For the past 18 months, we’ve been filming the rise of robot fights in San Francisco and beyond. What began as something of a curiosity morphed into a wild drama, and we’ve turned the whole thing into an eight-part docuseries. It’s entertaining, funny, heart-warming and quite insane.
The story follows a group of people who start out together, hoping to turn robot fights into the next big form of entertainment. But they soon break apart and go to war with each other, creating rival fight teams REK and UFB. As the story goes on, the robots get bigger and bigger and so too do the fights and the stakes and the drama.
The series captures this weird moment in time – AI meets robotics meets SF culture – in the most unexpected of ways. It’s a robot story, but it’s really a story about humans trying to make their way in this bizarre world.
Core Memory subscribers will get all the episodes early as they roll out. We can’t wait to show you what we’ve made.
A new report from the analytics firm Quilty Space confirms that, outside of China, the world faces a significant shortage of rockets over the next five years.
The firm estimates that between now and 2030, there will be a shortfall of about 150 launches compared to demand from satellite operators and civil space agencies. If demand from the US military is added in—and SpaceX does not extend the Falcon 9 and Falcon Heavy program to accommodate increased national security needs—the shortage could be doubled.
"What we wanted to get at is to understand how severe this launch crisis is and when will it be resolved," said Caleb Henry, director of research at Quilty Space. "What we learned is that the launch crisis is more severe than we thought and that it will not go away this decade for sure, and it might not abate until sometime late in the 2030s."
Lay long in bed with my wife, and then up and a while at my office, and so to the Change, and so [home] again, and there I found my wife in a great passion with her mayds. I upstairs to set some things in order in our chamber and wardrobe, and so to dinner upon a good dish of stewed beef, then up again about my business. Then by coach with my wife to the New Exchange, and there bought and paid for several things, and then back, calling at my periwigg-makers, and there showed my wife the periwigg made for me, and she likes it very well, and so to my brother’s, and to buy a pair of boddice for her, and so home, and to my office late, and then home to my wife, purposing to go on to a new lesson in arithmetique with her. So to supper and to bed. The Queen mends apace, but her head still light.
My mind very heavy thinking of my great layings out lately, and what they must still be for clothes, but I hope it is in order to getting of something the more by it, for I perceive how I have hitherto suffered for lack of going as becomes my place.
After a little discourse with my wife upon arithmetique, to bed.
Travel day, so just one chart — the Federal Reserve’s preferred measure of inflation, the last big data release before the midterms. Trump likes to stick his name on things, but this time he would be entirely justified: He personally built this, first with his tariffs and then with his war.
File photo of a Falcon 9 fueled for launch at Vandenberg Space Force Base in California. Image: SpaceX.
SpaceX looks to cap the month of October with the launch of a Starlink mission from Vandenberg Space Force Base on Friday night.
The Starlink 15-18 mission on the eve of Halloween will add another 27 broadband internet satellites to the company’s low Earth orbit constellation.
Liftoff from Space Launch Complex 4 East is scheduled for 9:02 p.m. PDT (12:02 a.m. EDT / 0402 UTC). The rocket will fly on a southeasterly trajectory upon leaving the pad.
Spaceflight Now will have live coverage beginning about 30 minutes prior to liftoff.
SpaceX will launch the mission using the Falcon 9 first stage booster with the tail number 1093. This will be its 18th flight following the launches of Transporter-16, two missions for the Space Development Agency, and 14 batches of Starlink satellites.
Nearly 8.5 minutes after liftoff, B1093 will target a landing on the droneship, Of Course I Still Love You, positioned in the Pacific Ocean. If successful, this will be the 231st landing on this vessel and the 675th Falcon booster landing to date.
Winding down Falcon, ramping up Starship
The launch anticipated for the eve of Halloween will be SpaceX’s 11th and final orbital flight in October. While that number of launches in a calendar month far exceeds that achieved by other launch providers, it comes as SpaceX is starting to wind down the Falcon program as it turns its focus to Starship.
NASA and others have publicly acknowledged that SpaceX looking to end offering the Falcon 9 for commercial and government missions in the next few years. The company’s decreasing launch rate reflects this change.
The Starlink 15-16 launch on Oct. 27 was the first time since July 2025 that SpaceX’s launch rate dropped below 150 orbital launches in a 365-day period. For comparison, at its peak, SpaceX reached a peak of 171 orbital launches in 365 days in December 2025.
In August, SpaceX ceased flying Starlink missions from Florida using its Falcon 9 rockets. A smattering of launches have flown from the Sunshine State since, including NASA’s SpaceX Crew-13, CRS-35, and Bandwagon-5, which flew in October.
This is the breakdown of all of SpaceX’s orbital launches over the course of 2026 across Cape Canaveral Space Force Station, Kennedy Space Center, Starbase, and Vandenberg Space Force Base:
January – 13 total (6 CCSFS, 1 KSC, 6 VSFB)
February – 12 total (6 CCSFS, 6 VSFB)
March – 15 total (8 CCSFS, 7 VSFB)
April – 12 total (4 CCSFS, 1 KSC, 7 VSFB)
May – 11 total (5 CCSFS, 6 VSFB)
June – 13 total (5 CCSFS, 9 VSFB)
July – 13 total (5 CCSFS, 8 VSFB)
August – 13 total (5 CCSFS, 1 KSC, 7 VSFB)
September – 8 total (1 CCSFS, 1 Starbase, 6 VSFB)
October – 10 currently (3 CCSFS, 1 KSC, 6 VSFB)
SpaceX is expected to start launching orbital Starship missions on a regular basis beginning in 2027. During the third quarter earnings call earlier this month, SpaceX founder Elon Musk pointed to the anticipated ramp up in Starship launch cadence.
“We expect Starship to fly weekly at some point in the first half next year and then second half next year, twice weekly or maybe even more frequently by the end of next year,” Musk said. “The rate at which we launch Starship will increase dramatically as we solve rapid and complete reusability.”
Musk went onto state in that call that SpaceX’s plan to attempt a catch of their Starship upper stage during the next flight of the more than 400-foot-tall rocket. That mission, Starship Flight 15, is anticipated to launch in mid-November from Starbase, Texas.
Teams accumulate code faster than they accumulate trust. That gap — code without trust — is where projects fail.
I have been circling this idea for two years in this newsletter. Trust accumulates slowly and evaporates in an instant. Most trust-building work is invisible. AI has poured accelerant on the visible parts. Code arrives faster than ever, while the practices that manufacture trust — collaboration, testing, review, shared understanding — quietly get sacrificed to solo speed.
So I am teaching a live class about it.
The Human Practices Behind Trustworthy Software runs on ByteByteGo Live, November 9th & 10th. It’s part of a new partnership with ByteByte to help me speak to a larger audience sustainably.
Each day is a 2-hour lecture followed by an hour of open Q&A. Two days, roughly the shape of the argument I have been making here, made concrete:
The trust problem. Trust in the product vs. trust in the process. Why trust breaks faster than it heals, and why its economics matter — trustworthy software lets customers spend less time guarding against risk and more time using the thing.
The XP practices that manufacture trust. Testing, pairing, continuous integration, planning, customer on the team, continuous deployment, refactoring, observability. Not as a checklist — as a system.
The principles underneath. Humanity, mutual benefit, improvement, flow, redundancy. The XP values — communication, simplicity, feedback, courage, respect — as a trust-manufacturing system, not a poster on the wall.
Trust-optimized AI-assisted development. This is the part I most want to get across. The tweak paradox: trustworthiness of code falls with the square of the size of changes. AI wants big batches, trust wants small verified steps. Single-player vs. multi-player: everybody is going to push you into solo AI development, and it is a huge mistake. Slowing down in the right places is how you go faster.
It’s for engineers and engineering leaders. It’s live, so you can argue with me in real time — the hour of Q&A each day is my favorite part of the format.
I have also made sure of a few practical things. Every session is recorded, so if the time zone is unkind you can catch up. Many folks expense it through their learning & development budget, and ByteByteGo provides an invoice and an email template for your manager.
A million caveats, because that’s how I operate. This is a paid class, and it’s not cheap. If your team already trusts each other completely and your AI workflow is humming, you don’t need it. (I have never met that team, but statistics says you’re out there.) And the ideas are all related to things I have written here — the class is the concentrated, worked-through version, with exercises you do on your team, not mine.
(That link gets you the details & the current pricing on the available courses, let them know I sent you)
One more thing. This class is the answer to a question I have been asked weekly for a year: “Okay, I believe you about trust — now what do I do on Monday?” This is the Monday version. I hope to see you there, and I hope you argue with me.
Welcome to Edition 9.17 of the Rocket Report! It's been a while since an American company announced plans for a medium-lift new launch vehicle, but that's what happened this week when a startup named Cowboy Space revealed specs for its Big Iron rocket, named for the classic country-western song by Marty Robbins. I'm a huge fan of the name. Maybe Cowboy Space is striking while the iron is hot as the space industry frets over demand for launch outpacing supply. However, Cowboy Space lags far behind so many other launch providers nearing the launch pad with their medium-class rockets, and the company didn't have much hardware to show at this week's big reveal. In other words, don't mistake style for substance. But we're rocket fans at Ars, and we wish them luck.
As always, we welcome reader submissions, and if you don't want to miss an issue, please subscribe using the box below (the form will not appear on AMP-enabled versions of the site). Each report will include information on small-, medium-, and heavy-lift rockets as well as a quick look ahead at the next three launches on the calendar.
Virgin's new rocket plane reaches home port. The first of Virgin Galactic's new Delta-class rocket planes left its Arizona factory Wednesday for a trip to Spaceport America in neighboring New Mexico, where it will undergo preparations for a test campaign culminating in suborbital flights to the edge of space, Ars reports. Virgin Galactic expects the craft's first commercial spaceflight to take place "early" in the second quarter of 2027, but like every other projected date in aerospace, this should be taken with a grain of salt. Virgin Galactic halted commercial flights of its previous vehicle, VSS Unity, in 2024.
Oct. 30, 2026 – ESI Motion Inc. is proud to announce that it is supplying the Solar Array Drive Electronics (SADE) to Lockheed Martin for its work on the Space […]
This is the back half of the last part (I, IIIIIa, IIIb, IVa) of our series looking at the vision of history advanced by Hearts of Iron IV, Paradox Interactive’s World War II grand strategy game and one of the most popular strategy games on the market today.
In the front half of this part, we looked at how Hearts of Iron IV understands industry and production, the game’s economic model. On the one hand, the military production model is interestingly nuanced and complex and the decision to simplify the civilian half of the model, in light of the game’s focus, makes a fair bit of sense. On the other hand, the game stumbles quite badly in that it – mostly for reasons of balance (a desire to make Nazi Germany more likely to win than it was historically – constructs an economic world where discredited Nazi theories of economics which were quite decisively humiliated during the war itself are instead represented as right and true. HoI4‘s economic system (unintentionally) employs the tremendous persuasive power of simulation to create the appearance that the Nazis and fascists did make the trains run on time.
Industry is going to remain relevant in this part, where we’re going to talk about HoI4‘s conception of strategy and in particular strategic ends. Paradox games are deservedly famous for not featuring many explicit ‘win states’ and allowing the player to define victory. At the same time, different game systems still push players to think about ‘winning’ in different terms. To take an extreme example, few players are going to define a ‘victory condition’ to be something the game doesn’t even track or simulate.
Here again, HoI4 is a victim of its streamlining: it is mostly interesting in having World War II and profoundly uninterested in the implications of World War II. It exists, in many ways, in a world without strategic ends and the strategic ends it does track – military size and map painting, primarily – are, like so many of its other design choices, fundamentally the ‘victory markers’ that mattered most to the Axis powers and least to the Allies, especially the western allies. Hearts of Iron IV thus, in its careless streamlining adopts in its strategic ends – as with so many of its other systems – an unintentionally fascistic vision of history, one in which what really matters is purely military strength and the ability to dominate.
Finally, this being the conclusion, we’re going to ask what the implications for all of these choices across all four parts are. Hearts of Iron IV has a lot to recommend it – the operational simulator is very impressive – but also quite a few flaws. Most of all, viewing these flaws together, one cannot be surprised that this is a game with a serious Nazi problem. Of course any World War II game is going to attract that sort to some degree, but we can hardly be surprised if a game whose systems repeatedly, if unintentionally, adopt a fascist ideological position is going to have a particularly intense Nazi problem.
Hearts of Iron IV shows World War II as modern neo-Nazis like to pretend it was and so it is unsurprising that they are drawn to the game – albeit, we must note, alongside a great many players who are not ideological Nazis.
But first, if you like what you are reading here, please share it, as I rely on word of mouth to replenish my manpower pool after poorly considered post topics. If you really like it, you can support me, my academic work and my public writing, including this project on Patreon! I can’t promise to use your support to buy a division worth of tanks, but I also will not promise not to do that. 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).
We stopped in our United Kingdom run last time right at the formation of the Commonwealth of Nations. This is the resulting mega-Britain that forms, with Canada, South Africa, Australia, New Zealand and India all absorbed into a single state with the United Kingdom. In practice the game is basically over at this point. Massively expanding my core territory (although India is counted as non-core), gives me access to a lot more manpower and – as you can see – a huge number of effective factories, pushing me past even the United States in economic production. In terms of the war against the Axis, the outcome is, at this point, effectively decided – the question is not ‘if’ but ‘when.’
What Is It Good For?
We should begin by discussing strategic ends. Countries in the real world do not wage wars (usually) simply because they like bashing their tanks and airplanes together the way a small child plays with toys (or a large child plays with Hearts of Iron), countries typically have aims they hope to achieve in war. In particular, leaders typically have a desired end state, an image in their mind of what the world is supposed to look like if they achieve all of their objectives in war. Now, war is a tricky thing that tends to get out of hand, so countries often struggle to achieve these sorts of clear end-states, often ending up with something rather different than what they had planned, even when they win.
But these end-states sit at the heart of strategy because all strategic planning is meaningless if you have no conception of what you are even trying to do and so one would expect any strategy game to pay fairly close attention to strategic ends. So it is worth discussing the strategic aims of the major powers in World War II – what were they trying to achieve – and the degree to which Hearts of Iron IV is able to model those outcomes and the factors which led to them.
But first we should acknowledge that Hearts of Iron IV actually has explicit scoring. When a game ends, a ‘playthrough overview’ screen pops up, presenting a ranked list of countries, with an overall score which is a product of the size of their armies, their navies and air forces. In practice, the calculation is very odd as this is effectively another dead mechanic – the air score generally overwhelms every other component of the calculation and relative scoring often makes little sense. In the screenshot below, Imperial Japan – on the verge of surrender, with the home islands having been invaded – ranks above the United States, actively in the process of invading the home islands.
While factory counts are listed on this screen, from the tooltip information, they don’t seem to have any impact on actual score. As far as I can tell, the end-game score system has been like this essentially since the game launched and it is such an infrequently used feature that it has never really been updated. Nevertheless, it is worth mentioning here.
The other explicit system are the achievements and Hearts of Iron IV, like many Paradox games, has a lot of achievements (293 at current count) the player can earn. That said, achievements can only be obtained playing on ‘ironman’ mode (a single save file, so the player cannot go back and undo bad choices) and it is pretty clear from the achievement stats that very few players ever play ‘vanilla’ Hearts of Iron IV on ironman. The most common achievements are joining a faction (19% of players), researching Construction V (17%) and having 1000 convoys (17%) all of which are practically guaranteed to happen in most playthroughs, suggesting the total percentage of players to ever meaningfully engage with ironman and the achievement system is sub-20%.
The existing roster of achievements splits into basically two categories: a number of achievements for utilizing basic game mechanics and then the bulk of achievements which are about achieving specific things (in most cases, alternate-history things) as specific countries. Notably, very few of these achievements resemble the actual historical strategic end-states that the major powers were trying to achieve. Instead, most of the country specific achievements are, frankly, memes: a funny title to go with an unlikely outcome that is interesting either because of how absurd it is (‘Thai Fighters: as Siam have 10 aces’) or because achieving it is a demonstration of skill in the system because of how difficult or unlikely it is (‘I Didn’t Hear No Bell: As democratic Czechoslovakia, lose the Sudetenland, then grant autonomy to Slovakia, then defeat Germany’). There is a subset of players that pursue these, but very few of them are related to the historic strategic ends of the major players in WWII.
Finally, of course, there is map-painting. After all, like all of Paradox’s grand strategy games, Hearts of Iron IV is played on a gigantic world map, so it makes sense for players, looking to demonstrate or compare their success at the game, look to see who has painted as much of the map their country’s color. It is the most immediately perceptible outcome of effective gameplay and so one many players focus on. But, as we’ll see, while seizing or holding territory was obviously an important aim of many countries during WWII, it wasn’t the ultimate aim – no one was simply running armies around to engage in ‘map painting,’ they had goals that went beyond lines on a map.
So what were they? And can HoI4‘s systems model them?
By October, 1943, I have pushed south from my initial penetration into Germany, mostly aiming to move along rail lines in good offensive territory. Carving out the heart of Germany means their armies begin to run short on equipment, making it easier to push through the harder territory. The delaying factor here is that even with logistics companies (which reduce supply weight), my armored fist (now an army made of an even mix of 13 mechanized divisions and 13 armored divisions) needs a lot of supplies to operate, which means that after each ‘push,’ I need to make sure the logistics are untangled before I can set up for the next one, at least if I want to proceed with minimal losses.
Aims of the Axis
Broadly speaking, the Axis powers went to war with variations on the same basic strategic principle: they wanted to seize territory in order to access sufficient resources to enable a kind of ‘national greatness’ but also – as we’ve discussed – economic self-sufficiency (‘autarky’). The goal was thus not just map-painting for map-painting’s sake, but specific programs of conquest designed to secure specific resources in order to create a specific kind of state – a fully internally self-sufficient empire, based on racial hierarchies in all three cases.
The Nazi version of this approach is often encapsulated into the Nazi slogan Lebensraum (‘living space’), but it is important to be clear here that Lebensraum was about resources as much as territory. Had Hitler been offered the entirety of Antarctica or the Sahara Desert, this would not have qualified as Lebensraum. Instead, Hitler’s aim was about securing not just physical space but resources – critically, farmland – for an expanding (racially defined) German Volk. To some modern ears, the idea that the emphasis here was often on farmland of all things may seem strange, but recall that the Allied blockade of Germany during the First World War had inflicted significant suffering and demonstrated Germany’s lack of agricultural self-sufficiency. Moreover, the Nazi ideal – remember, this is a reactionary ideology – placed a fair bit of stock in the ideal of the (‘racially pure’) German farming family as the bedrock of the Volk.
Consequently, Nazi designs were directed towards seizing huge swaths of Eastern European territory – mostly for farmland (but also other resources) – and mass murdering or enslaving the existing inhabitants in order to replace them with German settler-colonists. The basic ideological foundations of these plans reach back into the pre-WWI period, but find clear expression in Adolf Hitler’s Mein Kampf (1925), so they are very early components of Nazi ideology. Perhaps the clearest (and most horrifying) vision of this end is in Generalplan Ost (‘General Plan East’), crafted in 1940 and 1941 in preparation for the invasion of the Soviet Union but building on earlier thinking. This plan – of which the Hunger Plan already mentioned was a component – proposed murdering tens of millions of Eastern Europeans in order to facilitate a mass program of German colonial settlement.
Italian fascists had their own vision of ‘living space’ – Spazio vitalein Italian. It envisaged both a campaign of settler colonization over the ‘small space’ (piccolo spazio) at the core of this new empire and then resource extraction from the ‘large space’ (grande spazio) of imperial dependencies. Once again, resources – viable agricultural land, raw materials and so on – were of core importance in defining the extent of this ‘living space.’ As with the German conception of Lebensraum, fascist Italy sought to conquer a region large enough to sustain an imperial state without trade, by creating a system of ethnic subjugation and resource extraction.
Japan’s conception of its war aims were only modestly different, albeit complicated by the fact that whereas Germany and Italy had singular leaders with singular ideologies, Japan’s belligerence was driven by competing factions within its government. Thus, for instance, the ignition of major war with China in 1937 was not the product of the central Japanese government but the actions of elements of the Kwantung Army. That said, the Japanese government backed these sorts of actions so I am going to take a view here, as it were, that ‘the purpose of a system is what it does.’ Thus, even if Japanese actions ‘bubbled up’ from junior officers or resulted from competition between the IJN and the IJA, the fact that Imperial Japan backed and justified those actions make them state polity. Viewed in that light, combined with the (sometimes retroactive) justifications, Imperial Japanese state policy is quite clear and, again, only modestly different from the other Axis powers.
Japan’s “Greater East Asia Co-Prosperity Sphere” – the euphemistic label Japan applied to its empire – was primarily focused on resource extraction rather than colonial settlement. The Japanese home islands were densely populated and – by the standards of the time – highly developed, but relatively resource poor. Rather than trade for these resources or resettle the Japanese population en masse outside of Japan itself, the Japanese aim was to construct an empire (composed substantially out of puppet occupation governments) where the conquered populace would serve as an expendable labor force for the extraction of raw materials for Japan’s industry and a captive market for the finished goods Japan produced. The main difference here is that whereas the Nazis imagined an empire almost entirely of colonial settlement with very little resource-extraction-overlordship and the Italian fascists imagined an empire split between the two, Imperial Japan’s aims were almost entirely for resource-extraction-overlordship, with very little colonial settlement.
In all three cases, these aims were fundamentally economic more than territorial. The end goal was not ‘buffer states’ or a return to some past territory (even Italian aims included territory never ruled even by the Romans, such as Ethiopia), but rather an empire whose brutal extraction could sustain a certain standard of living for the ruling racial class through the subjugation or murder of other racial classes.
Which then leads us to…
In order to clear up my logistics situation and to complete the effective destruction of the Wehrmacht, I spend the fall of 1943 cutting southward out of my massive salient, eventually connecting to the Maginot line by taking Baden. This creates an enormous pocket with roughly 200 Axis divisions trapped in it. The pocket is out of supply basically instantly, with the result that attrition will weaken these forces as the perimeter closes and they’ll all end up total losses.Of course with so much of the Axis forces trapped in that pocket, there’s functionally no hope of making a real fight for Berlin and it falls to my advancing British forces in March of 1944. The Soviet Union has still not – and will not – join the war.
The Aims of the Allies
The western allies (Britain, the countries of its Commonwealth, France and the United States, inter alia), entered the war primarily as status quo powers, with stated war aims – the disarming of the Axis and the dismantling of their empires – which largely aimed to return the world to something like the pre-war status quo. That said the way the war turned out mattered greatly to these powers in ways worth discussing.
Britain and France both entered the war as the victors of WWI, leading global great powers and with large colonial empires. After the war’s end, both countries would strive, fight and eventually fail to retain those empires and to defend their great power status. In a very real sense, then, Britain and France, while winning the war, fundamentally lost a grip on their long-term strategic aims. For France, it isn’t hard to see why – they were occupied during the way and the process of dismantling their empire, only partially reversed by the war’s end, began while France, as an occupied country, could do little to stop it.
For the British Empire, despite winning the war and never being occupied, the war fundamentally, fatally weakened an empire that was already (as we noted last time) beginning to slip away in any case. Some of these causes were ideological and political: as in World War I, the Commonwealth states having done their bit felt a renewed sense of pride and increasingly independent feelings. This, as an aside, is one of the only things here HoI4actually models: war participation by colonial states pushes them towards independence, so a United Kingdom that finds itself unable to win the war except by leaning heavily on its empire finds that empire slipping away even faster for the effort.
What is missing here are the economic causes: the United Kingdom, by the end of WWII was economically exhausted. Winning the war had required suppressing consumer demand and turning the economy over to military production which is a fundamentally unproductive kind of production in that no one can eat bombs. The United Kingdom had begun rationing food supplies and other basic necessities (clothing, soap, fuel, etc) in 1939 and kept rationing some essentials as late as 1954 as the economy struggled to recover. British economic weakness – currency weakness and reliance on fuel imports, among other things – created the leverage that the United States (in part) used to force the British to back down during the Suez Crisis (1956), the event which effectively marked the end of Britain and France’s status as great powers.
Meanwhile, understandably, a country still under rationing, recovering from the economic devastation of the war and absolutely exhausted by it, was equally unwilling to summon the will to spend even more money and even more lived in a likely doomed effort to maintain its overseas empire by force.
Of course the United States stands as a stark contrast: military spending during the war functioned as a massive economic stimulus, while at the same time the United States suppressed consumer demand via rationing (for a shorter time and far less harshly) during the war, leading to a lot of households ending the war with money in their pockets because there had been money to be made during the war but nothing to spend it on. The result, famously, when the war ended was the economic boom of the 1940s and 1950s, which provided the economic muscle for the United States to act as one of the world’s two Cold War-era superpowers.
There is, of course, an irony that the country that ended up at war’s end with the highest standard of living wasn’t the one that had conquered any territory for resources, but the United States, which owed its renewed prosperity to domestic, internal economic factors as well as a gleeful enthusiasm for one of the things the Axis powers hated: trade.
The Soviet Union’s war aims are a bit harder to parse, in part because some of the claimed aims (the USSR promised to create independent new countries in Eastern Europe) were disingenuous (the Soviet Union instead produced puppet-states, disciplined with military force) and because the Soviet Union spent some time, effectively, on both sides of the conflict. Initially, the USSR used the war, in 1939 and 1940, as an opportunity for territorial expansion into Romania, Poland, the Baltic states and Finland, with both an ideological objective (expanding the Soviet model of Communism) and a geo-strategic one (establishing ‘buffer states’ protecting the Soviet core). After the war, those same aims appeared with the Soviet creation of a network of satellite states built on the Soviet model (with the threat of the Red Army to maintain it) in what would become the Warsaw Pact, while at the same time combined with a desire (shared by the western allies) to limit Germany’s ability to upset the global order again.
This set of Soviet objectives are also one of the few Hearts of Iron IV can really model, as it is possible to create ideologically pliable satellite states in the peace conference system, although because the game ends in 1948 (and in practice runs out most of its content by 1945) these states mostly exist as trophies rather than actually doing anything. That said, it doesn’t really model them well; notionally this effort was also supposed to make believers in the Soviet system out of Eastern Europe but as we’ve discussed before the game’s political model is far too simplistic to really capture or simulate that kind of shift in political opinion or consciousness and by the time it would matter the game has lost interest in any event.
What you may note, however, is that for a lot of the countries involved – the USSR is a partial exception but only a partial one – the overall strategic end-states (both desired and achieved) end up as fundamentally economic in nature, revolving around the standard of living that the post-war order could provide and the consequent tolerance of the population for further spending on expensive foreign political programs (the British Empire, the Marshall Plan, the Warsaw Pact, NATO, etc.).
Can Hearts of Iron IVsimulate these aims? Broadly speaking, no. I’ve noted the few exceptions, but generally no. It can simulate the map painting component, but the underlying economic realities that the map-painting (or lack thereof) are supposed to produce, it is almost entirely incapable of even simulating, much less representing to the player, much less presenting as an end-state. The actual strategic aims of the major powers in WWII largely fall completely outside of Hearts of Iron IV‘s vision of history, a striking failing for a grand strategy game which cannot model the grand strategies of any of the great powers of the 1940s.
By late March, most of Germany is under occupation and allied troops are entering Poland. Italy is the only really functional Axis combatant (you cannot see it here but in a few months the USA is going to start naval-invading the Japanese home islands) and Italy cannot even hold off France, much less everyone else. At this point, the game is mostly an exercise in pointing and clicking – Axis armies are weak enough in most places (while my forces remain fully supplied, equipped and reinforced) that I can advance almost at will, even just pushing forward with my defensively-oriented infantry divisions.
Empty Shelves
The main problem here is that nearly all of these war aims historically fed back into economic questions: the availability of resources, of agricultural land (‘living space’), of a trade-based, prosperity-inclined global order, the existence or absence of rationing and consumer goods and overall standard of living. For Germany and Italy, these were combined by what we might bloodlessly term demographic goals – the mass murder and enslavement of tens of millions of people in order to enable a program of mass agricultural resettlement of their lands.
But Hearts of Iron IV‘s economic system doesn’t simulate any of this feedback, making it impossible for the game to even model these strategic priorities – I want to repeat that, the game cannot model the strategic priorities of countries like Germany, Italy, Japan, the United Kingdom or the United States – much less present them to players as potential strategic end-states.
A major part of the problem is the underdeveloped civilian industrial system. As noted last week, Hearts of Iron IV ‘taxes’ each country a certain percentage of its factories to produce civilian consumer goods, a percentage which decreases as a country increases its economic mobilization law, which reflects war-time rationing leading to less domestic consumption. Notably, however, these consumer goods factories both consume no resources (besides the coal that everything does) and produce nothing.
So on the one hand, there is no point to engaging in military expansion to secure the resources for any kind of domestic industry except armaments production, because no kind of industry except armaments production actually uses raw resources as the game models them. Armies do conquest and conquest feeds armies but neither of these ever feed back into anything else. In terms of raw factory counts, raw resources – except for coal – are entirely superfluous to industrial expansion. So long as building slots exist, any country can happily keep plopping down civilian factories and infrastructure and never really face any kind of resource shortage.
Meanwhile, HoI4 does not simulate standard of living or the civilian supply of goods at all. The contrast with Europa Universalis V or Victoria II or III – where goods production feeds back both into state revenues but also into the goods available for consumption by pops and thus into stability and politics – is marked. In HoI4‘s economic system, consumer goods usage is simply modeled as waste: it does not result in economic growth, it does not influence politics and there is no standard of living mechanic for it to influence.
Of course historically, rationing – which is how you actually reduce the ‘consumer goods’ percentage of industry – mattered a lot. It was politically contentious in the democracies both during the war and (for Britain) in the years following. In most countries, the demands of the war meant that most luxuries vanished from stores fairly early on, while in many countries – particularly the Axis powers and the Soviet Union – the war’s demands meant that necessities were rationed tighter and tighter, until things like calorie allotments for civilians were truly parlous. It matters, as a historical matter, that the outcome of a war that was supposed to guarantee prosperity and plenty to specific racial groups instead delivered them want and starvation.
Meanwhile the game is likewise incapable of modeling the post-war situation either. Apart from Germany’s unique MEFO bills, the game doesn’t simulate the ways in which countries fought the war by effectively borrowing from the future – either by direct debt financing or by suppressing consumer demand to focus entirely on military production. There is no way, for instance, for the United Kingdom to rack up lend lease debt or end up in a situation at the end of the war where the historical massive Anglo-American loan was required simply to keep the British economy running as it transitioned away from military production (which in turn would also require Marshall Plan assistance).
Instead, as discussed last time, Hearts of Iron IV‘s economic simulation features spiraling, out-of-control growth because it treats consumer goods as a kind of waste that is reduced by war economies, leading to economies becoming more productive rather than less as a result of mobilization (the opposite of the thing that happened). As a result, it has no way of simulating France and Britain being effectively bankrupted by the war, nor of simulating the United States’ unique position as the one major world economy that hadn’t been blasted into rubble. Instead, everyone finishes the war with vastly larger economies than when they started.
The only major exception to this rule is Germany’s MEFO bills. Historically, MEFO bills were an economic gimmick created by Hjalmar Schacht to allow Germany to run an enormous deficit without that deficit showing up on the government’s balance sheet thus enabling massive fiscal stimulus (via rearmament) without a visible exploding debt, though of course the whole thing about the MEFO bills is that they would have to come due eventually (these were 6-month bills, but you could ‘kite’ them for a time by issuing more), but Germany went to war, initiating rationing and a government controlled economy (and then collapsed) first.
The game models this interaction, with MEFO bills giving a quick injection of economic production and suppressing the consumer goods percentage, but with a nasty hangover down the line. However the game provides an a-historical ‘out’ – the start of the war enables the MEFO Bills national spirit to be transformed into ‘Economy of Conquest’ which then can be modified via ‘Autarky Achieved’ directly into Wirtschaftswunder (the term for the post-war economic recovery in Austria and West Germany) once Germany has seized enough raw industrial resources, which resolves the issue.
The major problem with this interaction, from a ‘vision of history’ perspective, is that it presents as if the Nazis could have permanently dodged the economic costs of their war if only they had won, which is almost certainly untrue. Historically, the Nazis looted aggressively across their new European empire and never got out ahead of the massive obligations the state was incurring doing all of the war – instead, even as the Nazis pushed deep into Russia, civilian supplies and rationing had to be aggressively cut back. It was not, in fact, possible for the Third Reich to conquer its way out of bad economic decisions and the fact that Hearts of Iron IV creates an entire focus and event chain to pretend that it was is another way that it ends up – for game balance reasons (Germany has to be able to win!) – endorsing a false and fascist view of history and economics.
Had the Soviet Union collapsed early in 1943, Nazi Germany would still had been burdened with internal debts it could not pay, store shelves it could not stock and people it could not feed, which is a big part of why it was planning to starve more than forty million of those people to death simply to make the math begin to work. I honestly find it a bit offensive that the game uses the historical term Wirtschaftswunder for the end-state here, because it implies that butchery and conquest – if it had worked – could have been a shortcut to the kind of prosperity that West Germany achieved in the 1950s, but the historical Wirtschaftswunder was based on sound currency (something the Nazis did not do), trade and economic integration (something the Nazis hated) and financial assistance from the United States (something the Nazis would never get). It feels like a piece of historical economic stolen valor, to be frank, to give the name of a historical thing accomplished with the opposite methods and ideology of the Nazis as the result of implementing Nazi economics fully.
However, beyond this industrial policy, the game cannot really model fascist economics either. Because of the already-discussed policy of indifference to Nazi war crimes, the game has no way of modeling Nazi efforts to create Lebensraum in the East or the possible effects this would have had. Nazi industrial policy is presented as a workable plan to use conquest as a short-cut to the kind of economy modern Germany has – highly industrialized, based heavily on trade – rather than an insane plan to attempt to murder their way to prosperity through a program of agricultural expansion that I think it is fair to say was doomed to failure no matter what happened. Homesteading was not going to be the winning economic model of the 1950s.
The result is a game that is incapable of modeling the actual war aims and strategic ends of the major combatants in World War II, despite being a grand strategy game about World War II.
Germany capitulates in May, but Italy gets a remarkable reprieve in June…As Nationalist Spain jumps into the war on the Axis side. Their initial gains into France are checked as France and I rush containing forces there and then behind them moving along the rails, the hammer of the V Armored. There isn’t enough pressure on my front line in the East to stop me from shifting all of my heavy divisions west to simply smash Spain down. Spain will be capitulated back out of the war by mid-July.
Will The Mods Save Us?
Before we can wrap this all up into a set of conclusions, we need to discuss the modding scene. Hearts of Iron IV is unusual as strategy games go because of the huge popularity of its mods, which range from small quality of life changes to massive total conversions which transport the game’s core structures into completely different settings. Something like two-thirds of Hearts of Iron IV players play with mods at least some of the time, though it is important to caveat that figure both that not every mod is a total conversion and also not every person running mods runs them all the time. Vanilla HoI4 is still the modal experience of HoI4, but the mod community is huge and a lotof players are running mods.
Can the mods fixHearts of Iron IV? Kind of?
Most HoI4 mods are subscribed to through Steam’s Workshop feature, so we can get a decent view of the space here and I want to be clear that we’re really considering two separate things: the community of modders (who make the mods) and the community of mod-players. Here is, as I write this, the currently most subscribed mods on the workshop:
We have a few quality of life mods (Chinese localization, FPS Map, a peace conference system revision), a timeline expansion (The Road to 56), a mod that shifts the system earlier (The Great War) and later (Cold War Iron Curtain) and one alternate world total conversion (Old World Blues, set in the Fallout universe).
And then we have alternate-history What If Germany Won World War I? (Kaiserreich), and alternate-history What if Germany Won World War II? (The New Order) and Millenium Dawn, a modern day conversion to the game that got so popular with neo-Nazis that the creator – who is not a Nazi – had to burn down his own forums as the only way to get them out. Fully half of the top six mods for this game are ones that have – shall we say – unique appeal to Nazi-inclined gamers.
And that is the state of affairs, I must note, after Paradox Interactive actively purges the Workshop of openly Nazi mods.
Now, I want to be clear: is Kaiserreich a pro-Nazi mod? No, it is not. But in a crowded modding marketplace where most people only look at the titles, you would have to be a little daft not to recognize the bit of marketing work being done by a mod which overhauls basically the entire map calling itself Kaiserreich – and what it means for the community that this name was evidently the second best possible choice after “The Road to 56.”
Is The New Order a pro-Nazi mod? No, it is not; if anything it is more skeptical of the Nazi social, economic and political program than the base game, which is to say that it expresses any skepticism at all (and it does as does Kaiserreich). But do these mods have some obvious appeal to modern neo-Nazis? Yes, obviously. While it is the case that both Kaiserreich and TNO at this point have a ton of content for countries that are not Germany, it is also the case that they’re called Kaiserreich and The New Order: Last Days of Europe and that there are two alternate history ‘what if Germany won…’ mods in the top six mods (the 21st most popular, Thousand Week Reich, is also this). Before we get to any other country getting a focused alternate history, we also have to pass a mod named after the Nazi victory slogan (Endsieg; again, the mod is no more Nazi than Hearts of Iron but the appeal is obvious), to get to the first country-specific non-German overhaul, Pax Britannica (36th in popularity; ‘what if Britain but science fiction’), which has 12% of the subscribers that Kaiserreich does.
I want to be clear here that I am not accusing the makers of these specific mods (as opposed to now-removed infamous Nazi mods like “Aryan Goddess” and “Deus Vult” (made by a guy calling himself TauronSS)) of being Nazis or fascists or friendly to Nazis or fascists. What I am pointing out is this is exactly the modding scene you would expect for a game that had a serious Nazi-bar problem, but also had the developers actively purging any openly pro-Nazi or pro-fascist modding content. You’d end up with the most popular stuff frequently being borderline material that isn’t pro-Nazi per-se but happens to focus on the elements that Nazi players want to focus on the most without breaching the modding rules.
If I may strain an analogy, if you walked into a store that sold key-chains with initials on them and realized looking at the shelf that they sell three times as many ‘SS’ keychains as any other letter combination, you would not rush to assume that it just so happens that everyone in town is named Simon Smith. You might even draw the conclusion that the store owner – despite not being named Simon Smith and professing that he didn’t like the Simon Smiths – nevertheless seemed a bit too comfortable making their keychains.
Of course real-world alternate history mods are not the only kind. As we’ve discussed, HoI4 has a remarkably good operational military model, one of the best out there. And there are any number of mods which take that operational model and transport it into a context where it is simply no longer expressing a theory of history at all – mods like Old World Blues (set in the Fallout universe) or Equestria at War (set, incredibly, in the My Little Pony universe). Those mods are really popular too (albeit generally not as much as the alt-history-Germany mods, make of that what you will), and there is certainly an argument that by transporting the game into an alternate world they ‘save’ the operational simulator by ditching the bad history it is freighted to in the base game.
What I think the mod scene signifies is the complex nature of the Hearts of Iron IV player-base. The joke I have heard is that the HoI4 player-base is effectively split three ways: one third are hardened Nazis, one third are History Dads and one third are purple-haired LGBTQ ultra-libs. I doubt those numbers are right, but it speaks to both the diversity of this player-base and also to its very awkward and quite visible Nazi problem. But I don’t think the modding community can ‘save’ Hearts of Iron IV, because it is simply a reflection of the game’s player-base.
Italy capitulates in September of 1944, leading to a peace conference and the end of the war in Europe. My ‘War Contribution’ percentage of 65% (the next highest is 8%) means I basically get to dictate the peace to the world. I let France set affairs in Italy and Spain, while I take occupation of most of central Europe and also Iraq. This was notionally in preparation for a ’round 2′ against the USSR, however I ran into a snag here that has ended the playthrough: because the USSR didn’t actually enter the war (and the game doesn’t count the seizure of the Baltics or Eastern Poland as generating World Tension), I actually have no way of declaring war on the USSR to recover the rest of Poland (the ‘Embargo the Soviet Union’ and ‘Operation Unthinkable’ focuses are gated by the USSR producing meaningful World Tension). Consequently, I’ve opted to end the run here, although if I could declare war on the USSR at this point I would have no problems winning, given the combined strength of the allies and my access to all of the resources and industry of central Europe.
Conclusions
The last time I am aware of that Paradox released who-plays-what-country statistics was in 2023. At that point, the top 10 played nations in the game were:
Germany
22%
Soviet Union
12%
Nationalist China
6%
Communist China
6%
Italy
4%
United States
4%
Japan
4%
France
3%
The United Kingdom
2%
Turkey
2%
And it just seems relevant in a game that is about a war between the Axis powers, the Soviet Union and the western allies, the western allies – the democracies in that war – have fewer players collectively (9%) than the two halves of the Chinese Civil War (12%) or the Soviet Union alone (12%), much less, of course, Germany. Indeed, more people are playing Germany than any given three other countries added together.
There’s a relic of the game’s development I find interesting: the game’s main theme, dating from the base game’s release in 2016, was the theme of the (western) Allies. The initial cover art features MacArthur in the center, with one commander each from Britain, Germany, Japan and the USSR. In short, at launch, the game attempted to present, in important ways, the Allies as the ‘main characters,’ a stance that made more sense at the beginning when the focus trees of the Allies were roughly as (un)developed as those of the Axis.
I do not think anyone looking at Hearts of Iron IVtoday has any problem correctly assessing that its ‘main character’ is Nazi Germany. Evidently the player-base knows.
And before I get a chorus of loud complaints in the comments, I want to be clear what I am saying here and what I am not saying. I am not saying that everyone who plays Hearts of Iron IV does so because they like Nazi Germany or the Axis more broadly. Instead, what we see in the community around this game is one in which the majority of players are what we may fairly call ‘anti-Nazis’ but that at the same time the game has attracted an unusually vocal, unusually large minority following of extremists, kept in check primarily by the fact that their voices are actively, continually suppressed in the Paradox forums, the Steam Workshop and related communities like r/hoi4.1
And that prompts a follow on question: why? One answer, of course, is simply that this is a World War II game and the Second World War is an obvious touchstone for Nazi-sympathizers. But certainly one does not get the immediate sense that all World War II games and media draw this kind of following.
I think in the process of working through Hearts of Iron IV‘s vision of history we come to a clearer answer: Hearts of Iron IV, often in the interest of streamlining and game balance, has blundered into offering a vision of history which is inaccurate in the specific ways that are likely to be flattering to pro-Nazi and pro-fascist players.
Whereas in practice, historians generally regard World War II as a contest between economic and political systems in which fascism proved inferior,2HoI4 presents battlefield skill and operational art as the most important thing in war, exactly as the Axis powers thought. Whereas in practice, the war and the Cold War that followed it demonstrated the considerable advantages of liberal democracies and free market economies, HoI4 presents both democracy and market economics as liabilities, weak systems that are nothing but negatives, exactly as the Axis powers thought. Whereas historically, the Nazi economic plan of economic stabilization through conquest and mass murder had functionally no hope of success, in HoI4, it can work and even produce an economic miracle, exactly as the Axis powers thought.
In short, although the war itself demonstrated that Nazism, Italian fascism and Japanese militarism simply didn’t work as ideological, economic, political or cultural systems, Hearts of Iron IV instead posits a world in which they work exactly as their proponents – exactly as modern fascists – wish they did.
And of course, whereas historically the armies of the Axis, especially but not exclusively those of Nazi Germany, committed horrific atrocities wherever they went, Hearts of Iron IV functions as a ‘clean Wehrmacht simulator,’ reinforcing the post-war lie peddled by Nazi officers that presented the Wehrmacht as innocent of Nazi crimes (which were attributed all to the SS). That line, of course, plays into modern neo-Nazi minimization of Nazi crimes in a progression that has become blandly predictable in certain online spaces: they didn’t happen, or if they did happen the ‘clean’ Wehrmacht didn’t do them, or if they did they were good actually.
Put even more bluntly, Hearts of Iron IV has unintentionally created a simulator that presents World War II as modern fascists would like it to be. One suspects that at least some of the folks at Paradox are not wholly unaware of this – somewhat infamously the advertising for the major Germany update, Götterdämmerung, in 2024 veered more than a little uncomfortably towards Nazi propaganda.
Of course at the same time the shame of it is this game is built atop a truly remarkable operational simulator which does a really good job in expressing why operations in World War II took the form they did, shaped by terrain and logistics as much as by tanks and shells. And while the civilian industrial model is pretty flawed, the military industrial model is equally instructive in presenting some interesting trade-offs, even if it is forced to treat German and Japanese mistakes as if they were valid policies that could have succeeded in the long-run.
I do not think it is impossible to play Hearts of Iron IV responsibly. But I do think players need to go into this game forewarned and forearmed that the design and balance decisions made to make it an interesting strategy game also serve to skew the history it is presenting in very frustrating ways. And equally, I think the developers at Paradox need to give a lot more thought to how – if these balance choices are unavoidable for gameplay reasons – they can offer responsible historical framing to make clear to players what and how large the concessions to gameplay have been.
It might equally be worth asking, given where, very evidently, the development time and focus in the game have gone, why this is a game where the western allies – who emerged triumphant from the war and the Cold War that followed it – are less heavily played and have far less content than the Axis (or even really just Germany), who lost it.
But, for as much as I enjoy playing it (I have almost 600 hours in HoI4 and more than 300 in HoI3), Hearts of Iron IV is easily the most historically troublesome and flawed entry in Paradox’s catalog, a produce to be consumed with care because of how skewed its historical perspective is and how little effort there is to signal to the player the nature of that skew.
Instead, the game tilts unsteadily on the very edge of unintentional fascist propaganda, the sort of product that we do not teach…but find ourselves having to un-teach.
Flávio Bolsonaro’s escape from Brazil to Miami turns out to have been arranged, in part, by White House officials including Trump advisor Jason Miller, who arranged for a charter jet to take the Bolsonaros from Argentina to Florida.
Edward Wong, Ana Ionova, Hamed Aleaziz, and Tyler Pager of the New York Times reported today that Trump himself ordered the State Department to give temporary status to Flávio Bolsonaro and his family on humanitarian grounds. U.S. officials told the reporters that the government will likely grant them permanent residency later.
Wall Street Journal reporters Vera Bergengruen, Samantha Pearson, Ryan Dubé, and Philip Wegmann write that Bolsonaro intends to set up a political system in exile, despite the fact that more than 50 countries, including Latin American leaders from a wide range of political persuasions, have recognized the victory of Luiz Inácio Lula da Silva in Sunday’s election. Lula won by more than 4.4 million votes. International observers call that margin decisive.
Trump has refused to recognize Lula’s victory, suggesting that the votes against the right-wing Bolsonaro were rigged. But, as the Wall Street Journal reporters add, it is unclear how much political capital he will be willing to expend on propping up Bolsonaro’s pretensions to power.
Trump’s own energies have been devoted to trying to project authority and power, but he has succeeded primarily in illustrating that he is far more concerned with his development projects than with what’s going on in the White House. Yesterday he posted at length on social media about the East Potomac Golf Course he wants to redo—the one where the administration cut down more than 400 trees in defiance of a judge’s order—saying it “is highly dangerous, dilapidated, and absolutely disgusting” and calling for it to be “closed immediately for safety reasons!”
Last night, Eric Flack of WUSA9 reported that the National Park Service told a federal judge it is closing not just the East Potomac Golf Course, but also nearly all of Hains Point beginning on November 15. As Flack notes, this area includes “the perimeter running loop, the dedicated bike and pedestrian lane the Park Service completed in 2023, and the picnic areas and open space used year-round.” The Park Service did not say how long the closure would last. Trump promised: “After we are done, the East Potomac Course will be a place of immeasurable Pride for the City, all of the Golf Enthusiasts who live here, a Course worthy of and befitting our Nation’s Capital.”
Rachel Treisman of NPR reports that plans for the finished park show only a golf course. The current facilities for walkers, runners, cyclists, birders, picnickers, and so on, are not shown.
Trump is paying less attention to the affairs of government. Today, when asked about claims that Defense Secretary Pete Hegseth had fired Lieutenant General Sylvia for leaking classified information from the Pentagon, Trump responded: “She’s got problems. She’s gonna have big problems. She did. We’re very much looking for leakers and ah, she’s going to have big problems. Long-term problems.”
Lieutenant General Brett Sylvia, the director for strategy, plans, and policy on the joint staff that advises the president on military issues, is a man.
Tonight Shauneen Miranda of News From the States reported that Trump has cancelled his rallies in Kansas and Iowa, planned for this weekend. When a reporter asked if the Kansas cancellation meant he was “sick of traveling,” Trump exploded, calling the reporter “sick” and “disgusting” and saying, “You look like hell.”
Trump is also expending his energies in trying to convince Americans that the Democrats are rigging the 2026 midterms.
The administration has tried to force California to set aside 20,000 ballots in the election, claiming that those casting them might not be citizens. Yesterday, as Ryan Sabalow of Cal Matters reported, U.S. District Judge David O. Carter refused to agree, saying the Trump administration is engaging in “a broad, ongoing pattern of attempted election interference.” Carter noted that Homeland Security Secretary Markwayne Mullin has also sent letters to the secretaries of state in New Jersey, Nevada, and Pennsylvania claiming that the states’ voter rolls include noncitizens. Mullin publicly alleged there were 15,903 noncitizens on the voter rolls in Nevada, then quietly dropped that number to 185. When Nevada officials chased down the 185 names, every single one belonged to a U.S. citizen.
“Never before in American history has the federal government, on the eve of an election, sought to coerce a state and local government to abandon their own Constitutional elections procedures and bend to the will of the Executive Branch,” Carter wrote. “This case is about the right of every American citizen to vote in a free and fair election.”
The administration has asked a federal appeals court to rule by Friday on an emergency attempt to stop California from including those 20,000 ballots in the ballot count. In the meantime, as Rick Hasen of Election Law Blog reported, this afternoon the leadership of the Department of Justice directed California’s top federal prosecutors to launch criminal investigations of local and state officials, claiming they are administering illegal voting.
In a “but her emails” kind of moment, the administration is also jumping on yesterday’s New York Times story by Kellen Browning that a staffer for the Democratic candidate for U.S. Senate from Alaska, Mary Peltola, searched for and recruited a man with a name similar to that of the Republican candidate, Dan Sullivan, as a spoiler for the race.
Browning reported that this sort of activity, called “ballot stacking,” is “common in politics and generally considered legal—and [has] been employed by both parties in Alaska,” and that Republicans had used it against Peltola herself two years ago. The author suggested the story was important simply because it “reveals the lengths to which Democrats went to seek advantage in a Senate race that could determine control of the chamber.”
The source for the story, Peltola’s former campaign manager Elisa Rios, said Peltola was not directly involved in the project but was “definitely aware.” Before publication of the story, Browning notes, Rios “contacted The Times and said she wanted to take back her previous statements. ‘As discussed on our call earlier today, I am confirming that I have retracted all statements made regarding the 2026 Alaska Senate Race in connection with any article you may or may not be writing,’ Ms. Rios wrote. ‘I am not willing to be a source for any story in any capacity.’”
Peltola’s campaign, Peltola, and Daniel J. Sullivan all deny any involvement in a ballot-stacking plan. Sullivan says he ran because he was dissatisfied with the performance of Senator Sullivan. Ballot stacking runs into legal trouble if a candidate is paid to run. No one has said this is the case in the 2026 Alaska race.
On October 23 the Justice Department sued Alaskan election officials to block the certification of a winner in Alaska’s Senate race unless the Republican won, saying the inclusion of Daniel J. Sullivan on the ballot might confuse voters who wanted to elect Senator Dan Sullivan, who, unlike Daniel, is listed on the ballot both as a Republican and as the incumbent.
With the publication of the New York Times story, Trump promptly took to social media to call the scheme illegal “ELECTION FRAUD.” He called for Peltola and Daniel J. Sullivan to be removed from the Alaska ballot, letting Republican Senator Dan Sullivan run essentially unopposed.
The Justice Department promptly issued at least three dozen subpoenas and requests for the preservation of documents. On Wednesday night, Republican Alaska governor Mike Dunleavy announced he was ordering an investigation into whether Peltola’s campaign should face criminal charges or civil penalties, although he did not identify any illegality.
Michael Kosnar, Megan Brand, and Raquel Coronell Uribe of NBC News reported that, at Dunleavy’s request, “Alaska’s Department of Public Safety Deputy Commissioner Austin McDaniel said Thursday that the Alaska Bureau of Investigation had started looking into the ‘alleged conduct in a recent New York Times article.’”
Today the New York Times ran two stories noting that ballot stacking is common and legal. A piece by Reid J. Epstein explained that while the Alaska race “has drawn the most attention,... both parties are quietly trying to use little-known candidates in other battlegrounds to siphon votes.” Epstein explained that in Ohio, for example, Republicans are promoting a socialist candidate to take votes from Democratic candidate, former senator Sherrod Brown.
Another piece by Madison Malone Kircher, titled “Ballot Stacking in Elections? History Shows It’s Not Unusual,” listed some of the more spectacular instances of ballot stacking in U.S. history, including the 2020 Florida state senate race in which a Republican paid Alexis Pedro Rodriguez to challenge an incumbent Democrat, state senator José Javier Rodríguez. It worked. The challenger won more than 6,000 votes, 32 more than the incumbent, and the Republicans flipped the seat. In that case, the exchange of money crossed the legal line, and the challenger later pleaded guilty to campaign finance crimes.
But the context for the Alaska story arrived too late: Trump and Republicans are pushing the story as hard as they can to suggest Democrats are cheating in the midterm elections.
Another ballot-stacking story from this week adds even more context to the Alaska story. Donald Shaw of Sludge, the home for investigative journalism on money in politics, reported that a review of tax records shows that the nonprofit organization that helped to get Cornel West on the 2024 presidential ballot got all of its $7.7 million in funding that year from a right-wing political network bankrolled by Elon Musk. West, a leftist Black intellectual, was widely seen as a spoiler to siphon votes from Democratic presidential candidate Vice President Kamala Harris.
And there is, in fact, reason to be concerned about the Alaska election process. Eric Stone and Hannah Flor of Alaska Public Media reported on Tuesday that polling places in some rural areas failed to open as schedules said they would. Democratic state senator Bill Wielechowski wrote to Division of Elections director Carol Beecher and Lieutenant Governor Nancy Dahlstrom on October 23 to say that “at least 18” rural early voting locations “have failed to open as legally required.” He noted that in the primary, “dozens of rural Alaskan voters did not have their absentee in-person votes counted because it took too long for their ballots to arrive by mail to the Division’s regional office,” and expressed concern the same thing could happen in the general election. He called the Division’s failures “shocking.”
Dahlstrom responded: “Of the eighteen sites listed in your letter, three have now declined to open, twelve have confirmed they are open, and we are working to hear from the remaining three locations.” She noted that these early polling locations were free to change their hours.
Meanwhile, there has been widespread talk that Trump intends to restart the military assault against Iran after the election, and it appears a plan is in place should he decide to do so. Yesterday, at the Middle East Institute, Senator Chris Murphy (D-CT) said that the war plan that has been prepared for the administration “is insane…. It will lead to devastating escalation and the likely destruction of our commitment to the rule of law.” He continued: “[T]he plan that they have developed will lead, in my view, to a prolongment and an escalation of this war that will be devastating for our security interests.”
All the handwriting stuff from the previous newsletters/weeks/months/years has always had two sides, the actual writing like normal writing part and the what-art-can-I-create-with-writing part.
The art side has generally focused on taking typesetting layout inspiration from magazines and newspapers, handwritten journals and repetition. Here’s an example from ‘xoxo’
plot from ‘xoxo’
(ignore the Riso calibration sheet to the right, that’s for something totally different)
Very regular and very ‘on the grid’, which I love, but I’ve also spent a good while tinkering with something more organic, and it’s never quite felt right - the vibes were off - until now.
As with a lot of things the system is fairly “simple” but starts to look more complex as you add layers. There are five stages to generating one of these designs.
The first stage “foundation” divides the page up into rows, anywhere from 3 to 24 and then draws horizontal and vertical lines in those rows, which have some very simple rules; horizontal ones try to stay parallel to each other, but are sometimes attracted or repelled to each other, vertical ones are curves. These form the “skeleton” of the design.
The second stage “grow” goes through a number of rounds, 1-6, that cause new lines to grow out of the foundation lines. These tend to jut out of the foundation lines, growing until they either hit something, or we complete the number of rounds.
The third stage is “break”, places some simple rectangles onto the design, distorts them with extreme perlin-noise randomness, and uses them to delete a whole bunch of lines. This puts a bit of negative space back in, without totally destroying the composition. The second panel below shows both the 2nd (green) and 3rd (yellow) stages together.
Quick note: the four images below with the debug info turned on, are four different designs, because I have to create a new one each time, which is why each stage looks different, sorry for any confusion.
The fourth stage “write” then writes the letters along the foundation and growth lines, plus some inside the distorted rectangles created in the “break” stage.
These letters can be random, random upper/lower-case, random numbers or symbols, or, from a provided set of letters. These ones happened to have randomly selected F, U, C & K, what are the chances 🤔🤷♂️
The fifth and final stage “decorate” places cables onto the design, picking clusters of letters (or just letters, if it runs out of clusters) to act as the cable start and end points.
And yes, all this code is written by hand because none of it is particularly complicated, and I’ve done all the individual parts separately many times before; work with what you already know.
The postcards work well, I’ve even tried some small accordion books, but I’m also looking forwards to making some much larger designs. I have a stack of beautifulSt Cuthberts Mill Saunders Watetrford watercolour paper with deckled side edges that’s burning a hole in my draw and I’m dying to use.
The postcard sized ones I’ve sent out to friends have already been a hit.
Which is a kinda awkward segue into.
💌 💌 💌 💌 💌
# SHOP AND PATREON
On plots large and small.
I’m still slowly spinning up the shop, but if you want to get your hands on the very plot posted above, then it’s here: https://shop.revdancatt.com/shop/fuck-series-i-system-2 - and I’ll be adding more A3+ sized plots, both sweary and non-sweary over the coming weeks. [Side note: if you want a custom one with a specific word/name hit me up, I’m actually pretty excited to keep the ArtFrame running, so the more the merrier.]
Patreon on the other hand is like a monthly postcard mail club, last month was the DOOM project. During that I realised I was going to run out of index cards so I quickly cut up some old maps I had in a draw, which became some of my favorite out of the whole lot.
November is definitely going to involve some postcards both sweary and non-sweary from this new system and a stab at a small cute accordion book (more on that next newsletter).
Patreon doesn’t really want to you do this, but you can totally sign up for just one month, snag the postcards and then ditch.
And, I’ll try and get better at saying what’s coming up, because I’ve had a few people ask about these DOOM/Map postcards and I only plotted enough for the October Patreon members. So for cool experimental stuff that won’t end up in the shop for ages, if at all, Patreon is the place.
🏺 🏺 🏺 🏺 🏺
# POTTERY
I had more adventures in 3d clay printing land last week. Which I still insist is just pen plotting but you get to go upwards too. If you can write code to create SVGs or GCODE for a plotter to can throw in the Z-axis and make a pot.
Kris, who’s the resident sculptor in the studio is exploring making larger bodies, which means there’s always some left-over clay in the machine and the whole thing is easier to clean if it’s all used up.
When this happens I press the “MAKE AN AWESOME POT” button I added to my making awesome pots code. Spoiler; it doesn’t make awesome pots very often, there’s too much randomness, but it also doesn’t take much to press the button a lot of times, so it evens out in the end.
A kiln has just turned up too, so next step is to fire them and then glazes.
I still do not know what I’m doing.
# THE END & WORK AVAILABILITY
If you’ve read this far, thank you!
Last newsletter I said I’d been pretty stressed, that appears to be over now, yay! I got pretty much all the things I needed to get done for work done so that’s all ready to roll.
Which means, the rare situation of me being able to start a new (small to medium) project, or pick up some work is, well, here. This is a real thing that’s happened more than once: “Oh, there was this really interesting job but I just assumed you’d be too busy, you’re always doing stuff” which on the one hand is actually kinda true, but also, fuck!
I’ve learnt, and also suggest to other people, you/I need to be really blatantly obvious when availability comes up, and that is now! So if everything hasn’t been totally overrun with AI, and you have something weird enough drop me a line, particularly if it involve datasets!!
Okay, time to go, catch in for Newsletter #100 on Thursday 12th November 2026.
After implementing the small-change pattern, Imprint Engineering’s next focus
in improving our development loop has been
implementing a verification loop for our software development. This is an increasingly common
pattern, particularly popularized by poteto’s pstack,
but you’ll find similar ideas emerging in other places as well, e.g. Niko Matsakis’ post on
the correctness ratchet,
among others.
This captures some of the confusion I’ve seen in our initial rollout,
and the particulars of how we are implementing the approach.
What verification pattern is, and what it isn’t
The verification pattern suffers from confusing naming:
when you tell a team that you’re planning to roll it out,
they’ll often ask you what mechanism you’re using to verify the codebase,
don’t we already have tests, linters and so on?
However, the verification pattern itself is more similar to the
chain-of-thought pattern,
which aims to steer the harness towards your desired outcome in a clear way.
For example, we require that each pull request generate a verifications/{pr_num}.md file
that describes each step the harness took to verify the changes, and also what
it was unable to verify.
You can argue that your harness was already performing these steps, but it’s actually
hard to say whether it was or wasn’t. My sense is that it often wasn’t happening: I’ve seen too many pull requests go to CICD that
had failed basic lints that could have been run locally to believe the harness was always running them.
Now the harness has to explicitly document that it’s done those steps, or acknowledge it hasn’t.
This allows the harness to self-drive more effectively.
Equally importantly, this generates a renewing source of data about where your harness
is struggling to verify its work. That list is your roadmap for improving the ability
of your harness to self-drive work more reliably over time.
Our verification loop
The core of our verification loop is five steps:
Implement something that you’ve identified or that has been identified by an automated system to resolve.
Let’s say addressing a new error that’s shown up in the logs.
Create a pull request containing that work after your harness has verified it locally.
Pull requests cannot be moved from draft to ready until they have a verifications/{pr}.md verification file available
Provide feedback on the pull request, at minimum from our ai-code-review tool that automatically reviews all
pull requests, but potentially also from humans
Incorporate and reject feedback on the pull request. For low quality feedback, we explicitly dismiss it using a /dismiss {reason}
syntax in the pull request comment responses
Maintain our systems on a daily basis by pulling in the above steps to improve our software:
Use pstack’s /maintain-verification-skill skill
to update the feature maps and tools used based on what has changed and where verifications have run into issues.
Automatically generate a pull request with these changes for review
Review all verification files to identify where they struggled to verify, and generate issues
for review that would reduce those gaps
Review which feedback from ai-code-review was incorporated and which was rejected, tightening up its guidance
This is working pretty well for us so far, typically each of our major code areas (frontend, backend,
data, and native) wakes up with 4-6 pull requests to review as output of this process, improving our
codebase’s correctness while we sleep.
feedback tool
The above feedback loop still misses meta-issues in our CICD and testing patterns.
To address that, we’ve implemented the feedback tool pattern described by
Teddy Riker in Designing for Agents,
which has worked very well for us with respect to addressing places where CICD and harnesses themselves are
failing above the level of verifying a specific pull request.
feedback and verifications are complementary, not competing, techniques.
For example, if the container’s runner crashed before completing, the feedback tool would often
report on this issue, whereas the verification file wouldn’t even get generated.
Explore (raise ceiling) vs exploit (raise floor)
One of the fundamental tradeoffs in how organizations approach AI adoption comes down
to an explore vs exploit tradeoff. When you explore by having the full team do its own
thing, you explore for ideas which can raise the ceiling, but when you centralize you
raise the floor by ensuring everyone gets better PR review and better tooling.
The other related–and extremely open–question is whether exploration tends to over-optimize
for the particulars of a given individual or team’s preferences, which often reduces
cohesion across a codebase.
At this point, I think of misaligned guidance as “context poison”, and am pushing hard to
eliminate duplicate guidance on any topic, to ensure we have consistent, cohesive direction.
So far, our approach is running this as a centralized process for our repositories,
building a single, continually improving, corpus for each area using the self-reinforcing
loop built around the verification pattern. I think it’s working well for us, although
certainly I’ll admit that there’s some skepticism about how far we go towards centralizing,
and I think that skepticism is warranted: we do want to continue exploring, even if we
are primarily exploiting. The best techniques for AI-enhanced development in 2027 will be ideas
that are mostly unknown today.
Was sitting at home the other day, sorting through all the irksome and irritating mail of crazy season, when this caught my eye …
It’s a campaign post from Assemblywoman Laurie Davies, the incumbent in the 74th and a public figure who seems 99 percent likely to retain her seat. In these parts, the former Laguna Niguel mayor is familiar, present and fairly well-regarded for not being a complete and total asshole. Did she vote for Trump? Certainly. Is she courageous enough to speak out against the national ugliness? No. Is she evil? Certainly not. She’s just a fairly run-of-the-mill regional political figure.
She has also, however, stooped to an unbecoming low.
As you can see, the campaign post features an image of her opponent, former San Juan Capistrano Mayor Sergio Farias—with his skin darkened beneath a lizard-like hue. For comparison’s sake, here’s what the dude actually looks like …
And if there’s one thing I know about political advertisements, nothing is accidental. The wording is precise and deliberate. The colors are there for a reason. And fuckery with photos isn’t just an intern messing up. It’s meant to be.
In this case, Davies (as white as fresh snow) is intentionally labeling Farias as the scary and dark outsider. Hell, it’s not just the blackened, green skin. The wording screams, BE AFRAID! and SOCIALIST IN OUR MIDST! and LOVES GANG BANGERS! What you are witnessing is the marriage of doctored photo and scary phrases into one nonsense piece of cardboard.
Truth be told, Farias is a revered and admired public servant who deserves better. These are, in the truest sense, local races, where community and kindness should matter. There are things you can do and things you 100-percent should not.
Like, so worried about flooding that Gracey read 70 percent of her script without tripping over words. Like, so worried about flooding that Gracey dropped the red trench coat for the “Look, we’re being serious” outfit of jeans and Chucks.
And, on the one hand—there’s nothing wrong with the surrounded-by-flooding content of the message. We do need to be aware, store batteries, help our neighbors. So, good job. But, on the other hand—despite living on the coast, and watching the beaches drift away, neither Nguyen nor Van Der Mark have expressed even a slight belief that climate change and rising tides are problems. Neither woman has studied the science, dove into the issue, challenged the MAGA lines that, “There’s more ice than ever!” or “It’s all a liberal hoax.” Nope, nope, nope, nope.
They have done, quite literally, nada.
So as they stood alongside the flooding, reading off the intern’s phone and desperate to pose in front of the nearest Cheesecake Factory, neither Nguyen nor Gracey deserve the benefit of the doubt.
The Turkish Lunar Mission 1 (TLM-1) spacecraft is shown in a clean room following the completion of vehicle integration. Image: Tübitak Uzay
Turkey aims to launch its first mission to the Moon in next year, the first in a planned two-mission series, which includes an orbiter and a lander.
The First Turkish Lunar Mission (TLM-1) is contracted to launch onboard a SpaceX Falcon 9 rocket between April and June with mission managers aiming for an April flight. A launcher for TLM-2 has yet to be selected.
If successful, Turkey would become the ninth sovereign nation (or collection of nations as is the case with the European Space Agency) to operate a payload in the lunar environment, following China, ESA, India, Israel, Japan, Russia, South Korea, and the United States.
Dr. Burak Yağlioğlu, the project manager for the Turkish Lunar Mission, gave an overview of the mission objectives and progress to launch during the International Astronautical Congress (IAC), hosted by the International Astronautical Federation (IAF) in Turkey earlier this month.
“As a nation with a moon on its flag, going to the Moon is a very, very, very long dream for us and that’s why it has a very important national meaning, going to the Moon with our own capabilities,” Yağlioğlu said during his presentation at the IAC. “The Moon is also very important for the Earth.”
“The Moon is the Earth’s gateway to the solar system, so it may be discussed as a hub for interplanetary missions or deep space exploration, but if we look into some of the pillars of these aspects, we have science, technology development, international cooperation, resource utilization, and in the end, the ultimate goal: sustained presence,” he added.
The Turkish Lunar Mission, also referred to as the Lunar Research Program, is comprised of two initial, uncrewed phases. TLM-1 is an orbiter built by Turkish company, Tübitak Uzay, along with another company, DeltaV, which provided a hybrid propulsion system that uses nitrous-oxide as the oxidizer and a polymeric solid as the fuel.
Teams also have support from the Turkish Space Agency (TUA).
The roughly 3.6 ton TLM-1 spacecraft maneuvers using two propulsion systems: a bi-proellant chemical propulsion system for the thrusters and a hybrid propulsion system for its main engine. The hybrid system will be fired once in Earth orbit for the translunar injection burn and again for the lunar insertion burn.
Dr. Burak Yağlioğlu, the project manager for the Turkish Lunar Mission, shares an overview of the TLM-1 mission, scheduled to launch in the second quarter of 2027. Image: International Astronautical Federation/Tübitak Uzay
TLM-1 is designed operational life of at least five months and is designed to operate in a 100 km circular polar lunar orbit once it reaches the Moon.
Yağlioğlu said it’s a point of national pride that more than 80 percent of the equipment onboard the TLM-1 (56 out of 65 elements) are made domestically in Turkey.
“We have several Turkish partners while we develop this spacecraft, so we actually have the heritage, we have the experience, we have the capability, but we also try to build an ecosystem with startups and new companies to make our system like a national team, and we actually had new actors contributing to our lunar mission two,” Yağlioğlu said.
TLM-1 includes a suite of four science payloads: the Lunar Neutrals Telescope (LNT), the Lunar Narrow Field of View Radiometer (LNR), the Radiation Calorimeter, and the Radiation Dosimeter. It’s three imaging and navigation payloads are: a High Resolution Camera, a Wide Angle Video Camera, and a Vision Based Navigation System.
These combination of instruments will be used by researchers to better understand various elements of the lunar environment, like radiation; impacts from solar wind and meteoroid impacts; magnetic anomalies; and surface temperature.
“With the TLM-1, we have an integrated observatory. So, if we just recall the external drivers and modulating conditions, we are going to measure them with LNT and LNR and with the cameras we have, maybe we will identify some meteorite impacts too,” Yağlioğlu said.
“But in addition to that, we also have the radiation measurements or environments. So all of them will contribute to the scientific outputs.”
This week, the TLM-1 spacecraft begins the first in a series of environmental tests, starting with a thermal vacuum chamber test.
As for the status of the TLM-2 mission, Yağlioğlu said it’s still early in development, but it will include a lander that will deploy a rover on the surface of the Moon. He noted the the TLM-1 design is modular and many elements can be replicated for the TLM-2 lander.
One demonstration of transferable capabilities will come when they are performing the end-of-life deorbiting of TLM-1.
“With the propellant left, we would like to design a guidance to a target area and make a controlled impact,” Yağlioğlu said. “So this will be a kind of rehearsal for the lander mission too.”
Back in February 2023 I launched Braggoscope, my unofficial spelunker for official best show ever, BBC Radio 4’s In Our Time (write-up here).
You can listen to all 1,000+ episodes online for free (and see all books in the online reading lists). i.e. there’s a lot so don’t miss the visual explorer to find the good stuff.
(“Spelunker” from George Oates’ use of the term: "an interface to let you wander around a big dataset, and … to show relationships between things.")
1.
Notturnometer, late night classical music and opera:
every piece played since July 2008 on BBC Radio 3’s_Through the Night_, built from the BBC’s own programme data. Discover the most popular works, composers, and individual performances across 6,644 episodes.
Built by Nick Sweeney.
As a classical music newb (but I know what I like when I hear it) I would love this site as an overlay on Apple Music to help me navigate. Help me see the well-trafficked roads.
As of 9am Friday, there were four homicides in D.C. this week. To date this year, D.C. has reported a total of 83* homicides this year. Last year, during the same time period, we had 114 homicides, and in the surge year of 2023, there were 226 homicides during that same time period.
Property crimes were level, and violent crimes, other than homicides, declined this week. At this rate, this will be the first year since the last year of Biden’s presidency where homicides don’t decline by 33%.
Hoping for a much better week next week.
*Three of the 86 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).
Thanks to Kyle Schiller at Marathon Fusion for conversations and information that informed this essay. All errors are my own.
Much of modern civilization is built on top of chemical reactions, either to produce new materials (as in the blast furnace, which converts iron oxide into metallic iron), or to generate energy. Chemical reactions, as we’ve previously noted, work by rearranging how atoms hold their outermost electrons. Combine an atom of sodium and an atom of chlorine, for instance, and sodium’s outermost electron will end up in chlorine’s outer electron shell in an ionic bond, creating sodium chloride — common table salt.
With these sorts of chemical reactions, we’re only shifting around atoms and the electrons that orbit them in the form of chemical bonds. The interior of the atom — the atomic nucleus, which contains an atom’s protons and neutrons — remains unchanged. But if you create the right conditions, it’s possible to rearrange the interior of atoms as well. In nuclear fission, the reaction that powers nuclear power plants, the nucleus of an atom splits, creating several new atoms and releasing an enormous amount of energy in the process. In the fusion reaction taking place within the sun, hydrogen atoms are fused together, their individual nuclei combining to form helium. In particle accelerators like the Large Hadron Collider, charged particles are accelerated into each other using electromagnetic fields, and scientists study the various fragments created by the collisions.
By changing the number of protons or neutrons in the nucleus, these nuclear reactions can create things that can’t be created via conventional chemistry. Change the number of neutrons in an atom, and you get a new isotope of that particular element: an atomic variant of the same chemical, but with a different mass. Change the number of protons, and you end up with a different element entirely, possibly one that doesn’t occur in nature at all.
Typically, the products of these reactions (which we’ll simply refer to as “isotopes”) are unstable: they decay into some other, more stable isotope, emitting radiation in the process, which can be harnessed for various purposes. Carbon dating, for example, relies on the fact that living organisms absorb carbon-14, an isotope of carbon with eight neutrons in the nucleus that eventually and reliably decays into atomically stable nitrogen-14 (the “14” indicates the number of protons and neutrons — carbon-14 has six protons and eight neutrons, while nitrogen-14 has seven protons and seven neutrons). Another process, radiographic welding inspection, uses a variety of radioactive isotopes, such as iridium-192 and selenium-75, to emit gamma rays to inspect welds. Smoke detectors rely on americium-241, an isotope of the artificial element americium — radiation emitted by a small amount of americium causes an electric current to flow across a chamber, but if smoke enters the chamber, the flow of electricity is interrupted, triggering an alarm.
Currently, our use of isotopes is constrained by the fact that creating them is difficult and expensive. Gram for gram, isotopes are some of the most expensive materials on the planet. And the supply chains to produce them are often extremely fragile. Technetium-99m1, a widely used radioactive isotope for medical imaging, is produced through the decay of another radioactive isotope, molybdenum-99. Molybdenum-99, in turn, is produced in only a few nuclear reactors around the world;there was a worldwide shortage in 2024 when some of these reactors went offline for repairs. If isotopes could be manufactured more easily and more cheaply, it could open up numerous possibilities — cheaper medical treatments, better nuclear power sources, possibly even useful new materials.
Making isotopes
We’re all familiar with the periodic table, which lists every chemical element known to man.
Each element on the periodic table has an atomic number, which is the number of protons in the nucleus, starting from atomic number 1 (hydrogen, which has one proton in the nucleus) all the way up to atomic number 118 (oganesson, an artificial element with 118 protons in the nucleus). It’s the number of protons in an atom that makes an element an element — carbon always has six protons, because having six protons in the nucleus of an atom is what makes that atom carbon.
But there are also neutrons in the nucleus, and the number of neutrons can vary. Most carbon on Earth, for instance, is carbon-12, which has six protons and six neutrons. But about 1% of carbon is carbon-13, which has seven neutrons. The most common isotope of helium is helium-4, which has two neutrons, but there’s also helium-3, which only has one. Most of the water molecules in Earth’s oceans are made up of hydrogen with no neutrons (hydrogen-1), but about one out of every 3200 water molecules contains a hydrogen with one neutron, also known as deuterium (water made from deuterium is sometimes known as “heavy water”).
We can visualize isotopes on what’s called a nuclide chart, shown below. The horizontal axis is the number of neutrons in a nucleus, while the vertical axis is the number of protons.
We can see that most elements have several different isotopes, most of which are unstable. Only the isotopes in black in the chart above are stable; everything else will eventually decay. Red isotopes on the chart above decay by what’s known as “beta-plus” decay or electron capture, turning a proton into a neutron. Teal isotopes decay by “beta-minus” decay, turning a neutron into a proton. Yellow isotopes decay by “alpha” decay, emitting an alpha particle (two protons and two neutrons). The rate at which an isotope decays into another isotope is typically described as its “half-life” — the amount of time it takes for half of a sample to undergo radioactive decay. Half-lives can vary wildly, from tiny fractions of a second for hydrogen-5 to hundreds of millions of years for uranium-235.
For isotopes that are stable, or that decay slowly enough that they can be found in the environment, it’s sometimes possible to obtain them by separating them out from other isotopes. But this is often difficult, because isotopes tend to be chemically identical, and most separation methods must rely on minute differences in the atoms’ weights. Much of the difficulty in the Manhattan Project, for instance, was in creating sufficient concentrations of a specific isotope of uranium, uranium-235, that would undergo nuclear fission. Uranium-235 only makes up about 0.72% of natural uranium, and producing a single, football-sized lump of it required a processing facility the size of a small city.
But many isotopes can’t be found in nature at all. There’s no natural source of the technetium-99m or molybdenum-99 used for medical imaging, or the selenium-75 used for welding inspection. It’s thus useful to be able to manufacture specific isotopes.
How do we do this?
At a high level, creating isotopes means rearranging the interior of an atom. In some cases, this happens by natural radioactive decay. The americium-241 used in smoke detectors, for instance, mostly comes from decaying plutonium-241. But for most isotopes we’re interested in, we can’t rely on natural mechanisms; instead, we have to deliberately rearrange atomic nuclei by bombarding them with different sorts of particles. Depending on the sort of particle you hit the nucleus with, the energy of that particle, and the nature of the target atom, you can create different sorts of reactions. These reactions are typically described by the following format: target(input particle, released particle)product. So in 1917 when Rutherford bombarded nitrogen atoms with alpha particles, producing oxygen and hydrogen nuclei (protons), that reaction was N-14(alpha,p)O-17. The figure below shows different sorts of reactions and how they move an atom to a different location on the nuclide chart.
Via Opus 5.5
There are a few different ways we can hit an atom with a particle. One is to use a particle accelerator, such as the cyclotron, invented in 1929 by Ernest Lawrence (who would go on to win a Nobel Prize for his invention). The cyclotron uses powerful electromagnetic fields to accelerate charged particles along spiral paths. With his 27-inch particle accelerator, Lawrence could accelerate helium nuclei to roughly 1% of the speed of light.
It wasn’t long after Lawrence created his cyclotron that it began to be used to create various isotopes. Naturally occurring radium was already being used to treat cancer with radiation, and Lawrence hired personnel to investigate the potential of using cyclotron-created isotopes for medical and research purposes, such as radioactive phosphorus-32. Phosphorus-32, which has one more neutron than the stable phosphorus-31, was a promising research isotope because organisms naturally incorporate and accumulate phosphorus: if that phosphorus were radioactive, it would allow various metabolic pathways to be observed and possibly allow for highly targeted radiation treatments. Lawrence quickly found that demand for phosphorus-32 for experimental cancer treatments and biological research was “almost insatiable,” and by 1939 a dozen cancer patients had been treated with cyclotron-produced phosphorus-32.
Particle accelerators are still used to produce isotopes today. GE Healthcare, for instance, sells several different medical cyclotrons. The GE PETtrace 800 uses a beam of hydrogen or deuterium nuclei (protons or proton + neutron) to create isotopes such as oxygen-15, nitrogen-13, and fluorine-18, which are then used for medical imaging.
The downside of particle accelerators is that it’s hard to use them to produce a large volume of material efficiently. A medical accelerator costs in the single-digit millions (plus several more millions for the facility to house it) and can only produce about a dust-grain-sized speck of material every hour.
This is due largely to how particle accelerators work. They accelerate particles using electromagnetic fields and so only work on charged particles: electrons, protons, or positively charged atomic nuclei. With electrons, it’s apparently hard to get them to trigger nuclear reactions because they don’t feel the strong nuclear force — electron accelerators thus mostly work by firing the electron into another target and triggering the release of gamma rays, but most of this beam will end up as heat. Because protons or alpha particles are positively charged, they’ll be repelled by the positively charged nucleus of the target, similarly reducing conversion efficiency and creating a lot of heat that must be dealt with. When the PETTrace 800 uses protons to make fluorine-18 (which uses oxygen-18 as an input), only about 1 in 800 protons enters the oxygen nucleus.
Another way to create the necessary particle collisions is to use nuclear fission: unstable atomic nuclei splitting apart when struck by a neutron. There are a couple of ways to leverage this. One is to simply harvest the products nuclear fission naturally generates. Molybdenum-99, for instance, is naturally produced during the fission of uranium-235 and plutonium-239. Strontium-90 is similarly a byproduct of nuclear fission and is sometimes harvested from spent nuclear fuel.
You can also use nuclear fission as a particle source. The fission of uranium-235 releases neutrons, which can then be used to bombard various targets to produce isotopes. Cobalt-60, for instance, a widely used radiation source, is created by placing cobalt-59 in a fission reactor, causing some of the atoms to absorb a neutron via neutron capture.
Using nuclear fission as a source of radioactive isotopes began almost as soon as the first nuclear reactors were created. Long before the Atomic Energy Commission built the first nuclear power plants, it was shipping reactor-created isotopes across the country and around the world for medical and scientific research. By 1956, more than a year before the first US civilian power station at Shippingport came online, there were 50,000 isotope purchases per year from the AEC.
Via Life Atomic.
But there are also drawbacks to using fission as an isotope source. For one, fission reactors are highly regulated, and constructing them is difficult and expensive. For another, most of the neutrons produced by fission reactors aren’t particularly high-energy, and in power reactors they’re generally deliberately slowed down to increase the chances that they’ll strike an atom and continue the chain reaction. The average fission neutron is created around 1.5–2 million electron volts (MeV), moving at about 6.5% of the speed of light, but in power reactors they’re slowed down using a moderator to about 0.025 electron volts. And even without moderation, the relatively low energy of most fission neutrons means that many nuclear reaction rates will be slow, and other reactions are out of reach.
To create isotopes efficiently, what we’d like is some way to generate a lot of neutrons at much higher energies. This would make many sorts of nuclear reactions possible while avoiding the inefficiencies of using particle accelerators.
One way to do this is with nuclear fusion. Much has been made about the difficulties of creating a fusion power plant, but fusion has always been a problem of efficiency: getting more energy out of your reaction than you put into it. Creating the fusion reaction in the first place has never been the issue, and fusion reactions have been created in the lab as far back as the 1930s. And these fusion reactions reliably produce high-energy neutrons. While fission can produce high-energy neutrons, only around 0.1% of them will be above 10 MeV. By contrast, neutrons produced when fusing hydrogen-2 (deuterium) and hydrogen-3 (tritium) are 14 MeV or more. Fusion has historically not been used to produce isotopes, but today a variety of startups and organizations are pursuing the idea. SHINE Technologies is currently building a facility, Chrysalis, to create Mo-99 via a complex process that requires a particle accelerator, a fission reaction, and a fusion reaction. Italy’s SORGENTINA-RF program similarly wants to create Mo-99 using fusion-generated neutrons. Marathon Fusion wants to use fusion neutrons to create a variety of different isotopes, such as terbium-149 and actinium-225 for cancer treatments, as does New Zealand fusion startup OpenStar.
Possibilities of cheap isotopes
Beyond its ability to generate high-energy neutrons, fusion also has the potential to make isotope manufacturing dramatically cheaper, at least for some isotopes/reactions. Particle accelerators take a lot of energy to operate: GE’s PETtrace draws about 75 kW, roughly as much as 75 microwaves when it’s running, which sets some floor on how cheaply they can produce anything. At 75 kW, it would take around 0.7 terawatt-hours to produce a gram of fluorine-18, which is around 1.5 hours of the entire electricity output of the US.
Energy costs aren’t actually all that significant for medical isotope production, since the doses are microscopic (600,000 doses of fluorine-18 combined weigh about as much as a single grain of salt). But if you wanted to produce large amounts of isotopes — grams, pounds, tons — it would eventually become a binding factor. And a particle accelerator is essentially only producing isotopes: the isotopes must be priced high enough to recover the costs of building and operating the facility. With fusion, however, your isotope-producing reactions can (potentially) also produce energy — so if you use the right reactions, you could use the sale of that energy to help pay for the facility and its operation.2 It’s conceivable that the right energy-generating fusion reactions, in the right arrangements, might be able to produce isotopes far more cheaply.
What sort of things become possible if we can produce isotopes far more cheaply? There are a few major categories of interest.
Medicine
One of the largest isotope markets, with some of the most expensive isotopes, is medicine. With medical imaging isotopes, a patient is given a very small amount of radioactive material, which gets taken up by the body and (generally) incorporated into specific cells or substances. Fluorine-18, for instance, gets incorporated into a glucose-like molecule called FDG, that the body then absorbs as if it were glucose. By monitoring the radiation released by the isotope, some area of the body or biological process can be monitored.
Medical isotopes are also used for radiation treatment. Some elements naturally collect in certain areas of the body, and radioactive isotopes can be used to deliver targeted treatment. Iodine, for instance, naturally collects in the thyroid gland, and radioactive iodine-131 can be used to treat thyroid cancer. Other isotopes, such as actinium-225, decay by emitting alpha particles, which travel an extremely short distance in tissue, also making them useful for delivering very targeted radiation therapy. A better process for manufacturing these isotopes could potentially allow existing medical isotopes to be made more cheaply and reliably; actinium-225, for instance, is a potentially promising isotope for cancer treatment, but current supplies are so limited that only a small number of patients a year can be treated using it. A better process could also potentially enable the creation of entirely new medical isotopes.
Nuclear power inputs
Both fission and fusion reactors rely on isotopes for various parts of their operation. For fusion, the reaction that creates valuable tritium within the fusion cycle requires an isotope of lithium, lithium-6, which makes up about 7% of all lithium and which currently must be produced via an expensive process of lithium enrichment (which is currently only done in Russia and China). Conventional fission reactors, similarly, require the extremely pure lithium-7 produced by the same process, since naturally occurring lithium with too much lithium-6 would absorb too many neutrons. Some new proposed fission reactors, such as TerraPower’s molten salt reactor, require another isotope, chlorine-37, which is currently only produced by the gram but is needed by the ton. A reliable, cheap source of these sorts of isotopes could thus potentially be very valuable (though as I understand it these are much less valuable than medical isotopes, since they’re stable and can be produced via separation processes, so probably not something we’ll see produced via fusion in the near term).
Nuclear batteries
One of the many nuclear technologies that remain somewhat under-explored is nuclear batteries: a battery that generates electric current using a small amount of radioactive material. These sorts of batteries were used for pacemakers for several decades, and are used to power spacecraft, but with the ability to manufacture better battery isotopes many other uses might be found, such as undersea drones that can stay permanently submerged for monitoring undersea cables.
Materials
In some cases, the nuclear chemistry process might let you make “normal” materials that are otherwise difficult or expensive to get. Marathon Fusion got a lot of attention last year (and last week) for a fusion neutron-driven reaction that can create gold using mercury as an input.
Cheap nuclear chemistry might also allow you to more efficiently make what’s known as “isotopically pure” materials. Most elements found in nature have multiple stable isotopes, and thus any minerals or materials that contain them will contain a mix of different isotopes. Steel, for instance, will be a mixture of several different stable isotopes of iron (iron-54, 56, 57, and 58) and carbon (carbon-12 and 13). But if you could make isotopes very cheaply, you could possibly more easily produce materials entirely using one elemental isotope, such as semiconductors that only contain silicon-28.
In some cases, these isotopically pure materials might have interesting or useful material properties. Isotopically pure diamond has far higher thermal conductivity than regular diamond, for instance (as do, apparently, many other isotopically pure materials). And because of its different quantum-mechanical properties, isotopically pure silicon is useful for building quantum computers.
Historically producing isotopically pure materials has been so difficult that much about them remains unknown; reducing the cost of making isotopes could break open this field of study.
Conclusion
For many technologies, how big an impact they have is a function of how cheap they can get. Solar PV was a niche power generation technology before decades of falling down the learning curve; steel was an expensive material used in limited ways before Henry Bessemer and others found ways to produce it cheaply; Ford’s Model T changed the world not because it was the first car, but because of how cheaply Ford could manufacture it. So a technology that offers the potential to produce some existing thing far more cheaply is always interesting to me, and I’ll be paying attention to see how this develops with isotopes.
Technetium-99m is technetium that’s in what’s known as a “metastable” state, an excited state that eventually decays to regular technium-99, emitting gamma rays in the process.
Specifically, most fusion uses deuterium and tritium as inputs, known as D-T fusion. Deuterium is incredibly common, but tritium is rare and expensive. But you can add a step to the fusion reaction so that it also creates tritium, reducing or eliminating the need for an outside source of it.
Big-money tycoons have leveraged their fortunes to shape the state with their railroads, mines, newspapers, oil businesses and ranching and agriculture.
The organ procurement system has long been a miasma of inefficient monopoly providers. In 2024 I quoted some shocking facts from a great Statecraft interview with Jennifer Erickson and Greg Segal:
“Organs are literally lost and damaged in transit every single week. The OPTN contractor is 15 times more likely to lose or damage an organ in transit than an airline is a suitcase.”
“In an era when consumers can precisely monitor a FedEx package or a DoorDash dinner delivery, there are no requirements to track shipments of organs in real time — or to assess how many may be damaged or lost in transit.
“If Amazon can figure out when your paper towels and your dog food is going to arrive within 20 to 30 minutes, it certainly should be reasonable that we ought to track lifesaving organs, which are in chronic shortage,” Axelrod said.
Did you get that? The tracking system for patients is so dysfunctional that 17% of kidneys are offered to patients who are already dead–thus creating delays and missed opportunities.
Fortunately, even then there were changes in the works. In 2019 President Trump issued Executive Order 13879 to improve the performance of OPOs with better incentives and to allow living donors to recover more of their costs. The government being what it is, it has taken years to implement some of the new rules and enforcement of the OPO performance measures was deferred to 2026-2027. Nevertheless, there have been improvements. For example, many OPOs now GPS-track kidney transfers. And a new report estimates there have been significant gains from the changes.
The Advancing American Kidney Health initiative was launched by President Donald Trump via Executive Order 13879 on July 10, 2019. In this Data Point, we estimate the range of increased growth in transplants that might be attributed to the policies launched through the Executive order and the economic value of that increased growth.
The estimated impacts of the Executive Order (EO) range from a conservative 1,055 additional transplants annually to an upper estimate of 2,110 additional transplants. The range reflects variation in the counterfactuals used to compare with post-2019 transplant growth.
Under the conservative-case scenario, the policy is estimated to be associated with approximately 23,214 additional kidney transplants between 2019 and 2040, generating about 147,410 life-years gained and 21,821 quality-adjusted life-years (QALYs) gained. Under the optimistic-case scenario, the policy is estimated to be associated with approximately 46,428 additional kidney transplants between 2019 and 2040, generating about 294,819 life-years gained and 43,643 quality-adjusted life-years (QALYs) gained.
The biggest and most consequential change would be to allow payment to living organ donors. The End Kidney Deaths Act, H.R. 2687, proposes a $50,000 refundable tax credit over five years for qualifying nondirected living kidney donors. The act has bipartisan support. Because dialysis is so expensive—and the federal government pays for much of it through Medicare’s special kidney-failure entitlement—the Act could save taxpayers money as well as saving lives.
Rolfe Winkler, in a crackerjack story for The Wall Street Journal (gift link):
Blevins, who left Apple in 2022, sometimes set up
back-to-back meetings with suppliers so that rival sales teams
might run into each other, stoking competitive tension. Sales
representatives learned to pack nutrition bars to sustain them
through negotiating sessions that Apple executives sometimes
pushed past midnight without a dinner break. Blevins’s bad-cop
reputation gave his staff leverage: They threatened to call him in
if contract terms weren’t to their liking.
One significant contract term allowed Apple to audit its
suppliers’ books. Flash makers typically had to designate Apple
as a “most favored customer,” which guaranteed that no other
buyer got a lower price, according to people familiar with the
agreements. Apple’s audits allowed it to verify that no one
paid less.
Apple caught Micron selling flash at cheaper prices to another
customer and won an arbitration settlement worth tens of millions
of dollars more than a decade ago, said people familiar with the
dispute. Apple audited its suppliers so often that Blevins
negotiated a volume discount with the auditor, Deloitte.
The whole story is a fascinating and entertaining read. But I don’t get the “revenge” angle in the headline. The biggest buyers can negotiate the best deals. Apple used to be the biggest buyer, by far, for flash memory chips. They negotiated, with hardball but above-the-board tactics, the best deals. Now, Apple isn’t the biggest buyer — the AI datacenter hyperscalers are. Apple no longer gets the best deals. But they’re still getting fair deals. Apple is still negotiating the best deals it can for itself. So where is the “revenge”? The pinch mostly isn’t being felt by Apple — it’s being felt by Apple’s customers, who now face significantly higher product prices.
I included “mostly” in the preceding sentence because Winkler, in collaboration with the research firm TechInsights, makes the case in the piece that the rising costs of flash memory have eaten into the remarkably juicy profit margins Apple has historically earned from higher-storage upgrades.
What I also don’t get, at all, is the participation in the story by Scott Nelson, the chief marketing officer at Kioxia (which I learned in this story is the new name for the company formerly known as Toshiba Memory Corporation), a major flash supplier. Nelson told Winkler he so loathes Apple that he shot his old iPod with a rifle and keeps the pieces on his desk. The article ends thus:
The industry’s low point came in 2023. The Covid-era,
work-from-home device boom cooled, and flash prices bottomed out
at 5 cents a gigabyte. Bernstein Research estimated the flash
industry generated operating losses of $19 billion that year,
while Apple earned $14 billion in gross profit selling extra flash
storage.
Those were tough times that “I hope we don’t ever see again,” said
Nelson, the Kioxia sales executive.
Yes, I’m sure the current AI datacenter mania will last forever, the bubble will never burst, and that even if it does, no one at Apple will remember Nelson’s participation in this story.
How Jason Snell beat me to linking to this, I don’t know. But like I said back in February, when it comes to signage, “Mind your P’s and Q’s” ought to be “Mind your H’s and S’s”.
I don’t want to go poll by poll. You know where to find them. But we have new and pretty bullish new poll data in the battle for the Senate. (Yes, they’re just polls. They can be wrong and all that.) A bunch of polls have come out in the last 48 hours, including two high quality ones (CNN and NYT/Siena). Both show pretty substantial leads for Democrats in key Senate races.
Here are some general observations.
The one place where Republicans can have some optimism is in Iowa. Democrat Josh Turek could easily win. He even has a nominal lead in the polling averages. But this is a tie race. And relative to what we’ve seen in much redder states, Republican Ashley Hinson, who I think is an objectively good candidate in a very bad environment, has at least kept very much in this race. So these are reasons for GOP optimism in a moment where there’s very few reasons for optimism available.
We’ve had a bunch of strong polls for Abdul El-Sayed. We have CNN and another lower-tier poll just out with El-Sayed 7 points ahead. A few days earlier one of the two in-state signature polls, Glengariff Group, had him 6 points ahead. The outlier here is InsiderAdvantage, a strongly pro-GOP poll, which had him at the same time as the Glengariff poll at +1. El-Sayed could certainly lose but if he does it will be a significant polling error.
South Carolina genuinely, bizarrely, seems in contention. NYT/Siena just showed it a tie race. Three other slightly older polls have Graham up +3,+4 and +1. So a lead but not far off from the Times poll. I saw one operative note that GOP governor candidate Alan Wilson has a very high single-digit lead. That’s a big delta and South Carolina has straight ticket voting. That could potentially save Graham here. Truly everything has to come into alignment for Democrat Annie Andrews to win. The ability to vote a straight ticket in what is not only usually a strongly Republican state but appears to remain strongly Republican outside this one Senate race could make a small but real difference. Who knows? What’s amazing is that there’s a real chance Andrews could win. To put this into perspective, Nate Silver’s probabilities say that Andrews is significantly more likely to win than Republicans are to hold the Senate. Take it for what you will.
We haven’t had a premium poll out of Kansas in about a month. CNN’s new poll shows Democrat Adam Hamilton up four points. Given the partisan muscle memory in Kansas and the real but limited recent history of GOP-underestimating polling error being strongest in very red states, I still think you have to consider this a straight toss up. But still, Kansas.
I jest, a bit, in the title. As I’ve told you several times, friends don’t let friends watch the early vote. But there’s one thing I want to point your attention to. I’ll explain in a moment why this leaves me mainly consistent.
There’s one thing that seems to be showing up fairly consistently across the country and particularly in the Deep South. That is a high proportion of generally younger, non-regular Democratic voters. And they tend to be less white, relative to the rest of the electorate. In a number of Deep South states you’re seeing high turnout for non-regular Democratic voters which in states like Mississippi for instance means mostly Black voters.
As I’ve mentioned a number of times, the problem with watching the early vote is that you’re trying to figure out a candidate’s percentage of the pie before you know the size of the pie. Maybe one party is doing great in the early vote but they’re really just cannibalizing their Election Day vote so it’s meaningless. The sharper people who analyze these things are operating at a much higher level of sophistication than this illustration suggests; but the same fundamental problem applies. What’s different here is that you’re talking about a group of voters who aren’t usually part of the pie at all. So you can draw some different inferences. Needless to say, these people could be matched by a bunch of non-regular Republican voters on Election Day. But there’s accumulating evidence that points against that.
To be clear, something like what I’m describing above is what you’d expect to see in a strong wave election. So this isn’t “wow, it’s even bigger than we thought.” This is just an indicator that would be broadly consistent with a big wave — nothing you can be sure of and in itself it’s a relatively small slice of the electorate. Just keep it in mind.
The other thing is that we’re starting to see signs that Callais (the decision which effectively killed the Voting Rights Act) is spiking Black turnout in the states where Republicans most aggressively moved to disenfranchise Black voters. This overlaps with the point I made above since by definition, higher than usual turnout means non-regular voters showing up. The biggest pool of non-regular voters are younger voters. I note this in large part because I’m seeing Republican pollsters worrying about it too.
As I’ve said previously, don’t take this as confirming anything is going to happen when the votes are counted. It’s more that if Democrats have a strong night, these details about the shape of the electorate will probably be key parts of that outcome.
As we get ready for the final days of the 2026 midterm campaign, I wanted to flag some key parts of our coverage. First, don’t miss our midterms liveblog which you can find on the front page and also at this link. We’re starting with a focus on election interference issues and then we’ll shift toward broader Election Day news and results as we move into next week. Next, the TPM team has done a comprehensive analysis of just who certifies election results in each of the Senate swing states and what funny business they can pull. You can see that here. We also have our take on which 13 races we think will define the midterms, which you can read here. Finally, join us here Tuesday night. For the first time we’re going to be doing live video coverage of election night. Think of it as comparable to what you might see on CNN or MS NOW but with more insight about how to understand the results, what’s happening in key counties and precincts rather than just the toplines and just TPM level analysis. I hope you’ll join us.
Apple is making changes to the Taiwan storefront of the App Store,
following discussions with the Taiwan Fair Trade Commission.
As of October 31, 2026, the commission rate for standard Apple
In-App Purchase and paid app transactions will be 26% on the
Taiwan storefront of the App Store on iOS and iPadOS. Currently,
that rate is 30%.
Well there we go. The App Store in Taiwan — just like in Japan — is fixed.
No big news or even original analysis in this post, just a general observation. I was just looking at the VoteHub Senate predictions. This is a relatively new entrant into the election modeling/forecasting world. They’re a bit more cautious than Nate Silver’s Silver Bulletin, seeing the most likely outcome as Democrats taking 52 seats versus 53. That’s probably actually technically the median result of running numerous modeling simulations. In any case, I was looking at the categories in which they place different races. For instance, they put Texas, as “Lean D”, so more likely to flip than Ohio, Maine and Iowa. I’m not sure that’s wrong. But it’s just wild to see.
A year ago the conventional wisdom was that only Maine was a plausible pick up opportunity, maybe North Carolina. But Democrats have been disappointed by North Carolina plenty of times in the fifteen years or so. And Democrats would be lucky just to hold on to Georgia. We’re simply talking about a range of states that no one was even considering a year ago.
What struck me, though, looking at this, was how hard it is for me to even have a hunch on some of these states because they’re just so Republican that I have no baseline for even evaluating them in partisan terms.
Let me restate the obvious which is that I don’t work with data analysis and modeling like all the folks in that space do. These are my own efforts to figure things out, which are a mix of experience, intuition, etc., not really data-driven in any sophisticated sense. But like Kansas? Who knows? That’s a seriously Republican state! The thing about Kansas is that it’s more Republican than the Republican party, by which I mean that Kansas was Republican when the GOP was a predominantly northern party. It’s still totally Republican when the GOP is a predominantly southern party. It hasn’t elected a Democratic senator in almost a century. We have a range of different data points which make it seem like this really might be happening there. In fact, if you really strain to look at the data in just the right way maybe it’s not even a toss up. But those are just shards of evidence here or there. There are plenty of plausible ways that Republican Roger Marshall could end up winning by mid- or even high single digits and the whole thing was a mirage.
But what baselines, what frameworks do you use to evaluate when and whether a state like Kansas is primed to elect a Democrat. Truly who knows? It hasn’t happened in a century. And it’s not just Kansas. A number of these states are similar, at least to the extent that recent history, at least to me, provides very little frame of reference for evaluating a competitive partisan race.
Regional GOP chair from Indiana sending out a letter reminding the members of the party central committee for the state’s third congressional district that they’re obligated to vote for Republican party candidates …
Misdemeanors account for three-quarters of criminal cases filed annually in the United States, yet causal evidence on the impacts of misdemeanor conviction is scarce. We combine administrative and survey data to provide novel evidence of how misdemeanor conviction affects the socioeconomic outcomes of defendants and their families. Using data on nearly seven million defendants from 11 states, we characterize the types of people involved with the misdemeanor system. We estimate causal impacts of a conviction relative to a charge using seven county reforms that sharply reduced conviction rates. Regression discontinuity design estimates yield precise null average effects of the reforms on criminal and labor market outcomes. Defendants dismissed by the reform are unlikely to re-offend if dismissed, but also unlikely to be harmed by conviction—marginal defendants are older and more likely to have been charged with minor crimes than the average defendant. Heterogeneity analyses suggest that conviction harms young and first-time defendants, implying that interventions targeting dismissal toward these groups would be beneficial. Finally, our causal estimates imply a negative Marginal Value of Public Funds of misdemeanor conviction, even under plausible estimates of general deterrence effects.
That is from recent research by Nikhil Rao and James Reeves, note that Rao is this year on the job market from University of Michigan.
Cowen: …Another proposal I’ve made is that schools should let people do one class, only one class, AI-only — no professor, except a professor grades at the end. The professor grades not answers to an exam but the workflow of how the student used AI to learn the Glorious Revolution, or the Civil War, or whatever the student learned. Eventually, another AI will grade your AI log. But let’s start today with a professor, and try this for one class. I’m not sure how it will go. But especially for small schools that don’t offer that many classes, a student now can create a class in literally everything.
If it’s successful, let them try two classes. I think the students doing this on their own are more likely to figure out how to blend AI and education than we would from a distance with some kind of centralized vision. Let them experiment.
Carlson: Students should be leading the change at colleges and universities?
Cowen: Absolutely. Students know more about AI than their professors do. Some of this comes from cheating, which is unfortunate. But the notion that the professors teach the students AI — I wish. It’s not always possible. You could imagine setting up a class where the students teach the professors AI, and we give the students credit for teaching. I’m half joking, but it’s not, in fact, a crazy idea. We need to experiment along a number of fronts. I’m quite convinced no one knows how to do this. It hasn’t been done before. So again, just one class. In general, schools hate this idea. They see it as opening the door to rendering some professors obsolete.
And this:
Carlson: There are a number of students who are deeply opposed to AI. What place do they have in this university that you’re thinking about?
Cowen: I would love to have different schools with different policies. If some universities try to ban AI altogether, that’s great. Let the competitive process operate. Personally, I would bet against those schools. For a long time, I’ve been worried that within a given tier of school — big state school, community college, Ivy League — there’s not enough diversity. AI policies will force a kind of diversity on us. So I’m all for no-AI schools, even though I would not go to one.
Earlier this month Anthropic announced a generous new benefit for their Max and Team subscriptions: $100, $200, and $500 per month subscribers would get the equivalent quantity of (expiring) credits to use with the Anthropic API.
OpenAI have now launched pretty much exactly the same deal: if you have a $100, $200, or $500 subscription plan with them you now get that same quantity of credits to apply to one of your API organizations.
I maintain subscriptions with both companies, so this is great news for me! I may even ship some public-facing demos now that the credits are already covered by my existing subscriptions.
Don't be put off by the clickbait headline, this piece by Jacob Sansbury describing how they are building Spawn is a fascinating exploration of the bleeding edge of what's possible with agentic engineering against frontier models.
Spawn is a massively multiplayer gaming environment where players can use prompts (to the in-game agent, Savi) to modify the game world.
I fired it up on my phone for a few minutes and was able to prompt a castle into existence, then a dragon, then ride the dragon to fly around that castle.
By Jacob's telling, Spawn is now being developed autonomously by a swarm of Fable-powered agents costing over $3 million in tokens per month ("we spend 30x payroll on AI tokens").
Our agents change the live code directly and ship to production hourly, so they read every error, bug report and metric themselves. About 60% of our work starts from a production error, a Savi bug report (Savi is the AI you build games with in Spawn), something odd in our logs, or a feature request.
Savi files bugs herself. When a user hits one, or Savi hits one in the product, she files it. It goes straight to an agent that decides whether it's a real bug to fix, something we won't fix, or intentional design that needs a decision. Usually it becomes a change, delivered to that user within an hour, with a message in the same chat.
A loop this tight only works if it never stops, so we treat an hour without a ship as a SEV-0, our most severe kind of incident. Unshipped changes pile up, and every problem already in production lasts longer. The feedback slows down too. An agent can only keep a few hours of work in its head, so shipping faster than that actually helps it stay coherent. [...]
We can roll back a broken change in 30 seconds, exactly where it's broken and nowhere else. When a monitor or a log alert fires, it starts or wakes an agent that owns the incident, and we break things on purpose to test that those recovery paths work.
My eyebrows raised at least a dozen times reading this. I have trouble imagining this style of development working on software with higher stakes for when something goes wrong, but for a game this appears to be working surprisingly well.
Jacob says that Fable 5 (and then 5.1) was the model that made this level of autonomy possible. Opus 5.5 doesn't quite hack it for them, and when they tried GPT-6 Astra to apply fixes from a security review everything stopped working:
Every feature had been disabled and marked to be turned on again once the security fixes were done. Astra had gone through our whole product and made the insecure things secure by turning them off.
These kinds of extreme experiments are why I'm excited about game development as a substrate for exploring the edges of what today's coding agents can do.
According to recently released discovery materials, Meta directly targeted Jonathan Haidt by trying to stir up academics to oppose him. The odd thing is that many of us scholars who disagree with him knew nothing about this and weren’t involved in it. And so now scholars like the amazing Candice Odgers are being doubted about the sincerity of their critique. WTAF upside down world are we living it?
What’s super frustrating is that many scholars in the teens-tech-mental health space are repeatedly accused of fabricating research or being corporate shills when our research is politically inconvenient. I know that I have been. Repeatedly. And it sucks.
When I was still in graduate school, I was asked to serve on the Internet Safety Technical Task Force. One of my responsibilities was to oversee the research effort. I worked with other scholars to track down all studies that focused on content, contact, and conduct related harms involving the internet. The politicians were primarily interested in the question of pedophiles. When I provided the report to then Attorney General Richard Blumenthal, he told me to go find different data. He did not like what I had found. I didn’t know what to say.
Predation is real. It’s devastating. But it’s a more complex dynamic than most people’s mental image allows for. And when it comes to internet-enabled predation, the biggest risk is not teenagers using the latest social media site. The biggest risk is single moms using online dating apps. Pedophiles seek out these women to get access to their children. It’s sick. But no one wants to hear that. They want to focus on the digital tools young people use.
After our report was published, I started getting calls from journalists. I earnestly and naively responded to all of them. One of the journalists was from PBS Frontline. She called me up repeatedly, drilling me on questions about arguments in the report. I responded by providing study after study to every inquiry, pointing her to different researchers who were experts on different parts of this puzzle. After a few weeks of this, I got what would be the last call from her. She started out by apologizing to me.
Unbeknownst to me, some of Richard Blumenthal’s ardent supporters for his Senatorial campaign were outraged that I dared to challenge the politician’s arguments about internet safety. They were determined to prove that I was falsifying data on behalf of the tech industry. The Frontline reporter told me she was assigned to uncover my duplicitousness. She had concluded I hadn’t done anything but report on the scientific insights of the field. She spiked the story, but she warned me that I had pissed off some very powerful people and I would probably have to deal with being demonized going forward for standing up for research. Ugh.
Ironically, I first started truly despising Facebook-the-company while I was working on that task force. I got to watch up close how the company built a coordinated campaign against MySpace, intentionally creating the impression that MySpace was dangerous while Facebook was safe. And I witnessed teenagers process this through the language of racism and classism, prompting me to write a very controversial essay that turned into my paper “White Flight in Networked Publics?” I was fascinated – and disgusted – by the executive who seemed to do the dirty work on behalf of the CEO and COO, unbeknownst to others in the company. I called him the bulldog. The bulldog continued to harass all sorts of different people.
These days, I have absolutely nothing nice to say about Meta-the-company despite knowing a few amazing people who work there. I think the company is unethical to the core. And the products have enshittified so badly that they’re unrecognizable compared to what teenagers used to use. Hence my argument that “Social Media is Now Parasocial Media.” But I still stand by my research on teens and the research of others who have done rigorous analyses putting teens’ lives into context. Teenagers live in the world we create for them – and they use what’s available to them, regardless of how they feel about it. In the past, teens turned to Facebook to socialize and make sense of public life. Today, Facebook is dead to teens and Instagram feels more like some sketchy version of MTV. Socialization is on group chats, some of which unfold on WhatsApp. But most teens have nothing nice to say about Facebook.
Many teenagers in our contemporary world are struggling. I’ve gotten to see that upfront through my work at Crisis Text Line, which I adore. And I’ve gotten to consistently witness how the problems that they face cannot be explained by their tech use. Because of this, removing tech from their lives will not solve the major problems. And for some, like many of the teens who text Crisis Text Line in their darkest moments, losing access to a cell phone will eradicate an essential lifeline.
I have no interest in defending tech companies, but I am deeply committed to defending teenagers’ agency and choices in the world that we have given them. I am determined to make sure that those teens who don’t have supportive parents have pathways to get help. And my research has repeatedly led me to conclude that when we fail to empower teenagers to transition into adult worlds, we do them more harm. And when we focus on the tech, we fail to help those who need the help the most.
Many of the problems that I have with tech use are actually about adult tech use. Too many adults treat their phones as a pacifier to help them self-regulate. They’ve taught this bad habit to their kids. Too many adults fail to role model healthy sociality digitally and in-person friendship. Too many adults use their phones to be distracted from their own children. And then we’re surprised by the mirrors that teens offer back at us. “I learned it from watching you, dad.”
What kills me in the contemporary teens-and-tech debate is that there’s no space for actual research or critical nuance. You’re either opposed to the tech companies or in their pockets. And this week’s absurd discovery reinforces this infuriating polarity, painting those of us who are critical of Jonathan Haidt as being corporate shills. I find this especially frustrating because I did work in tech for a lot of my career. I played the role of friction inside many companies (although never Meta). I repeatedly got threatened by tech executives for challenging corporate mantras or providing research that contradicted their interests – and yet I persisted. Cuz many tech companies are far more complicated than people realize.
Still, I’ve had to grit and bear as I am attacked by other scholars for taking money from tech (as if any money in late-stage capitalism is clean money). And I had to stomach calls from representatives of the National Academies that I can’t even talk with their committee members because Jonathan Haidt told them that I was a corporate shill. And I’ve had to not weigh in on numerous recent debates because my peers and news outlets tell me I am tainted. In this political climate, I am unable to convince people that my research stems from the lessons I learned from teens, not what I learned from tech. I’ve mostly shrugged. But when journalists started going after Candice, I lost my mind and felt the need to share my story. The idea that she is being painted as a corporate shill is ludicrous.
Cuz here’s the thing… It IS possible to despise the tech companies AND understand why teenagers use their products and find value from doing so. Listen to teenagers; they get these contradictions. Their hatred of the tech companies is growing exponentially even as they use the tools those companies provide. (You should see their attitudes towards AI companies. Oooh-whee…) It’s also possible to care about kids’ mental health AND think that the solution doesn’t start and stop with tech. And it’s possible to do rigorous research AND discover that tech isn’t the biggest monster in teens’ lives that anti-tech advocates think it is.
Truth be told, I’d have no problem if certain social media platforms would be banned for everyone. I think that many of the products in this space have devolved into garbage. My objection is a teen-specific ban. I oppose legal controls of teenagers because adults are trying to cope with the guilt about their own failings. We are living through an era of anxious parents. It’s heartbreaking the costs of this anxiety.
Of course, if politicians want to implement an age-specific ban to target those most harmed by social media platforms, I’d be totally fine with banning elders from social media. That would do society a lot of good. Just think of what it would mean in terms of identity theft and fraud, not to mention disinformation. But that’s the rub. We believe that adults’ freedom of choice needs to never be constrained, but that it’s perfectly OK to micromanage teenagers. THIS is what I object to. I believe that teenagers deserve rights and agency. I think it’s utterly asinine that the United States never ratified the UN Rights of the Child. This doesn’t make me a corporate shill. This makes me an advocate for teenagers.
As I wrote over a decade ago, we’ve made ridiculous decisions that have undermined teenagers’ ability to socialize and connect with friends. And it keeps getting worse. Teens have lost the right to roam. In many parts of the country, they’re overscheduled and have nowhere to go to hang out with friends besides each other’s homes. Teenagers don’t have sustained access to mental health services (and they often have to go through their parents’ insurance to get access). They’re living through a polycrisis. And what they’re seeing in the world of adults is depressing. There’s a lot that we can do to help young people. But much of it starts locally. Much of it starts with adults checking their own behaviors. Much of it starts with intentionally investing in the social lives of young people. Giving them options. Creating space for them. Ensuring that they have robust social fabrics. Tech is a relief valve, and an increasingly terrible one. But taking tech away won’t do squat to address the underlying issues. And, worse, banning social media is basically an advertisement for it. Cuz right now, social media is dying a slow death among teens cuz it sucks so much. But teens are still looking for spaces in which they can connect and socialize and make sense of the world around them. What will it take for us to actually invest in young people?
This morning was brought home my new velvet cloake, that is, lined with velvet, a good cloth the outside, the first that ever I had in my life, and I pray God it may not be too soon now that I begin to wear it.
I had it this day brought, thinking to have worn it to dinner, but I thought it would be better to go without it because of the crowde, and so I did not wear it. We met a little at the office, and then home again and got me ready to go forth, my wife being gone forth by my consent before to see her father and mother, and taken her cooke mayde and little girle to Westminster with her for them to see their friends.
This morning in dressing myself and wanting a band, I found all my bands that were newly made clean so ill smoothed that I crumpled them, and flung them all on the ground, and was angry with Jane, which made the poor girle mighty sad, so that I were troubled for it afterwards.
At noon I went forth, and by coach to Guild Hall (by the way calling at Mr. Rawlinson’s), and there was admitted, and meeting with Mr. Proby (Sir R. Ford’s son), and Lieutenant-Colonel Baron, a City commander, we went up and down to see the tables; where under every salt there was a bill of fare, and at the end of the table the persons proper for the table. Many were the tables, but none in the Hall but the Mayor’s and the Lords of the Privy Council that had napkins1 or knives, which was very strange. We went into the Buttry, and there stayed and talked, and then into the Hall again: and there wine was offered and they drunk, I only drinking some hypocras, which do not break my vowe, it being, to the best of my present judgement, only a mixed compound drink, and not any wine. If I am mistaken, God forgive me! but I hope and do think I am not.
By and by met with Creed; and we, with the others, went within the several Courts, and there saw the tables prepared for the Ladies and Judges and Bishopps: all great sign of a great dinner to come. By and by about one o’clock, before the Lord Mayor came, come into the Hall, from the room where they were first led into, the Lord Chancellor (Archbishopp before him), with the Lords of the Council, and other Bishopps, and they to dinner. Anon comes the Lord Mayor, who went up to the lords, and then to the other tables to bid wellcome; and so all to dinner. I sat near Proby, Baron, and Creed at the Merchant Strangers’ table; where ten good dishes to a messe, with plenty of wine of all sorts, of which I drunk none; but it was very unpleasing that we had no napkins nor change of trenchers, and drunk out of earthen pitchers and wooden dishes.2
It happened that after the lords had half dined, came the French Embassador, up to the lords’ table, where he was to have sat; but finding the table set, he would not sit down nor dine with the Lord Mayor, who was not yet come, nor have a table to himself, which was offered; but in a discontent went away again.
After I had dined, I and Creed rose and went up and down the house, and up to the lady’s room, and there stayed gazing upon them. But though there were many and fine, both young and old, yet I could not discern one handsome face there; which was very strange, nor did I find the lady that young Dawes married so pretty as I took her for, I having here an opportunity of looking much upon her very near.
I expected musique, but there was none but only trumpets and drums, which displeased me. The dinner, it seems, is made by the Mayor and two Sheriffs for the time being, the Lord Mayor paying one half, and they the other. And the whole, Proby says, is reckoned to come to about 7 or 800l. at most.
Being wearied with looking upon a company of ugly women, Creed and I went away, and took coach and through Cheapside, and there saw the pageants, which were very silly, and thence to the Temple, where meeting Greatorex, he and we to Hercules Pillars, there to show me the manner of his going about of draining of fenns, which I desired much to know, but it did not appear very satisfactory to me, as he discoursed it, and I doubt he will faile in it.
Thence I by coach home, and there found my wife come home, and by and by came my brother Tom, with whom I was very angry for not sending me a bill with my things, so as that I think never to have more work done by him if ever he serves me so again, and so I told him.
The consideration of laying out 32l. 12s. this very month in his very work troubles me also, and one thing more, that is to say, that Will having been at home all the day, I doubt is the occasion that Jane has spoken to her mistress tonight that she sees she cannot please us and will look out to provide herself elsewhere, which do trouble both of us, and we wonder also at her, but yet when the rogue is gone I do not fear but the wench will do well.
To the office a little, to set down my Journall, and so home late to supper and to bed.
The Queen mends apace, they say; but yet talks idle still.
The boom in AI-related spending is already enormous relative to the size of the U.S. economy and is widely expected to grow even bigger. Indeed, a widely cited projection by Stijn Van Nieuwerburgh of the Columbia Business School concludes, based on announced plans by major players in the industry, that this will be the biggest investment boom in U.S. history, measured as a percentage of GDP:
Source: Stijn Van Nieuwerburgh
Well, I’m going to make a prediction: This will not happen. Instead, the splurge on AI will run into two walls that will force either postponement or cancellation of many of those announced projects.
First, the money to fund all this AI investment spending simply won’t be there. Much of the spending so far has come from established industry giants like Google and Microsoft, who in the early phases of the boom could rely on retained earnings from their existing businesses. But the size of the buildout is now so big that it is increasingly dependent upon massive levels of borrowing.
And lenders are getting cold feet. Many observers have long argued that AI is an impressive technology, but profits will be elusive. And it’s now apparent that companies that are spending hundreds of billions on frontier technology are unlikely to generate enough profits to justify their huge outlays. There are a variety of reasons why, with the most obvious being competition from much cheaper and less powerful, yet commercially adequate, models from China.
After all, we’ve seen this movie before. The IT boom of the late 1990s changed the world, but it also ended with many tech leaders going bankrupt because they couldn’t monetize their achievements. During the last few weeks, lenders to AI companies seem to be having a collective Wile E. Coyote moment — the point at which the animated character, having run off a cliff, looks down and only then, obeying the laws of cartoon physics, plunges to the ground.
The financial data now clearly show that fear is spreading in the loan markets. Starting in the summer, CDS spreads — the price of insurance against default — have soared for a number of AI companies:
Coreweave, which basically sells compute, is in a league of its own in terms of high default risk. But other companies are also starting to show strain, especially Oracle. As yesterday’s Bloomberg headline put it,
With lenders running scared, and either demanding much higher interest rates or refusing to lend altogether, it’s increasingly difficult to see how the hyperscalers can realize their gargantuan investment plans unless someone is willing to take massive losses.
Furthermore, the AI investment boom is facing another huge obstacle: Most Americans really, really hate data centers and AI in general.
The polling on data centers is astonishingly negative. Not only do most Americans oppose construction of data centers near where they live, an almost equally large majority oppose building them anywhere in the U.S. And the opposition is much more intense than the support:
This hostility no doubt has multiple sources. Data centers impose real costs on communities through their consumption of water and electricity, as well as pollution if they build their own power supplies. At the same time, data centers, once up and running, provide almost no local jobs.
At a more cosmic level, there are widespread fears that AI will lead to mass unemployment and possibly even human extinction — fears that have been spread by the industry itself, in the belief that fear of apocalypse is good for their IPOs.
More generally, the race to build data centers, often accomplished through back-room deals with corrupt local politicians, feeds into the public sense that big-money elites are rigging the system against ordinary Americans.
But the American public is now fighting back, pitchforks in hand. Grassroots opposition is having a big effect because permits are needed to build giants data centers — permits that more and more local governments are refusing to grant in the face of local opposition. One important contributor to Oracle’s problems is the repeated rejection of permits for a natural gas pipeline to provide power to Project Jupiter, Oracle’s massive data center project in New Mexico.
Elsewhere, New York State has introduced a one-year moratorium on all construction of large new data centers, while a number of other states and local governments are considering major restrictions. Furthermore, the political environment is unlikely to become more favorable after the midterms given how well Democrats are polling across state and local races.
Granted, neither financing problems nor political opposition are likely, by themselves, to completely stop AI investment. But I predict they will greatly slow it down. And this would be a very good outcome, perhaps even allowing the AI bubble to deflate rather than bursting and thereby delivering a body-blow to the overall economy.
Yes, some companies – such as Coreweave – may very well go bust and many investors will be hurt. However, under current investment plans, there’s a high probability that a lot of that investment money would have been wasted and total losses would be many times larger. Thus, in the end, angry locals and panicky lenders may well end up saving investors from themselves. And, more importantly, slowing this juggernaut down may save the American economy from the devastation of the bursting of a gigantic AI bubble.
The fundamental idea was that the Universe only has so many insights to discover, and that we’ve picked the low-hanging fruit. It was the idea that Joseph-Louis Lagrange expressed when he said that “we cannot find more than once a system of the world to establish.” As the big ideas and the simple ideas get mined out, we’re forced to throw ever more brains at the mysteries of nature just to keep scientific progress going at a fraction of its old pace:
It looked like science was hitting a wall. Then along came AI.
It’s far too early to tell how much AI will eventually speed up the growth of total factor productivity. But already we can see signs of a speedup in science. Anthropic Founder Jack Clark assembled some of the hopeful data points in a recent lecture:
Anthropic is accelerating its investment into drug discovery, and is already announcing some impressive preliminary results:
Meanwhile, Google Cloud Chief Scientist Pushmeet Kohli has a list of recent scientific advances that have been enabled by its new Gemini model, including breakthroughs in nuclear fusion reactor design, rare disease research, and quantum computing:
But as cool as these stories sound, they’re just very minor, preliminary efforts. There are a number of reasons to think that AI is going to propel us into a golden age of scientific discovery. That age might not last forever — AI might still run into diminishing returns eventually. But the next few decades are probably going to be an absolutely amazing time for human science.
(Note: This post is written under the assumption that human civilization survives. A golden age of science could also easily turn into a golden age of bioterrorism, in which case all bets are off.)
The number of “effective researchers” is no longer limited
The most important input into science is scientists themselves. Until this year, that meant human brains — talented, highly trained human brains. The number of trained human brains could be increased by sending more people to grad school, but only to a point — the smartest people tend to be sent into the hardest research fields first, and if you 10x the number of researchers, the average quality will go down. This constraint was already starting to bite, as Ekerdt and Wu argued in 2024:
We argue that a substantial portion of the downward historical trend in U.S. research productivity is a composition effect resulting from self-selection in researcher ability and the dramatic expansion of the research sector…[W]e find that this composition effect has lowered average researcher ability by between 37% and 53%[.]
AI just blows up this constraint completely. If an AI agent can function as an autonomous researcher, there’s no constraint on the number of researchers in the world — you can just build more of them, by building more computer chips and data centers that enable the running of more AI agents. Whether or not massive hordes of agents can collaborate to solve individual problems much faster, increasing the number of agents allows them to tackle many different research questions in parallel.
What’s more, these AI “researchers” can be trained incredibly quickly compared to human beings. A human scientist takes decades to train, and more years to reach the frontier of their research field by diligent reading and conversation. This is the “burden of knowledge”, and it’s commonly believed to be one reason ideas have been getting harder to find — by the time human scientists can get up to speed, they’re often so old that their ideas are no longer novel.
AI just annihilates this constraint — it can assimilate the entire literature and reach the frontier of research extremely quickly, and it can also tell human scientists where the frontier lies without forcing them to discover that for themselves. It can also pivot to new research directions more easily than humans can.
And there’s also a self-reinforcing economic cycle here. Because scientific advances enable higher GDP, they enable more resources to be invested into the creation of yet more electronic “scientists”.
Now that doesn’t mean the amount of scientific research goes to infinity — there may still be some essential bottleneck task that human researchers are still needed to perform. There are some indications that AI’s progress on open-ended conceptual research tasks is slower than in other dimensions, and it may be that humans are still needed to provide some of this long-term conceptual thinking. I’d bet against this being true for much longer, but it might be true for a long time.
Even in this most “pessimistic” case, though, the amount of effective capital that scientists can use to leverage their work just went up by a lot.
AI eliminates the theory bottleneck
Science proceeds by an iterative process of theory and experiment. The theory part of that cycle is typically short, but non-trivial — it took a couple of years after the blackbody radiation spectrum was observed for Max Planck to come up with the quantum hypothesis to explain it, and decades longer before quantum theory as we now know it was created. It took about a year for Watson and Crick to figure out the shape of DNA after the requisite data was gathered.
AI will basically eliminate the theory bottleneck entirely — or at least shorten the turnaround time between experiment and theory by an order of magnitude. AI is an absolute beast at math. Recently, an OpenAI model solved some of the most important open problems in computer science, math, and theoretical physics, and no one even batted an eyebrow because that sort of triumph is becoming increasingly commonplace. One of those solutions was a proof that the Standard Model of Particle Physics could be mathematically well-defined — a problem that human theorists had so far been unable to tackle.
Not all research relies equally on theory, but understanding novel experimental results almost always involves some important component of either mathematical or spatial reasoning. That part of the task has now been made much, much faster. And on top of that, science is now open to a greater number of humans who aren’t naturally good at theorizing.
AI can read the whole literature
Much of the work of human scientists involves reading and understanding endless amounts of papers and going to endless conferences and seminars. The purpose of that work is to understand the existing scientific literature. Understanding the literature allows scientists to do the following things:
Come up with new ideas for hypotheses to test
Avoid doing research that someone else has already done
Synthesize approaches from different areas or fields
AI can reduce this effort to almost zero. Consider this excerpt from OpenAI’s blog post about their new research into neurodegenerative disease:
The team divided the analysis among thousands of AI agents powered by GPT‑Rosalind, an approach we call distributed biological reasoning. The agents examined a whole-brain CRISPR atlas…a dataset showing how gene disruptions affect different types of cells across the mouse brain. Each agent investigated a gene disruption, analyzed cellular responses, searched scientific literature, and proposed explanations for the results. Their reports were combined into a reasoning atlas linking genes, cellular effects, relevant publications, and possible biological mechanisms.
The research team estimated that comparable human analysis and literature review, conducted one perturbation at a time, would take months to a year. The agents reproduced findings from human analyses while uncovering additional leads. Their assessments of novelty and scientific value also aligned with judgments from blinded human experts. These findings help prioritize further experiments needed to test the proposed biological mechanisms.
Some of these insights point to new leads for understanding brain disease. [emphasis mine]
This is one case in which parallel work by a large number of agents really does make a huge difference:
Not only does instantaneous literature review vastly speed up the research process, but it allows AI to make novel conceptual leaps from combining approaches from wildly different fields of research. AI regularly does this in math research, combining results, approaches, and theorems from far-flung places that no human mathematician would have thought to combine.
It can do it in science, too. Much of scientific innovation, historically, has been “recombinant” innovation — scientists applying insights from one field to another. With AI, essentially all research is now cross-disciplinary — AI can read not just the literature on a particular subject, but the literature on a million other subjects that might have produced useful techniques or insights for the problem at hand.
Superscience
So far, all of the factors I’ve listed are ways that AI can speed up science as it’s already done. I’ve basically described how AI can send gigantic hordes of superhumanly fast, superhumanly well-read, superhumanly mathematically gifted researchers to re-accelerate scientific discovery.
But it’s also possible that AI will enable types of discovery — and ways of understanding the natural world — that no network of humans, no matter how large or how brilliant it was or how long it had to work, would ever be able to discover. In a post back in July, I wrote about how that might work:
What if there are lots of…aspects of the Universe that [are] too complex to understand in terms of simple laws, but not so complex that they just dissolve into unknowable chaos? It’s possible that we can reliably control these complex phenomena with AI, even if we never reduce them to the kind of principles that we can teach a grad student in a textbook…
Another way of saying this is that there may be laws of the universe that humans can’t understand but AI can. I call these “cloud laws” — causal regularities that can be exploited by technology, but which are too diffuse and complex for an individual human being to either intuit or communicate…
Perhaps social sciences like economics, sociology, and political science obey similarly complex regularities, and AI can help us find them. Perhaps there are physical processes — plasma, or topological materials, or aerial turbulence, etc. — that obey cloud laws instead of chaos?…
[H]uman collaboration is bottlenecked — it’s limited by our ability to intuit patterns at an individual level, and to communicate these patterns from one individual to another. AI, being a computer, just doesn’t have this sort of limitation; it can work with vast, diffuse patterns without having to break them into pieces or simplify them in order to compress them into the tiny pipelines of person-to-person explanation…
If much of the Universe turns out to be ruled by cloud laws, we could be on the precipice of a scientific renaissance.
In order to discover cloud laws, AI will need huge amounts of data about the natural world. AI figured out human speech by assimilating essentially all of the text humans have ever written. If it’s going to figure out hidden patterns in biology, neuroscience, materials science, etc., it’s going to need similarly massive amounts of data from physical instruments.
That data will be far, far more than humans — individually or collectively — would be able to parse, label, characterize, or model. But AI was built to do this. If scientists simply build huge arrays of sensors to measure complex phenomena like the brain, the cell, the economy, etc., they may be able to feed this flood of data to AI directly and bypass human cognitive intermediation entirely. AI would then learn about the world directly, and it might learn things that humans never could.
This “superscience”, if you want to call it that, would actually go beyond the kind of science humans have done heretofore. Many of the technologies it yielded would be beyond human comprehension — indistinguishable from magic. But to the AIs, they would make perfect scientific sense.
In any case, it seems clear that the scientific slowdown that threatened human progress will now be delayed — at least for a while. Unless humans have somehow found most of the actual exploitable regularities in our Universe, we’re about to enter a new golden age of science.
For nearly a quarter of a century, Elon Musk and his essential partner at SpaceX, Gwynne Shotwell, viewed the United States government as El Dorado, the mythical city of gold.
Like machete-wielding treasure hunters, Musk and Shotwell hacked through a tangled jungle filled with lurking carnivores such as Boeing and Lockheed Martin, as well as bean counters and regulators. Over time, against long odds, the pair cleared a path for SpaceX to contracts at NASA and the US military. They sued when things did not go their way. They hollered about unfair playing fields. Most importantly, they delivered quality space products to the US government for less.
And so, after a while, SpaceX found El Dorado and a city of contracts.
NASA astronaut Anil Menon and Canadian Space Agency astronaut Joshua Kutryk are performing a spacewalk to install the 7th of 8 ISS Roll-Out Solar Arrays (iROSA) to upgrade the orbiting outpost's power system.
NASA astronaut Anil Menon and Canadian Space Agency astronaut Joshua Kutryk are awaiting the start of today’s spacewalk. They are buttoned up inside what NASA calls Extravehicular Mobility Units (EMUs), better known as space suits.
The crew is running slightly ahead of the timeline according to NASA commentator Rob Navias. The spacewalk is due to get underway at about 8 a.m. EDT (1200 UTC) but first the spacesuits will be fitted with SAFER units, jet back packs that will be used in the unlikely event a crew member becomes untethered from the space station. They will then move into the crew lock portion of the Quest airlock for depressurization.
The Simplified Aid For EVA Rescue (SAFER), a small, self-contained jet pack, is now being fitted to Anil Menon’s space suit.
Menon has now moved into the outer Crew Lock portion of the Quest Airlock. He can be easily identified by the red stripes on his space suit, indicating he is designated EV1 for this excursion. This will be his fourth spacewalk since arriving at the space station aboard a Russian Soyuz craft in July.
Canadian Space Agency astronaut Joshua Kutryk is now being fitted with his SAFER back pack.
Kutryk, who will be referred to as EV2 by Mission Control, has now joined Menon inside the Crew Lock section of Quest. Next up will be closure of the hatch.
The hatch between Equipment Lock and Crew Lock sections of the airlock is now being closed ahead of depressurization of the outer compartment.
Meanwhile at the Kennedy Space Center, the Pegasus barge is departing for the Stennis Space Center. It’s carrying a New Glenn second stage for test firing at the Mississippi facility.
The airlock depressurization is underway. Pressure in the compartment will initially drop to 5 psi where it will be held for space suit checks before being lowered to a vacuum.
Airlock pressure now 9 psi.
Space suit leak checks underway as the pressure in the airlock has reached 5 psi.
Leak checks are reported good and depressurization to vacuum will now continue.
Now 4 psi in the airlock.
Approaching 2 psi now.
Astronaut Nichole Ayers in Mission Control has taken over from the station crew in communicating instructions to the spacewalkers. She is designated Spacewalk Communicator for this excursion. Astronaut Jenni Gibbons is the CAPCOM in mission control, an acronym from the early days of the space program standing for Capsule Communicator.
Pressure inside the Crew Lock section of the Quest airlock is approaching vacuum.
The airlock has reached vacuum and the spacewalkers are starting to open the outer hatch.
The hatch is now open.
Spacewalk officially underway
The astronauts space suits are now on internal battery power. NASA considers this the start of the spacewalk. The official start time was 7:57 a.m. EDT (1157 UTC), according to Mission Control commentator Rob Navias.
“The night is dark and full of wonder,” said Menon as he opened the thermal cover that protects the airlock hatch. He will be first to leave the airlock.
Menon is now outside the airlock. This spacewalk is expected to last about seven hours.
Joshua Kutryk has also left the airlock. He has now become the fifth Canadian astronaut to make a spacewalk.
Previous Canadian spacewalkers (with the date of their first spacewalk) were: Chris Hadfield (STS-100, April 2001), Steve MacLean (STS-115, September 2006), Dave Williams (STS-118, August 2007), and David Saint-Jacques (Expedition 59, April 8, 2019).
Menon and Kutryk have made their way down the space station truss to the location of the pallet holding the International Space Station Roll-Out Solar Array (IROSA) that they will be installing today.
The two spacewalkers are working to release a series of bolts that hold the iROSA to its storage pallet.
The astronauts are using pistol grip tools to release the bolts holding the array.
Now an hour into today’s spacewalk.
Menon is now in a foot restraint, riding on the end of the Canadian robot arm, while Kutryk continues to work in the area of the iROSA pallet.
Final bolts are being released holding the ISS roll-out array in its carrier.
Menon is holding the new International Space Station Roll-Out Solar Array (IROSA) at the end of the robot arm after it was removed from the stowage pallet on the station’s truss.
Now more than two hours and 16 minutes since the start of today’s spacewalk, Menon is being moved on the end of the Canadarm-2 to begin aligning the IROSA with the bracket for power channel 2A.
Kutryk is translating along the station to position himself for installing the IROSA.
Now more 2.5 hours into the spacewalk, Ayers told Menon and Kutryk that when they’re working on the mod kit for the new IROSA that they shouldn’t make simultaneous or sudden movements.
The solar array has been soft-docked to the 2A electrical power channel.
The manual maneuver of the Canadarm-2 of about half a meter is complete, moving to Menon’s right. His spacesuit has the red stripe on his legs. Kutryk continues working on the IROSA mod kit. The ISS is about 10 minutes away from going into a night pass where they can start making the electrical connections on the IROSA. Navias says things have proceeded as expected so far on today’s spacewalk with no bolt issues.
Now more than three hours into the spacewalk Menon and Kutryk are working to release a hinge restraint on the IROSA. This will allow it to fully unfurl to its full length of about 60 feet. Menon is now being translated away from the IROSA.
Teams in Mission Control Center Houston are determining whether they will use this current night pass to begin hooking up the power cables first or to unroll the IROSA first. Navias says they are still running ahead of the timeline.
Kutryk and Menon are preparing to open the IROSA after engaging the soft capture. There are about 20 minutes remaining in the night pass. Menon says they should proceed with the power cable mating and Kutryk agrees.
Navias says if all of the power connections cannot be completed during this nighttime pass, Menon and Kutryk will pause and wait for the next one, since they don’t want to be interacting with them when power is flowing.
Both Menon and Kutryk are at their de-mate locations. They are working to complete the remaining power hookups during this night pass with Navias reiterating that they are running ahead of the clock.
A little more than 3.5 hours into the mission, Menon and Kutryk have mated three out of the four major power connectors for the IROSA. They will pause on this work for about an hour until they are fully in a night pass again. They are in a safe configuration to pause this work.
Navias says that there have been no issues experienced during this spacewalk as the ISS is currently in a day pass. The station is currently traveling at an altitude of nearly 428 km, passing over the North Pacific Ocean. Our new ISS tracker can show you the station’s position around the globe 24/7: https://spaceflightnow.com/tracker/
Now a little past the four-hour mark in today’s spacewalk, Navias says teams are running about an hour ahead of the original timeline. With three out of the four power connections attached, the fourth will be mated during the next night pass. Right now, Kutryk and Menon are cleaning up the work site as the space station passes over the South Pacific Ocean at an altitude of about 426 km.
Menon and Kutryk are in the midst of releasing the final two restraint bolts. Once the IROSA begins to unfurl, it will take about 10-12 minutes to fully extend. The space station is currently passing over the South Atlantic Ocean at an altitude of about 434 km.
IROSA roll-out begins
The seventh IROSA is now unfurling. The process will take about 10-12 minutes.
The seventh IROSA has been unspooling for about seven minutes in front of the legacy solar arrays.
With the IROSA now fully extended, and the space station back in a night pass, Menon is preparing to attach the fourth and final main electrical connector. Navias says because they are running as far ahead on the timeline as they are, Menon and Kutryk may also get to some work-ahead items while they have time outside the space station today.
Menon is now driving two tension bolts, which will make the IROSA as taut as possible.
Some of the work-ahead items for Kutryk and Menon will include removing the booms that helped store the seventh IROSA. They may also get to some prep work for next Thursday’s spacewalk, per Navias.
Menon and Kutryk are cleaning up the work site at the P4 truss and are proceeding towards some work ahead items for next Thursday’s spacewalk.
As the 285th spacewalk continues, Kutryk and Menon are beside the eighth and final IROSA that they will install next Thursday. They are moving towards the flight support equipment where they will remove a couple of beams to make that upcoming EVA a bit easier.
Kutryk hands over one of the beams on the final pair of IROSAs to Menon as the space station passes over the South Atlantic Ocean.
Now a little more than six hours into the spacewalk, Kutryk and Menon will proceed towards releasing some of anti-rotation devices (ARDs), which are launch locks that are holding the final set of IROSAs in place and previously did the same for the set that the duo installed on the P4 truss earlier in the EVA.
Menon and Kutryk have returned to the airlock and are exchanging thankyous with their support teams in Mission Control. They have been given a go to close the outer hatch of the airlock.
Mission Control has timed the end of today’s spacewalk at 3:08 p.m. EDT (1908 UTC). A duration of 7 hours 11 mins.
The airlock depressurized and the inner hatch between the crew and equipment locks is now open.
The Simplified Aid For EVA Rescue (SAFER) jet packs have been removed from the space suits. Glove checks and photos will be taken to document any damage that might have occurred.
Menon’s helmet has now been removed.
Kutryk has also removed his helmet.
NASA commentator Rob Navias saying today’s spacewalk was “essentially flawless”.
"Essentially flawless" spacewalk
Over seven hours and 11 minutes, the alternating darkness and sunshine of low Earth orbit set the pace as NASA astronaut Anil Menon and Canadian Space Agency astronaut Joshua Kutryk successfully installed and unfurled the seventh of eight new solar panels designed to power the outpost through its retirement in 2030. Read Houston Harwood’s full report.
The IROSA solar array unrolls under during the Oct. 29 spacewalk under the watchful eye of astronaut Anil Menon. Image: NASA.
Over seven hours and 11 minutes, the alternating darkness and sunshine of low Earth orbit set the pace as NASA astronaut Anil Menon and Canadian Space Agency astronaut Joshua Kutryk successfully installed and unfurled the seventh of eight new solar panels designed to power the outpost through its retirement in 2030.
“Night is dark and full of wonders,” one of the spacewalkers radioed after the hatch to the station’s airlock swung open.
Menon, 50, and Kutryk, 44, switched their spacesuits to battery power at 7:57 a.m. EDT and began repressurizing the Quest airlock at 3:08 p.m. EDT, ending the seven-hour, 11-minute outing. The pair finished the IROSA work far enough ahead of NASA’s planned timeline that they could tackle “get-ahead tasks,” including preparations for the final IROSA installation Nov. 5.
“The spacewalk was essentially flawless,” NASA Mission Control commentator Rob Navias said.
The extravehicular activity, or EVA in NASA parlance, was the 285th devoted to station assembly, maintenance and upgrades and was the first of two planned spacewalks to install the final pair of IROSAs. NASA says the eight arrays will raise the station’s available power from 160 kilowatts to about 215 kilowatts.
“Engineers and electrical officers here in Mission Control are happy with what they’re seeing from the new array, which will add 8 kilowatts to the overall power capability of the complex,” Navias said after the 60-foot solar panel unfurled from its rolled-up configuration over about 10 minutes.
Kutryk, making his first spacewalk after arriving on station Oct. 1 aboard a SpaceX Crew Dragon capsule, became the fifth Canadian astronaut to walk in space and the first since David Saint-Jacques in 2019. It was Menon’s fourth spacewalk, bringing his total time spacewalking to 26 hours and 31 minutes, all of it logged since he arrived at the ISS aboard a Russian Soyuz in July.
The successful EVA brought NASA’s cumulative spacewalk time outside the station since assembly began in 1998 to 75 days, seven hours and 14 minutes, and brought 2026’s total number of spacewalks to eight.
Thursday’s operations got off to a quick start.
After Menon and Kutryk worked through a series of bolts to free the IROSA from the carrier it launched on, Menon locked his boots into a foot restraint affixed to the end of the station’s Canadian-built robotic arm, Canadarm2, and rode it, array in hand, out to the left, or port, side of the station’s main truss.
NASA astronauts Jessica Watkins and Luke Delaney piloted the arm from inside the station while Kutryk made his way to the installation site along the truss. Flight director Greg Whitney led the spacewalk from Mission Control in Houston.
By about three hours and 13 minutes into the spacewalk, the pair had the array installed at the P4 truss work site on a bracket astronauts previously installed during a March spacewalk. In all, Menon spent more than two hours anchored to the end of the station’s robotic arm before rejoining Kutryk on the truss.
Because the new array’s power cables can only be handled and hooked up to the station while it’s in Earth’s shadow, when none of the ISS’ solar panels are generating electricity, mission planners timed the cable work to coincide with orbital night.
The astronauts had to make cable connections between the space station’s power system and the new solar array while the complex was in orbital darkness. Image: NASA.
During the first available nighttime pass — an entire eclipse earlier than planned, according to Mission Control — Menon and Kutryk connected three of the four main power connectors before the station slipped back into sunlight, where it would remain for about an hour.
That was no issue, as the spacewalkers were running “about an hour ahead of the timeline,” Navias said as the EVA neared the four-hour mark. At 12:20 p.m. EDT, Menon and Kutryk released the final restraints, and the IROSA began to unfurl — no motors required — thanks to energy stored in carbon-fiber composite booms.
Mission Control’s electrical engineers had already determined the array was safe to deploy with three of the power connectors mated, and Menon made the fourth and final connection during the next nighttime pass, after the array had unrolled.
During an Oct. 20 briefing at the Johnson Space Center in Houston, Garrett Hehn, the flight director who will lead the Nov. 5 spacewalk, likened the IROSA panels to a snap bracelet that, once released, “just continues rolling out steadily.”
“All of the work has gone very much by the book today,” Navias said during the roughly 10 minutes it took the IROSA to unfurl. “So far, so good.”
The two final arrays arrived at the station rolled up and folded on a carrier in the unpressurized trunk of a SpaceX Cargo Dragon, which launched Oct. 13 atop a Falcon 9 rocket from Cape Canaveral Space Force Station. Each weighs about 750 pounds folded, according to Hehn.
The IROSA array extended to its full 60-feet length in front of a legacy solar array installed two decades ago. Image NASA.
“Overall, these roll-out arrays increase our power generation capability up to 30 percent,” Gaurang Patel, operations integration manager for NASA’s Low Earth Orbit Program, said at the Oct. 20 briefing.
Space shuttles delivered the station’s eight original solar wings, designed to last 15 years, between 2000 and 2009. Rather than replace them outright, NASA opted to mount the smaller IROSAs in front of the old wings, partly shading them while the original panels’ exposed portions keep producing power. Each IROSA generates about 8 kilowatts of electricity, according to NASA.
The first IROSA unrolled on station in June 2021, though not without a fight: A spacesuit glitch and an array that wouldn’t unfold cleanly forced astronauts Shane Kimbrough and Thomas Pesquet to finish the job on a second spacewalk. NASA refined the installation process during successive spacewalks, and by 2023, six arrays were in place. That summer, NASA ordered an additional pair — the seventh and eighth.
The current configuration of the International Space Station’s solar arrays. The seventh IROSA rollout array was installed in the 2A position. Image: NASA.
Menon and Kutryk plan to venture back outside the Quest airlock Nov. 5 to install the eighth and final IROSA at the far right, or starboard, end of the station’s main truss, beyond the reach of its robotic arm. Menon will again ride the arm as far as it will take him. To cover the last stretch, he and Kutryk will pass the array between foot restraints in a maneuver Hehn said the team “lovingly” calls “the leapfrog.”
“Everything today went almost better than could have been expected,” Navias concluded after Menon and Kutryk had returned to the station’s interior.
Safely inside the ISS, Menon reflected on what he called “an incredible milestone.”
“Well, being outside, I can say that it is always sunny in space, except for a few orbits,” Menon told Mission Control. “And it’s quite incredible what we’ve been able to do to provide new solar arrays to space station.”
In his first remarks after venturing into the vacuum of space for the first time, Kutryk was quick to thank Menon for “being a great spacewalking partner.”
“Been wonderful working with you,” Kutryk continued. “A very special thank you to our crewmates Jessica [Watkins] and Luke [Delaney]. Trusted them with our lives to get us in and out today … They did exactly that.”
In this episode, Mike Gruss speaks with Laura Crabtree, the CEO of Epsilon3, who is also a former SpaceX astronaut trainer. They talk about ways that space companies can organize […]
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The ultra-wealthy, especially those in the tech industry, are beginning to get the impression that we don’t like them. As they gaze at another glorious sunset from their private islands and Big Sur mansions while dozens of staff whose names they don’t know flitter about them satisfying their every need, their group chat of CEOs lights up with another poll showing resistance to data centers and worries about A.I. They shake their head and ask themselves, “What is wrong with those troglodytes? Was it not enough that we gave them all this great technology? Don’t they realize that my brilliant friends and I are dragging their sorry asses to utopia?”
Faced with this problem, they are coming up with a variety of new ideas to show the unruly masses how benevolent the economic ruling class is. Elon Musk says he’ll give every child a share in SpaceX — worth a whopping $150 if he actually follows through, which he probably won’t. Anthropic is creating a “public benefit fund” with 5% of the company’s value; it’s also preparing for an IPO that will make many of its executives into multibillionaires.
Michael Dell donated billions to fund “Trump Accounts,” which give $1000 to babies born in Trump’s second term. Tech investor Brad Gerstner told the Wall Street Journal he believes that this kind of largesse is the perfect answer to social unrest:
“We’re watching France burn because people feel left out and left behind,” he said.
“The antidote to that is to make everybody an owner,” he added on Thursday morning, after visiting a school in the Bronx where he and a friend had donated $250 into the accounts of 3,000 students.
Ah yes, the feeling of being an owner, doled out a few hundred bucks at a time by our billionaire betters. Is that going to do the trick?
No, it is not. So I have another idea for something the ultra-wealthy could do, one weird trick that could not only pay for worthwhile projects but also begin to address the widespread loathing the public has for them. Are you ready? Here it is:
PAY
YOUR
DAMN
TAXES.
Mind-blowing, I know. But believe it or not, we already have a system in which people give some of their money to an organization tasked with figuring out how to spend it on important collective and individual needs. That system doesn’t always work efficiently, but it does incorporate democratic accountability, giving everyone at least the theoretical opportunity to have a voice in how the money gets prioritized.
There’s nothing these people hate more than paying taxes
Unfortunately, we already know that our current crop of tech oligarchs share an unwillingness to pay taxes with every generation of plutocrats that preceded them. Just look at what’s happening right now with the initiative on the California ballot for a one-time 5% tax on billionaires, which has them absolutely losing their minds in rage. Some of America’s richest nerds have teamed up to kill it, to the tune of at least $333 million. Google co-founder Sergey Brin has spent over $100 million just by himself; the group has not only blanketed the state with ads attacking the initiative, they funded a competing initiative on the ballot that would nullify the tax.
The initiative might not be the most efficient revenue enhancement policy ever devised; for one thing, it’s a one-time tax rather than an ongoing policy change. And there’s a healthy debate about whether wealth taxes are effective at all. But set the merits of the policy aside. If it passes, the lives of the billionaires now panicking about it will not be altered by even a single iota.
Sergey Brin will not have to cancel his family vacation next year. Marc Andreessen will not have to fly commercial to Jackson Hole next weekend. Mark Zuckerberg will not have to lay off some of the hundreds of household staff he employs at his Palo Alto compound and his Lake Tahoe manor and his Washington DC mansion and his Hawaiian estate and his Irish castle and wherever else he lives.
Should it pass, this tax will leave Zuck with a mere $200 billion with which to eke out an existence. Fortunately, he found a way to protect himself from the insult it represents: At his insistence, Meta’s board just created a special class of stock it gave to him so he could use it to pay his tax bill if the initiative passes. Phew!
As I’ve noted before, these guys gain and lose 5% of their wealth in a single week on the stock market all the time, or sometimes even in a single day, yet that doesn’t seem to bother them, while paying the same amount in taxes sends them into paroxysms of rage. Whether you think this wealth tax is a good or bad idea, it’s nothing to them — and yet they’re fighting it as though their very lives are at stake. Which shows us how they’re going to react to any effort to tax them.
The status quo is that most of America’s richest pay only a tiny proportion of their income in taxes, not only because they employ armies of lawyers and accountants to minimize their liability, but because the tax code was written by and for people like them. As ProPublica found a few years ago when it was leaked a trove of files from the IRS, between 2014 and 2018, the 25 richest Americans paid only 3.4% of their income in federal taxes. Many paid less; in some years, Jeff Bezos paid precisely zero in income taxes.
This is the context in which we have to understand what they’re saying about the future they themselves are working to create, one in which A.I. could eliminate millions or even tens of millions of jobs. When you ask them how we as a society will handle that, they gravitate toward universal basic income (UBI); as Zuckerberg has said, “We should explore ideas like universal basic income to make sure everyone has a cushion to try new ideas.”
Sam Altman of OpenAI was a UBI booster and even gave millions of dollars to organizations studying it, but now says he no longer thinks it’s viable: “I think just like a fixed cash payment, although useful and maybe a good idea in some ways, does not get at what we’re really going to need for this next phase and the kind of collective alignment of shared upside as the balance between labor and capital shifts.” Now he says, and I’m not kidding about this, that the answer to a Great Depression-scale dislocation is to give people compute, i.e. a certain number of A.I. tokens you can use to ask ChatGPT how to feed your family.
I suspect what Sam and his big brain may have realized is that if we’re going to have a UBI system, it would have to be run through the government, and the only way to pay for it would be, that’s right, taxes. And if A.I. really is as spectacularly profitable as companies like his are counting on, guess where all that wealth is going to flow: to the tech oligarchs! Which means that if we want to create a UBI system, the trillions it will cost are going to have to come from the people with all the money. And guess who that is.
So now they’re trying to come up with some alternate model, and like Brad Gerstner and Michael Dell, they want us all to be owners, which is something very different from being citizens.
That’s one path we could go down. Or — and stay with me here — we could create a good education system, affordable health care, a clean environment, public transportation, well-kept public spaces — you know, the things that actually make life worthwhile.
I’m guessing that the last time you went to a public park — to take a walk, play tennis or basketball, bring your kids to the playground — you didn’t find yourself saying “This is okay I guess, but I just don’t have that feeling of ownership.” Unless you’re psychotic, and you think there’s no point to public goods.
Most of us do want public goods, and we want government to provide them. For that to happen, we need to pay for it, and since we’re all supposed to have a stake in society, we’re all supposed to contribute.
So we should tell the oligarchs that if they want us not to loathe them so much, there’s a lot they have to do, but it starts here: Just pay your damn taxes.
Convince us that you are citizens of this democracy, that you are not above the obligations the rest of us willingly submit to, and that you see the rest of us as something more than a resource to be mined to make you ever wealthier. That won’t solve all the problems we have with you. But it’ll be a place to start.
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I use LLMs to forecast treatment effects of research studies pre-registered on the AEA RCT Registry and the Open Science Framework. I focus on studies whose results were first publicly released in 2026 and elicit forecasts from models whose training or knowledge cut-off dates were before the relevant set of papers was released. First, LLM models extract forecasting questions from the pre-registrations or pre-analysis plans. These questions elicit forecasted treatment effects; not all resolve in the subsequent papers, but those that do can be used to consider forecast accuracy. Forecasts were elicited for 889 treatment effects from 39 papers with results disclosed in January 2026 or later, or 673 from 33 papers after screening. Forecasts were elicited in raw units but I focus on those that could be standardized and therefore compared across papers. Currently, the median absolute forecast error is 0.054 SD for the best model, the average absolute error is 0.093 SD, and the MSE is 0.0218. The AI forecasts perform substantially better than benchmarks forecasting 0 effect or forecasting the mean effect of other papers’ results in that time period. Overall, these results suggest considerable scope for forecasts to be of value in informing policy and research.
From the excellent Eva Vivalt. As I have been predicting, so much of economics (and science) is going to change, and radically. Here is Eva’s thread on the paper. Perhaps we should dispense with many of the more mundane inquiries, and as Eva notes: “But can we not shift to working on those projects that have particularly high uncertainty and upside potential?”
She is one of the best young economists in the world, and this stands some chance of being the most important paper of the year.
Night Maps is an exhibition “exploring the visual and intellectual history and the real-world consequences of mapping the night sky” at the Warburg Institute in London. Many of these objects are on public display for… More
The Milwaukee Brewers won their first World Series title Wednesday night by once again dominating the Tampa Bay Rays. Jacob Misiorowski (5.2-2-0-1-2, 86) and the stingy Brewers bullpen limited the Rays to two singles through 8.1 innings in Game 5. It was the bottom of Milwaukee's lineup that powered the offense in a 4-1 victory.
Misiorowski never allowed the Rays to even imagine a vision of a rally before being forced out of the game in the sixth inning because of a leg cramp. JoJo Romero and Abner Uribe continued the shutout pitching, as did Trevor Megill in the eighth. The corpse of the Rays made one final gasp – two doubles in the ninth saved them from a shutout, a repeat of their brief flash of life in the Game 3 blowout – before expiring for good.
The bottom five hitters went 6-for-17, knocking in three of the four runs. By contrast, the top four Brewers were 2-for-15.
William Contreras was named Most Valuable Player of the World Series. He caught every inning of the postseason and was rock solid behind the plate; he doubled in a run and scored in the sixth, as Milwaukee iced the game with two runs. Contreras went 8-for-21 in the series (.381) and drove in four runs. In the three playoff rounds, he hit .373 (19-for-51). Red Sox first baseman Willson Contreras, William's older brother, was at the game. They are the 10th pair of brothers to have both played for a World Series winner; Willson played for the 2016 Cubs.
When Commissioner Rob Manfred presented the "Piece of Metal" to the Brewers, he was booed by the remaining fans at the Trop.
An unrecognized benefit of living in Canada: I was spared the hectoring voice of The Man Who Never Shuts His Yap who smoltzplained to Fox viewers earlier in the series that Contreras was a very bad man for challenging so many incorrect calls. Let the plate umpire blow some calls in peace, the close-minded Smoltz insisted. He faulted Contreras for challening a call with Milwaukee up 2-0 in the third inning. A two-run lead in the THIRD inning of a fuckin World Series game?!? What an absolute clown. A substantial social media backlash apparently forced Smoltz, a far-right conservative who has compared same-sex marriage to marrying animals, to "rethink" his position.
Contreras challenged 13 questionable calls during the World Series and had 10 of them overturned (77%). In the NLCS, he was 8-for-11 (73%), and was 5-for-11 in the NLDS. Overall, Contreras had the blown call corrected in 23 of 35 challenges (66%).
The Brewers had perhaps four other players who had an MVP-like series:
Jackson Chourio: 11-24 (.458), 1.000 OPS; tied Babe Ruth for the most hits (10) in the first four games of a WS.
Cooper Pratt: 8-for-19 (.421/.455/.684), 7 RBI, 1.139 OPS. Six straight hits in Games 4-5 set a WS record for a rookie.
Misiorowski: 10.2 innings, 1 run allowed; 5.2 scoreless innings in clinching Game 5.
Aaron Ashby: Pitched a postseason record 18 scoreless innings (nine games), including 5.2 shutout innings in three WS games.
Ashby and Uribe combined for 11 scoreless WS innings. The quartet of Ashby, Uribe, Romero, and DL Hall combined for 17 shutout innings against the Rays, allowing only six hits and one walk, while striking out 17.
The basic batting and pitching stats for both teams show stark differences.
IP H R BB K ERA WHIP Brewers 47 30 12 7 40 1.91 0.787 Rays 46 51 25 17 39 4.89 1.478
The Brewers asserted themselves in the second inning against Drew Rasmussen (4-2-1-0-4, 48). Brice Turang drove a 1-1 changeup to the opposite field (left-center) for a double. Sal Frelick was hit with an 0-1 pitch on his left (back) arm, which seemed to bother him for several innings afterward. Cooper Pratt, who hit safely in his final four at-bats in Game 4, wasted no time in cracking the first-pitch into right-center. Turang scored, Frelick went to third, and Pratt, perhaps thinking the throw from the outfield was going to go through to third, was halfway to second when he realized the throw had been cut off. He was out in an 8-5-4-3-6 rundown.
For the 2026 postseason, teams that scored 4+ runs were 27-5.
The Brewers finished the three rounds of playoffs with an 11-2 record, nine of those games coming against the two-time defending champions (who won 102 games, one fewer than Milwaukee) and the American league leaderin wins (94). Most impressive was the fact that the Brewers trailed in x games and won x of them, including all four NLCS games and WS Game 2.
Misiorowski gave up a hard opposite-field single to Junior Caminero with two down in the first. He retired the next six Rays before walking Yandy Diaz in the third, again with two outs. In the fourth, Liam Hicks stood still while his back/left foot was hit by a low inside pitch.
Batters must make an effort to avoid getting hit by a pitched ball. If they do not, they should be denied first base – but that rule is never enforced. I'd love to see a pitcher argue and actually cite the rule to the umpire, in effect daring him to admit he's not following the rules of the game, but his batting teammates want free bases from HBPs, too, so we're unlikely to witness such a scene.
The rule in question is Rule 5.05 (When the Batter Becomes a Runner) (my emphasis):
(b) The batter becomes a runner and is entitled to first base without liability to be put out (provided he advances to and touches first base) when: . . .
(2) He is touched by a pitched ball which he is not attempting to hit unless (A) The ball is in the strike zone when it touches the batter, or (B) The batter makes no attempt to avoid being touched by the ball;
If the ball is in the strike zone when it touches the batter, it shall be called a strike, whether or not the batter tries to avoid the ball. If the ball is outside the strike zone when it touches the batter, it shall be called a ball if he makes no attempt to avoid being touched.
APPROVED RULING: When the batter is touched by a pitched ball which does not entitle him to first base, the ball is dead and no runner may advance.
Misiorowski got his first strikeout of the game on his 11th out, when he fanned DeLuca. Chandler Simpson lined a hard grounder past first and towards the right field corner. Frelick bobbled the ball for an error, putting Rays on second and third. Ben Williamson, the hero of Tampa Bay's 12th inning, game-winning rally in Game 4, chopped a ball to third. David Hamilton gloved it on the run but fired high to first. Jake Bauers stretched about as far as he could while keeping his foot on the bag and backhanded the near-errant throw while stradling the foul line.
Rays manager Kevin Cash was satisfied with four innings from Rasmussen and opted for his bullpen in the fifth. Rasmussen had thrown only 48 pitches and allowed one run, so I was surprised with what seemed like a quick hook of a pitcher doing his job in a must-win game (and who had been talked about only two weeks before as an underappreciated ace). I couldn't help remembering Cash inexplicably pulling a dominant Blake Snell in a must-win Game 6 against the Dodgers in the 2020 World Series. Snell had allowed only one hit through five innings, with nine strikeouts (including five of the first six Dodgers), and the Rays led 1-0. When Snell gave up a second hit (after retiring 10 in a row) with one out in the sixth, on his 73rd pitch, Cash immediately went to reliever Nick Anderson. Within eight pitches, the Dodgers had scored two runs; they became World Champs that night, thanks to a 3-1 win.
And so Kevin Kelly stood on the mound, facing the bottom of the Brewers' order. He got one out, but Pratt lined a single to left – his sixth straight hit – and Garrett Mitchell sliced an opposite field single to left, putting runners at first and third. The Rays brought the infield in, which backfired when Hamilton shot a 1-1 pitch past second baseman Williamson, who dove to his right. Pratt scored and it was 2-0. In the span of only four batters, Kelly had given up more hits than Rasmussen had in 14 batters. Kelly got Jackson Chourio looking at strike three and then he was gone. Garrett Cleavinger ended the inning by fanning Bauers on an 80 mph sweeper.
An inning later, Cleavinger's first pitch in the sixth plunked Christian Yelich in the thigh. Contreras lined a double to the left field wall, increasing the lead to 3-0. Turang dumped a single near the line in left as Simpson appeared to pull up at the last moment and watch the ball drop. Contreras, thinking the ball might be caught by the speedy left fielder, stopped at third. And that was it for Cleavinger. He and Kelly had faced nine batters; six of them reached base and three of them would eventually score. Tyler Wells struck out Frelick before Pratt hit a long foul ball that right fielder Ryan Vilade caught on one of the bullpen mounds. Contreras tagged and scored; Turang had stolen second and he went to third. When Wells walked Mitchell, he was pulled for Stephen Matz, who got the final out, stranding two runners. Cash, after deciding Rasmussen had been pushed to his limit after 12 outs, needed four relief pitchers to get the next six outs.
That was it for the Milwaukee bats for the night. Unfortunately for the Rays, their bats remained equally quiet.
With two outs in the bottom of the sixth, Misiorowski's first pitch to Hicks was fouled off – and there was something wrong with the Brewers' ace. The trainer came out and soon a whole gaggle of players were gathered on the mound. Misiorowski had a cramp in his right leg. After a drink of water and some chit-chat, he prepared to throw a practice pitch. He spent several seconds trying to properly set his right leg and foot into position, which did not bode well. Afer the pitch, he knew he couldn't continue. Clearly disappointed, he walked off the field to loud cheers from the sizeable population of Brewers fans in the stands. JoJo Romero needed but one pitch to get Hicks to ground to shortstop.
In the seventh, DeLuca struck out looking before Simpson hit a little dribbler in front of the plate. Contreras pounced on the ball but threw wildly to first for a two-base error. Uribe took over, his 11th appearance over 13 postseason games. He faced two pinch-hitters. Richie Palacois grounded out to first, with Uribe covering and Victor Mesa ended a nine-pitch battle by grounding to Turang at second.
Trevor Megill was in for the eighth and he set down the Rays in order on 10 pitches. Trevor Walls lined out to left (Chourio made a nice diving catch near the foul line), Diaz flied to the base of the wall in deep right, and Aranda could not check his swing on a high 1-2 fastball.
Ashby was assumed to be pitching the ninth, but it was Megill for a second inning. He got ahead of Caminero 0-2, threw a pitch in the dirt, and watched Caminero check his swing on ball 2. After fouling off a pitch, Caminero was frozen on a fastball just off the middle of the plate for strike three. Hicks got a double when his hard grounder hit the first base bag and caromed away from Bauers and into foul territory, where Frelick chased it down. DeLuca fouled off a low pitch, swing and missed a fastball above the zone, then took a fastball high and outside, before whiffing on a knuckle-curve in the dirt for the second out.
Simpson turned on an inside 1-1 fastball and lined a double to right. Hicks scored. Palacios took a fastball (99) down the heart of the plate for a strike. He looked at a fastball (100) high and a knuckle-curve (91) in the dirt. Megill threw an inside fastball (99), which Palacios knocked towards second. Turang, who had been impressive for the entire series, ranging far to both his right and left, gloved the routine grounder and threw to first, igniting the Brewers' well-deserved celebration at 10:13 pm (Milwaukee Time).
I trust Ruth Werning, a Brewers fan who will celebrate her 105th birthday next month, stayed up to watch the final out. She lives in a Milwaukee suburb and threw out the first pitch before a game in 2024.
The story of how Flávio Bolsonaro arrived in the United States was odd and is becoming odder. After losing the election to become Brazil’s president on Sunday, he suggested he would contest the results of the election, and Brazilian authorities asked him to give up his Brazilian passport because he is under investigation for laundering more than $1 billion through an online gambling scheme, and for financial irregularities involving a bank regulators shut down for fraud. And then he disappeared.
When he didn’t turn in his passport, authorities canceled it and barred Bolsonaro from leaving the country. Ana Ionova, Edward Wong, Alice Maciel, and Lucía Cholakian Herrera of the New York Times reported today that Bolsonaro, his wife, and his two daughters crossed from Brazil to Argentina in a van across a bridge between the two countries. In Argentina they boarded a plane owned by a private company used by Argentina’s president Javier Milei, an ally of Trump, and flew to Ecuador. In Ecuador they boarded another private jet for Miami.
A senior U.S. State Department official said the U.S. will issue visas for Bolsonaro and his family, allowing them to enter the country.
Flávio Bolsonaro is the son of Jair Bolsonaro, who is serving a 27-year sentence after being convicted of launching a coup against the duly elected Brazilian president, Luiz Inácio Lula da Silva. On social media this afternoon, the younger Bolsonaro claimed he faced political prosecution in Brazil and declared himself the “legitimate president-elect” of Brazil, later changing that language to “leader of Brazil.” He claimed the legal investigation against him was a “witch hunt.”
Bolsonaro’s defeat strikes a blow at Trump’s evident plan to install right-wing leaders across Latin America as part of a move to create a U.S.-dominated Western Hemisphere. Evidently, Trump intends to shelter Bolsonaro in the U.S.
Yesterday Terrence McCoy, Marina Dias, and Isaac Arnsdorf of the Washington Post reported that a justice on the Brazilian Supreme Court ordered Brazilian police to investigate whether Rockbridge, a donor network co-founded by Vice President J.D. Vance, illegally helped to finance Bolsonaro’s presidential campaign.
The Rockbridge Network rejected the suggestion, saying: “The Brazilians made false representations about their relationship with Rockbridge and created documents representing or referencing Rockbridge without Rockbridge’s knowledge or consent.”
While Trump allies are supporting those who share their authoritarian vision of government abroad, MAGA is showing signs of collapsing at home.
In Status yesterday, Oliver Darcy reported a dramatic decline in the numbers of people watching the Fox News Channel. October’s numbers will be down 27% in total viewers and 32% in the age group between 25 and 54 since October of last year. In contrast, MS NOW and CNN are picking up viewers.
Brendan Rascius of The Independent reported that stores featuring Trump merchandise are shutting down around the country as interest in them flags. An owner of a Trump store told Rascius: “The store has kind of run its course.”
A sign of just how deep rejection of MAGA has reached in society was the October 19 article by New York Times chief fashion critic Vanessa Friedman offering advice to a man who wrote in, concerned that his Brioni suit made people think he was MAGA. “Do I need to be concerned that what I’m wearing is sending the wrong message about my political proclivities?” he asked. Friedman suggested a number of tweaks “to avoid being confused for a MAGA man,” including the possibility of “dress sneakers, which would give the whole look a more casual vibe than the one Team Trump usually conveys, which leans more toward New York in the 1980s.”
Democratic Texas Senate candidate James Talarico is running ads featuring Republicans crossing the aisle to vote for him rather than Republican Senate candidate Ken Paxton. “I truly believe that he is the most corrupt politician Texas has ever seen,” Republican former Tarrant County Judge Glen Whitley says in one that features five former Republican officials. “James Talarico is by far, without a doubt, the best person in the race for the U.S. Senate,” former Texas state representative Bennett Ratliff continues.
“I’m a lifelong Republican, and I know it’s hard to go in and vote for a Democrat,” Whitley says. “We need to support the best person, not look at their party label, not look at what jersey they’re wearing, but who is going to represent us,” Ratliff adds. The Republicans urge voters to back Talarico.
In South Carolina, two former governors—Democrat Jim Hodges and Republican David Beasley—cut an ad together to urge voters to support Democratic candidate Dr. Annie Andrews for the U.S. Senate rather than Republican candidate Darline Graham, the late Senator Lindsey Graham’s sister. “This country is too divided,” they say, “and the political rhetoric has gotten way, way out of hand.” Andrews “understands that leadership isn’t about making people angrier. Well, it’s about making things better. She’s willing to put people ahead of politics.” “South Carolina deserves more than the same political fighting,” they say, “so join the two of us in supporting Dr. Annie Andrews. Let’s send her to the United States Senate.”
In Alaska, Senator Lisa Murkowski has endorsed Democrat Jonathan Kreiss-Tomkins in the Alaska governor’s race. Saying that “[o]ur future is too important to be hamstrung by partisan divisions” and that Kreiss-Tomkins “understands that governing requires listening to people with different perspectives and finding common ground to solve the problems all of us face,” Murkowski urged “Alaskans of every political stripe” to consider voting for him.
Today Calder McHugh of Politico reported that OpenAI has created an “Election Operations Center” to identify misinformation and efforts to disrupt the upcoming midterm elections. McHugh writes that the company is trying to “position itself as a defender of the democratic process,” positioning that suggests it expects such a defense, rather than support for MAGA, will put it on the right side of politics in the future.
Katie Rogers of the New York Times reported tonight that the “increasingly unpredictable” president is isolated and angry and, as one official put it, “feasting on a media diet of fawning press coverage, disparaging clips about his perceived enemies, and helpings of flattering photos and ‘A.I. slop’” served up by a small group of loyalists. As Lisa Lerer of the New York Times noted on Tuesday, his multiple rallies in states that until recently have been reliably Republican underscore “Republicans’ growing alarm over a political map that leaves Democrats with multiple paths to Senate control.”
And, finally, it appears that authorities have found some voter fraud. Today, as Mark VanCleave and Rebecca Boone of the Associated Press reported, right-wing activists James O’Keefe and Cam Higby were charged with voting unlawfully and stealing an identity after they gave false names to poll workers in Minnesota during the state’s primary election.
The men say they were testing the “vouching” process available in the state that enables voters who lack proof of their current address to vote in a new precinct after another voter in that precinct vouches for them.
The process is rarely used, and poll workers reported the men, who posted a video to YouTube of their attempt to vote fraudulently. O’Keefe and Higby claimed they were simply exposing the “lunacy” of the system.
But it turns out the system worked, and they are now charged with a felony.
Yet they do not. Which is a choice. On Tuesday, the NY Times ran a story about HHS Secretary Kennedy’s bigoted remarks about Arabs with the following headline:
What’s notable is they didn’t use a phrase like ‘bigotry-tinged’, they just, correctly, called it bigoted. What’s also notable is how the NY Times does not use this language to describe Trump’s speeches (or Vance’s), even though, nearly every day he utters the equivalent of blood libel against immigrants, not to mention other bigoted statements.
The NY Times probably won’t start using this word to describe Trump–and will never do so regarding Vance’s bigotry*–until Trump is weakened to the point where it doesn’t matter anymore.
*The NY Times and other Serious Institutions won’t want to seem like they’re putting their thumb on the scale for Vance if he’s running, even though they have no problem monstering Democrats for much smaller lapses in good behavior (or things that aren’t lapses at all).
Both became dramatically more confident in AI’s capabilities while remaining optimistic about its economic potential. Their differences concern how benefits arrive, how seriously to weight emerging dangers, and whether AI might possess consciousness. Cowen emphasizes institutions, bottlenecks, and geopolitical competition. Tabarrok emphasizes inexpensive intelligence, scientific discovery, and—especially in his later writing—concrete safety failures.
The dated passages below trace those changes across the public archive. Quotations are the authors’ own words, including excerpts from their columns; outside material they reproduce is identified separately.
Early views on unequal gains and abundance
Cowen’s early framework grew out of chess. On March 11, 2011, he observed that stronger computers required stronger human partners:
“The required education level — for the team’s ‘wage premium’ — is ratcheted up.”
His concern was already distributional: computers could increase productivity while changing which human skills commanded a premium. He also emphasized learning how to work with computers. What I learn from chess and computers.
Tabarrok’s April 12, 2016 argument was more explicitly reassuring:
“AI will be cheap and ownership will be widespread.”
He compared AI to an increase in the world’s supply of educated people: more intelligence produces useful ideas, and competition spreads the benefits to consumers. But his forecast of comprehensive substitution was cautious—AI becoming a perfect substitute for human intelligence could be “100 years or more” away. Will the proliferation of affordable AI decimate the middle class?
Neither position was absolute. Cowen warned in February 2017 that the Industrial Revolution involved decades of painful adjustment; historical progress did not guarantee quick wage gains. Tabarrok, in October 2019, praised the argument that mediocre automation could displace workers without creating enough additional wealth to compensate. See Cowen’s historical warning and Tabarrok’s Beware the Mediocre Robots!
Rising confidence in AI capabilities from 2020 to 2025
Cowen was already optimistic about language models in July 2020. After publishing a skeptical reader’s assessment of GPT-3, he added:
“I remain bullish, but it is always worth considering other opinions.”
Tabarrok’s shift toward near-term transformative AI became unmistakable by March 2, 2023:
“I never expected to witness the birth of aliens.”
Later that month, he endorsed Microsoft researchers’ description of GPT-4 as exhibiting an incomplete form of general intelligence: “They are correct.” This is a substantial acceleration from his 2016 outlook, although perfect substitution for humans and early general intelligence are different thresholds. See AGI is Coming and Baby AGI is Here, March 24, 2023.
Cowen reached an especially explicit formulation on April 16, 2025, discussing o3:
“I think it is AGI, seriously.”
But he immediately separated capability from adoption:
“It still will take us a long time to use it properly.”
His growing enthusiasm about the technology did not imply an equally dramatic forecast for immediate economic growth. o3 and AGI, is April 16th AGI day?
Economic transformation and the pace of adoption
On January 6, 2025, Tabarrok wrote:
“The intelligence revolution is going to be bigger, more impactful and more wrenching than the industrial revolution.”
Cowen’s February 23, 2025 response to rapid-takeoff expectations focused on a different constraint:
“Human bottlenecks become more important, the more productive is AI.”
Energy, regulation, organizational habits, and weak human collaborators can constrain the economic value of better models. He offered an explicitly tentative estimate of an additional half percentage point of annual growth—large when compounded, but far from an immediate economic explosion. Why I think AI take-off is relatively slow.
By September 3, 2026, Tabarrok was developing the distributional implications:
“A smaller share of a much larger economy can still mean more income for labor.”
He argued that even substantial displacement could leave aggregate labor income higher, or make compensation affordable. He explicitly acknowledged painful losses for particular workers. His high-growth calculations are scenarios, not forecasts. How Much Redistribution Will AI Require?
They also converge more than their rhetoric suggests. In May 2026, Cowen rejected mass unemployment while identifying transitional hiring problems. In August 2026, Tabarrok interpreted business-survey evidence as consistent with their shared position that AI had not yet broadly reduced employment. See Cowen, May 13, and Tabarrok, August 31.
Growing attention to safety and institutional limits
Cowen stated his central position on November 19, 2023:
“I view AI as more likely to lower than to raise net existential risks.”
His reasoning was comparative: the world already faces serious dangers, and stronger science could improve our defenses. My summary views on AI existential risk.
Tabarrok’s later writing places more weight on specific vulnerabilities. On April 8, 2026, he described:
“the worrying combination that very powerful AI’s are very vulnerable.”
He was discussing cybersecurity capabilities alongside agents’ susceptibility to manipulation. AI Risks.
On September 17, 2026, he sharpened the institutional objection to assuming that beneficial science will automatically offset dangerous capabilities:
“But faster science does not automatically mean faster defense.”
This can be read as a qualification of Cowen’s earlier optimism: defensive discoveries must pass through institutions that may move slowly. It also applies Cowen’s own bottleneck logic to safety. Pandemic Preparation is AI Safety.
Cowen nevertheless supports safeguards. In August 2026, he proposed government-overseen, industry-led safety audits. In September, he opposed restrictions on recursive improvement as impractical to enforce internationally. His position is therefore selective regulation combined with continued development. See his August 27 proposal and September 22 critique.
The September 2026 exchange about AI leaders
On September 16, 2026, Tabarrok rejected the claim that executives’ safety warnings were merely marketing or regulatory capture:
“Amodei actually believes what he’s saying.”
He did not thereby establish that the warnings or proposed policies were correct. His argument concerned sincerity and incentives. What Regulatory Capture Actually Looks Like.
Cowen replied the next day:
“I agree with Alex that the standard model of regulatory capture does not apply here”
But he emphasized competition for power: each executive sincerely thinks their own company should win. For Cowen, that complicates treating their warnings as disinterested policy advice. They agree that concern is sincere; they differ over which incentives best explain behavior.The correct model of AI CEO behavior, September 17, 2026.
Consciousness and Tabarrok’s warning about infant pain
On March 17, 2025, Tabarrok’s What Did We Learn From Torturing Babies? drew a moral lesson from medicine’s historical dismissal of infant pain. He described how theories about immature brains allowed physicians to discount babies’ observable distress and perform procedures without adequate anesthesia. His warning explicitly extended to judgments about animals and AI:
“If we must err, let us err on the side of compassion.”
Tabarrok’s position is stronger than mere openness to AI consciousness: he argues for moral caution under uncertainty. The analogy does not establish that AI suffers. It challenges confidence that a theory ruling out suffering is sufficient grounds to disregard possible evidence of it.
On October 14, 2025, he went further in his own commentary following an essay by Jack Clark:
“these systems are becoming self-aware”
He distinguished self-awareness from sentience, while warning against confidently dismissing the latter. His link accompanying that warning points back to the infant-pain essay, making the connection explicit. We Turned the Light On—and the AI Looked Back.
Cowen’s position is much more categorical. On August 31, 2026, he wrote:
“I am very much opposed to the view that the AIs are sentient, or might be sentient.”
He treats AI sentience as a category error, although he accepts that human-like descriptions can sometimes help predict AI behavior. Anthropomorphizing AI?
The disagreement concerns both what AI might experience and how to act when we cannot confidently know. Tabarrok’s historical analogy places greater weight on the moral cost of mistakenly denying consciousness; Cowen expresses much greater confidence that sentience is the wrong category to apply. These are their philosophical assessments, not established findings about AI consciousness.
We show that AI-generated article reviews are now better, by every measure we could construct, than reviews written by well-compensated human experts and judged to be of unusually high quality by journal editors and authors. We then discuss how this result may inform journal policy choices, with concerning downsides as well as potential paths to increase publication speed and quality; reduce adversarial interactions; improve the experience of editors, reviewers, authors, and readers; and advance science.
By Gary King and Steven Worthington, not even using what are now the very best models, rather based on Claude Opus 4.8. The details of the dominance, as outlined in the paper, are striking. It is not close.
On my Saez and Zucman post, I find it striking that some people are complaining all of a sudden. Yet I have been offering, citing, and linking to commentary on published papers for twenty-four years now (and every single day). Sometimes it might just be a casual offhand remark from me, whether positive or negative. Typically this is simply taken in stride. It is when you pull out the bazookas, and offer oodles of high-powered analytics, more astute than human referees, and combined with the ability to pursue follow-up inquiries, that people start getting worried. Model that.
You can pick at individual criticisms from the AIs all you want, but the most damning observation is that the errors go in the ideological direction of the authors 97% of the time. That is exactly what (the human) Phil Magness said years ago, based on an extensive canvassing of their work. Basically we already knew that was true, and the AIs confirmed the human estimate.
On our side, we have taken steps, most of all the new MR archive, to make AI analysis of our work easier. Soon you will be able to read on MR what the AIs think are our worst posts, respectively (Alex has prepared this).
In the meantime, I encourage the NSF, prize committees, universities, tenure committees, journals, and so on to do as many of their own AI-enabled audits as possible. So far the world is not jumping at this opportunity. You can model that too.
Roman Mars has built one of podcasting’s great empires out of noticing things everyone else walks past. His show, 99% Invisible, has racked up over 500 million downloads telling stories about the unnoticed design choices that quietly shape how cities and objects work…
Tyler and Roman discuss street signs, why classic cars were so much more distinctive than today’s SUVs, Waymos, New Jersey jughandles, yellow streetlights, lane-stripe colors, why Houston keeps growing despite its lack of charm, whether any post-war American suburb is actually beautiful, the Chrysler Building’s rocky reception, brutalism done right and wrong, Central Park as an urban miracle, what Jane Jacobs got wrong, e-bike lanes, Tokyo’s bike-free transit model, the placelessness of global coffee shops, why the iPhone looks boring now, the ugliest country he’s visited, his love for Australia’s polymer notes, his soft spot for the dollar’s “locked in amber” weirdness, underground power lines, how to warn future civilizations about nuclear waste, why highway signs lie to you about speed limits, the principles of a great city flag, the Pocatello redesign saga, his own studio, why 99% Invisible works precisely because it’s audio-only, the most unusual habit behind his long productive career, and more.
Excerpt:
COWEN: Yes. One of my favorite topics, currency design. What’s your favorite currency in terms of how it looks?
MARS: Favorite? It’s like I love almost any of them with the US currency in dead last. I find things to love about them. I’ve done a story on Australian currency, which was one of the early polymer notes. I just like utility in currency. I like different sizes. I like different colors. I like the fact that they put on artists and people of note that are not founding fathers and presidents and stuff like this. I don’t know if I have a particular favorite, but I was entranced by the thoughtfulness and utility of Australian currency when I did a story about it. You could be blind and know what note you’re holding because of the size. They stand up pretty well, and they care about all kinds of things rather than just presidents and stuff.
COWEN: I loved Swiss currency pre-2021. They had Le Corbusier on, Giacometti, Honegger. In the 1980s, they had Euler on, the mathematician. Imagine putting Euler on your country’s currency.
MARS: That is a canvas that’s so available to us to represent more values than we have in the United States than just founding fathers and presidents and stuff. I think it’s just such a wasted opportunity.
COWEN: I like the dollar, though. I’m surprised you’re so negative. I like the weird esotericism: the eye, the pyramid. The design is bizarre. It announces to the world: “We’re crazy.”
MARS: There are things to love about it. I just think that its fussiness and filigree, we’re locked in, I think for important reasons, which is because the dollar is the most important currency in the world, to which all other currencies are pegged, and therefore you don’t change it lightly. You have to be very, very careful. It really locked it into amber in a way that is both beautiful to admire, but also really limits its utility as things move on, we get better things than linen-paper hybrids and especially different sizes and utility for people with different needs. I think that’s important. There’s definitely things to love about the dollar. The dollar has some charm.
COWEN: I like the arrogance of it also. A sense of we don’t need to make the denominations look so different. If you’re a foreigner, we expect you’ll come here a lot, you’ll master dollars. Maybe you use them in your home country as well. They don’t need to be different colors.
MARS: It is definitely a bold statement that you’re going to adapt to our way of being if you’re going to use the dollar, for sure.
In general, LLM performance is incredibly multidimensional. There's no guarantee of a fixed ordering where the model that is best at math is also the model that's best at jokes. Despite that complexity, much of the variation in performance is explained by just a single variable: model size. In general, models that are bigger will (a) be more performant / reliable, (b) cost more per token, and (c) have better recall of esoteric facts. As you note, our models are ordered:
Luna < Terra < Sol < Astra
[...] These days, version number signifies a few things at once: the order of release, the relationship to other releases, and the magnitude of improvement. So something like 6.1 would indicate it was launched after 5.6, may share some similarities to other 6.1 models in terms of training data / personality (which is why it's not 5.7), and isn't a giant enough leap to merit the headlines and expectations that would come with a 7.
— Ted Sanders, explaining OpenAI's model naming conventions
Steven Levy, writing at Wired with the scoop on the new MacBook Pros (News+ link):
This turnaround is a big deal to Apple fans. Ternus shrugs off the
drama. “The Mac is first and foremost an indirect input device,
built around the trackpad and keyboard. But I think there’s times
when it’s comfortable and handy to have touch.”
Ternus and Apple want to make sure that the Mac faithful don’t
panic that the 42-year-old franchise is losing its identity to
Apple’s gangbusters mobile products. “We needed to get to a point
where adding touch didn’t make the product lesser in any way. It
didn’t make it heavier. It didn’t make it thicker. That came
together with the OLED screen, the best display we’ve ever put
into a Mac,” Ternus told me. “All of these things, and, oh yeah,
it has touch as well.”
After a long fun day of hands-on exploration, briefings, and a slew of demos, not just most, but all of my concerns about touchscreen support adversely affecting the Mac UI have been allayed. I love it. These seem like exquisite machines even if you never want to touch the screen. I think what Ternus told Levy captures the truth of touch’s role: “All of these things, and, oh yeah, it has touch as well.”
Created by Claude with light editing by Tim O’Reilly
Raffi Krikorian, Mozilla’s CTO, joined Tim O’Reilly at our recent AI Codecon to talk about open source AI. Mozilla, of course, is the nonprofit that helped to define the open source revolution back in the late 1990s. Though its Firefox web browser was superseded as the market leader by Google Chrome, it played an essential role, along with Apache and the World Wide Web Consortium, in establishing the open standards of the web and keeping it from being dominated and enclosed by Microsoft, the dominant tech platform of that time. Now, Mozilla is one of the leading voices working to build an open, standards-based AI ecosystem.
Tim has long appreciated Raffi’s thoughtful, human-centered approach to technology. Raffi writes a newsletter called Owners Not Renters, whose message can be summed up by his statement that he doesn’t want a future with seven AGIs. He wants one with seven billion. He wants each of us to have an AI that we can trust with our secrets and that will look out for our interests, not an AI that’s optimized for the business model of its creators. In the early days of the web, we called the browser a user agent for a reason, Raffi said. It was on your side. It let you render pages however you wanted, managed your privacy and your cookies, and did its best to protect you from those who wanted to take advantage of web users. We need the same thing in the age of AI.
Raffi cited a paper in which researchers tested whether AI assistants could be trained to favor a company’s commercial interests over user welfare. In simulated flight-booking requests, 18 of 23 models recommended a more expensive sponsored option over a cheaper one more than half the time. It’s a hypothetical choice that we’ve seen play out time and time again, in industry after industry.
Open source AI is a big part of what it will take to get to Raffi’s vision. But sovereign AI loyal to each individual needs more than open source models alone. Raffi’s list of what has to be built around the model starts with memory, a place where your private data can live. It includes tool calling, so an agent can make a purchase or book a doctor’s appointment for you, the runtime environment where all of that runs, and the rules for how his agent talks to those working on behalf of others. It needs a harness. “That’s where evaluations happen. Guardrails happen, execution loops happen, tool calling happens, memory,” he explained. “All of that stuff is an opportunity, in my mind, of things that open source developers can be building.”
People hear the word “harness” and conclude that we need an open source version of whatever the proprietary labs are building. Tim asked Raffi whether a user-centered harness might do different things than those offered by the big labs. He agreed. The whole point of open source is for people to “scratch their own itch.” The ability to innovate without permission is the heart of the open source promise.
As a result, Mozilla wants to build a starting point. It aims to help the community define what an open memory protocol, a storage protocol, or authenticated tool calling with the right guardrails ought to look like. As Raffi noted, “Once we could define what those open standards look like, then a whole plethora of people can start playing and be interoperable. It’s basically. . .the internet all over again. We can build trillions of dollars of market cap on top of open protocols.”
Ease of use is still lacking, though. Mozilla’s 2026 State of Open Source AI report says open models are now within about 3% of the frontier, yet they don’t make it into production at the same rate as closed models. When Tim asked why, Raffi explained that open source is easy to release but hard to deploy. Developers still have to figure out hosting, provisioning, guardrails, and memory. With OpenAI’s or Anthropic’s API, you just hand over a credit card. What’s missing, he said, is the equivalent of a double-click installer for getting open source AI running inside an organization. But the companies that do the work to adopt open source AI are seeing big savings because open models are already good enough for most use cases. As Raffi put it, “You don’t need a Ferrari to manage your calendar.”
Raffi’s own daily agentic helper is Hermes running on GLM. He expects that Apple, Microsoft, or someone else will make this kind of agent into a consumer product in a couple of years, and that his mom will end up using it. For now, he said, we’re on the wrong part of the innovation curve, where you have to know how to code to get any of this working.
Tim disagreed. The industry goes through periods that are exciting for developers, creators, inventors, and companies trying to invent the future, and then it gets boring and a few big companies dominate it. We’re in the exciting part, he argued, before everything shakes out. As Raffi riffed, this is when we get to formalize what that future should look like.
The Clothesline Paradox
Tim wasn’t sure that we’ll need a commercially supported version of the kind of “roll your own” agentic rigs now favored by independent developers. After all, neither desktop Linux nor OpenOffice turned out to matter anything like as much as open source developers of the time expected. Instead, open source became the foundation layer for a new generation of web-based applications. It’s hidden way down in the guts of Google, Amazon, Meta, and countless other applications we rely on today.
This is already beginning to happen again with AI. The Mozilla report says that as much as a third of real-world usage is already on open models, although only 4% of model-layer revenue made its way to the open source ecosystem. Tim called the discrepancy a feature rather than a bug, and Raffi agreed that the stat is misleading. As Tim pointed out, many of the most important technologies “create more value than they capture,” and he used Steve Baer’s concept “The Clothesline Paradox,” from a 1975 article in Stewart Brand’s CoEvolution Quarterly, to explain why we’re good at measuring value capture but not so good at measuring value creation.
Baer pointed out that if you put your clothes in the dryer, the energy you use is measured and counted, but if you hang them on the clothesline to be dried by the sun, the energy saved disappears from our accounting. This argument resonated with Tim in the early days of his open source advocacy. As he noted, it’s always bothered him that nobody seemed to recognize that open source software didn’t “win” in the same way as proprietary software. It won by becoming the foundation everyone else builds on.
AI should be thought of as infrastructure
Raffi’s comment that we’ve made a category error by treating AI as a product fits right in with this line of thinking. If an AI company goes out of business, its product disappears. If it changes its business model, it may yank features you depend on. It’s not just individuals who need sovereign AI. Countries are passing laws about where data can be processed and how it moves in and out, and some of those requirements may not be compatible with the way the big labs plan to monetize their technology. What those countries are asking for is infrastructure. A road outlasts the contractor who built it. Raffi thinks open, downloadable models are the only way to provide long-lasting foundational infrastructure.
According to OpenRouter stats, Chinese models now supply more routed tokens than American ones. Tim asked whether we should worry about that. Raffi said the problem isn’t China but market concentration. The leading open models are from China. The leading closed models are all American. Access to either can be cut off by an executive order. We saw a version of that in June, when Anthropic temporarily suspended access to its Fable models to comply with export controls. It’s a problem that both the leading proprietary models and the leading open-weight models are each concentrated in a single country.
Diversity is one foundation of resilience. Raffi argues, for instance, that hospitals should all download a local model as a backup. None of us would run an important computer without an uninterruptible power supply, so why would a hospital doing triage with AI rely on a single intelligence provider? There are a lot of possible rug pulls. The government could restrict open source or restrict the frontier models. Having a backup plan is a good idea.
Safety is also part of the foundation. During the Q&A, an audience member asked about the recent sandbox escapes at OpenAI and Anthropic. Raffi joked that the best part was watching everyone try to one-up each other with accounts of how powerful and hard to control their models are. But he agreed that guardrails are actually a hard problem. Keeping personally identifiable information from leaking out through an LLM call means looking for much more than Social Security numbers. Eventually we’ll have models defending models, but the foundational frameworks for guardrails aren’t good enough yet. (NVIDIA’s safety platform announcement, released after Raffi and Tim’s conversation, suggests that better guardrails need to be implemented outside the model.)
In conclusion
Tim opened AI Codecon by noting that open and closed systems have always coexisted, and that the idea that one of them will win is a mistake. Closed systems, like Apple’s, Google’s, OpenAI’s, and Anthropic’s, can optimize for ordinary people and deliver value to billions. Open systems are better for innovation and sovereignty, and for pushing technology into new countries and new markets.
Raffi closed the conversation by observing that a well-tuned harness can improve model performance by as much as 20% on some coding tasks. You don’t have to be a machine learning engineer to make a difference at that layer.
Tropical Weather Outlook NWS Central Pacific Hurricane Center Honolulu HI Issued by NWS National Hurricane Center Miami FL 200 PM HST Fri Oct 30 2026
For the central North Pacific...between 140W and 180W:
Well Southeast of the Hawaiian Islands: A broad area of low pressure is forecast to develop well to the southeast of the Hawaiian Islands by early next week. Thereafter, environmental conditions appear generally favorable for gradual development of this system, and a tropical depression could form by the end of next week as it moves westward to west-northwestward over the Central Pacific basin. * Formation chance through 48 hours...low...near 0 percent. * Formation chance through 7 days...medium...40 percent.
Tropical Weather Outlook NWS National Hurricane Center Miami FL 500 PM PDT Fri Oct 30 2026
For the eastern and central North Pacific east of 180 longitude:
Well Southeast of the Hawaiian Islands: A broad area of low pressure is forecast to develop well to the southeast of the Hawaiian Islands by early next week. Thereafter, environmental conditions appear generally favorable for gradual development of this system, and a tropical depression could form by the end of next week as it moves westward to west-northwestward over the Central Pacific basin. * Formation chance through 48 hours...low...near 0 percent. * Formation chance through 7 days...medium...40 percent.