of alkylates - motor fuel additives made using LPG as feedstock. For California, shrinking alkylate supply compounds concerns of a potential gasoline shortage due to declining fuel production and exports from Asian refiners struggling to access Middle Eastern crude oil. Alkylates are highly sought in California because they burn cleaner than other additives, and the state requires a unique gasoline blend to reduce smog.” [Reuters]
The US has lost 42 aircraft so far in the war with Iran, most of which (24) are MQ-9 Reaper drones. [National Security Journal]
Housing
The House passes its version of the Senate’s Road to Housing Act, without the build-to-rent restriction, 396 to 13. [NPR]
The NYT has a big, data-driven opinion piece on the need for the US to build more homes to bring down the price of housing. “The situation in expensive coastal areas, however, is far worse. They have enacted onerous zoning and building rules that limit home construction. They have allowed the “not in my backyard” instinct to prevail. Many of these areas vote Democratic and identify as politically progressive, yet their housing policies have increased inequality. By maximizing home prices, these parts of blue America have benefited existing homeowners, who tend to be older and richer, at the expense of everyone else. Nationwide, the relationship between home prices and home construction is even stronger than many Americans realize.”
Because California makes it so difficult to remove people living in a residence (whether they’re there legally or not), some California landlords are hiring “squatter removal services” to intimidate illegal squatters from vacating the properties they’re occupying. “Jacobs claims to have developed a long list of tools and tactics that enable him to remove squatters far faster than the court system, all while staying within the bounds of the law. Chief among them is a weapon he carries on every job: a katana, a curved Japanese sword that’s more synonymous with samurai warriors than clearing squatters. “In most industries, swords just don’t make any damn sense,” Jacobs says. “In this particular one, it actually does.” The lightly regulated katana, he explains, is an ideal weapon for indoor self-defense and intimidation.” [Reason]
Washington state legalizes scissor stairs, interlocking stairways that let you combine two stairways in one shaft. Scissor stairs are, like single-stair apartment buildings, a space-saving building design feature that’s common in other countries but mostly illegal in the US. [Sightline]
Manufacturing
Because of their microscopic size and their sensitivity to minute changes in chemical concentrations, semiconductor fabricators invest an enormous amount of effort into process control to minimize the number of defects that occur on a microchip. Defects nevertheless still occur, and when they do there’s often no real way to repair them. But that doesn’t mean the entire chip is useless; it just means you need to find a way to use it without the damaged areas. “The chip powering the Neo is Apple’s A18 Pro, the same chip first used inside the iPhone 16 Pro two years ago, but with one key difference. The Neo version of the chip has a “5-core” graphics processor, one less than the version inside the 2024 iPhones, indicating that Apple was able to save some of the A18 Pro chips with a defective core for future use. Defective cores can be disabled, leaving a chip that still functions perfectly well to power different, often cheaper devices—in this case an entry-level laptop instead of a top-of-the-line iPhone. It is the latest example of Apple deploying a decades-old chip industry strategy to squeeze profits from lesser-performing processors by selling them like eggs, gas, diamonds or hotel rooms, segmented by good, better and best.” [WSJ]
In a doh moment last week, I realized I was missing a key dynamic in my thinking about AI: commodification.
The specific problem was that vgr_zirp, the RAG bot I’ve been training and tuning on my older writing, was acting boringly omniscient and tasteless, engaging deeply on topics I know nothing about, and more importantly, don’t care about. Conversations the real me would walk away from were playing out in dull ways. Claude Sonnet’s far greater knowledge and far larger circle of care (the union of all human cares ever rendered textually) were seeping in too much. I had to add filters and guardrails modeled on my own ignorance, indifference, and blindspot areas to get it to behave more interestingly and tastefully, and not sully my good name.
Too much commodity intelligence and indiscriminate caring were seeping into what I’m trying to design to be a differentiated and opinionated intelligence with a real-person personality (a stylized version of my own).
A lot of people, myself included have noted that LLMs offer a homogenized kind of intelligence that resembles index funds (see my LLMs as Index Funds, April 1, 2025, for one version of this argument). This view, I’m now convinced, does not go far enough. In advanced, innovation-based economies, index funds are collections of high-market-cap stocks that are still individually pretty differentiated and far from the commodity asymptote all economic goods and services tend towards. LLMs are much farther along the curve. The capabilities they manifest rest on vast corpuses of data that are not just public and with the equivalent of “high market cap,” but largely commodified. LLMs are not just index funds, they are dominantly commodity index funds.
LLMs are the informational equivalent of portfolios of coal, gold, and potatoes. The components may differ in intrinsic value and exist in varied quality grades, but are fundamentally fungible. Information embodied in LLMs is mostly high-paradigm and high-consensus common knowledge. LLMs know about fringe, crackpot, and low-consensus ideas in the same way markets know about emerging and penny stocks and junk bonds, but the center of gravity (or indexical perspective if you like) of both lies in commodified knowledge.
What is the informational equivalent of commodification? I pointed out one aspect of the answer 3 years ago, and dubbed it the Labatut-Lovecraft-Ballard (LBB) arc, inspired by reading Benjamin Labatut’s When We Cease to Undersrand the World, and the fiction of H. P. Lovecraft and J. G. Ballard.
We might sketch a three-stage psychohistory of a disturbing new expanded reality, as more and more minds become stretched to accommodate it:
In the first, Labatutian stage, a handful of minds are forced to bear the brunt of the full, uncontrolled assault of a new idea on the human psyche.
In the second, Lovecraftian stage, a much larger group of somewhat inoculated minds willingly ventures forth to encounter a somewhat familiar, but still unsettling version of the idea, serving as an avant garde engaged in rebuilding social realities as required around it.
In the third, Ballardian stage, the construction of new social realities is (relatively) complete, but the costs and inherent contradictions have not yet been apprehended. The expanded reality has been civilized but not tamed. All minds are shaped by it, whether or not they are consciously equipped for it.
Benjamin Labatut’s book (one of the best of this century so far) explores the insanity-inducing effects of new-to-humanity knowledge, on the first minds that encounter it, via a series of quasi-fictional accounts of such encounters in the lives of famous scientists. My model is basically an account of how the human mind adapts fully and collectively, primarily through socialization. The larger the number of people who have experienced a piece of knowledge, the more domesticated it is, and the less able to cause madness. Labatutian psychosis leads to Lovecraftian cosmic horror leads to Ballardian banality.
In a talk shortly after that post, I argued that this partly explained crazed reactions to AI (remember Blake Lemoine?), but I didn’t complete the theory. Commodification effects complete the theory, but the mechanism is subtler than I anticipated at the time.
It is important to note that commodification is not the same as universal accessibility. Gold is a commodity, but most people in the world possess little to none. Classical mechanics is a fully commodified body of knowledge, but only a small fraction of humanity has the aptitude and educational preparation to understand and use it to the fullest extent widely available textbooks can teach. To the rest it can be the source of magic (eg. a double cone rolling “uphill” on a pair of slanted, diverging sticks).
The OpenAI proof of an 80-year-old math problem may have been beyond human mathematicians, but it rested on fully digested Ballardian priors, so to speak. The Labatutian era for that problem was circa 1946 when Erdos first posed it to himself and understood its significance. Human mathematicians have annealed it over 80 years into a familiar bit of mathematical territory, at least to mathematicians in the relevant subfields.
AIs trained on Labatutian data are highly differentiated, fragile, and unreliable. AIs trained on Ballardian data are highly commodified, robust, and reliable. To extend the analogy past AI to my favorite neck of the woods, protocolized knowledge has entered the utility stage past commodification, and is generally embodied by the “tool use” part of agentic AI. A very clear tell is that it runs on CPUs rather than GPUs.
To understand why it is a valid step to go from speaking of commodified knowledge to commodity intelligence, you have to understand a few features of AI of the sort we have today that justify such extrapolation:
Performance degrades outside the training set (though the training set is larger than the experiential base of many humans, so finding the actual boundaries, rather than simple errors or hallucinations, can be hard)
Performance degrades with time past the training epoch (a necessary consequence of what noted as the “overfitting without regularization” of constantly evolving internet data, which is a feature, not a bug)
Performance degrades if you try to train a model on its own output without additional new raw information entering the loop (“model collapse”)
These is reasonable phenomenology by the way, and visible in human intellligence too, despite the differences in architecture. We would be very surprised, like “is there phlogiston in there?” level surprise, if these phenomena didn’t manifest. They provide reassurance that AI does not appear to violate the known principles of information theory or thermodynamics. Megawatts worth of matrix multiplications don’t produce phlogiston in datacenters.
We don’t have a theory of how LLM-and-human style intelligence works, but we have strong evidence that there is no magic going on. The emergent phenomenology is like markets or weather, not theology.
A few things tend to confuse people into believing in magical properties:
Unexpected playability of domains. Many knowledge domains are turning out to be what I have started thinking of as unexpectedly playable (stronger subset: self-playable). Though a domain may not be technically a closed world like chess, and though there may be no obvious “physics” to it, capable of being abstracted into a “physics engine,” there is enough rule-like regularity that you can get farther with seemingly informationally impoverished data than you think. Code and protein folding are prototypes but more impressive examples are emerging. For example, recovering 3d geometry from 2d projection data (like photographs) is “unexpected playability of large corpuses of photos.” Egocentric video for training robots is another example. The various symmetries of many artificial and natural objects allows this.
Local entropy reduction. Agentic AI is exceptionally good at cleaning up messy local conditions and getting them into locally well-ordered states that are beyond normal human capabilities. This can seem magically negentropic, but is still local. Claude Code cleaning up your decades of downloads into a nicely organized library still requires wattage being expended entropically in a datacenter somewhere, mostly likely the backyards of people you don’t deal with socially.
New-for-you (secondary Labatutian) effects: This is the subtlety I was mentioning earlier. Normal knowledge commodification curves are limited by human aptitude and the patience of human teachers. So human physicists who understand advanced physics don’t have patience for humans who lack the aptitude to (say) earn a physics degree. They ignore crackpots. But an AI embodies commodified physics knowledge in a form that expands access to people previously priced of that commodified knowledge market. For these newly empowered people, a counterparty who engages with them triggers something similar to a Labatutian paranoia. The knowledge is not new, but they get it via a raw encounter rather being socialized into its Ballardian form, and embark on a solo LBB arc in a solipsistic reality tunnel.
Once you account for such wrinkles and clear away the red herrings created by worshippers, the idea that AIs today are commodity intelligences becomes intelligible and useful.
It also explains, at least to my satisfaction, the strange allure of the idea of “general” intelligence despite the obviously specific, training-context-adapted and contingent nature of all known biological and artificial intelligences. It’s the result of confusing two notions of “generality.” Generality as in “generally available in the market” is not the same as generality in the sense of totalizing universality.
Commodified knowledge is “general knowledge” in the sense tested by trivia/quiz contests. In grade school, we actually had a subject on the curriculum called “GK” and kids good at it (I was one of them) got put on quiz teams to represent their class or school. General intelligence of the sort we actually have today is simply AIs trained on general (ie commodified) knowledge.
But the theological motte-and-bailey move that conflates it with some totalizing-universal divine-omniscience idea of “Artificial General Intelligence” traps a great many of even the smartest people. A category error motivated by theological yearnings, validated by second-order Labatutian psychoses, sustained by epistemic bubbles, and encouraged by sketchy business roadmaps that need a story to justify trillion-dollar investments.
This widespread category error has consequences beyond the annoyance of the future getting hamstrung by getting “AGI” branded. My simple example of a bot being rendered boring by the seepage of commodity intelligence is a small example. A general intelligence in the strong sense could only have improved the bot (a God making the bot a more fully realized ideal version of me say). It would not have injected boring tastelessness.
There are bigger, costlier mistakes you can make if you pretend commodity intelligence deployed at scale is the same thing convergence towards divine omniscience.
The biggest mistake is perhaps this: Instead of marveling at and exploiting the capabilities of the truly amazing AIs we have built, you end up worrying about the features and flaws of incoherent and ill-posed thought experiments that simply don’t matter.
Take this for what you will but in this piece the NYT seems to be coming around to a point I’ve been making for the last three or four months: “Mr. Trump has decided to double down, presenting himself as politically all-powerful even in the face of indications that he is not.”
A collaboration between the California Geological Survey and the USGS, the Sierra Nevada Earth Science Atlas “provides the most detailed geologic framework mapping of California’s most iconic landscape to date. This web page hosts the… More
In a blog post, David Smith discusses the challenges of getting good maps on the Apple Watch version of Pedometer++, version 8 of which shipped last month. “App design on watchOS is a really fun—but… More
There is a pernicious and persistent pattern among many partisan pundits and politicians, pertaining to public debt. When their own party is in power, they minimize or ignore the problem, but as soon as the other guys win the presidency, they start shouting that the debtpocalypse is upon us.
Do I follow this pattern? Maybe a little bit. As recently as 2022, in Biden’s second year as President, I was not very worried about U.S. government debt. My reasoning was that A) interest rates were going to go back down after the surge in inflation had ebbed, preventing borrowing costs from getting severe, and B) Biden-era inflation had eroded some of the government’s debt burden.
But I still warned that there was some limit to government borrowing — eventually, at some difficult-to-predict point in time, too much debt would cause first interest rates and then inflation to soar. And I warned against listening to “fiscal arsonists” like the MMT folks, who aggressively advocated for higher government deficits.
And by 2023 — still under Biden! — I was starting to worry a lot more. Interest rates weren’t coming down much, making austerity more necessary — except no one, including Democrats, was talking about austerity. And by 2024 — still under Biden! — I was warning that there was no good reason for all the deficit spending we were still doing, and that continuing on our current path would run the risk of spiraling inflation:
So I definitely didn’t wait until Trump came to power to start worrying about the debt. But I do admit that under Trump, my worries have intensified. The Democrats listen to intellectuals — although the party has become more dominated by progressives who tend to worry less about government debt, there was always the possibility that concerted shouting by pundits like myself could shift the consensus among left-leaning think-tankers and staffers, who could then pivot the Dems back to the fiscal austerity of the Bill Clinton years.
Republicans — especially Trump and his movement — are a different beast entirely. They stopped listening to egghead intellectuals a long time ago, and even the finance-industry and right-wing think-tank types who have some residual impulse toward fiscal hawkishness have steadily lost influence as MAGA heads toward full cult-of-personality status. The only person in the Trump orbit who even talked about fiscal hawkery was Elon Musk, but this glimmer of hope1 faded when DOGE utterly failed to reduce government spending:
So when Trump returned to the presidency and DOGE flamed out, my mounting alarm turned to full-blown panic:
Anyway, it’s a year later, and I’m still panicking. Trump has been about as bad on deficit spending as Biden was (which is actually less bad than I expected him to be!), but a rise in long-term interest rates is making the debt less sustainable, and Trump seems uninclined to do anything about it. Nor do I expect rate cuts or AI-fueled growth to ride to the rescue here. As for Democrats, they’re playing with fiscal fire by proposing tax cuts for the upper middle class.
As I see it, the only hope here is to start scaring people. Bipartisan fear of deficits back in the late 1980s and early 1990s — probably spurred by high interest payments — forced every contender in the 1992 election to promise their own version of austerity. If we can raise the alarm now, there’s the possibility that both parties might be pushed toward fighting the debtpocalypse for populist reasons.
Government interest costs are exploding, and we’re borrowing more to pay the interest
A lot of economists will tell you that the government isn’t like a household, so you can’t think about government debt the way you think about your own mortgage or credit card debt. That’s very true. But there are still some similarities between governments and households, and one of them is that both have to pay interest on their debt every month. Debt, after all, is simply a promise to pay back a certain amount of money at a certain time, and monthly interest payments are part of that.
Government debt is a bit like a floating-rate loan. Yes, Treasury bonds and bills have fixed interest rates, but they’ve got to be rolled over when they mature. The average maturity of U.S. debt is a little less than 6 years. Interest rates started going up in early 2022, so we’re starting to see a big increase in monthly interest payments:
Everybody talks about how the U.S. had such high debt after World War 2, but the thing about that debt is that it was borrowed at very cheap rates — about 1.5-2%. That’s why interest costs stayed so low after the war. In the late 1980s and early 1990s, interest costs were high because interest rates were high, even though we didn’t have nearly as much total debt relative to our GDP.
As of 2026, we’re in double trouble. Our national debt is back up above 100% of GDP — similar to what it was right after WW2 (and much higher than in 1990). But now the interest rates our government has to pay on its debt are almost twice as high as they were after WW2:
Trump, as it turns out, has kept the annual budget deficit at about the same size it was during Biden’s term, relative to GDP:
But things are worse under Trump than they were under Biden, for three reasons.
First, this is a very large annual deficit, and it’s all being borrowed at the new, higher interest rates. In addition, during Biden’s first two years in office, inflation eroded the debt.2 Inflation is back down to a fairly low-ish level now, meaning the debt isn’t getting eroded. And finally, interest rates have now been high for long enough that the debt Trump borrowed in his first term to pay for Covid relief is now being rolled over at higher rates.
So right now, the national debt continues to explode, because the government is borrowing money just to pay the interest on the money it borrowed before. This increased debt naturally results in even greater interest costs, forcing the government to borrow even more to fund those interest payments. And so on. Interest payments and debt just go to the moon.
This isn’t some far-future scenario — it’s happening right now. But unless something changes, it’s going to get a lot worse:
"A kidney transplant does not work like buying a gallon of milk. Neither does hiring or getting into a medical residency. In these markets, both sides care deeply about who they end up with, and a good outcome depends on more than money.
Alvin Roth has spent his career studying what makes those systems succeed or fail. His work designing kidney exchange programs showed that even when people desperately want to help each other, the market can still break down unless the rules create the right kind of match. In this episode, Dart and Al discuss matching markets, moral economics, and the hidden rules that shape opportunity, fairness, and work itself.
Alvin Roth is an economist and professor at Stanford University best known for his work on market design and matching theory. He received the 2012 Nobel Prize in Economic Sciences for his work on stable matching and the design of markets used in medical residencies, school choice, and kidney exchange.
In this episode, Dart and Al discuss: - Why some markets depend on matching - Why fit matters more than money - What makes a market stable - Why real markets are messy - The difference between theory and engineering - What “repugnant transactions” are - Why societies ban some exchanges - How social norms shape markets - Why work is also a matching problem - And other topics…
Alvin Roth is the Craig and Susan McCaw Professor of Economics at Stanford University and recipient of the 2012 Nobel Memorial Prize in Economic Sciences, awarded with Lloyd Shapley for the theory of stable allocations and the practice of market design. His work has helped design matching systems for medical residencies, public school admissions, and kidney exchange programs. He is the author of Who Gets What — and Why and Moral Economics: Why Good and Bad Markets Exist.
"It was so fun talking to Alvin Roth, winner of the 2012 Nobel Prize in Economics.
"One of my favorite books of all time is Who Gets What and Why, which has shaped the way I view labor markets. His second book, Moral Economics, came out last week and it’s so so good - endlessly thought provoking, funny, and sharp. In the podcast, we talk about controversial markets and what makes something repugnant, how to think about exploitation and coercion, and what that means for labor markets.
"Check out the latest episode of The Economics of Work and Al's new book Moral Economics!
"Moral Economics from Basic Books:
Amazon: https://a.co/d/0cu6ZCLm
Podcast Episode:
Apple: https://lnkd.in/esVGQQx5
Spotify: https://lnkd.in/e4sr844Q
Youtube: https://lnkd.in/eif7DHMS"
At least four Russian military satellites changed their orbits to match that of a Finnish-American radar surveillance satellite in the last week, raising questions about Russia's intentions amid an ever-expanding standoff high above Earth.
The maneuvers were identified through open source orbital tracking data. Greg Gillinger, a retired Air Force space intelligence officer, revealed the orbit changes Friday in a special edition of his Integrity Flash newsletter, published by Integrity ISR, a private business that provides "combat-proven operational support and elite training that enhances mission success across ISR (Intelligence, Surveillance, and Reconnaissance), cyber, space, and targeting domains."
The Russian satellites in question, designated Kosmos 2610 through 2613, launched together on April 16 on a Soyuz-2.1b rocket from Plesetsk Cosmodrome in northern Russia. Over the last week or so, the four satellites adjusted their inclinations—the angles of their orbits to the equator—by less than a degree.
Guy on left desperate to know he won’t wind up looking like guy on right
In case you missed this, Donald Trump says he will not be attending his son’s wedding this weekend.
Luckily, he has a good excuse: He’s a dickhead.
Seriously, that’s pretty much his (un)stated reason for refusing to witness the knot tying between Donald Trump Jr. and Bettina Anderson. Or, as the president wrote on social media: “I feel it is important for me to remain in Washington, D.C., at the White House during this important period of time.”
And, eh … this seems like a pretty solid spot to remind people that, since returning to the White House, Donald Trump has played golf, well … let’s actually put AI to good use here …
And even though I loathe Donald Trump, Jr., and even though Bettina Anderson is the walking embodiment of a soulless ghoul, I actually feel weirdly bad for the couple. I mean, hells—your dad is the president! Of the United States! And while he has never shown any real love for you (Don, Jr.), and while he has the compassion of a lamp, and while he’s probably missing the event to raw dog a 14-year-old prostitute, and while it seems quite, eh, expected for a father to attend his son’s wedding …
Wait. Where was I?
Oh, right. Donald Trump is awful. We all know his refusal to attend has nothing to do with this “important period of time” and everything to do with, “don’t feel like going, bruh.” Hell, 14 active duty United States presidents found time to attend the weddings of their children—including (a) John Tyler, who allowed his blessed Elizabeth to marry William Waller inside the White House (even when it lacked a bullet-proof ballroom!); (b) FDR, who drove all the way to Delaware (FDR, Jr.) and Massachusetts (John) to watch his two sons drop some vows; (c ) Harry Truman, who returned to Missouri to attend Margaret Truman’s wedding to Clifton Daniel. And lord knows, nobody vacations in Missouri.
In 1977, Chip Carter married Caron Griffin. Jimmy was there. Of course.
So the next time some white-bread Christian pastor with a mega-church and a private jet compares the president to Jesus Christ, ask whether Jesus Christ would miss his son’s wedding under the guise that he needs to oversee the irrational bombing of a far-away nation.
On May 22, 1964, in a graduation speech at the University of Michigan, President Lyndon Johnson put a name to a new vision for the United States. He called it “the Great Society” and laid out the vision of a country that did not confine itself to making money, but rather used its post–World War II prosperity to “enrich and elevate our national life.” That Great Society would demand an end to poverty and racial injustice.
But it would do more than that, he promised: it would enable every child to learn and grow, and it would create a society where people would use their leisure time to build and reflect, where cities would not just answer physical needs and the demands of commerce, but would also serve “the desire for beauty and the hunger for community.” It would protect the natural world and would be “a place where men are more concerned with the quality of their goals than the quantity of their goods.”
“But most of all,” he said, it would look forward. “[T]he Great Society is not a safe harbor, a resting place, a final objective, a finished work. It is a challenge constantly renewed, beckoning us toward a destiny where the meaning of our lives matches the marvelous products of our labor.”
Johnson proposed rebuilding the cities, protecting the countryside, and investing in education to set “every young mind…free to scan the farthest reaches of thought and imagination.” He admitted that the government did not have the answers to addressing all of the problems in the country. “But I do promise this,” he said. “We are going to assemble the best thought and the broadest knowledge from all over the world to find those answers for America. I intend to establish working groups to prepare a series of White House conferences and meetings—on the cities, on natural beauty, on the quality of education, and on other emerging challenges. And from these meetings and from this inspiration and from these studies we will begin to set our course toward the Great Society.”
Johnson’s vision of a Great Society came from a very different place than the reworking of society launched by his predecessor Franklin D. Roosevelt in the 1930s. Roosevelt’s New Deal had used the federal government to address the greatest economic crisis in U.S. history, leveling the playing field between workers and employers to enable workingmen to support their families. Johnson, in contrast, was operating in a country that was enjoying record growth. Far from simply saving the country, he could afford to direct it toward greater things.
Immediately, the administration turned to addressing issues of civil rights and poverty. Under Johnson’s pressure, Congress passed the Civil Rights Act of 1964, prohibiting voting, employment, or educational discrimination based on race, religion, sex, or national origin. Johnson also won passage of the Economic Opportunity Act of 1964, which created an Office of Economic Opportunity that would oversee a whole series of antipoverty programs, and of the Food Stamp Act, which helped people who didn’t make a lot of money buy food.
When Republicans ran Arizona senator Barry Goldwater for president in 1964, calling for rolling back business regulation and civil rights to the years before the New Deal, voters who quite liked the new system gave Democrats such a strong majority in Congress that Johnson and the Democrats were able to pass 84 new laws to put the Great Society into place.
They cemented civil rights with the 1965 Voting Rights Act protecting minority voting, created jobs in Appalachia, and established job-training and community development programs. The Elementary and Secondary Education Act of 1965 gave federal aid to public schools and established the Head Start program to provide comprehensive early education for low-income children. The Higher Education Act of 1965 increased federal investment in universities and provided scholarships and low-interest loans to students.
The Social Security Act of 1965 created Medicare, which provided health insurance for Americans over 65, and Medicaid, which helped cover healthcare costs for folks with limited incomes. Congress advanced the war on poverty by increasing welfare payments and subsidizing rent for low-income families.
Congress took on the rights of consumers with new protective legislation that required cigarettes and other dangerous products to carry warning labels, required products to carry labels identifying the manufacturer, and required lenders to disclose the full cost of finance charges in loans. Congress also passed legislation protecting the environment, including the Water Quality Act of 1965 that established federal standards for water quality.
But the government did not simply address poverty. Congress also spoke to Johnson’s aspirations for beauty and purpose when it created the National Foundation on the Arts and Humanities. This law created both the National Endowment for the Arts and the National Endowment for the Humanities to make sure the era’s emphasis on science didn’t endanger the humanities. In 1967 it would also establish the Corporation for Public Broadcasting, followed in 1969 by National Public Radio.
“For better or worse,” Johnson told the University of Michigan graduates in 1964, “your generation has been appointed by history to deal with those problems and to lead America toward a new age. You have the chance never before afforded to any people in any age. You can help build a society where the demands of morality, and the needs of the spirit, can be realized in the life of the Nation.
“So, will you join in the battle to give every citizen the full equality which God enjoins and the law requires, whatever his belief, or race, or the color of his skin?” he asked.
“Will you join in the battle to give every citizen an escape from the crushing weight of poverty?...”
“There are those timid souls who say this battle cannot be won; that we are condemned to a soulless wealth. I do not agree. We have the power to shape the civilization that we want. But we need your will, your labor, your hearts, if we are to build that kind of society.”
Kieran Healy kindly accepted my implicit homework assignment yesterday, and wrote a piece on Apple Sports’s bizarre “zero sum” team stats visualization:
It also doesn’t do away with the core problem. That problem is
principally one of information design rather than data
visualization. What I mean is that what we’re trying to organize
is, in effect, fifteen pairs of related but fundamentally distinct
numbers. If we had fifteen cases and two variables things
would be simple. But with fifteen variables and two cases … well,
this is not the kind of thing you can make a single effective and
non-confusing graph out of. That’s why I kind of sympathize with
the designer. In a constrained space they have to show thirty
numbers (thirty two, including the score). Lots of information. A
straight table seems like it would be boring. Surely there’s some
way to thematically integrate the numbers in a visually appealing
manner that brings out some of the relationships across the rows.
That’s what graphs do; it seems like the right thing to reach for.
But at its heart this information is not a graph. It just sort of
looks like one, and that ends up confusing people.
Just a crackerjack explanation for why this presentation in Apple Sports is confusing, and for why it is a difficult problem to solve. The problem is further complicated by the fact that Apple Sports shows the same screen for all sports, just with different sport-specific stats. I think the solution is to just present these numbers in a table. Yes, tables are boring. But they’re not confusing. What Apple Sports is doing, in an attempt not to be boring, is confusing.
Sidenote: Healy writes:
I don’t know much about basketball, but I do know a bit about data
visualization and in a pleasing coincidence my former student
Josh Fink is the A-VP of Basketball Data Science for the Spurs.
I don’t want to get Healy in any trouble, especially after he responded to my prompt with such a remarkably thoughtful, helpfully illustrated little essay, but I was under the impression that it’s illegal for any professor at Duke not to know much about basketball.
James Poniewozik, writing for The New York Times (gift link):
He didn’t land the pope, but he got a Beatle. He didn’t have a new
project to announce, but he left us with a song (in fact two). He
didn’t choose to end his show, but he ended it his own weird,
wonderful way.
Stephen Colbert hosted his final “Late Show” on Thursday night,
completing the story of the TV year’s most notorious and rancorous
cancellation. But his final hour-plus — an emotional and
delightfully bizarre wake for a comedy institution — turned it
into a cancellebration. [...]
In fact, the episode gradually revealed a story arc, more like the
closing episode of a surreal comedy than of a talk show.
Series finales are so difficult to do well. I find them compelling even when they fall a little flat. Colbert’s finale last night was just amazingly good. Good and fun and surprising and perfectly on-brand. And what a song to end on. Perfect.
Long argument short, Times New Roman isn’t bad, but it isn’t good. It is the median choice. But most of the circuit courts use it: the Third, Sixth, Eighth, Ninth, Tenth, and Eleventh. It could be worse: the First and Fourth not only use Courier New (the worst version of Courier, so of course it’s the one Microsoft shipped with Windows), but fully justify their text — contrary to the nature of a monospaced font. It could be better: the Second and Seventh use Palatino. (Note how much better that Seventh Circuit decision looks than the Second’s, with its wider margins creating a narrower column of text.)
But it can be much better. The Fifth Circuit was long typographically superior to its peers, using Century Schoolbook — a highly legible font with great tradition and the right vibe. But in 2020, the Fifth Circuit upgraded, switching to Equity, Matthew Butterick’s excellent type family (which, of course, is used throughout Butterick’s own web book, Typography for Lawyers). Here’s a before and after tweet noting the change. The results are typographically sublime (including improved margins).
The gold standard is the U.S. Supreme Court, which uses Century Schoolbook. Yes, I just praised the Fifth Circuit’s change from Century Schoolbook to Equity as an upgrade, but tradition and consistency have their place. The Supreme Court’s typographic style has been stunningly consistent for — no pun intended — well over a century. (If only that were true of their recent decisions. Rimshot.) Here is last month’s Louisiana v. Callais decision — the gerrymandering/redistricting case. Here is 1954’s Brown v. Board of Education. I’d give the nod to the older one, which made better use of proper small caps, but the overall consistency is obvious.
The text of every booklet-format document, including any appendix
thereto, shall be typeset in a Century family (e. g., Century
Expanded, New Century Schoolbook, or Century Schoolbook) 12-point
type with 2-point or more leading between lines. Quotations in
excess of 50 words shall be indented. The typeface of footnotes
shall be 10-point type with 2-point or more leading between lines.
The text of the document must appear on both sides of the page.
Every booklet-format document shall be produced on paper that is
opaque, unglazed, and not less than 60 pounds in weight, and
shall have margins of at least three-fourths of an inch on all
sides. The text field, including footnotes, may not exceed 4⅛
by 7⅛ inches.
Why the extra one-eighths of an inch instead of just 4 × 7? I don’t know. But 4⅛ × 7⅛ is exactly the size of the text field in the court’s own decisions.
Now compare the current 2026 rulebook to this edition printed in 1910 (with rules adopted in 1884). The consistency is striking — but, once again, the older version makes better use of small caps and just has a bit more vim and vigor to it. Just look at page 44, for example. It’s perfect. The current Court’s document formatters should aspire only to more closely ape the confidence and sturdiness of this older one. A century from now, U.S. Supreme Court decisions should look as similar to today’s as today’s do to those from a century ago.
The various circuit courts using lesser typefaces, looser margins, and lazier formatting should follow the Fifth’s lead and get their shit together. Tuck your shirt in, comb your hair, straighten your tie, and pop a mint in your mouth. If you’re a United States federal court, your typographic style should reflect that.
Back in 2020, Butterick took a well-deserved victory lap when the Fifth Circuit adopted Equity.1 He quoted Fifth Circuit Judge Don Willett, a typography fan who spearheaded the restyling project, on its rationale. Willett wrote:
[Why] did the circuit devote finite judicial energy to swapping
typefaces and widening margins? Simple answer: Our job is not
just to present clear opinions, but to present our opinions
clearly. Getting the law right is, of course, our tip-top
priority. Nothing matters more. ... But good enough is never good
enough. Our work is consequential, impacting the lives and
livelihoods of real people walloped by real problems in the real
world. The stakes are high, and we must present our best opinion,
not merely a passable one. And that presentation begins before
the first word is ever read.
In the very same post, Butterick sings the praises of the Apple Extended Keyboard II, and notes that he has several spares in reserve. I do keenly intend to take Butterick up on his standing offer to dine when next I’m in Los Angeles, but I worry that if we meet, we’ll trigger some sort of calamitous singularity of aligned taste. ↩︎
Following up on yesterday’s item re: Apple’s petition to the Supreme Court, here’s the Ninth Circuit ruling. It starts with a “Summary” that is specifically intended for the convenience of the reader. Page 50 is where it covers Apple’s argument regarding Trump v. CASA as precedent that an injunction on commissions should apply only to Epic Games, not to all developers in the U.S. App Store.
David Oks provides the clearest explanation I've seen yet of why consumer products that use memory are likely to get significantly more expensive over the next few years.
The short version is that memory manufacturers - of which there are just three remaining large companies - have a fixed capacity in terms of how many wafers they can process at any one time. This fixed wafer capacity is then split between DDR - used in desktops and servers, LPDDR - used in mobile phones and low-energy devices, and HBM - used with GPUs.
Until recently, HBM got just 2% of that wafer allocation. The enormous growth in AI data centers has pushed that up to an expected 20% by the end of 2026, and "a single gigabyte of HBM consumes more than three times the wafer capacity that a gigabyte of DDR or LPDDR does".
Memory companies have learned from the extinction of their rivals that you should always under-provision rather than over-provision your fabricator capacity. The profit margins and demand for HBM (high-bandwidth memory) will constrain the production of consumer-device RAM for several years.
This is already being felt in the sub-$100 smartphone market, which is particularly important to markets like Africa and South Asia.
(The original title of the piece was "AI is killing the cheap smartphone" but I'm using the Hacker News rephrased title, which I think does more justice to the content.)
We are back with another episode of Ashlee and Kylie gossiping about the latest in Silicon Valley.
First, a re-cap of our Alexandr Wang interview — his first real sit-down in eleven months — and what it actually revealed about Meta’s AI play. Wang seemed nervous hashing out the strategy in the studio, and we both keep circling the same puzzle: Meta has endless compute and top talent in Nat Friedman and Daniel Gross, so why does the model still feel underwhelming?
We get into Eric Schmidt getting booed off a commencement stage at the University of Arizona, which becomes a longer conversation about the generational fury aimed at AI. Everyone Kylie’s age seems to hate it, but is it due to misinformation or legitimate anger about jobs and data centers? Ashlee admits he’s more confused by this moment than anything he’s covered in tech: the predicted Wall Street collapse hasn’t come, the models keep getting better, and the valuations still make no sense.
Then, the news that broke minutes before we hit record: OpenAI won the Musk lawsuit on statute-of-limitations grounds. We dig into whether OpenAI’s shift from open-source nonprofit to for-profit was an original sin or just the only way to pay for the compute. Also, Ashlee’s texts with Sam Altman being part of discovery?!
In more Musk news, Bloomberg reported that Musk’s xAI stiffed staff on the $420 they were promised for feeding their tax returns into Grok. One host would decidedly not trust a chatbot with their financials, and the other already has. We also get into the strange new bedfellows: SpaceX selling compute to Anthropic, a company Musk has long been philosophically against.
We even take you behind the scenes at Core Memory — so study up and watch our latest videos on Phantom Neuro and Starfront Observatories. Consider this your homework on mind-controlled arms and galaxy photography. Essay due on our desk by morning.
Don’t forget you could win tickets to the Weezer tour by leaving an amazing review for our podcast wherever you listen.
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Hi, Paul Krugman here. Different city, different country, still not home. Unfortunately, couldn’t manage to do this one in a cafe, but we have been sitting in cafes a fair bit.
I just want to weigh in on a really kind of alarming report on consumer confidence that came out today. This is the long-running University of Michigan survey of consumer sentiment. It is kind of time hallowed. I don’t know that it’s necessarily the gold standard — there are other surveys — but this is the one that people really do focus on most.
The numbers are terrible, people. We’re hitting a record low on consumer sentiment which fits in with the general picture. We know that people are very upset about prices; they’re very upset about economic management; they just don’t feel that there’s anyone making any sense who’s in charge of things; which is all true.
I mean we can argue that objectively things are not as bad as all that. We have consumer sentiment that’s worse than at the depths of the financial crisis. We have consumer sentiment that is worse than during the stagflation circa 1980. And it’s hard to say that that’s really justified. But OK, the customer is always right. If people are feeling this down then we need to take that seriously.
But that is actually not the big issue. The really big issue is inflation expectations.
Now why do we focus on that? Inflation for a short period of time is not good but it’s tolerable. If we have a year of elevated inflation — even if you do something stupid, if you impose tariffs and raise consumer prices, or you start a war and mishandle it and you drive up oil prices that is not good. But it only turns into a really, really serious problem if it gets “entrenched” in the economy.
That is usually the term that people at the Federal Reserve use. And what they mean is this. If you think about how wages and prices are set, think about the process of inflation. Not all prices are set at the same time. There’s a kind of a leapfrogging in which each individual company, each individual employer is setting prices based both on inflation in the past and on inflation that they expect in the future. They’re looking over their shoulders at what they think competitors are going to be charging. They’re looking over their shoulders at what they think is going to happen to their costs.
And they need to do that because for many prices, it’s impractical and costly and disruptive to change them too frequently. So you set prices for a year in advance, something like that. You set prices for a while, which means that a lot of what’s happening to prices now is determined by what people think is going to be happening to prices in the future.
We don’t have great measures of what’s in the minds of people who are setting prices, but we have pretty good, or at least consistent over time, measures of what consumers expect. And, you know, we’re all living in the same society. So that’s telling you something about where we are in terms of expected inflation.
If you have a spike in inflation, if inflation comes and goes, but it doesn’t get built into expectations of higher inflation for a long time, then okay, you ride through it. Maybe people vote the bums out, but you ride through it.
If it gets built into expectations, then it’s a much a much more difficult situation. Then you have to somehow wring those expectations of high inflation out of the economy because if you don’t, inflation will just feed on itself. Prices will rise because everybody expects prices to rise and those expectations will be confirmed and it just goes on.
So if you want to return to an acceptably low rate of inflation and if people are expecting a high rate of inflation, then while there may be other ways, normally what we do is we put the economy through a wringer. which is what happened at the beginning of the 1980s.
After the inflation of the 1970s, inflation was eventually brought under control, but that would happen through years of extremely high punishing unemployment. Some people looking at inflation four years ago, looking at the inflation of 2021-2022 predicted that we’d have to do the same thing, that having seen a burst of inflation after decades of low inflation, that we were going to have to go through something like the end of the 70s stagflation, that we’d have to go through a severe recession with high unemployment for years to get inflation back down.
Something I called right — we all get things wrong, but something I called right — was that I said no, that that’s not going to happen, that it’s a false analogy. And the reason I said it was a false analogy was because medium-term expected inflation had not gone up very much.
Now, we go for medium term because we know that for short-term inflation, well, people’s expectations about that bounce around a lot, often driven by fluctuations in gasoline prices. But medium-term expectations are normally more stable, so if they rise that’s an indicator that you are starting to get entrenched inflation and things will be really bad.
In 2022 — sorry, let’s go back to 1980 — medium-term inflation expectations as measured by the Michigan survey were about nine percent — expected inflation over the next five to ten years was 9%. That was really bad. That said that people had basically internalized the inflation of the 70s and expected it to continue indefinitely.
This meant that actually getting inflation back down to tolerable levels was very costly and very painful.
In 2022, well, expected inflation over the next five years had crept up by a fraction of a percentage point, but it was still quite low. People were not at all building in anything like the expected inflation that prevailed before the great painful disinflation of the 1980s.
And so I was quite confident that the dire predictions about what it would take to bring that inflation back down were wrong.
Well, guess what? Especially in the last two months, expected inflation over the next five years has gone up a lot. It’s 3.9 percent in the latest Michigan release. That is, it’s not 1980 but it’s really bad. It’s the worst we’ve seen on that number since the early 1980s. It is saying that the person on the street is starting to believe after the tariff shock and now the Iran shock that we’re in a higher inflation environment. And we have to suspect that people making decisions about prices are thinking the same way.
They’re going to start building those expectations into pricing. So we’re starting to get the thing that everyone in the economics biz fears, which is entrenched inflation.
And if that’s happening, then the costs of the policy failures, the policy foolishness of the past year and a half are going to be a lot bigger than anyone is now reckoning. This is going to be an extremely painful situation that we have.
It looks, at least according to these preliminary indications, as if Donald Trump has managed to create the kind of environment that we had at the end of the 1970s stagflation, which means that this is going to be really, really ugly and that we are going to be paying the price for these misadventures for years to come.
Jeff Bezos went on CNBC earlier this week to opine about taxes and economic inequality. What he had to say wasn’t a shock: America’s 4th richest man praised billionaires and declared that he opposes taxes on the wealthy.
More surprising, perhaps, was how unprepared he was. Most of us, if we planned to spend almost an hour on national TV making pronouncements about taxes, would make at least some effort to get our facts right. Bezos didn’t.
But Bezos obviously suffers from billionaire brain, which I defined last year as
that special blend of ignorance and arrogance that occurs all too frequently in men who believe that their success in accumulating personal wealth means that they understand everything, no need to do any homework.
What was more interesting than the content of Bezos’s remarks was the fact that he chose to give the interview at all. Andrew Ross Sorkin, the interviewer, opened the discussion by saying
In these days, it feels almost impossible to pick up a newspaper without reading a headline about wealth in America, about the billionaire class, about wealth inequality and policy and everything else. And it’s taken a uniquely critical turn, I think.
Indeed. The critical turn has been especially severe for tech oligarchs like Bezos. And Bezos is obviously feeling the heat, sufficiently so that he’s trying — incompetently — to improve his image by “informing” the rest of us about how taxes and all that really work.
I’ll get to Bezos’s likely motivations shortly. First, however, let’s talk about the substance of his remarks.
Public discourse about taxes and inequality is, even more than discussion of other economic topics, infested with zombies — ideas that should be dead, having been proved wrong again and again, but that keep shambling along, eating people’s brains. What sustains the zombies is, of course, billionaire money, which keeps false claims in circulation as long as they seem to justify low taxes on the superrich.
Sure enough, it took Bezos only a couple of minutes to peddle a classic zombie lie about who pays taxes:
We already have the most progressive tax system in the world. The top 1 percent of taxpayers pay 40 percent of all the tax revenue. The bottom half pay only 3 percent.
These numbers aren’t remotely right unless Bezos is referring solely to federal income taxes — which are only part of the overall tax system. About 80 percent of Americans pay more in payroll taxes — FICA on your paycheck — than in income taxes:
Furthermore, state and local taxes generally fall more heavily on the working and middle classes than on the elite. As a result, the Institute for Taxation and Economic Policy has showed that the overall burden of taxes is only slightly higher for the affluent than it is for the working and middle classes:
These numbers are for 2019. Since then, the tax system has become even less progressive as a result of Donald Trump’s tariffs, which fall most heavily on lower incomes, and his tax cuts for the rich.
So Bezos doesn’t understand the most basic facts about taxes, nor did he make any effort to inform himself. He went instead with some numbers he thinks he heard somewhere — numbers that tell a story he wants to hear. As I said, billionaire brain.
Bezos also made some assertions about his own taxes:
These people sometimes say that, that, you know, I don’t pay taxes. That’s not true. I pay billions of dollars in taxes.
Seriously, does he want to go there? Yes, Bezos pays taxes. But ProPublica found that between 2014 and 2018 these taxes were less than 1 percent of his true income.
Bezos also decried corporate welfare. Again, does he want to go there? Amazon, like the oligarch who runs it, pays remarkably little in taxes as a share of its income:
I could go on: there was a lot of arrogant ignorance in that interview. But in a way the most interesting question is why Bezos gave it at all.
The answer, almost surely, is that Bezos is feeling the heat. There is a broad political backlash brewing against the excessive power of billionaires and the corrupting effect of their money on our democracy. This backlash is especially severe for tech oligarchs. A decade ago, Bezos and other tech billionaires were popular, almost folk heroes. No longer:
That slight uptick in 2025 is probably just a statistical blip — and there’s now a huge backlash brewing against AI. Here’s Eric Schmidt, the former CEO of Google, trying to hype AI in a college commencement address:
Last year Bezos and other tech billionaires evidently believed that they could insulate themselves from criticism — and secure their wealth against both taxation and regulation — by allying themselves tightly with Donald Trump. Notably, Amazon, along with Apple, Google, Meta, and Microsoft is one of the companies paying for Trump’s grotesque ballroom.
But Trump is now exploring new frontiers in presidential unpopularity, and Republicans are facing a wave of public revulsion so strong that it will probably overwhelm even their strenuous efforts to rig the midterm elections.
So paying court to the mad king isn’t looking like the smart political move Bezos and his ilk thought it was. How, then, can they defend themselves against the threat of taxes and regulations that might make them slightly less rich?
Well, Bezos evidently thought that the threat to his billions was sufficiently important to justify going on CNBC to lecture the rest of us about the evils of taxation — but not sufficiently important for him to learn a few facts first.
Somehow, I don’t think this new political strategy will work.
This is the fifth and last part of our series (I, II, III, IV, V) looking at how Carthaginian armies were raised and constituted. Over the last four parts, we’ve looked at the larger components of Carthaginian armies: the relatively small role of Carthaginian citizens, the more prominent role of North African conscripts, of Numidian and Iberian vassals, and of mercenaries and allies from Italy and Gaul. As we’ve noted, the place of many of these troops within Carthage’s armies changed over time, particularly in the third century as Carthage exercised a more direct presence in Spain, Gaul and Italy, thereby transforming mercenaries into vassals and allies.
To close off this week, I want to briefly discuss some of the ‘odds and ends’ of Carthaginian military forces that we haven’t gotten to yet, most notably the role of light infantry slingers from the Balearic islands and of war elephants. But I want to spend most of the time here discussing how these composite armies fight.
Now that, in and of itself, is a tricky proposition. For one, the composition of these armies quite evidently changed over time. Worse yet, for most of Carthaginian history, our sources provide us few battle accounts in which the dispositions and tactics are both detailed and reliable. We have a few early battle descriptions (mostly in Diodorus), but to put this effort at analysis on somewhat firmer ground, I propose to focus on the third century in particular.
But first, as always, raising large armies of mercenaries, subject conscripts, vassal warlords and allies is expensive! If you too want to help me invade Italy with a multi-ethnic army of diverse origins in a doomed effort to stop the Roman Republic, you can help by supporting this project over at Patreon. If you want updates whenever a new post appears or want to hear my more bite-sized musings on history, security affairs and current events, you can follow me on Bluesky (@bretdevereaux.bsky.social). I am also active on Threads (bretdevereaux) and maintain a de minimis presence on Twitter (@bretdevereaux).
Slings and Elephants
Before we get into the battles themselves though, we have a few more odds and ends to add to our armies, most notably Balearic slingers and war elephants. In both cases our sources don’t give us a ton of information to go on, but these were both regular parts of Carthaginian armies.
The residents of the Balearic islands had a well-earned reputation as exceptional slingers in antiquity; Phoenician settlement on the island of Ibiza in the seventh century steadily led the islands to drift into Carthaginian influence, making Balearic slingers available for Carthaginian armies, though as far as I know it remains very unclear how much actual governance Carthage exerted on the islands.
That said, while Balearic slingers are a recurring ‘specialist’ unit in Carthaginian armies, their numbers remain few. When we hear about their detachments, they’re really quite small. Hannibal, for instance, when disposing his forces in 218 sends 870 of his slingers to Africa and leaves 500 in Spain (Polyb. 3.33.8-16). While he is also taking some with him (so that is not a total count of his Balearic slingers) I think it is worth contrasting the scale of other troop movements in the dispositions: the force left in Spain is fifty-two warships, 450 African cavalry, 300 Spanish cavalry (Ilergetes), 1,800 Numidian cavalry, 11,850 Libyan infantry, and 21 elephants. 500 slingers seems a small detachment, in comparison. Likewise, the force heading to Africa was composed overall of 1,200 cavalry and 13,850 infantry alongside the 870 slingers. These are thus quite small detachments: small units of specialists rather than major contingents of an army.
From the excellent https://www.trajans-column.org/, a detail of scene 66 on Trajan’s Column showing a slinger, likely Balearian, with his sling and a set of slingstones; he wields a small shield as well, but is otherwise unarmored.
That said our sources (Polybius, mainly) often keeps track of them, so they’re a distinctive unit. In addition to the 1,370 slingers left behind, Hannibal took some number with him when crossing the Alps, but we can’t really track how many because in Hannibal’s army they always appear brigaded together with his lonchophoroi (who as you will recall, are also light infantry skirmishers, using javelins), in a combined unit of 8,000. I suspect that, at least by the time Hannibal is in Italy, the Balearians represent a distinct minority in that formation too. In that 218 disposition above, Hannibal (advancing into Spain reportedly with 90,000 infantry and 12,000 cavalry (Polyb. 3.35.1), a figure I suspect is inflated, but it is what we have), has essentially advanced on Italy with three-quarters of his force, splitting the remaining quarter to act as the core of armies to be formed up (if necessary) in Spain and Africa. That might imply something like 5,500 total Balearian slingers, of whom about 4,000 are with Hannibal. The problem, of course, is accounting for casualties: Hannibal loses half of his cavalry and three-quarters of his infantry getting to Italy (he drops into the Po River Valley with 20,000 infantry and 6,000 cavalry, Polyb. 3.56.4).
Even assuming a specialist unit like his slingers might have been spared the worst of the casualties, we might reasonably expect their numbers to at least be reduced by half, meaning that light infantry ‘brigade’ we see at Trebia might only have 2,000 (or even just 1,000) Balearians in it, with the rest made up of North African – and also perhaps Spanish or Gallic – javelin troops. Of course Hannibal’s army would subsequently expand back upwards with a fresh infusion of Gauls, such that by Cannae he had 50,000 troops (40,000 infantry, 10,000 cavalry), of which as noted above, at most we might expect a couple thousand to have been Balearian slingers.
In terms of equipment and fighting style, Balearic slingers fought unarmored, using slings and carrying small round shields, with spears for close-combat – though given their lack of armor, that must have been something of a weapon of last resort.1 So these were very light troops: very mobile, but not able to really stand up to anything. Hannibal never puts this mixed brigade into his battle line (that we’re told) – instead it is deployed as a screening force (Polyb. 3.72) or in rough ground (Polyb. 3.83) and withdrawing them before the main clash of infantry lines. Slings are really effective weapons in skilled hands – sling bullets can arrive with a lot of punch and be quite accurate at relatively long range – so even a small force of slingers mixed into a larger force of skirmishers would certainly make their presence known.
As for Carthage’s war elephants, we actually discussed war elephants at length way back in 2019. We may add a few notes here on Carthage’s elephants in particular. First, Carthage used war elephants, fairly regularly. The size of Carthage’s elephant corps seems to have been primarily limited by logistics: elephants were hard to move overseas (though it could clearly be done and the Carthaginians do it) and hard to keep supplied. Carthage had “nearly a hundred” elephants at Bagradas (255), supposedly 200 in Spain in 228 under Hasdrubal the Fair (Diod. Sic. 25.12; I suspect this number is quite inflated), but Hannibal marches out of Spain with just 37 elephants (Polyb. 3.42), leaving – as noted above – only 21 elephants behind, suggesting he only had 58 to start with.
Still my favorite Etruscan elephant plate (c. 275-270 BCE), from the National Etruscan Museum at the Villa Giulia in Rome. Given the Etruscan context of this famous plate, the elephant here might be Carthaginian, rather than Hellenistic. Interestingly, it is depicted with its calf in tow, which would make the grown elephant female, though generally only bulls were used as war elephants.
Carthaginian elephants, like Ptolemaic elephants, were drawn from the now-extinct North African elephant (Loxodonta africana pharaohensis), likely a relative of the smaller African forest elephant (Loxodonta cyclotis), not the bigger African Bush elephant (Loxodonta africana) you are likely more familiar with but which has never been domesticated. These North African elephants were smaller than the Asian elephant (Elephas maximus), which was a problem for the Ptolemies (who regularly faced Indian elephants in Seleucid service) but not really for Carthage. It is possible Carthage may have at times obtained Indian elephants in small numbers: Hannibal’s personal elephant was named Surus, ‘the Syrian;’ if he was from Syria, that would mean he was an Indian elephant imported by the Seleucids, although it seems equally likely to me that someone might name an uncommonly big North African elephant ‘Syrian’ because in its large size it resembled the larger Asian elephant (which a Carthaginian might associate with Syria – where the Seleucid elephant program was – rather than with India, where the elephants were actually from).
Of course ‘smaller’ doesn’t mean ‘small:’ male African forest elephants ‘only’ get to be about 7ft tall at the shoulders (compared to 9ft for Asian elephants and 10ft for African bush elephants), which is still a mighty big animal. As we discussed back in the original series on war elephants, the logistics demands of keeping elephants were substantial: they cannot be effectively bred in captivity so they must be captured and tamed and once domesticated, you have to feed them and they eat a lot. Nevertheless, they could be a clear military asset.
Alas, we know very little about how the Carthaginian elephant corps was organized: it’s unclear who the mahouts (the skilled elephant drivers) would have been or how they fit into Carthage’s mobilization system. It was clearly an important component of Carthaginian power – Carthage mints coins with elephants on them, likely as a symbol and expression of Carthaginian power (especially in places where elephants were not native, so the only elephants around would be Carthaginian war elephants).
Via Wikimedia Commons, a Carthaginian quarter-shekel from Spain, showing on elephant on the reverse. It’s striking to me that Punic coins with elephants on them seem more common in Spain and Sicily – where the elephants would have to have been imported – than in Africa itself, where they were native.
How a Carthaginian Army Fights
Unlike Roman, Macedonian or Greek armies, we don’t have any discussions of Carthaginian tactics from the Carthaginian point of view, or even artwork from Carthaginian contexts showing things like battles. The closest the sources come are some general comments by Polybius, which I think have to be treated with a great deal of caution. We’ve already seen that Polybius’ depiction of Carthage’s armies as wholly mercenary is at best deceptive. Likewise, his comment that Carthage “entirely neglects its infantry” and merely “pays some slight attention” to its cavalry (Polyb. 6.52.3) doesn’t stack up against the performance of Carthaginian arms in the third century: Carthaginian infantry appears, if less capable than the Romans, more capable than Greek or Macedonians, while Carthaginian cavalry appears flatly superior. So we have to be careful simply taking Polybius’ word for things when it comes to Carthage’s military ability.
That leaves us reliant on Carthage’s battles to understand how Carthaginian armies tend to fight. There are a few things to note here. First, in the third century, Carthage loses battles with Rome somewhat more often that it wins them – never nearly so lopsided as the Hellenistic record against Rome, mind you – even with Hannibal considered in the record. I want to note that out front because our sources tend to focus more on the occasions where Carthage wins against Rome (because it is to some degree surprising) and so that is when we tend to get something like a complete order of battle that lets us assess Carthaginian tactics. But I don’t want to give a distorted impression of effectiveness here: Carthaginian armies are a real threat that can beat Roman armies in the field, but the Romans win more than they lose.
All that said, I think there are some things we can say about how Carthaginian armies fight. These armies tend to be somewhat more cavalry heavy than Hellenistic or Roman armies, although they maintain a strong infantry ‘backbone.’ Tactically, because Carthaginian armies are so varied in composition (given the variable numbers of mercenaries, allies and vassals they may have), they tend to have much more varied dispositions than Roman or Macedonian armies (which both have a fairly ‘standard’ battle plan), but there is a preference towards envelopment using cavalry (as distinct, I’d argue, from Macedonian ‘breakthrough’ using cavalry). Finally, there is also a clear preference in placing mercenaries and auxiliaries in high-casualty positions that is remarkable, especially compared to Roman or Macedonian armies which tend to place their most reliably troops – who tend to be the highest status (citizen or Macedonian) troops in the center.
So let’s look at a few Carthaginian armies in action to see how this plays out.
The pitched battle from the First Punic War (264-241) we get the most details for is the Battle of Bagradas River (255), which is where Marcus Atilius Regulus’ (cos 267, 256) expedition to North Africa – which had been making gains – falls apart, necessitating a naval rescue mission to extract what is left of his army later that year. Polybius (1.33-34) is our best account of this battle and he doesn’t give us a ton of detail, but what he does give us, I think, is indicative of how Carthage expects to fight.2
The Carthaginian army, led in part by the Greek mercenary general Xanthippus, arrives with 12,000 infantry, 4,000 cavalry and nearly 100 elephants, which is a very cavalry (and elephant) heavy force, though it seems like nearly all of the infantry here is heavy African infantry (Libyans and perhaps also Carthaginian citizens). The Carthaginians draw up with the ‘phalanx of the Carthaginians’ in the center, with the elephants strung in a single line in front of them. Xanthippus puts his own mercenaries on the right wing – right where a Macedonian commander would have put his elite infantry in an Alexander-Battle formation – a but splits the remaining cavalry across both wings. The Romans seem to respond to the threat of the elephants by forming up unusually deep and thus also narrow (Polyb. 1.33.9-10), which turns out to have been the catastrophic mistake of the battle.
What ends up happening is that in the center, the Romans are able to push past the elephants, but have their lines disordered by it and as a result are thrown back by the Carthaginian heavy infantry. Meanwhile on the flanks, the numerically superior and more capable Carthaginian cavalry quickly routs the Roman cavalry and begins what we’ll see is a standard Carthaginian tactic – double-envelopment – wrapping around the Romans on the flanks. The one spot where the Romans perform well is, ironically, against Xanthippus’ mercenaries on his right (the Roman left), where the Romans are able to get around the elephants (and presumably inside the cavalry) to engage the Carthaginian right-wing and send it reeling back to camp (Polyb. 1.34.4). The envelopment proves fatal: no army can fight effectively if beset on all sides and the Romans are no exception (unless Julius Caesar is leading): repulsed in the center and then encircled, the Roman army falls apart, with the Carthaginians able to inflict heavy losses – all but 2,000 out of a force of 15,500 – in the rout.
What I think is most striking is that here already we see the Carthaginians doing what is going to become a standard approach in Hannibal’s battles, double-envelopment with cavalry. This is, I think, quite distinct from the Macedonian practice of ‘Alexander-battle’; somewhat ironically the Carthaginians essentially are doing the ‘Total War tactic’ that I spent some much time insisting the Macedonians do not do. Whereas the Macedonian approach is generally to try to ‘breakthrough’ with their cavalry often at the point where an army’s center joins one of its wings – and generally only on one flank, with the other flank merely buying time – the Carthaginians really are looking to ‘flank.’ Put another way, Macedonian cavalry goes through one side, but Carthaginian cavalry goes around both sides, aiming to disperse the enemy cavalry screen at the flanks and then loop around the flanks and rear of the enemy force rather than smashing through.
Vassals and Allies on the Battlefield
Moving forward chronologically, we can look at some of the dispositions of the Second Punic War to see some of the same patterns as at Bagradas, but also – because our sources (mostly Polybius, now with some Livy) provide more detail – some additional details.
After a major skirmish at Ticinus, Hannibal’s first major pitched battle in Italy is the Battle of the Trebia (218; Polyb. 3.71-4; Livy 21.54-56). Hannibal’s plan here is clearly another envelopment battle, similar in conception to Bagradas. Hannibal sets up a single line of ‘line infantry’ (both his African ‘heavies’ and his Spanish and Gallic ‘mediums’) in the center and his cavalry on the flanks. But he then does two things to reinforce his flanks: he deploys his elephants there, rather than along the center, and he has his skirmishers – initially deployed in front of his army as a screening force – retreat to the flanks once they had bested the Roman velites. The result is that Hannibal ends up stacking up his cavalry and elephants and skirmishers against the Roman cavalry on the flanks. That must have left his main infantry line somewhat thin: he has less ‘line infantry’ than the Roman force (probably around 25,000 Roman and socii heavies against c. 21,000 Carthaginian heavies and mediums, when you subtract out the velites and Carthaginian ‘lights’ (Balearians and lonchophoroi) and what he has is meaningfully lighter, but he has to match the same width.
Via Wikipedia, a decent map of the Battle of the Trebia after the Carthaginian lights had fallen back behind their main force and the Roman velites had been driven back. Livy and Polybius actually disagree slightly about where the elphants went: Polybius puts them in front of the cavalry, Livy out on the wings outside the cavalry (for some reason this map does neither).
But we get another interesting note here that, as we’ll see, is a trend. Polybius reports of Hannibal’s losses, “for they all were very glad about the battle, [thinking it] as a great accomplishment, for it happened that the losses of the Iberians and Libyans were few, most of the losses being of the Celts” (Polyb. 3.74.10). Now given what Polybius has told us – that the Gauls, Iberians and Africans are all in one line – it’s not quite clear how that outcome happens (the Iberians, at least, are no more heavily armored than the Gauls!), but as we’re going to see, it is something of a pattern.
Hannibal’s next major battle is at Lake Trasimene (217) but this is something of a rarity: an actual ambush at battle-scale rather than a pitched battle. While ambushes are common in small actions, it is actually quite rare for one field army to ambush another: field armies are so big they are quite hard to hide and tend to have a lot of scouting. That makes this kind of ‘true’ large-scale ambush quite rare, but it also means the dispositions and tactics aren’t really applicable to the more common pitched battles. There is, however, one detail that is worth noting, which were the casualties among the Carthaginians, of which Polybius says (Polyb. 3.85.5), “He [Hannibal] now rested his own [troops] and honored the dead of the highest ranks, thirty in number; the overall losses were fifteen hundred, of which most were Celts.”
Which gets us to Cannae (216), which I have analyzed elsewhere and so needn’t do in detail here. The plan is once again double-envelopment using cavalry deployed on the flanks and a relatively weak center, with Hannibal’s innovation here coming in two parts: first the center is arced forward to invite the Romans to attack it and second Hannibal pulls his North African troops – his heaviest and most reliable – into two formations that sit on the flanks of the combined Spanish and Gallic ‘medium’ infantry main line. The result, famously, is that the Romans, when they push back the Gallic-and-Iberian center, will put the Africans around their flanks, while Hannibal’s cavalry first disperses the Roman cavalry and then completes the encirclement by striking the advancing Roman infantry force in the rear.
Via Wikipedia, a decent enough diagram of the Battle of Cannae’s opening positions, although the map on my WotR article is somewhat better.
Now there are solid tactical reasons to arrange the army this way – Hannibal does, after all, win the battle – but it is hard not to see another consideration at work: almost all of the heavy losses are guaranteed to be sustained by the Iberian and Gallic troops. By contrast, the North African troops, who are by this point every bit as heavy as Roman troops (Polyb. 3.114.1; Livy 22.46.4) are not placed into the thick of things but held off onto the side, where they mostly avoid the brunt of the Roman assault. The Numidian cavalry seems to have been given orders to skirmish, to ‘tie up’ Rome’s socii cavalry, while it is the Iberian and Gallic cavalry that has to punch through and attack to create the encirclement.
There is a consistent pattern here of risking Iberian and Gallic troops in order to preserve Carthaginian, African and Numidian troops. And the result is predictable. Polybius (3.117.6) gives Hannibal’s losses at Cannae as, “of Hannibal, the Celts lost 4,000, the Iberians and Africans 1,500 and the cavalry 200.” One wonders, given that division of losses, if – when Polybius says that the Gauls and Iberians are in the center – Hannibal has in fact put the Gauls in the absolute center (furthest forward), with the Iberians on their wings and the Africans on the Iberian’s wings, essentially creating a ‘spectrum of peril,’ with the Gauls in the most dangerous spot and the North Africans in the safest.
Hannibal’s deployment at Zama (Polyb. 15.11; Livy 30.33) echoes this concern: he puts the elephants out in front (like Xanthippus at Bagradas fifty years prior) and then in his first line he puts Ligurians, Gauls, Balearians and Mauritanians: his skirmish specialists (the Balearians) and then all of his expendable auxiliaries. He may have intended these fellows to retreat to the flanks like at Trebia, but in any case he made no preparations for them to withdraw down the center – when they did so they were cut down by the next line (Polyb. 15.13.3-10). Then behind that line he places his North African and Carthaginian citizen troops – fresh levies from North Africa; the Romans would have put these greenest troops in the front, but Hannibal shelters them in his second line. Finally, perhaps having learned something from the value of the Roman triarii, Hannibal puts his own veterans in a third, final line in the rear.
Had Hannibal won at Zama, rather than lost, we’d presumably have had another line of Polybius about how the great majority of his losses were taken by the Gauls and Ligurians (and Mauritanians) that he threw forward at the outset of the battle.
That said, we get quite a different approach at the Battle of Metaurus (207). The sources for this battle are, I should note, something of a mess (with Polyb. 11.1-3 and Livy 27.48 not quite agreeing), but a mess that is untangled quite capably by J.F. Lazenby, Hannibal’s War: A Military History (1998), 189-90. Hasdrubal’s army is a mix of Iberians, Gauls and Ligurians, with thirty elephants. Hasdrubal’s problem is that his army is quite outmatched and he knows it, fighting the battle because he has no other choice, having not yet had time to fortify a camp. The battlefield had hilly terrain on Hasdrubal’s left, so he seems to have settled on a gambit of trying to concentrate all of his combat power on the right so as to smash the Roman left.
What is striking then is that Hasdrubal stacks his right – the ‘hammer’ arm – with his elephants and his Iberians, places his Ligurians in the center (where they need to hold) and then puts his Gallic troops up on the hill on his left. It suggests that he doesn’t have a whole lot of faith in those Gauls, because in the event the hill is sufficiently steep that the Romans can’t even really approach their position (Polyb. 11.1.5). In the event, the Romans win when C. Claudius Nero, commanding the Roman right (making no headway up that hill and realizing it), detaches part of his force to extend the Roman left (while leaving a pinning force), wrapping around the flank of Hasdrubal’s right-flank-hammer. But what I think is notable is that where Hannibal – confident and expecting victory – exposes his Gallic troops to let them take the brunt of the losses, Hasdrubal – panicked and merely trying to avoid defeat – puts his Gauls where they can do the least harm.
Both sentiments seem to suggest that the Barcids, at least, held their Gallic allies in relatively low esteem: expending them when convenient but avoiding relying on them whenever possible.
Conclusions
Carthaginian armies were complex creatures – far more so than something like a typical polis army. What I find perhaps most interesting is that for the most part, expansive Carthaginian recruiting was more about broadening Carthage’s base of military resources than it was about acquiring specific capabilities. Carthaginian generals do not seem to use Gallic, Ligurian, Iberian, Greek or Italian troops in dramatically different roles than their own North African troops. Indeed, Gallic and Iberian ‘mediums’ are deployed as line infantry the same as Carthaginian citizen or North African ‘heavies.’ We do not get, for instance, the fairly clear contrast in positioning and usage between ‘heavies’ and ‘mediums’ that we see in Hellenistic armies, though of course they have a pike-phalanx to consider. Instead, when Carthage recruits in Gaul and Spain, they seem to want more troops rather than different troops. After all, they already have capable javelin light-infantry (North African lonchophoroi) and heavy line infantry, they just want more of those roles.
The exceptions are clear: Balearic slingers and Numidian cavalry. These are specialist troops that supply new capabilities – longer-range skirmishing (a factor, for instance, at Trebia, where they outrange and outshoot the Roman velites) from the slingers and highly capable, fast-moving skirmish cavalry from the Numidians. Carthage’s heavy cavalry in turn, is a mix of Carthaginian citizen cavalry, North African cavalry, and Iberian or Gallic cavalry – depending on what is available given the time period and location.
The result was not necessarily a more tactically complex army – Carthaginian armies seem to have had fewer moving parts than Roman ones – but the challenge of leading such a polyglot, multicultural army must have been considerable, as Polybius himself alludes to (Polyb. 1.67.4-9), especially when the very recruiting principles of these troops were different: some citizens, some conscripts, some mercenaries raised with money, some allies raised with promises, some vassals raised through very particular personal relationships with the generals themselves. That complexity may serve to explain to some degree why Carthage preferred long-serving generals over a regular rotation: the relationships generals established and their personal knowledge of their armies would have been difficult to pass on. By contrast, Roman armies, while more tactically complex, where organizationally much more ‘plug-and-play,’ each army working more or less like the next.
There is a frustrating tendency in the scholarship to denigrate Carthaginian war-making and I suspect the rather ‘motley’ nature of these armies – which do not look very much like the western ‘ideal’ of an army (uniform and almost mechanical in its function, a ‘war machine’) – contributes quite a lot to this. But Carthage was a military over-performer, especially in the third century: Carthage withstood Pyrrhus and was able to go two full rounds (and one more) with Rome, albeit losing in the end.
I’ve mentioned this before, but the contrast with the Hellenistic kingdoms of the East is so striking: Carthage spends a combined forty-years at war with Rome in the third century, peaking at more than 160,000 men in the field, matching Rome on land and at sea,3 matching the Roman capability of fighting in multiple theaters simultaneously and not-infrequently defeating Roman armies. By contrast, in the second century, the Seleucids and Antigonids manage to fight Rome for just fourteen years combined (including the Fourth Macedonian War, which isn’t even an Antigonid war!), lose every major battle and never manage to put more than 80,000 soldiers or so in the field at any one time (the Antigonids don’t even get close to that).
In short, if we understand the complex Carthaginian mobilization system as an effort to reach more broadly for military resources, we ought to understand it as a success. Carthage, from 254 to 201, deploys massively more military resources than comparable large (larger in the case of the Seleucids) Hellenistic states.
That said, the system was not without flaws. The largest was that it was quite obviously more fragile than its Roman equivalent. Hannibal, despite stunning victories, struggles to get a critical mass of Rome’s socii to revolt. By contrast, Carthaginian control in both North Africa and Spain was relatively more easily disrupted, as shown by the Mercenary War (241-237), the collapse of the Barcid system in Spain after the Fall of Carthago Nova (209) – although Carthage continued to maintain large armies in the area for another five years – and the ability of Rome to draw the Numidians away from Roman service through Masinissa’s defection in 203.
Via Wikipedia, a Numidian coin showing a Numidian king, possibly Masinissa (r.203-148) or perhaps Mcipsa (r. 148-118). Interestingly, that Numidian king is represented in Hellenistic style, complete with a Hellenistic diadem, an intentional employment of Greek symbols of kingship in a very non-Greek context.
It is also worth noting that while Carthage’s strategy of recruiting non-state warriors from Spain and Gaul enabled it to field a lot of raw manpower, the warriors they got in the bargain were not as heavily or expensively equipped as either the Romans or Carthage’s own North African troops. The Carthaginian system was thus one that, by the Second Punic War, if not earlier, was forced to seek quantity over quality in order to match the staggering effectiveness with which the Romans had turned Italy into a machine for the generation of military power.
I also suspect, had the Carthaginians not been defeated by Rome, that their system of long-serving generals setting up veritable fiefdoms abroad would have eventually spelled disaster for the Carthaginian Republic. In a sense, we watch this same development play out in the Late Roman Republic, but the Barcid private empire in Spain was if anything even more of a private fiefdom than anything enjoyed by the Late Republic’s ‘rogue generals.’ One imagines, had Carthage continued with an empire that other Carthaginian figures would feel compelled (as rival Roman dynasts felt so compelled in the first century) to establish their own bases of power, leading to predictable results.
All of that said, Carthage’s military system deserves better than to simply be treated as a failure or – even more inaccurately – as the product of an ‘unwarlike’ people. Certainly, the Carthaginians were not able to overcome the Roman Republic – but no one else, not the ‘warlike’ Gauls or the ostensibly more ‘western’ (despite being more eastern) Hellenistic kingdoms – no one else was able to either.
Carthage got the closest, by far, for which the Romans would never forgive them. Ironically, had the Carthaginians been worse at war, Carthage might well have lasted longer.4
SpaceX’s first Starship Version 3 rocket takes off from Pad 2 at Starbase during the Flight 12 mission on May 22, 2026. Image: SpaceX
SpaceX launched a revamped Super Heavy-Starship rocket Friday on an “epic” flight to test more powerful engines, enhanced control systems and a host of other upgrades needed to streamline operations and improve safety and reliability.
One of the Super Heavy booster’s 33 methane-fueled Raptor 3 engines shut down early during the climb out of the lower atmosphere and additional engines failed to run properly during an attempt to fly the stage back to its planned splashdown point off the Texas Gulf Coast.
The Starship upper stage was equipped with six third-generation Raptor engines and one of three optimized for operating in vacuum shut down early during the climb to space. The flight computer kept the other five engines running longer than originally planned to make up for the shortfall, putting the craft on an acceptable sub-orbital trajectory.
It was not immediately known what might have triggered the premature engine shutdowns, but once in space, the Starship appeared to perform in fine fashion, deploying 22 Starlink internet satellite simulators from an upgraded Pez-like dispenser. Two of those were equipped with cameras that sent back images of the Starship from the viewpoint of the simulators.
Those cameras will be used on future flights to assess the health of the spacecraft’s heat shield.
Despite the engine issue, SpaceX founder Elon Musk thanked company employees.
“Congratulations @SpaceX team on an epic first Starship V3 launch & landing!” Musk posted on his social media platform X. “You scored a goal for humanity.”
NASA Administrator Jared Isaacman, who flew in to watch the launch, added his own praise.
“Congrats @SpaceX team and @elonmusk on a hell of a V3 Starship launch,” Isaacman posted. “One step closer to the Moon…one step closer to Mars”
The upgraded Super Heavy-Starship blasted off on time at 6:30 p.m. EDT from a new, beefed up pad at SpaceX’s Starbase launch site on the Texas Gulf Coast. Launch followed a last-minute scrub Thursday due to a minor glitch with a launch pad system and two weather delays before that.
Generating up to 18 million pounds of thrust — twice the liftoff power of NASA’s SLS moon rocket — the 33 methane-burning Raptor engines at the base of the Super Heavy first stage pushed the 407-foot-tall rocket skyward atop a brilliant torrent of blue-white fire.
It was the first launch of a redesigned “version 3” Super Heavy-Starship and the first use of SpaceX’s second Texas launch pad, designed to better withstand the rigors of repeated launches by the world’s most powerful rocket.
Two minutes and 24 seconds after liftoff, now out of the dense lower atmosphere, the Starship upper stage’s six Raptors ignited just before the Super Heavy first stage fell away.
The booster immediately flipped around as planned to reverse course and head back toward Starbase for a controlled splashdown in the Gulf while the Starship upper stage continued the climb to space.
But multiple Raptor engines did not fire as expected and the booster was not able to reach the planned splashdown point, presumably dropping into the Gulf well short of its target.
The Starship upper stage reached an acceptable sub-orbital trajectory despite the single engine failure it experienced. The Starlink simulators were successfully deployed but a planned in-space Raptor restart was not attempted.
Splashdown confirmed! Congratulations to the entire SpaceX team on the twelfth flight test of Starship! pic.twitter.com/XXBAtryPpL
The test flight ended on a positive note as the Starship endured the fiery heat of re-entry in apparently good shape with little of the thermal damage seen on previous flights.
During the descent, the ship successfully carried out a maneuver intended to test the structural limits of its rear fins, followed by a dramatic banking maneuver like future Starships will carry out during normal landing operations.
Just before reaching the Indian Ocean, the Starship re-started two engines, flipped to a vertical orientation and descended to an on-target splashdown. It then tipped over as expected, broke apart and exploded in a spectacular fireball.
Other than the single Raptor failure during ascent, the Starship appeared to meet SpaceX’s expectations, coming through the stress of launch and re-entry in apparently good shape.
Version 3 test flights are major milestones for SpaceX as the company works to perfect the first fully reusable rocket for operational use launching government and commercial satellites along with science probes and, eventually, piloted flights to Mars.
The flights also are critical to NASA, which is paying SpaceX to develop a version of the Starship upper stage for use as a lander to carry the agency’s Artemis astronauts to the surface of the moon starting in 2028. Shortly thereafter, NASA plans to begin launching multiple missions per year and to build a base near the moon’s south pole.
In the near term, NASA plans to launch its next Artemis mission in 2027, sending up four astronauts in an Orion capsule atop an SLS rocket to rendezvous in Earth orbit with SpaceX’s lander and an alternative being built by Jeff Bezos’ Blue Origin.
NASA plans tests with both landers during the Artemis III mission, but the flight will proceed even if only one is available. Both companies must launch a successful unpiloted moon landing mission before the agency will attempt to land astronauts in 2028.
Neither company has yet put a moon lander in space and both face daunting test schedules. With version 3 of its showcase rocket now available, SpaceX is working to transition from sub-orbital test flights to orbital missions while continuing work to perfect the systems that will be needed for moon missions.
A major challenge is the ability to autonomously refuel a Starship lander in Earth orbit before it can head for deep space. The version 3 Starship now features the attachment points and fuel-transfer systems that will be needed for those operations.
SpaceX says the first in a series of orbital refueling tests is planned before the end of the year.
The Deep Space Advanced Radar Capability (DARC) Site 1 in Western Australia is already delivering early tracking data for AUKUS partners, with full operational capability targeted for 2027. This milestone […]
SpaceX’s IPO prospectus casts Starlink Mobile as more than a remote-area backup, with next-generation direct-to-smartphone services designed to be “on par with terrestrial mobile networks” even in urban areas.
SpaceX launched the newest version of its Starship vehicle for the first time May 22, completing most of the test objectives planned for the suborbital flight.
Until this past weekend, a contractor for the Cybersecurity & Infrastructure Security Agency (CISA) maintained a public GitHub repository that exposed credentials to several highly privileged AWS GovCloud accounts and a large number of internal CISA systems. Security experts said the public archive included files detailing how CISA builds, tests and deploys software internally, and that it represents one of the most egregious government data leaks in recent history.
I have a bunch of actual newsletter-type personal news update items I need to share, so I figured I’d share them all at once as a kind of life update. Taken together it feels like a definite phase shift. I guess this might be my Act 2 finally getting started? I feel like I’ve been promoted to Regional Manager of the Internet.
It’s a bit all over the place (“the fox has many Act 2s, the hedgehog has one big Act 2”?), but also all around fun in a way that feels like it should be illegal in the grimdark climate of today. Still I’m not complaining.
Protocol Institute
The Summer of Protocols program I was leading for the last 3 years is spinning out as The Protocol Institute. , who was a researcher in the first cohort, will be leading the new org as Managing Director, and I’m going to be the Director of Research. I wrote about my plans in that capacity last week in our magazine, .
As you might expect, we’re looking to raise funds, so if you like the sound of what we’re up to, get in touch at venkat@protocol-institute.org. If you know any organizations or high-net-worth individuals that might be interested, introduce me to them.
The program to date has been running at about a million a year since 2023, almost entirely bankrolled by the Ethereum Foundation, but with small amounts of support from other sources. The EF told us to stop living in the basement and go get a job, so that’s what we’re going to try and do. We’re hoping to raise $1.5-2 million for 2027. Timber and I are working on a pitch deck, and I’ll share in this newsletter in the next few weeks.
This is the first time I’ve gotten involved in a non-solo startuppy team thing in 15 years. The SoP program started out as a narrow solo consulting gig around the growth problems of Ethereum, but over three years morphed into a much bigger thing — research, fieldwork, education, field-building, publishing, scene-making, and hundreds of alumni/participants of various programs worldwide. It was initially meant to be a transient program to jumpstart a broader conversation around protocols (which it more than did), but the more we dug into the topic, the more we realized that we were exploring a huge and weirdly unexplored and undertheorized invisible current in technology evolution. So around a year ago, we started talking about doing what is now PI.
And then the agentic AI explosion happened, and it rapidly became clear that protocols were going to collide explosively with AI in an epic evil-twins type encounter, like Godzilla meeting King Kong.
We have a bit of spin-out funding from the Ethereum Foundation that will last us through the end of the year, after which we have to find funding or Timber and I turn into pumpkins at midnight on December 31, 2026. More tragically, the fragile young field of protocol studies will turn into a pumpkin and you don’t want that to happen.
Long Now Labs
One of the first programs of the new institute is a collaboration with the Long Now foundation, through its new Labs program, led by . There are two open grant opportunities, The Book of Time and Epistemic Cycles. As befits my new Act 2 éminence grise status, I’m on the jury for the program even though I’d rather be competing.
The success of this program will greatly increase the chances of Timber and I not turning into pumpkins, and of the Protocol Institute getting tangled up with AI to make benefit future of planet by inventing New Nature.
Apply for these grants if you have ideas. Tell your creative friends to apply.
Strange Rules/Monsters Between Worlds
On a related personal note, my Bucket Art project has evolved into an installation collaboration with Famous Actual Artist ™ Simon Denny called Monsters Between Worlds (a reference to my Gramsci Gap essay among other things) at the Strange Rules art exhibition at the Venice Bienalle, devoted to the emerging Protocol Art scene (which the Summer of Protocols program helped meme into being).
The two pieces facing each other in the center of the picture below are plotter-based reinterpretations of my Boat #1 and Sun #2 bucket art pieces. The black and white one on the right wall is based on the cover of one of the Summer of Protocols essays, Protocols in (Emergency) Time, by Olivia Steiert.
I can take some credit for inspiring the name of the show too 😎, via my essay Strange New Rules on last year, which kicked off our efforts to develop the protocol fiction genre (now 3 anthologies and 40+ stories old). I’m now memeing at institutional levels.
The Strange Rules show is curated by Famous Actual Artists™ and Holly Herndon, and godfathered by Hans Ulrich Obrist of the Serpentine Gallery, who was once described to me as the “pope of the art world.” I’ve known this crowd casually for about a decade, but this show marks my formal debut into the art world.
Right at the top. It’s the only way. My Not-Yet-Famous Real Artist™ friends are all jealous of me.
And I didn’t even have to tape a banana to a wall.
It cracks me up that I’ll likely never be published as a “real writer,” but I’ve acquired a top-tier artist credential almost entirely by accident. If you’re going to be in Venice this summer, stop by the Palazzo Diedo (which houses my old pals the Berggruen Institute) and check it out. I haven’t checked it out myself yet, but will likely be there in October for the closing if the airlines still have fuel to fly then.
vgr_zirp Update
My vgr_zirp bot experiment on the resurrected archival Ribbonfarm has been unexpectedly successful, creating a bit of a problem for me, since it’s now burning API dollars.
The whole point of the migration to a cheap static-site setup initially was to save big on hosting. Now it looks like the bot will cost more to run than the old blog. So I’m in the market for some tastefully well-aligned sponsorships to keep building and provisioning this. You can see some house sponsorship banners rotating on the bot’s pages. I’d like to put some paying-sponsor banners there.
In the couple of weeks since I launched it, readers have logged over 1500 sessions, costing me over $150 in API fees, and the usage is rising steadily, causing me some anxiety.
The use case I anticipated, which is readers old and new diving into the content archives, is the second most common use case. The most common use case (and I guess I should have seen this coming) is people using the bot as a much cheaper consultant/advisor than me. This thing is terking muh jerb and I’m having to literally train my replacement 🤣.
I’m currently working on a couple of peer bots covering current writing, other corpuses like my past academic work, my Secret Consulting Notebooks, etc. and ways to turn the set of bots (tentatively named mixture_of_vgrs) into a true self-disrupting consultant. (I also made a similar but less mature bot, C3PO, trained on the Protocol Institute archives).
I’m getting lots of comments on how unique vgr_zirp is, and requests to share the construction methodology. It’s evolved significantly past the soul.md pattern I started with, but isn’t yet cleaned up enough to release as a reusable template, since it’s all very artisanal and bespoke and heavily tuned to my material.
It’s also turned into an absolutely fascinating technical project (see details here) that I want to keep evolving. I didn’t think it would be this easy to get to the artisanal AI frontier but apparently I’m doing at least a couple of things nobody else is.
You can read the publicly shared chat transcripts here, and also subscribe to them via RSS. Basically, what I thought would be an unchanging museum site is turning into a kind of coral reef of secondary content on a scuttled ship.
I guess Ribbonfarm is having its own Act 2, independent of mine.
World Machines Project
A brief heads up. The World Machines Project (WMP) I kicked off a few weeks ago is now live as a collaborative effort by half a dozen contributors at worldmachines.org.
The Prime Radiant is starting to take shape, and the vibecoding of psychohistory has begun. Join us. This month we’re reading Revolution in Time in the Contraptions Book Club, which is the feeder activity for WMP, so we’re currently figuring out how to engineer a suitable temporality into the Prime Radiant.
TensTorrent
Finally, I want to mention TensTorrent, the AI hardware startup I’ve been consulting for since 2019, which has been my other big gig besides the protocols work. The CEO, Jim Keller, is my oldest client (I’ve been working with him since 2011, across AMD, Tesla, Intel, and now TensTorrent).
This is easily the most technically exciting work of my consulting career, right at the esoteric bleeding edge of frontier AI, and it’s finally entering the industry spotlight. I still can’t actually talk about my work there due to NDA constraints, but finally enough information is public that you can explore for yourself. If you’re a low-level AI developer, check out their developer hub, and there is also a cool QuietBox AI workstation you can buy (I’m lusting after it myself, but can’t yet justify it till I improve my lower-level AI chops).
You can try out the tech yourself here on the demo cloud. If your company is looking to own its own AI hardware/IP infrastructure, TT should definitely be on your radar. If you’re interested, I can introduce you to their sales folks.
First Thoughts on Act 2
This feels like it’s going to be a year of serious changes for me. I bought a house (and went into serious debt 😬) for the first time at age 51 two months ago, while all this was unfolding. At the same time I was going through the at-once cathartic and bittersweet project of archiving Ribbonfarm properly (that was before the bot gave it a weird and unexpected new possible lease on life).
It feels like not just the beginning of my Act 2, but the beginning of my personal exit from the Gramsci Gap the world’s been in since 2015, when I tagged it the Great Weirding. But it also feels like it’s going to be a long time before the whole world is out of it, so it’s a precarious sort of contingent exit.
As I said, it feels like it should be illegal to be moving on into the new world amid the gathering grimdarkness. My Be Slightly Monstrous slogan from last November (aka -1mo BCC; Before Claude Code) feels justified now. I keep thinking a Balrog-style bigger monster is going to derail AI and drag us early-exit types back into the gap by our ankles.
The old world dying, the new world struggling to be born, and I’m monstrously having fun even as elsewhere events are teetering on the edge of horrifying.
One way or another, Act 2 is going to be very interesting.
I was thinking last night about the denouement of the Broadview Six case, a collapse which I’m told by some legal observers stands a non-trivial chance of seeing some of the prosecutors disbarred. And I contrasted it with the series of TPM Reader emails about the “fancy lawyers.” A number of these emails start out with some version of, I’m not part of the legal elite, I’m just working here in the trenches as a lawyer in [this or that mid-sized city in the United States]. Or maybe, my background is in elite law but I’m down here in the trenches, etc.
Let me say upfront, in advance of what I’m about to write, that I certainly recognize that these are to an extent caricatures, idealized forms in a binary account which can break down quickly when examined up close. But caricatures exist because they contain essential, revealing truths. And when I thought about yesterday’s events in that courtroom in Chicago, I had this strong sense of this is the rule of law we’re fighting for and these are the people who are fighting. And this matters so much more than that world of legal-speak mystification telling ordinary but knowledgable Americans that what their Constitution says is something that can only be plumbed by someone with rock-star reasoning skills and an Ivy League JD.
We’ve seen many versions of this during the ICE reign of terror across major American cities. It shows both the strengths of the real and meaningful rule of law as well as the key democratic elements of our judicial system that have tended to hold up much better under the Trumpist assault than most of the bill of goods we’d been sold on at the elite levels of power. Grand jurors simply refused to bring indictments, a heavy, heavy lift since a grand jury is a collection of ordinary citizens, few of whom have probably ever been on a grand jury before, whose only source of facts or legal counsel is the prosecutor trying to get the indictment. Jurors acquit after minutes or hours, often in ways that blur ordinary factual analysis with jury nullification (which whatever you’ve heard is a totally legitimate part of the judicial process).
In the Broadview case, you had a number of defense lawyers, in several cases former AUSAs from the same U.S. Attorneys office, fighting tooth and nail against what was clearly an abuse of prosecutorial power or just a comically weak case but one that at least seemed legitimate in the narrow sense. By this I mean that the case shouldn’t have been brought and was almost certainly headed to an acquittal but was arrived at through a proper process. They pushed every button and felt for every weak point. And over the last month, first slowly and then in a torrent, the whole thing fell apart: because from day one it was tainted by a scale of prosecutorial misconduct the judge, herself a former prosecutor, said she’d “never seen” in a lifetime of reviewing grand jury transcripts.
Defense attorney Chris Parente, after quipping that the defendants appeared to be good candidates to receive paydays from Trump’s “weaponization fund,” noted that this misconduct mattered far beyond the fate of the remaining four defendants. “It does impact other cases. I know there are other cases right now where people are trying to get grand jury transcripts, and other judges are trying to weigh, like, is the U.S. Attorney’s Office acting in the right way? And based on what I’ve heard having come out of that office, I’m sick to my stomach about what you just described to me. And if it happened here, I can tell you that it’s probably happened in other offices …”
What happened in this case didn’t come from one of Trump’s clown show DOJ lawyers, one of those ones who’ve never tried a case or are known more as Trumpy influencers. All the key actions appear to have come from career lawyers in that office. Now, maybe they were always crooked prosecutors. It’s certainly not that prosecutorial conduct is unknown. But the particular actions in this case speak to a broader contagion — some mix of political pressure and corrupt disinhibition.
If I’m understanding the transcript of yesterday’s closed door hearing correctly, the key misconduct at the grand jury was the work of Sheri Mecklenburg, a 20-year veteran of that office who was the original lead lawyer on the case. Back in February, seemingly out of the blue and with no apparent warning, she withdrew from the case and announced she’d been assigned to work on the Senate Judiciary committee under Sen. Dick Durbin (D-IL). (That’s where she’s working now. Curious whether Durbin has any comment.) The Broadview case was always some mix of abusive and laughable, a wildly overcharged case, which is now again evidenced by the fact that Mecklenburg had to repeatedly commit grave prosecutorial misconduct to secure an indictment. It simply doesn’t add up to me that a career prosecutor, near retirement eligibility, would commit what I’m told is disbarment level misconduct on behalf of a case like this without some major outside force being involved. Possible? Of course. But given the larger political context in which this happened, pretty unlikely.
Nor should we ignore the possibility of disinhibition. If the attorney general is openly crooked and violating his oath, why not? There’s no punishment or consequences.
Regardless, we need to find out. We’re seeing the ultra-high-profile cases where DOJ lawyers indict a former FBI director over a photo of seashells. But there are certainly many more cases out there like what happened in Chicago. And we need to find out all about it.
Following up on the points outlined in the immediately previous post, this evening House leadership abruptly canceled a war powers vote because they realized it might pass.
All power is unitary. Every victory or defeat in one area strengthens or weakens you everywhere else.
More fallout from yesterday’s courtroom drama in Chicago. The original prosecutor in the Broadview Six case, Sheri Mecklenberg, withdrew from the case with little or not advance notice in late February and announced she was taking a position as a DOJ detailee working for the Senate Judiciary committee under Sen. Dick Durbin (D-IL). The hearing yesterday pointed to her as the source of most or all of the grand jury misconduct though not the redactions part of the misconduct, which took place after her departure.
I saw a baby jaywalking. I saw the most pregnant woman in the world jaywalking. I saw two kids jaywalking on their hands, a man jaywalking with a chair on his head. I saw cops jaywalking. I saw people on every mode of transport jayriding in every possible direction; a guy on a one wheel breaking a land speed record, a scooter, a bike, a double bike, a unicycle, a silver stallion. Where was Casey Neistat? I didn’t see him. But I saw a man jaywalk with his buttocks very out, wearing only angel wings and a golden cup on his nuts. I saw a nun jaywalking while smoking a joint. Weed was everywhere. People smoked cigarettes with joyful impunity, butts flicked hither and thither because The Floor is the Garbage. All the toilets are mostly broken. A middle-aged white woman two seats down from me used the word “fuck” more in a minute than I’ve used in a lifetime. Another middle-aged white woman broke into tears at the sight of Colin Jost, fanning herself saying omg omg omg like she was fourteen and the Paul McCartney had just appeared (he’d appear next week). I saw people yelling into cellphones, crying into cellphones, taxi drivers whispering in Hindi into cellphones like they were running an OnlyFans ASMR account for fans in Delhi. Make note: It’s illegal to walk your dog without taking a phone call here. I’ve seen a thousand people kissing, a million people hugging. Someone did human diarrhea in front of us as we walked near Washington Square Park. Here be Robert Frank’s old home and studio around the corner from CBGB, which is now a shop selling expensive suits. I saw the bald villain from A Princess Bride. He’s a tiny one! I watched him monologue in a small theater on the edge of (in the?) West Village for two hours and only “rested my eyes” a couple of times despite being jet-lagged out of my mind.
The really good news is, as of 9am this morning, D.C. had no homicides for an entire week, unlike the last two weeks which were bad. At this time last year, D.C. had experienced 59 homicides, compared to 31* this year, so this is a vast improvement. There were increases in some other crime categories, though robberies decreased slightly.
As has been the case throughout the year, car-related crimes and muggings (officially “robberies”) are down dramatically compared to the same time last year. Hoping for another homicide-free week next week: the weather should be nicer next week, so we’ll have to wait to see if more people will be out and about instead of hunkering down inside. Still great news though.
*Three of the 34 murders reported this year actually occurred in other years (e.g., a missing persons case from 2023 turned into a homicide case this year with new evidence).
Here's the short version, from the issue's overview in World in Brief.
"Alvin Roth investigates repugnant markets
"Would you like to buy a kidney? How about heroin? Or sex? Don’t worry: you haven’t wandered down the wrong alley—these and other morally questionable transactions are the subject of a new book by Alvin Roth, a Nobel-prize winning economist. Published in Britain on Thursday, “Moral Economics” looks at the murky world of “repugnant transactions”: deals in which buyers and sellers happily transact, but which onlookers would rather ban on moral grounds.
"For Mr Roth, moral economics is about trade-offs. Are the harms of allowing an activity greater than those of disallowing it? Policy, he argues, should weigh both. Two principles emerge. First, bans never fully work: motivated buyers and sellers find workarounds. Second, prohibition generally reduces the size of the market; it would be cheaper and easier to buy heroin if it was legal. It might also be safer. That leaves Mr Roth asking whether the restrictions or the market cause more harm. Here, too, the answer is that it depends."
###########
And here's a link to the longer review, from the Free Exchange column. That column is unsigned, but others on the web have attributed it to Gavin Jackson, who did interview me about the book. Here is the resulting review:
My review of the review is that it missed some of the nuances in my book, but many aspects of the big picture came through clearly:
"The picture that emerges from the book is of a deeply moral person, who believes in bodily autonomy, in not subordinating individual lives to a collective and in not accepting unnecessary deaths to spare some people from feeling squeamish."
SpaceX got within 40 seconds of launching the first flight of a taller, more powerful version of its Starship rocket Thursday, but a pesky problem with the launch tower kept the vehicle bound to Earth for at least one more day.
Clouds and rain showers cleared the area around SpaceX's launch site in South Texas, leaving mostly sunny skies over the Starship launch pad Thursday afternoon. SpaceX pushed back the launch time by one hour, but the countdown appeared to proceed smoothly once propellants began loading into the rocket.
That was true, at least, until the countdown clock paused 40 seconds before liftoff. The launch team repeatedly attempted to resume the countdown, only for the computer controlling the launch sequence to stop the clock again. There were five holds in all before SpaceX called off the launch attempt.
Congress left for the holiday weekend a day early today after a number of Republican members of Congress appear to have mutinied against President Donald J. Trump and his loyalists.
Trump’s $1.776 billion slush fund and his agreement with acting attorney general Todd Blanche that the government would not prosecute him or any of his associates for crimes related to tax laws apparently were a bridge too far for a number of Republicans, especially as his job approval rating has fallen to a grim 34%.
Republican senators met for nearly two hours today with acting attorney general Todd Blanche in a meeting that Andrew Desiderio of Punchbowl News reported was “incredibly hostile.”
Republicans were angry they had no advance warning about the plan, questioned the legal basis for the fund, were unhappy with Blanche’s descriptions of how payments would work, and said they wanted no part of it. As former Senate majority leader Mitch McConnell (R-KY) put it: “So the nation’s top law enforcement official is asking for a slush fund to pay people who assault cops? Utterly stupid, morally wrong—Take your pick.”
As many as 25 Republican senators spoke out against the slush fund and pitched ideas about how to draw some limits around it. Scott MacFarlane of Meidas News reported that senators want to know “what is Trump trying to mask by offering up this controversial fund? I mean, the optics of this are terrible. This looks bad, so is it a diversion technique? Is it some way of masking a different issue altogether?”
Dan Alexander of Forbes reported today that the tax immunity Todd Blanche is extending to Trump could save him more than $600 million on the estimated $1.4 billion he made in 2025 from crypto and licensing ventures and on the $100 million hanging over him from a previous tax bill.
Michael Gold and Carl Hulse of the New York Times reported that Republican frustration with the White House has been exacerbated by anger that Trump has intervened in Republican primaries to sink Republican incumbents he thinks have been insufficiently loyal to him.
One Republican senator texted Desiderio to say: “Our majority is melting down before our eyes.”
In the end, Republicans were so angry about the slush fund and immunity agreement that Senate leadership decided not to try to pass $72 billion of funding for immigration agencies, left out of an earlier funding package, out of fear Democrats would force Republicans to vote on the slush fund.
Even before they decided to avoid the vote, Republicans had dropped from the measure the $1 billion Trump wants for security for his ballroom.
House Republicans had their own meltdown. House Republican leaders pulled a vote to stop Trump’s war on Iran based on the War Powers Act, recognizing that they did not have the votes to defeat it. Representative Brian Fitzpatrick (R-PA), who voted with Democrats to pass such a measure last week, told Megan Mineiro, Robert Jimison, and Michael Gold of the New York Times that the next time the measure comes to a vote, it will pass.
As members head home to observe Memorial Day, the solemn remembrance of those Americans who gave their lives to defend the nation, they will likely hear an earful from their constituents about the $1.7 billion slush fund, the promise of immunity over Trump’s tax crimes, the $1 billion Trump is demanding for his ballroom, Trump’s unpopular war on Iran, and now the administration’s increasing threats against Cuba and Greenland, Trump’s unpopular war on Iran, and now the administration’s increasing threats against Cuba and Greenland, and about dramatically increasing prices.
On Tuesday, four Republicans joined Democrats to advance a resolution against the Iran war in the Senate. “Vote by vote, Democrats are breaking through Republicans’ wall of silence on Trump’s illegal war,” Senate minority leader Chuck Schumer (D-NY) said. “Today proved our pressure is working: Republicans are starting to crack, and momentum is building to check him. We are not letting up.”
I think active listening is the term that the team came up with for “something that sounds fancy but really just means the way ad targeting platforms work already”. Then they got over-excited about the new metaphor and added that first couple of slides that talk about “voice data”, without really understanding how the tech works or what kind of a shitstorm that could kick off when people who DID understand technology started paying attention to their marketing.
This FTC press release appears to confirm that's pretty much what happened:
CMG, MindSift and 1010 Digital Works claimed their “Active Listening” branded marketing service listened in on consumers’ conversations overheard by smart devices, in real time, to target advertising [...]
According to the complaints, this service did not, in fact, listen in on consumers’ conversations or use voice data at all—nor did the service accurately place ads in customers’ desired locations. Instead, the service the companies provided consisted of reselling—at a significant markup—email lists obtained from other data brokers.
The FTC also clarify that hiding an "opt-in" to using voice data in terms of service would not be acceptable, as tricks like that do not constitute "adequate consent":
The FTC also alleged that all three companies deceived potential customers by claiming that consumers had opted into the Active Listening service. The company, however, did not seek or obtain consumers’ consent, according to the complaints. Instead, the companies claimed that consumers had “opted in” by agreeing to the terms of service that people have to accept when downloading and using apps. Clicking through mandatory terms of service does not constitute “opt-in consent” for such an invasive service or for use of consumers’ voice data from inside their homes. If the Active Listening service had functioned as advertised, this collection and use of consumers’ voice data without adequate consent would itself violate Section 5 of the FTC Act.
Attempting to myth bust the conspiracy theory that our mobile devices target ads to us based on spying through the microphones continues to be my least rewarding niche online hobby. It's nice to have a new piece of ammunition.
Speaking of Apple and sports, here’s another one from Apple Newsroom:
This Saturday, May 23, Apple TV will present a special live Major
League Soccer match captured exclusively on iPhone 17 Pro — marking the first time iPhone will be used to capture the entirety
of a major professional live sporting event broadcast. Developed
in partnership with MLS, the milestone broadcast will feature the
LA Galaxy vs. Houston Dynamo FC, streaming live on Apple TV from
Dignity Health Sports Park in Carson, California, during the final
weekend of MLS play before the regular season pauses for the FIFA
World Cup 2026 in North America.
The word “major” is doing a bit of work in the phrase “major professional live sporting event” here, but it’s still quite a moment for iPhone photography. Apple started using iPhone 17 Pro cameras during Friday Night Baseball games last year, but this will be the first event to use them exclusively.
Apple today filed a request with the Supreme Court in an attempt
to reverse key lower court rulings over the App Store injunction
in its long-running legal battle with Epic Games. [...] In its
petition, Apple is asking the Supreme Court to review two
questions.
The first is whether Apple should have been held in contempt for
charging a commission on purchases made outside the App Store. The
second is about the scope of the injunction.
On the first point, Apple argues that the original injunction did
not specifically address commissions. Instead, it says the order
only prevented Apple from blocking developers from including
buttons, external links, or other calls to action directing users
to external purchasing options.
According to Apple, that is not the same as saying the company
could not charge a commission on those purchases. The Ninth
Circuit acknowledged that the text of the injunction did not
address commissions, but still upheld the contempt finding by
relying on the idea that a party can violate the “spirit” of an
injunction, even when the injunction does not specifically
prohibit the conduct at issue.
Apple’s argument here is that only the letter of the law matters, and the letter of the injunction did not say anything about charging commissions on external payments, and thus they can’t be held in contempt for violating something that was never spelled out explicitly.
As for the second point, regarding scope, Apple argues that the
injunction extends far beyond Epic itself, as it applies to all
registered developers worldwide with apps on the U.S. App Store
storefront. That includes developers that were never part of the
Epic case, and, as Apple has pointed out before, even companies
that compete with Epic.
Apple argues that this directly conflicts with the Supreme Court’s
2025 decision in Trump v. CASA, which limited the ability of
federal courts to issue broad injunctions that go beyond the
parties actually involved in a case.
Apple’s argument here is that even if the Supreme Court upholds the contempt finding, the exemption from commissions should only apply to Epic, not to all developers in the U.S. App Store. I am definitely not a constitutional law scholar, but I think this would have been a long-shot argument pre-CASA. But post-CASA I think Apple might have something here, with this Court.
Vegetation damaged by an EF-3 tornado in southern Mississippi appears in a tan line in an image acquired on May 12, 2026, with the OLI (Operational Land Imager) on Landsat 8.
NASA Earth Observatory/Lauren Dauphin
A powerful supercell storm produced multiple tornadoes across southern Mississippi on May 6, 2026. The longest and most powerful spanned five counties, delivering wind speeds up to 137 miles (220 kilometers) per hour and EF-3 damage, as gauged by the Enhanced Fujita Scale, to several areas.
Part of this tornado’s destructive path was visible to the Landsat 8 satellite when it passed over the area on May 12. Winds snapped, uprooted, and tore bark and branches off trees, creating a brownish track across the landscape. This area, south of Brookhaven in Lincoln County, was one that sustained EF-3 damage. National Weather Service (NWS) post-event damage assessments noted extensive tree damage, a home whose exterior walls collapsed, and a mobile home park “devastated with debris.”
The tornado covered much more ground than is captured in this scene. It began in St. Catherine Creek National Wildlife Refuge near the Mississippi River, approximately 60 miles (100 kilometers) west-southwest of Brookhaven. In just over two hours, it traveled nearly 82 miles (132 kilometers), placing it among some of the longest tornadoes recorded in Mississippi. Heavy tree damage occurred along its entire path, NWS surveys found, with several instances of EF-2 structural damage and bent or collapsed transmission towers.
Seven tornadoes occurred in Mississippi on the evening of May 6, according to NWS preliminary data as of May 20. The Mississippi Emergency Management Agency received reports of damage to more than 400 homes and dozens of businesses and farm buildings statewide after the storms, according to a news release, the majority of which were in Lincoln County.
The Gulf Coast and other southeastern states are not considered part of what’s commonly known as Tornado Alley, an area encompassing much of the U.S. central and southern plains where supercells tend to form. However, this belt of southeastern states is also tornado-prone, experiencing a relatively high frequency of tornadoes in spring and late autumn. Historically in Mississippi, the most monthly tornadoes—an average of more than seven—occur in April, while May averages just over three. Some recent analyses have found decreases in tornado frequency in the Great Plains and increases in the Southeast over several decades.
NASA Earth Observatory images by Lauren Dauphin, using Landsat data from the U.S. Geological Survey. Story by Lindsey Doermann.
It is important to see a few different developments coming together today up on Capitol Hill. As you likely saw there was a mini-revolt today among Senate Republicans over Trump’s slush fund and, to a secondary degree, over the ballroom. Because they wouldn’t agree to back the slush fund, they just left and went on recess. Not exactly a huge profile in courage. But it’s also at least delayed Trump’s new ICE funding bill. The ballroom, the slush fund, the ongoing retribution tour — these are all Trump’s big obsessions right now, as I noted this morning. But in something like a meta-ten-car pile-up, the different self-soothing efforts are bumping into each other. Trump just knee-capped Sen. Cassidy in Louisiana (he lost his primary) and Sen. Cornyn (endorsed primary challenger Ken Paxton). Two careers ended. Two senators who are really embittered. Trump also blindsided other Republican senators when he endorsed Paxton. They had no advance warning. Totally out of the blue. Party discipline is a thing. But you do it wisely. Trump’s made Cassidy, Tillis and perhaps now even Cornyn into chaos agents going into the midterms.
The point is, the retribution tour is colliding with the building spree and the Deserving Fascists Slush Fund. None of them have anything to do with helping the GOP in the midterms. The wheels are coming off.
It’s one of my bywords that all power is unitary. You don’t have it abroad and lack it at home, or have it on one issue and not on another. You’re always losing power or gaining it. And for a president, the gains and losses apply across the spectrum. There’s simply no strategy here. There’s impulse. There’s executive self-soothing. He’s reacting to his declining popularity at home by doing things that are making him less popular. He’s trying to push things through the Senate while antagonizing and assaulting the senators whose votes he needs.
These senators aren’t standing on any kind of principle. They’re looking at the midterms and trying to prevent their incumbents from having to defend payoffs to guys who assaulted cops, hit them with flag polls, took dumps in various congressional offices. They also don’t want to force their incumbents to give a billion dollars to build Trump’s ballroom while the voters are overwhelmingly focused on high gas prices and inflation.
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