Best non-fiction books of 2025

The year started off slow, but it ended up being a normally strong time for quality, readable non-fiction.  Here is my list, noting that the links lead either to my reviews or to Amazon.  These are roughly in the order I read them, not ranked ordinally.  Here goes:

Caroline Burt and Richard Partington, Arise, England: Six Kings and the Making of the English State.

Tirthankar Roy and K. Ravi Raman, Kerala: 1956 to the Present.

Agnes Callard, Open Socrates: The Case for a Philosophical Life.

Amy Sall, The African Gaze: Photography, Cinema, and Power.

Michael Krielaars, The Sound of Utopia: Musicians in the Time of Stalin.

David Eltis, Rethinking the Atlantic Slave Trades.

Philip Freeman, In the Brewing Luminous: The Life and Music of Cecil Taylor.

Daniel Dain, A History of Boston. Short review here.

Ezra Klein and Derek Thompson, Abundance.

Ian Leslie, John & Paul: A Love Story in Songs.

Benjamin E. Park, American Zion: A New History of Mormonism

Roger Chickering, The German Empire, 1871-1918.

Donald S. Lopez Jr., Buddhism: A Journey Through History.

Dan Wang, Breakneck: China’s Quest to Engineer the Future.

Keach Hagey, The Optimist: Sam Altman, OpenAI, and the Race to Invent the Future.

Joseph Torigian, The Party’s Interests Come First: The Life of Xi Zhongxun, Father of Xi Jinping.

Rupert Gavin, Amorous or Loving?: The Highly Peculiar Tale of English and the English.

Sam Tanenhaus, Buckley: The Life and Revolution that Changed America.

Erik Penman, Eric Satie Three Piece Suite.

Dwarkesh Patel, and others, The Scaling Era: An Oral History of AI, 2019-2025.

Jeff McMahan, editor, Derek Parfit: His Life and Thought.

Paul McCartney, Wings: The Story of a Band on the Run.

William Easterly, Violent Saviors: The West’s Conquest of the Rest.

Nicholas Walton, Orange Sky, Rising Water: The Remarkable Past and Uncertain Future of the Netherlands.

What else?  I will give you an update on anything notable I encounter between now and the end of the year.  And here is my earlier post on the best fiction of the year.

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What Now? Handling Errors in Large Systems

What Now? Handling Errors in Large Systems

More options means more choices.

Cloudflare’s deep postmortem for their November 18 outage triggered a ton of online chatter about error handling, caused by a single line in the postmortem:

.unwrap()

If you’re not familiar with Rust, you need to know about Result, a kind of struct that can contain either a succesful result, or an error. unwrap says basically “return the successful results if their is one, otherwise crash the program”1. You can think of it like an assert.

There’s a ton of debate about whether asserts are good in production2, but most are missing the point. Quite simply, this isn’t a question about a single program. It’s not a local property. Whether asserts are appropriate for a given component is a global property of the system, and the way it handles data.

Let’s play a little error handling game. Click the ✅ if you think crashing the process or server is appropriate, and the ❌ if you don’t. Then you’ll see my vote and justification.

  • One of ten web servers behind a load balancer encounters uncorrectable memory errors, and takes itself out of service.
  • One of ten multi-threaded application servers behind a load balancer encounters a null pointer in business logic while processing a customer request.
  • One database replica receives a logical replication record from the primary that it doesn't know how to process
  • One web server receives a global configuration file from the control plane that appears malformed.
  • One web server fails to write its log file because of a full disk.

If you don’t want to play, and just see my answers, click here: .

There are three unifying principles behind my answers here.

Are failures correlated? If the decision is a local one that’s highly likely to be uncorrelated between machines, then crashing is the cleanest thing to do. Crashing has the advantage of reducing the complexity of the system, by removing the working in degraded mode state. On the other hand, if failures can be correlated (including by adversarial user behavior), its best to design the system to reject the cause of the errors and continue.

Can they be handled at a higher layer? This is where you need to understand your architecture. Traditional web service architectures can handle low rates of errors at a higher layer (e.g. by replacing instances or containers as they fail load balancer health checks using AWS Autoscaling), but can’t handle high rates of crashes (because they are limited in how quickly instances or containers can be replaced). Fine-grained architectures, starting with Lambda-style serverless all the way to Erlang’s approach, are designed to handle higher rates of errors, and crashing rather the continuing is appropriate in more cases.

Is it possible to meaningfully continue? This is where you need to understand your business logic. In most cases with configuration, and some cases with data, its possible to continue with the last-known good version. This adds complexity, by introducing the behavior mode of running with that version, but that complexity may be worth the additional resilience. On the other hand, in a database that handles updates via operations (e.g. x = x + 1) or conditional operations (if x == 1 then y = y + x) then continuing after skipping some records could cause arbitrary state corruption. In the latter case, the system must be designed (including its operational practices) to ensure the invariant that replicas only get records they understand. These kinds of invariants make the system less resilient, but are needed to avoid state divergence.

The bottom line is that error handling in systems isn’t a local property. The right way to handle errors is a global property of the system, and error handling needs to be built into the system from the beginning.

Getting this right is hard, and that’s where blast radius reduction techniques like cell-based architectures, independent regions, and shuffle sharding come in. Blast radius reduction means that if you do the wrong thing you affect less than all your traffic - ideally a small percentage of traffic. Blast radius reduction is humility in the face of complexity.

Footnotes

  1. Yes, I know a panic isn’t necessarily a crash, but it’s close enough for our purposes here. If you’d like to explain the difference to me, feel free.
  2. And a ton of debate about whether Rust helped here. I think Rust does two things very well in this case: it makes the unwrap case explicit in the code (the programmer can see that this line has “succeed or die behavior”, entirely locally on this one line of code), and prevents action-at-a-distance behavior (which silently continuing with a NULL pointer could cause). What Rust doesn’t do perfectly here is make this explicit enough. Some suggested that unwrap should be called or_panic, which I like. Others suggested lints like clippy should be more explicit about requiring unwrap to come with some justification, which may be helpful in some code bases. Overall, I’d rather be writing Rust than C here.

Stoke Space goes for broke to solve the only launch problem that “moves the needle”

LAUNCH COMPLEX 14, Cape Canaveral, Fla.—The platform atop the hulking steel tower offered a sweeping view of Florida’s rich, sandy coastline and brilliant blue waves beyond. Yet as captivating as the vista might be for an aspiring rocket magnate like Andy Lapsa, it also had to be a little intimidating.

To his right, at Launch Complex 13 next door, a recently returned Falcon 9 booster stood on a landing pad. SpaceX has landed more than 500 large orbital rockets. And next to SpaceX sprawled the launch site operated by Blue Origin. Its massive New Glenn rocket is also reusable, and founder Jeff Bezos has invested tens of billions of dollars into the venture.

Looking to the left, Lapsa saw a graveyard of sorts for commercial startups. Launch Complex 15 was leased to a promising startup, ABL Space, two years ago. After two failed launches, ABL Space pivoted away from commercial launch. Just beyond lies Launch Complex 16, where Relativity Space aims to launch from. The company has already burned through $1.7 billion in its efforts to reach orbit. Had billionaire Eric Schmidt not stepped in earlier this year, Relativity would have gone bankrupt.

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Newest Starship booster is significantly damaged during testing early Friday

During the pre-dawn hours in South Texas on Friday morning, SpaceX’s next-generation Starship first stage suffered some sort of major damage during pre-launch testing.

The company had only rolled the massive rocket out of the factory a day earlier, noting the beginning of its test campaign, it said on the social media site X: “The first operations will test the booster’s redesigned propellant systems and its structural strength.”

That testing commenced on Thursday night at the Massey’s Test Site a couple of miles down the road from the company’s main production site at Starbase Texas. However an independent video showed the rocket’s lower half undergo an explosive (or possibly implosive) event at 4:04 am CT (10:04 UTC) Friday.

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The economics theory that could have saved the Trump presidency

Americans are not very happy with Donald Trump’s second term in office. Trump’s approval has trended downward since he returned to power, and has recently fallen again. Here are some numbers from Nate Silver:

Source: Nate Silver

Even Fox News admits how bad it’s getting:

Unhappy with the economy. Pain with prices. Unsure about Trump administration policies. It adds up to high disapproval among the president’s loyal constituencies…

Some 76% of voters view the economy negatively. That’s worse than the 67% who felt that way in July and the 70% who said the same at the end of former President Biden’s term…Large numbers, overall and among Republicans, say their costs for groceries, utilities, healthcare and housing have gone up this year…Voters blame the president. About twice as many say President Donald Trump, rather than Biden, is responsible for the current economy. And three times as many say Trump’s economic policies have hurt them (they said the same about Biden’s last year). Plus, approval of how Trump is handling the economy hit a new low, and disapproval of his overall job performance hit record highs among core supporters…

Trump’s job performance drew career-high disapproval among men, White voters and those without a college degree…Among all voters, 41% approve of the job Trump is doing, while 58% disapprove…For comparison, Biden’s marks were a bit better at the same point in his presidency: 44% approved and 54% disapproved in November 2021.

As Fox points out, it’s the economy, rather than immigration policy or culture wars, that’s driving these results. Despite employment, growth and inflation numbers that don’t seem too bad overall, Americans are deeply unhappy with their economy. Preliminary numbers for November’s consumer sentiment show it falling back to the low point it hit in 2022, during the height of the post-pandemic inflation:

Source: UMich

And as Fox notes, voters overwhelmingly blame President Trump, rather than Biden, for the economy. Even 42% of Republicans blame Trump rather than Biden, which must be a galling thing to tell a pollster on the phone. Analysis by David Shor finds that Republicans’ trust advantage is evaporating on issues like the cost of living, the budget deficit, and the economy in general.

Exactly why Americans hate their economy right now is a tough question. Sometime during the Biden administration, we saw economic sentiment decouple from the macroeconomic numbers that traditionally correlated with sentiment — in other words, we saw the beginning of the “vibecession”. Now after a modest recovery in 2024, we’re seeing another vibecession under Trump. What’s going on? Is it mortgage rates? Anxiety about AI? Are people displacing their concerns about social unrest onto their perceptions of economic conditions?

One possibility is that Americans are expressing their unhappiness about economic policy, rather than economic results. Both Trump’s approval and consumer sentiment fell abruptly during the recent government shutdown, and they also hit a previous low in May after Trump’s “Liberation Day” tariffs were announced. So low consumer sentiment, and low Trump approval ratings, might be Americans’ way of expressing unhappiness about what Trump is trying to do to the economy.

People must have an intuitive sense that the AI boom is the main thing propping up the macroeconomy right now, and that this could end at any moment. And they probably realize that the AI boom is having to fight against the headwinds created by Trump’s tariffs. They can also see that tariffs are causing localized harm to parts of the U.S. economy right now.

The part of the economy being hurt the most is manufacturing — exactly the sector that Trump has long pledged to help. Even as employment holds up in service jobs like health care and education, employment in goods-producing industries has plunged since “Liberation Day”:

In fact it’s not just manufacturing that’s hurting. Construction and transportation/warehousing jobs, which were booming in Biden’s final year in office, have basically collapsed under Trump. A lot of that construction was factories, which boomed more under Biden than at any time since the 1960s. Under Trump, the factory construction boom has begun to deflate.

But no sector is hurting worse than manufacturing, which continues to shed jobs at a rapid rate. Almost every type of manufacturing is doing badly, but the auto industry has swung from expansion under Biden to contraction under Trump:

What’s going on here? The obvious answer is “tariffs”. Here’s Reuters from a couple of weeks ago:

U.S. manufacturing contracted for an eighth straight month in October as new orders remained subdued, and suppliers were taking longer to deliver materials to factories against the backdrop of tariffs on imported goods…Backlog orders remained subdued as did export orders…Production was weak after briefly rebounding in September. Manufacturers have cited tariffs as a major constraint…

Tariffs are gumming up supply chains, resulting in longer delivery times to factories. The ISM survey’s supplier deliveries index increased to 54.2 from 52.6 in September. A reading above 50 indicates slower deliveries…Factories continued to pay more for inputs[.]

This story is not a one-off. In fact, we have seen a steady drumbeat of stories about American manufacturing’s tariff-induced woes since May. In September, Moody’s Analytics assessed that manufacturing was experiencing recession-like conditions, thanks to tariffs. The Institute for Supply Management, which interviews manufacturers, has been receiving an avalanche of tariff-related complaints, along with consistent pessimism about business conditions, for months now.

Things are not as catastrophic as they might have been. Resource prices have fallen worldwide, which has helped cancel out some of the tariffs’ impact. And Trump has backed off of some of his tariffs, especially on China, while granting a byzantine maze of exemptions and deferrals. The effective tariff rate on imports has risen, but only to 10.5% so far — considerably less than the headline rates that Trump has been throwing around on the news.

But although tariffs are hurting less than they would have if Trump had stuck to his guns, they’re certainly hurting to some degree. It’s entirely reasonable for the American people to be unhappy about their government intentionally hurting the economy, even if it doesn’t end up being as bad as promised.

It didn’t have to be this way. If Trump had listened to economists, he might have known that tariffs don’t work the way you might assume from watching CNN in the early 1990s — which, as far as I can tell, is where Trump got most of his ideas about the way the world works. If Trump had listened to economists, he might have understood why tariffs hurt manufacturing.

The reason is that tariffs include taxes on intermediate goods, which make production less efficient.

I’ve talked about this a number of times in the past, and I’ve shown some empirical evidence that tariffs on intermediate goods really do hurt U.S. manufacturing. But I’ve never really talked about the theory behind this idea. I really should talk about it, because if Trump and his people had understood this concept, they might have avoided a lot of pain and a lot of mistakes.

The theory originally comes from a 1971 paper by Peter Diamond and James Mirrlees. Diamond and Mirrlees realize that the government needs to tax the economy in order to produce various stuff (highways, education, research, etc.), and to redistribute income via the welfare state. Most types of taxes tend to distort the economy.1 But Diamond and Mirrlees showed that if the government can tax everything — cars, pizza, back massages, labor, and so on — at different rates, you can levy taxes without distorting economic production.

Now, that’s not that useful of a result. In reality, you can’t actually put different tax rates on every different kind of good or service. But the real value of the Diamond-Mirrlees result is that it shows what kind of taxes you don’t want to use: taxes on intermediate goods. They show that taxing intermediate goods is always worse than taxing either final goods — i.e., stuff consumers buy, like cars and pizza — or “factors of production” (i.e., labor, capital, land, etc.). You never want to tax stuff like steel, or auto parts, or computer chips that companies buy in order to produce other stuff.

If you like, here are some slides from Todd Lensman that explain the math of this result in a simplified form.

So why don’t you want to tax intermediate goods? Because you want to make as much stuff as you can make before you start redistributing it. If the purpose of taxes is to redistribute the economic pie,2 you want to redistribute as big of a pie as you possibly can. Taxes on things like steel, auto parts, and computer chips cause the economy to make fewer cars, houses, computers, etc. So when you collect taxes and then give people money to spend, there are fewer cars, houses, and computers for them to buy with the money you give them. You should have just let capitalism work its magic and make as much stuff as possible, and then worried about how to redistribute.

This is a very powerful and deep result. Diamond and Mirrlees made some simplifying assumptions in order to make the math easier, but other theorists came in later and did the harder math, and they showed that the basic result — no taxes on intermediate goods — holds for a pretty wide range of assumptions.

That’s a very useful real-world result! In fact, real-world tax systems in rich countries mostly stick to the Diamond-Mirrlees principle. Income and payroll taxes are taxes on “factor inputs”, so they’re OK. Corporate taxes allow you to deduct business expenses, so they’re also OK — you’re not taxing the cost of the intermediate goods that businesses buy.

U.S. sales taxes are actually bad, because they violate the Diamond-Mirrlees principle — lots of sales taxes are levied on B2B transactions. Europe does this much better — their value-added tax (VAT) is basically a sales tax that doesn’t get charged on the things businesses buy. America would be a bit richer if we switched from sales taxes to VAT, but we won’t, because sales taxes are used by our state and local governments, while a VAT would have to be nationally administered.

Anyway, Trump’s tariffs absolutely violate the Diamond-Mirrlees principle. When most people think about imports, they think about cheap stuff you buy on the shelf at Wal-Mart. Diamond and Mirrlees would be fine with taxing that stuff — the things on the shelf at Wal-Mart are “final goods”. But almost half of what America imports from overseas is intermediate goods. Here are numbers from 2019:

Source: SF Fed

Trump’s tariffs apply to all of those intermediate goods. That’s why carmakers are having trouble making cars right now. And it’s why even if Trump does mail tariff rebate checks to every American, the number of cars they’ll be able to buy with those checks will be fewer than they could have bought before the tariffs.

Because neither Trump nor any of his people understood the basic insight of Diamond-Mirrlees (1971), they are trying to redistribute a pie that they’ve already shrunk. And the American people don’t appear to be happy about it.

Are there ever situations where you’d want to tax intermediate goods? Yes. Like any economic theory, if you break enough of the assumptions, the basic result no longer holds. Costinot and Werning (2022) show that if your only taxes are income taxes and tariffs, you should use tariffs to reduce inequality. Basically, if imports from China hit a few kinds of American workers very hard, and you have no way to specifically compensate those folks,3 then you should have some tariffs on China, in order to protect those few workers. But even then, Costinot and Werning show that the optimal tariff will be very small — between 0.02% and 0.12%, compared with the 10% that Trump has enacted so far. The world isn’t exactly like Diamond-Mirrlees, but it’s pretty close.

So anyway, tariffs on intermediate goods are bad. Economists knew this, and shouted it from the rooftops. But the Trump administration prides itself on not listening to economists. JD Vance has declared that “the economics profession doesn’t fully understand tariffs”, and hardly a day goes by when Trump-aligned intellectuals like Oren Cass don’t sneer at the economics field.

And yet this willful ignorance comes with real political costs. No, economists don’t know everything about how the economy works. Maybe they don’t even know most things. But they do know some things, and one of those things is that taxing intermediate goods hurts the economy.

If Trump’s people had allowed themselves to understand that fact — if they had listened to the economists — Trump’s approval ratings might not be nearly so low as they are.

And if you’re a progressive, the temptation to laugh at Trump over all of this will naturally be very strong. But the right lesson here isn’t that “Trump is dumb” (though that is probably true). The right lesson here is that although there are lots of things they don’t know, and although they don’t get everything right, and although they’re often overconfident, economists are worth listening to, even when they don’t tell you what you want to hear. That’s a lesson that Biden and his people should have heeded before they unleashed a stimulus plan that macroeconomists predicted would exacerbate inflation. And it’s a lesson that will come in handy the next time Democrats are in charge of the economy.

Update: In the comments, Charlie Hammerslough relates his own experience with the tariffs:

Here’s the perspective of a start-up manufacturer of a physical good. Our product is made from steel parts that I’m currently in India to source. Plus off the shelf electronics and a lock that we import from China, because there is no other source.

We assemble the product in the US, creating jobs there. I *want* to manufacture in the US.

The electronics and lock have doubled in price since April. I’d love to cut and bend the steel in the US, but protectionist tariffs have increased local steel prices by 50%, reducing the advantages of domestic manufacturing.

So, tariffs are approximately 35% of the cost of the finished product. This is a struggle. Sometimes I want to bag it and just invest my money in something more predictable.

Yep. This is exactly how the Diamond-Mirrlees model works. Economics looks like this abstract math on a page, but that math is ultimately about real people and real businesses, with real stakes. I wish a lot more people in our government realized that.


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1

Except for land taxes and “lump-sum” taxes. Lump-sum taxes are where the government says “OK, every citizen give me $100”. Obviously that’s not going to fly in real life. Land taxes actually do work in real life, although they can logistically be tough to implement, due to the difficulty of distinguishing between the value of land and the value of all the stuff that’s built on top of the land.

2

Diamond and Mirrlees also allow for another purpose of government: to produce useful stuff, like infrastructure and education. But here, their solution is basically just “run the government production exactly like a private company would run it” — essentially, make some SOEs that minimize costs like a private company would. Easier said than done, right? But anyway, that doesn’t really affect the “intermediate goods” result.

3

From a Diamond-Mirrlees standpoint, the best way to compensate these folks would probably be to subsidize the industries that are subject to the most intense Chinese competition, rather than to send money to workers who get displaced.

Alnitak, Alnilam, Mintaka

Alnitak, Alnilam, Mintaka Alnitak, Alnilam, Mintaka


Train Wreck: Will transit sink the Interstate Bridge Project?

Lack of transit funding could derail the Interstate Bridge Project

No one has committed money to build or operate the key light rail segment of the IBR project.

The “deal” has always been that Washington state got a widened highway if Oregon got light rail.

The Trump Administration actively hostile to transit funding and to the Portland metropolitan area

IBR isn’t even planning on filing an application for federal funds until 2028, well after it starts construction

There is no plan for paying for the operating costs–neither of the region’s transit agencies–Tri-Met and CTRAN–have committed to spending the money

Much of Clark County doesn’t want anything to do with light rail, and certainly not to pay for it.

The project’s planing documents called for an agreement to be reached years ago–but it still hasn’t happened.

The last train to Clarksville?

A major, unfunded piece of the proposed $7.5 billion (soon to be $9-10 billion) Interstate Bridge Project is extension of a light rail line across the river into Vancouver.  But project proponents have gotten neither the money to build the light rail line, nor the money to operate it once built.

A political deal:  Light Rail for Us, a Wider Highway for You

Throughout its checkered two decade long history, the Interstate Bridge Project (nee Columbia River Crossing) has been a kind of grand compromise between highway boosters and transit advocates.  Some (mostly on the Washington side, really just wanted a bigger highway bridge), others (mostly on the Oregon side) wanted to extend Portland’s light rail system into downtown Vancouver (just across the Columbia River).  Oregon’s state Supreme Court even opined that the law authorizing the project was implicitly a political deal between the two states that incorporated just those terms.  Willamette Week called the cost of the freeway “a $2.5 billion bribe” to get Washington to accept light rail:

Oregon’s Supreme Court says light-rail politics drove plans for a new I-5 bridge.

The Oregon Supreme Court has succeeded in doing what scores of public meetings, thousands of pages of reports, and endless public relations spin could not: Give us the original rationale behind the proposed $3.5 billion Columbia River Crossing.  The answer, according to the court: The massive Interstate 5 bridge and freeway project is a “political necessity” to persuade Clark County residents to accept something they previously didn’t want—a MAX light-rail line from Portland to Vancouver.

If light rail can’t be built as part of the project, much, if not all of the enthusiasm and support for the project could easily disappear on the Oregon side of the river.  More to the point, the entire project’s authorization under Oregon’s landmark land use laws hinges on building the light rail line.  If light rail goes, the political, financial and legal foundations of the project could collapse.

No Funds yet for Transit Capital Costs

But the funding for both building and operating light rail transit as part of the project is just vaporware at this point.  For years, IBR officials have been counting on getting about $1 billion in federal grants to pay virtually all of the cost of building the light rail line, but they’ve put off even filing an application for those funds until 2028.  And the recent advent of the Trump Administration, which is hostile to transit generally, to big transit projects in particular, and to Portland especially.  According to Politico, Trump’s Transportation Department has proposed zeroing out funding from the Highway Trust Fund to transit.  This same department has cancelled major federal funding for California High Speed Rail, and New York’s Gateway tunnel project.  And a key provision of the “Big Beautiful Bill” was clawing nearly all of the money the Biden Administration awarded for Portland’s I-5 Rose Quarter widening project (which was the largest single grant from the Reconnecting Communities Program).  IBR officials haven’t presented any kind of contingency plan for paying for light rail construction, and the financial risks to the two state’s are magnified by a project schedule that calls for construction to start at least a year before they know whether the federal government will contribute anything to pay for light rail construction costs.  The latest project schedule shows that IBR won’t have a decision on federal funding until 2028 at the earliest, while construction is supposed to start in 2026.

Nor any funds for transit operating costs

As bad as the capital cost outlook is, the operating cost outlook may be even worse.  Late last year, the IBR project said it would cost approximately $20 million per year to operate light rail, which caused both local transit agencies–Tri-Met and C-TRAN–to balk.  Since then the agency has been looking to cut operating costs.  They have a new estimate that says, at least initially operating costs might be as low as $10 million annually, but there’s a catch:  it means dramatically reducing service frequency.  But so far, neither Tri-Met nor CTRAN have agreed to pay for light rail operations, nor have them come up with a source of funds to pay these costs.  That’s important for obvious reasons, but its also worth noting that the federal government has a policy of not making capital grants for projects for which state and/or local governments haven’t come up with the money to pay for operations.  In effect, not having money to run light rail trains is a barrier to getting federal funds to lay the track.

 

So far, the only solution that has been forwarded for dealing with the operating costs is to drastically cut back on light rail service.  If you don’t run so many trains, then operations don’t cost so much.  The big savings come from cutting back service from nine trains per hour at the peak, to just four trains per hour (the same as planned off-peak service).  Of course, the trouble with this is that if you don’t run as many trains, you don’t get the benefits of a high capacity transit system (reducing congestion, increasing accessibility, lowering pollution.  The project’s latest ridership estimates predict only about 5,000 riders per day, compared to an EIS estimate of more than 21,000 per day.  Both the cost-effectiveness of the light rail, and the analysis of its environmental impacts is contingent on running lots and lots of trains, frequently across the bridge.  If you run fewer trains, it will be cheaper to operate, but it will serve fewer passengers, and consequently do less to reduce automobile traffic and pollution.  And carrying fewer riders materially changes how the US Department of Transportation “scores” a proposed grant:  In general, USDOT funds only projects that are cost effective (that carry lots of passengers at low costs).  Reducing frequencies and passenger counts increases the per passenger cost of capital improvements, and makes the project less viable to US DOT, so much so that it may not qualify for capital funding.

Tri-Met is facing a major fiscal crisis

All of these problems are accentuated by the fact that Tri-Met, like many transit agencies around the United States, is facing a fiscal crisis.  In the wake of the Covid pandemic, and with the increased adoption of work from home, transit ridership has fallen dramatically.  At the same time, labor market tightness has pushed up the cost of hiring bus drivers, and on top of that, the one-time federal money that came to transit agencies to cope with the pandemic is running out.  What that means is Tri-Met is facing major budget cuts, as the Oregonian reported on November 20, 2025:

TriMet’s top leader warned Wednesday that the regional transit agency will have to cut service over the next three years to close a $300 million budget gap due to rising costs, declining ridership and lawmakers’ failure to pass a transportation funding package.

So if Tri-Met were to commit to pay for light rail service across the Columbia River, it would have to further cut existing service, especially bus service, to Portland residents.

Light rail isn’t popular in Clark County

Nor does it appear that CTRAN, the transit operator in Clark County. Washington, has either the interest or the wherewithal to pay for light rail.  For more than a decade, CTRAN has been building a series of bus rapid transit lines in Clark County, and for decades it has run a system of express buses to various locations (mostly employment centers) in Portland.  Those systems work well, and the agency is not inclined to cut them to move into light rail.  (And, ironically, given its circuitous routing and frequent stops, the light rail line would provide slower service than today’s express buses for Vancouver commuters traveling to job centers in Portland).

Light rail is far less popular in Clark County than in Oregon:  It’s often derisively (and baselessly) called the “crime train” and is seen as an example of “Portland creep“–Portland foisting its liberal green values on Clark County.  Many in Clark County don’t want to see light rail built at all, and even more have no inclination to pay for operating it.  In the Eastern suburbs of Clark County–far from the light rail terminus in Vancouver, residents are concerned that light rail costs will lead to cuts in their bus service, which have prompted the cities of Camas and Washougal to contemplate seceding from CTRAN.

 

What should be particularly concerning to policy makers is that IBR and other local officials have been kicking the can down the road on paying for both construction and operation of light rail.  The loudest alarm bells are the fact that the project schedule calls for the two state DOTs to start construction at least a year before they know whether they get any federal money to pay for light rail construction.  It is also disconcerting that the project’s schedule has called for coming up with a plan to pay for operating costs for years, and a 2024 project schedule predicted the agreements would be complete in February of 2025, (IBR-Integrated Task Schedule Progress Update #12 – 01-Jan-2024 FINAL) but still nothing has been resolved.  It appears that the IBR is looking to simply blunder ahead, even without funding, and when the federal government turns them down (or offers much less than the hoped for $1 billion) simply blackmails the two states to make up the costs.  It’s a cynical ploy, and hopefully no one will fall for it.

 

Friday 21 November 1662

Within all day long, helping to put up my hangings in my house in my wife’s chamber, to my great content. In the afternoon I went to speak to Sir J. Minnes at his lodgings, where I found many great ladies, and his lodgings made very fine indeed.

At night to supper and to bed: this night having first put up a spitting sheet, —[?? D.W.] which I find very convenient. This day come the King’s pleasure-boats from Calais, with the Dunkirk money, being 400,000 pistols.

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Geologic Core Sample

If you drill at the right angle and time things perfectly, your core sample can include a section of a rival team's coring equipment.

Live coverage: Falcon 9 rocket to continue Starlink deployments with launch from Cape Canaveral

File photo: A Falcon 9 stands ready for a Starlink mission at Cape Canaveral’s Space Launch Complex 40. Image: Michael Cain/Spaceflight Now.

SpaceX is planning to launch a Falcon 9 rocket from Cape Canaveral in the early hours Saturday as the company continues to expand its network of more than 9,000 satellites for the Starlink internet service.

Liftoff from Space Launch Complex 40 at Cape Canaveral Space Force Station is scheduled during a four-hour launch window that opens at 2:53 a.m. EST (0753 UTC). It will be the ninth of as many as 11 Starlink missions planned this month and the 109th Starlink delivery run for the Falcon 9 rocket this year.

Near-perfect conditions are expected, with the 45th Weather Squadron forecasting a less than five-percent chance of a weather rule violation.

Spaceflight Now will have live coverage starting an hour prior to launch.

After climbing away from pad 40, the Falcon 9 will pitch and roll on to a south-easterly trajectory to place its cargo of 29 Starlink V2 satellites into an orbit inclined at 43 degrees to the Equator.

SpaceX is flying B1090, a relatively new first stage booster making its ninth flight. After separating from the Falcon 9 second stage at an altitude of about 40 miles (65km), it will continue to arc higher over the Atlantic crossing the Karman line —considered to be the boundary of space — before plunging back to Earth and landing on the drone ship ‘A Shortfall of Gravitas’.

The second stage will fire for about six minutes to place the Starlink satellites stacked atop the rocket into a parking orbit. After coasting for about 45 minutes, the second stage will circularize the orbit with a one-second burn of its Merlin Vacuum engine.

Separation of the satellites into a 170×162 mile (274×261 km) orbit will occur an hour and five minutes into flight.

Another 28 satellites are scheduled to launch from the West Coast Sunday morning.

The Week Observed: November 21, 2025

What City Observatory Did This Week

Last train to Clarksville?  Lack of transit funding could derail the Interstate Bridge Project. No one has committed money to build or operate the key light rail segment of the IBR project. The “deal” has always been that Washington state got a widened highway if Oregon got light rail.

The Trump Administration actively hostile to transit funding and to the Portland metropolitan area. IBR isn’t even planning on filing an application for federal funds until 2028, well after it starts construction

 

There is no plan for paying for the operating costs–neither of the region’s transit agencies–Tri-Met and CTRAN–have committed to spending the money. Much of Clark County doesn’t want anything to do with light rail, and certainly not to pay for it. The project’s planning documents called for an agreement to be reached years ago–but it still hasn’t happened.

Must Read

The end of federal funding for transit?  Politico reports (paywall), that leaked documents show that the US Department of Transportation is proposing to eliminate federal funding for transit through the highway trust funds and also end the ability of states to “flex” highway funding to transit.  The results, according to Transportation for America, would be devastating for the nation’s transit systems.

In a statement, Transportation for America’s Steve Davis says:

“This short-sighted proposal will annihilate state and local transportation budgets, strand millions of Americans who depend on transit every day in red and blue states alike, produce chaos and increase congestion, seize control from states, and utterly fail to actually solve our most pressing long-term transportation funding issues. The highway formula program alone spends $20 billion more than what the gas tax brings in every year—stealing transit funds won’t change that.”

The good news, if there is any, according to Davis, is that this should put dramatically change the discussion over proposed transportation reauthorization legislation in the coming year.  This major existential threat to transit should end the “business as usual” approach to reauthorization, and provoke some serious examination of a program that has routinely raided general funds to subsidize highway construction and produced little to show for it in terms of tangible results like reduced congestion or improved safety.

 

Paul Krugman on cities and agglomeration economies.  There have been headlines claiming that New York’s election of Zohran Mamdani, a avowed Democratic Socialist as Mayor will prompt capitalists to run for the exits.  That’s not going to happen, for very good economic reasons, according to Paul Krugman

Why won’t plutocrats flee New York? For one thing, they’re not stupid (although they were hoping that voters were.) Mamdani might — might — be able to raise their taxes a bit. But they don’t really believe that free buses and city-run grocery stores will turn one of America’s safest cities into a post-apocalyptic landscape. And New York will retain formidable advantages thanks to agglomeration economies — the advantages of locating a business where many other related businesses are concentrated.

And New York has not only powerful advantages in productivity, it also turns out that it offers even larger advantages in the form of diverse, plentiful and convenient consumption opportunities.

The central city has much higher effective population density than any other city in America, which in turn supports a range of amenities — restaurants, shops, museums, shows and concerts, and more — that you can’t find anywhere else.

The advantages in consumption accrue to almost everyone in New York, but are especially valuable to those with lots of money to spend, which is why rich people can, and will continue to find the city a great place to live, even if the rents (and taxes) might be higher than say, Iowa.

A market premium for walkability.  Realtors are reporting that more home buyers are looking for homes in walkable neighborhoods, and that walkable properties command a growing premium over car-dependent housing.  The National Association of Realtors quotes one industry leader, Howard Hanna, as saying:

Walkability has become one of the most valuable amenities in today’s housing market. We’re seeing buyers pay 10% to 20% more for homes that offer a true ‘step-out-and-go’ lifestyle. It appeals to every generation, from young families who want stroller-friendly streets to seniors who prioritize mobility, health, and longevity.

According to Realtor.com, the share of listings that highlight neighborhood walkability has doubled in the past year from 0.6 percent to 1.3 percent.  While conspiracy theorists have characterized 15-minute cities as a globalist plot, the report from real estate professionals is that its actually a highly desirable consumer choice.  NAR says people are clamoring for walkability, and are willing to pay for it.

The hottest trend in urban design is the “15-minute city”—where theoretically it takes only 15 minutes to walk to anything you need.

New Knowledge

Visualizing 15 minute cities.  And,  speaking 15-minute  cities,  there’s a new study that maps accessibility in cities globally.  It also includes a web-based interface that allows users to examine, in great detail, variations in walkability and bikability.  Like other accessbility measures, such as Walk Score, the maps indicate how long it takes to reach a portfolio of  common destinations (stores, schools, parks and other points of interest) by bike or walking from each neighborhood in a city.

Here, for example, is a map of a portion of the Portland Metropolotina area, showing the region’s most accessible locations (in blue) and least accessible (in red).  As the authors explain:

These maps will tell you how much an area is “15 Minutes”. Each area’s colour represents the average travel time for an individual to reach its daily activity venues on foot or by bike. If this travel time is below 15 minutes, the area colour will be bluered otherwise.

The maps also allow you to drill down to individual hexagons to inspect specific values, and examine separately the proximity to destinations by broad category, as well as mode (biking or walking).

Because the authors have compiled data for cities around the world, you’re not limited to looking at US cities, or comparing US cities only to other locations in the US.  Here, for example, are side by side maps of the Houston metropolitan area compared to Paris (France, not Texas).  Paris is overwhelmingly walkable (with only a small amount of inaccessible locations on the periphery.  Houston, by contrast has a relatively few walkable areas in its center, and is largely automobile dependent (red).

Bruno, Matteo, Hygor Piaget Monteiro Melo, Bruno Campanelli, and Vittorio Loreto. “A universal framework for inclusive 15-minute cities.” Nature Cities 1, no. 10 (2024): 633-641.

Hard Landings

A graph of a stock market

AI-generated content may be incorrect.

When my flight took off from Madrid, my news feed was all about how Nvidia’s earnings had banished worries about an AI bubble. By the time I landed in NY, no they hadn’t, and Trump was threatening to execute members of Congress for saying that the military should disobey illegal orders.

So there’s a lot going on. Financially, the most striking may be the crash in crypto, which, as I wrote just two days ago, has become a Trump trade. Question: Is the ongoing plunge justified by fundamentals? Answer: What fundamentals?

But too tired to say much right now. Regular posting will resume this weekend.

MUSICAL CODA

We should all be using dependency cooldowns

We should all be using dependency cooldowns

William Woodruff gives a name to a sensible strategy for managing dependencies while reducing the chances of a surprise supply chain attack: dependency cooldowns.

Supply chain attacks happen when an attacker compromises a widely used open source package and publishes a new version with an exploit. These are usually spotted very quickly, so an attack often only has a few hours of effective window before the problem is identified and the compromised package is pulled.

You are most at risk if you're automatically applying upgrades the same day they are released.

William says:

I love cooldowns for several reasons:

  • They're empirically effective, per above. They won't stop all attackers, but they do stymie the majority of high-visibiity, mass-impact supply chain attacks that have become more common.
  • They're incredibly easy to implement. Moreover, they're literally free to implement in most cases: most people can use Dependabot's functionality, Renovate's functionality, or the functionality build directly into their package manager

The one counter-argument to this is that sometimes an upgrade fixes a security vulnerability, and in those cases every hour of delay in upgrading as an hour when an attacker could exploit the new issue against your software.

I see that as an argument for carefully monitoring the release notes of your dependencies, and paying special attention to security advisories. I'm a big fan of the GitHub Advisory Database for that kind of information.

Via Hacker News

Tags: definitions, github, open-source, packaging, supply-chain

Links 11/21/25

Links for you. Science:

Nanotech makes cancer drug 20,000x stronger, without side effects
Entry, replication and innate immunity evasion of BANAL-236, a SARS-CoV-2-related bat virus, in Rhinolophus and human cells
Archaeologists discover how oldest American civilisation survived a climate catastrophe
Small Language Models are the Future of Agentic AI
Can Narcissists Actually Change?
Emboldened, Kennedy Allies Embrace a Label They Once Rejected: ‘Anti-Vax’

Other:

Congressional Democrats Are Just as Spineless as Ever
Right-Wing Critics of Antisemitism Keep Strikingly Silent About Trump
The Democrats continue to tolerate backstabbers
I Want You to Understand Chicago
Democratic Whip Dick Durbin
Kennedy Center chief sucks at his job—and hates it
Yell Before It Is Too Late
Voters Ousted This Pennsylvania Sheriff After He Signed Up to Collaborate With ICE
He’s a citizen with a Real ID. ICE detained him anyway. Twice.
What Climate Change Will Do to America by Mid-Century. Many places may become uninhabitable. Many people may be on their own.
Why These Vichy Dems and Their Spineless Boss Need to Go Now
Democrats Were on a Roll. Why Stop Now?
How Elon Musk’s Changes to X Made Our Discourse Far Stupider
Masked ICE agents put damper on Oak Park Girl Scout food drive: ‘It’s heartbreaking as a mom’
The Summer the Internet Found Empathy — And How Quickly We Lost It
Why the conspiratorial right rallied around a flock of ostriches
Editing federal employees’ emails to blame Democrats for shutdown violated their First Amendment rights, judge says
Inside Washington’s Controversial Addiction to Autopens
Waukegan alderman says federal agents pulled guns on him: ‘There were four barrels pointed at me’
The Boss Has a Message: Use AI or You’re Fired
Off the Beaten Track: How is Life in China’s “Most Median City”?
Ethered
Only a Fraction of Republicans’ Much-Touted $50 Billion Rural Health Fund Can Help Struggling Hospitals Pay Their Bills
Good Job, Chuck
Bari Weiss wants to take down CBS News’ Standards and Practices unit for having ‘too much power’
The Latest Defense Against ICE: 3D-Printed Whistles
Everybody Stand Down: New Yorker Columnist’s Child Doesn’t Care About Sports Gambling
Is This the Haphazard End of Streateries in DC? (it’s a bad policy)
There Are No Weird Blogs Anymore Cause It’s More Fruitful to Drive Them Out of Business
At a Loss for Words

Collections: Hoplite Wars, Part II: Hoplite Equipment, Hoplight or Hopheavy?

This is the second part of what looks like it’ll be end up as a four part series discussing the debates surrounding ancient Greek hoplites, the heavy infantry of the Archaic (800-480) and Classical (480-323) periods. Last week, we outlined the contours of the debate: the major points of contention and the history of the debate and how it has come to its current – and I would argue, unsatisfactory – point.

This week, I want to stay laying out my own sense of the arguments and what I see as a viable synthesis. I’ve opted to split this into three parts because I don’t just want to present my ‘answers’ but also really use this as an opportunity to contrast the two opposing camps (hoplite orthodoxy and hoplite heterodoxy) in the process of laying out where I think the firmest ground is, which as we’ll see is something of a blend of both. That is a larger project so I’ve opted to split it up. This post will cover the question of equipment, both the date of its emergence and its use and function (which have implications for chronolgy and tactics). Then the next post will cover the question of tactics, both in terms of how the phalanx might have functioned on an Archaic battlefield where light infantry and cavalry remained common and important and how it may have functioned in a late-Archaic or Classical battlefield when they were less central (but still at least sometimes present). Then, at long last, the final post will cover what I think are some of the social and political implications (some of which falls out of the first ideas), which is actually where I think some of the most explosive conclusions really are.

However before I launch into all of that, I want to be clear about the perspective I am coming from. On the one hand, I am an ancient historian, I do read ancient Greek, I can engage with the main bodies of evidence (literary, archaeological, representational) directly, as an expert. On the other hand, I am not a scholar of hoplites: this is my field, but not my sub-field. Consequently, I am assessing the arguments of folks who have spent a lot more time on hoplites than me and have thus read these sources more closely and more widely than I have. I can check their work, I can assess their arguments, but while I am going to suggest solutions to some of these quandaries, I want to be clear I am coming at this from a pose of intellectual humility in terms of raw command of the evidence.

(Although I should note this post, which is on equipment basically is square in my wheelhouse, so if I sound a bit more strident this week it is because while I am modestly familiar with hoplites, I am very familiar with hoplite (and other pre-gunpowder) equipment.)

On the other hand, I think I do come at the problem with two advantages, the value of which the reader may determine for themselves. The first of these is simply that I am not a scholar of hoplites and so I am not ‘in’ one of these ‘camps;’ an ‘outsiders’ perspective – from someone who can still engage directly with the evidence – can be handy. The second of these is frankly that I have very broad training as a military historian which gives me a somewhat wider base of comparative evidence to draw on than I think has been brought to bear on these questions before. And that is going to be relevant, particularly this week, because part of my core argument here is that one mistake that has been repeated here is treating the hoplite phalanx as something special and unique, rather than as an interesting species of a common phenomenon: the shield wall, which has shared characteristics that occur in many cultures at many times.

As always, if you like what you are reading, please share it as I rely on word-of-mouth to find readers! And if you really like it, you can support this project over at Patreon; I don’t promise not to use the money to buy a full hoplite panoply, but I also don’t not promise to do that.1 And if you want updates whenever a new post appears, you can click below for email updates or follow me on Twitter and Bluesky and (less frequently) Mastodon (@bretdevereaux@historians.social) for updates when posts go live and my general musings; I have largely shifted over to Bluesky (I maintain some de minimis presence on Twitter), given that it has become a much better place for historical discussion than Twitter.

The Emergence of the Hoplite Panoply

We need to start with three entwined questions, the nature of hoplite equipment, the dates at which it appears and the implications for the emergence of the ‘true’ phalanx (and its nature). As I noted in the first part, while the two ‘camps’ on hoplites consist of a set of linked answers to key questions, the strength of those linkages vary: in some cases, answer A necessitates answer B and in some cases it does not. In this case, the hoplite orthodox argument is that hoplite equipment was too cumbersome to fight much outside of the phalanx, which in turn (they argue) necessitates that the emergence of the full panoply means the phalanx must come with it. Consequently, hoplite orthodoxy assumes something like a ‘hoplite revolution’ (a phrase they use), where hoplites (and their equipment) and the phalanx emerge at more of less the same time, rapidly remaking the politics of the polis and polis warfare.

By contrast, hoplite heterodoxy unlinks these issues, by arguing that hoplite equipment is not that cumbersome and so need not necessitate the phalanx, while at the same time noting that such equipment emerged gradually and the fully panoply appeared rather later than hoplite orthodoxy might suggest. But this plays into a larger argument that hoplites developed outside of close-order formations and could function just as well in skirmish or open-order environments.

As an aside, I want to clarify terminology here: we are not dealing, this week, with the question of ‘the phalanx.’ That term’s use is heavily subject to definition and we need to have that definitional fight out before we use it. So instead, we are going to talk about ‘close order‘ formations (close intervals (combat width sub-150cm or so), fixed positioning) as compared to ‘open order‘ (wide intervals (combat width 150cm+), somewhat flexible positioning) and skirmishing (arbitrary intervals, infinitely flexible positioning). And in particular, we’re interested in a big ‘family’ of close-order formations I am going to call shield walls, which is any formation where combatants stand close enough together to mutually support with shields (which is often not shoulder-to-shoulder, but often more like 1m combat widths). We will untangle how a phalanx fits into these categories later.

We can start, I think, with the easy part: when does hoplite equipment show up in the evidence-record. This is the easier question because it can be answered with some decision by archaeology: when you have dated examples of the gear or representations of it in artwork, it exists; if you do not, it probably doesn’t yet. We should be clear here that we’re working with a terminus post quem (‘limit before which’), which is to say our evidence will give us the latest possible date of something: if we find that the earliest, say, Archaic bell-cuirass we have is c. 720, then c. 721 is the last possible date that this armor might not yet have existed. But of course there could have been still earlier armors which do not survive: so new discoveries can shift dates back but not forward in time. That said, our evidence – archaeology of arms buttressed by artwork of soldiers – is fairly decent and it would be a major surprise if any of these dates shifted by more than a decade or two.

(An aside before I go further: I am focused here mostly on the when of hoplite equipment. There is also a really interesting question of the where of early hoplite equipment. Older hoplite orthodox scholars assumed hoplite equipment emerged in Greece ex nihilo and was peculiar to the Greeks, but this vision has been challenged and I think is rightly challenged (by, e.g. J. Brouwers, Henchmen of Ares (2013), reviewed favorably by Sean Manning here. In particular, the fact that a lot of our evidence comes from either Southern Italy or Anatolia is not always well appreciated in these debates. We don’t have the space to untangle those arguments (and I am not versed enough on the eastern side) but it is well worth remembering that Archaic Greece was not culturally isolated and that influences eastern and western are easy to demonstrate.)

And what our evidence suggests is that Anthony Snodgrass was right:2 hoplite equipment emerges peicemeal and gradually (and were adopted even slower), not all at once and did so well before we have evidence by any other metric for fighting in the phalanx (which comes towards the end of the equipment’s developmental timeline).

The earliest piece of distinctively hoplite equipment that we see in artwork is the circular aspis, which starts showing up around c. 750, but takes a long time to displace other, lighter shield forms, only pushing out these other types in artwork (Diplyon shields with ‘carve outs’ on either side giving them a figure-8 design, squarish shields, center-grip shields) in the back half of the 600s. Metal helmets begin appearing first in the late 8th century (a couple of decades behind the earliest aspides), with the oldest type being the open-faced and Kegelhelm, which evolved into the also open-faced ‘Illyrian‘ helmet (please ignore the ethnic signifiers used on these helmet names, they are usually not historically grounded). By the early seventh century – so just a few decades later – we start to get our first close-faced helmets, the early Corinthian helmet types.

Via Wikipedia, a black-figure amphora (c. 560) showing a battle scene. The warriors on the left hold aspides and wear Corinthian helmets, while the ones on the right carry diplyon shields (which look to have the two-points-of-contact grip the aspis does). I useful reminder that non-hoplite equipment was not immediately or even necessarily very rapidly displaced by what became the hoplite standard.

Coming fairly quickly after the appearance of metal helmets is metal body armor, with the earliest dated example (to my knowledge) still being the the Argos cuirass (c. 720), which is the first of the ‘bell cuirass’ type, which will evolve into the later muscle cuirass you are likely familiar with, which appears at the tail end of the Archaic as an artistic elaboration of the design. Not everyone dons this armor right away to go by its appearance in artwork or prevalence in the archaeological record – adoption was slow, almost certainly (given the expense of a bronze cuirass) from the upper-classes downward.

Via Wikipedia, a picture of the Argos bell cuirass with its Kegelhelm-type helmet dated to c. 720. Apologies for the side-on picture, I couldn’t find a straight-on image that had a clean CC license.

This element of armor is eventually joined by quite a few ‘add-ons’ protecting the arms, legs, feet and groin, which also phase in (and in some cases phase out) over time. The first to show up are greaves (which are also the only armor ‘add on’ to really stick around) which begin to appear perhaps as early as c. 750 but only really securely (there are dating troubles with some examples) by c. 700. Small semi-circular metal plates designed to hang from the base of the cuirass to protect the belly and goin, ‘belly guards,’ start showing up around c. 675 or so (so around four decades after the cuirasses themselves), while other add-ins fill in later – ankle-guards in the mid-600s, foot-guards and arm guards (quite rare) in the late 600s. All of these but the greaves basically phase out by the end of the 500s.

Via Wikipedia, a late classical (c. 340-330) cuirass and helmet showing how some of this equipment will develop over time. The cuirass here is a muscle cuirass, a direct development from the earlier bell cuirass above. The helmet is a Chalcidian-type, which seems to have developed out of the Corinthian helmet as a lighter, less restrictive option in the fifth century.

Pteruges, those distinctive leather strips hanging down from the cuirass (they are part of the textile or leather liner worn underneath it) start showing up in the sixth century (so the 500s), about two centuries after the cuirasses themselves. There is also some reason to suppose that textile armor is in use as a cheaper substitute for the bronze cuirass as early as the seventh century, but it is only in the mid-sixth century that we get clear and unambiguous effort for the classic stiff tube-and-yoke cuirass which by c. 500 becomes the most common hoplite armor, displacing the bronze cuirass (almost certainly because it was cheaper, not because it was lighter, which it probably wasn’t).

Via Wikipedia, from the Alexander Mosaic, a later Roman copy of an early Hellenistic mosaic (so quite a bit after our period), Alexander the Great shown wearing a tube-and-yoke cuirass (probably linen, clearly with some metal reinforcement), with visible pteruges around his lower waist (the straps there).
Note that there is a second quieter debate about the construction of the tube-and-yoke cuirass which we’re just going to leave aside for now.

Weapons are less useful for our chronology, so we can give them just a few words. Thrusting spears were, of course, a bronze age technology not lost to our Dark Age Greeks, but they persist alongside throwing spears, often with visible throwing loops, well into the 600s, even for heavily armored hoplite-style troops. As for swords, the Greek hoplites will have two types, a straight-edged cut-and-thrust sword of modest length (the xiphos) and a single-edged foward curving chopper of a sword (the kopis), though older Naue II types – a continuation of bronze age designs – continues all the way into the 500s. The origin of the kopis is quite contested and meaningfully uncertain (whereas the xiphos seems a straight line extrapolation from previous designs), but need not detain us here.

So in summary, we do not see a sudden ‘revolution’ in terms of the adoption of hoplite arms, but rather a fairly gradual process stretched out over a century where equip emerges, often vies with ‘non-hoplite’ equipment for prominence and slowly becomes more popular (almost certainly faster in some places and slower in others, though our evidence rarely lets us see this clearly). The aspis first starts showing up c. 750, the helmets a decade or two after that, the breastplates a decade or two after that, the greaves a decade or two after that, the other ‘add-ons’ a few decades after that (by which point we’re closing in on 650 and we have visual evidence of hoplites in close-order, albeit with caveats). Meanwhile adoption is also gradual: hoplite-equipped men co-exist in artwork alongside men with different equipment for quite a while, with artwork showing unbroken lines of uniformly equipped hoplites with the full panoply beginning in the mid-to-late 7th century, about a century to a century and a half after we started. It is after this, in the sixth century, that we see both pteruges – which will become the standard goin and upper-thigh protection – and the tube-and-yoke cuirass, a cheaper armor probably indicating poorer-but-still-well-to-do men entering the phalanx.

Via Wikipedia, the Chigi Vase (c. 650). Its hoplite scene is (arguably) the oldest clear scene we have of hoplites depicted fighting in close-order with overlapping shields, although the difficulty of depth (how closely is that second rank behind the first?) remains.

Consequently, the Archaic hoplite must have shared his battlefield with non-hoplites and indeed – and this is one of van Wees’ strongest points – when we look at Archaic artwork, we see that a lot. Just all over the place. Hoplites with cavalry, hoplites with light infantry, hoplites with archers (and, of course, hoplites with hoplites).

Of course that raises key questions about how hoplites function on two kinds of battlefield: an early battlefield where they have to function within an army that is probably still predominately lighter infantry (with some cavalry) and a later battlefield in which the hoplite is the center-piece of the army. But before we get to how hoplites fight together, we need to think a bit about what hoplite equipment means for how they fight individual.

Hoplite or Hopheavy?3

If the basic outlines of the gradualist argument about the development of hoplite equipment is one where the heterodox camp has more or less simply won, the argument about the impact of that equipment is one in which the orthodox camp is determined to hold its ground.

To summarize the arguments: hoplite orthodoxy argues, in effect, that hoplite equipment was so heavy and cumbersome that it necessitated fighting in the phalanx. As a result orthodox scholars tend to emphasize the significant weight of hoplite equipment. Consequently, this becomes an argument against any vision of a more fluid battlefield, as orthodox scholars will argue hoplites were simply too encumbered to function in such a battlefield. This argument appears in WWoW, along with a call for more archaeology to support it, a call which was answered by the sometimes frustrating E. Jarva, Archaiologia on Archaic Greek Body Armour (1995) but it remains current. The latest attempt I am aware of to renew this argument is part of A. Schwartz, Reinstating the Hoplite (2013), 25-101.

By contrast, the heterodox camp argues that hoplite equipment was not that heavy or cumbersome and could be used outside of the phalanx (and indeed, was so used), but this argument often proceeds beyond this point to argue that hoplite equipment emerged in a fluid, skirmish-like battlefield and was, in a sense, at home in such a battlefield, as part of a larger argument about the phalanx being quite a lot less rigid and organized than the orthodox camp imagines it. Put another way at the extremes the heterodox camp argues there is nothing about hoplite equipment which would suggest it was designed or intended for a close-order, relatively rigid infantry formation. There’s a dovetailing here where this argument also gets drawn into arguments about ‘technological determinism’ – a rejection of the idea that any given form of ancient warfare, especially hoplite warfare, represented a technologically superior way of fighting or set of equipment – which also gets overstated to the point of suggesting weapon design doesn’t particularly matter at all.4

This is one of those areas where I will make few friends because I think both arguments are actually quite bad, a product of scholars who are extremely well versed in the ancient sources but who have relatively less training in military history more broadly and especially in pre-modern military history and especially especially pre-modern arms and armor.

So let me set some ‘ground rules’ about how, generally speaking, pre-modern arms and armor emerge. When it comes to personal combat equipment, (almost) no one in these periods has a military research and development department and equipment is rarely designed from scratch. Instead, arms and armor are evolving out of a fairly organic process, iterating on previous patterns or (more rarely) experimenting with entirely new patterns. This process is driven by need, which is to say arms and armor respond to the current threat environment, not a projection of a (far) future threat environment. As a result, arms and armor tend to engage in a kind of ‘antagonistic co-evolution,’ with designs evolving and responding to present threats and challenges. Within that space, imitation and adornment also play key roles: cultures imitate the weapons of armies they see as more successful and elites often use arms and armor to display status.

The way entire panoplies – that is full sets of equipment intended to be used together – tend to emerge is part of this process: panoplies tend to be pretty clearly planned or designed for a specific threat environment, which is to say they are intended for a specific role. Now, I want to be clear about these words ‘planned,’ ‘designed,’ or ‘intended’ – we are being quite metaphorical here. There is often no single person drafting design documents, rather we’re describing the outcome of the evolutionary process above: many individual combatants making individual choices about equipment (because few pre-modern armies have standardized kit) thinking about the kind of battle they expect to be in tend very strongly to produce panoplies that are clearly biased towards a specific intended kind of battle.

Which absolutely does not mean they are never used for any other kind of battle. The ‘kit’ of an 18th century line infantryman in Europe was designed, very clearly for linear engagements between large units on relatively open battlefields. But if what you had was that kit and an enemy who was in a forest or a town or an orchard or behind a fence, well that was the kit you had and you made the best of it you could.5 Likewise, if what you have is a hoplite army but you need to engage in terrain or a situation which does not permit a phalanx, you do not suffer a 404-TACTICS-NOT-FOUND error, you engage with the equipment you have. That said, being very good at one sort of fighting means making compromises (weight, mobility, protection, lethality) for other kinds of fighting, so two equipment sets might be situationally superior to each other (panoply A is better at combat situation Y, while panoply B is better at situation Z, though they may both be able to do either and roughly equally bad at situation X).

Via Wikimedia Commons, a black figure amphora (c. 510) showing a mythological scene (Achilles and Ajax) with warriors represented as hoplites, but carrying two spears (so they can throw one of them).

Naturally, in a non-standardized army, the individual combatants making individual choices about equipment are going to be considering the primary kind of battle they expect but also the likelihood that they are going to end up having to fight in other ways and so nearly all real-world panoplies (and nearly all of the weapons and armor they use) are not ultra-specialized hot-house flowers, but rather compromise designs. Which doesn’t mean they don’t have a primary kind of battle in mind! Just that some affordance has been made for other modalities of warfare.

If we apply that model to hoplite equipment, I think it resolves a lot of our quandaries reasonably well towards the following conclusion: hoplite equipment was a heavy infantry kit which was reasonably flexible but seems very clearly to have been intended, first and foremost, to function in close order infantry formations, rather than in fully individual combats or skirmishing.

Now let’s look at the equipment and talk about why I think that, starting with:

Overall Weight.

I am by no means the first person to note that absurdly heavy estimates dating back more than a century for the hoplite’s ‘combat load’ (that is, what would be carried into battle, not on campaign) are absurdly high; you will still hear figures of 33-40kg (72-90lbs) bandied about. These estimates predated a lot of modern archaeology and were consistently too high. Likewise, the first systematic effort to figure out, archaeologically, how heavy this equipment was by Eero Jarva, skewed the results high in a consistent pattern.6 Equally, I think there is some risk coming in a bit low, but frankly low-errors have been consistently less egregious than high-errors.7 Conveniently, I have looked at a lot of this material in order to get a sense of military gear in the later Hellenistic period, so I can quickly summarize and estimate from the archaeology.

Early Corinthian helmets can come in close to 2kg in weight, though later Greek helmets tend much lighter, between 1-1.5kg; we’re interested in the Archaic so the heavier number bears some weight. Greek bronze cuirasses as recovered invariably mass under 4.5kg (not the 4-8kg Jarva imagines), so we might imagine in original condition an upper limit around c. 5.5kg with most closer to 3.5-4.5kg, with probably 1-2kg for liner and pteruges; a tube-and-yoke cuirass in linen or leather (the former was probably more common) would have been only modestly lighter, perhaps 3.5-4kg (a small proportion of these had metal reinforcements, but these were very modest outside of Etruria).8 So for a typical load, we might imagine anywhere from 3.5kg to 6.5kg of armor, but 5kg is probably a healthy median value. We actually have a lot of greaves: individual pieces (greaves are worn in pairs) range from ~450 to 1,100g, with the cluster around 700-800, suggesting a pair around 1.4-1.6kg; we can say around 1.5kg.

For weapons, the dory (the one-handed thrusting spear), tips range from c. 150 to c. 400g, spear butts (the sauroter) around c. 150g, plus a haft that probably comes in around 1kg, for a c. 1.5kg spear. Greek infantry swords are a tiny bit smaller and lighter than what we see to their West, with a straight-edged xiphos probably having around 500g (plus a hundred grams or so of organic fittings to the hilt) of metal and a kopis a bit heavier at c. 700g. Adding suspension and such, we probably get to around 1.25kg or so.9

That leaves the aspis, which is tricky for two reasons. First, aspides, while a clear and visible type, clearly varied a bit in size: they are roughly 90cm in diameter, but with a fair bit of wiggle room and likewise the depth of the dish matters for weight. Second, what we recover for aspides are generally the metal (bronze) shield covers, not the wooden cores; these shields were never all-metal like you see in games or movies, they were mostly wood with a very thin sheet of bronze (c. 0.25-0.5mm) over the top. So you can shift the weight a lot by what wood you use and how thick the core is made (it is worth noting that while you might expect a preference for strong woods, the ancient preference explicitly is for light woods in shields).10 You can get a reconstruction really quite light (as light as 3.5kg or so), but my sense is most come in around 6-7kg, with some as heavy as 9kg.[/efn_note]See K.R. de Groote, ‘”Twas When my Shield Turned Traitor!’ Establishing the Combat Effectiveness of the Greek Hoplite Shield” OJA 35.2 (2016) for a rundown.[/efn_note] A bigger fellow might carry a bigger, heavier shield, but let’s say 6kg on the high side and call it a day.

How encumbered is our hoplite? Well, if we skew heavy on everything and add a second spear (for reasons we’ll get to next time), we come out to about 23kg – our ‘hopheavy.’ If we skew light on everything, our ‘hoplight’ could come to as little as c. 13kg while still having the full kit; to be frank I don’t think they were ever this light, but we’ll leave this as a minimum marker. For the Archaic period (when helmets tend to be heavier), I think we might imagine something like a typical single-spear, bronze-cuirass-wearing hoplite combat load coming in something closer to 18kg or so.11

And now we need to ask a second important question (which is frustratingly rarely asked in these debates – not never, but rarely): is that a lot? What we should not do is compare this to modern, post-gunpowder combat loads which assume very different kinds of combat that require very different sorts of mobility. What we should do is compare this to ancient and medieval combat loads to get a sense of how heavy different classes of infantry were. And it just so happens I am wrapping up a book project that involves computing that, many times for quite a few different panoplies. So here are some brief topline figures, along with the assigned combat role (light infantry, medium infantry, heavy infantry):

  • A fully plate-armored late 14th/early 15th century dismounted knight: 24-27kg (Heavy Infantry).12
  • Hop-heavy, c. 23kg
  • Roman Hastatus/Princeps of the Middle Republic: c. 20-24kg (Heavy Infantry)
  • Macedonian Phalangite: c. 20kg (Heavy Infantry)
  • Typical Hoplite, c. 18kg
  • Hellenistic Peltastai: c. 17-18kg (Heavy Infantry, modestly lighter than above)
  • Gallic Warrior: c. 14kg (Medium infantry, assumes metal helmet, textile armor so on the heavy side for the Gauls)
  • Hop-light, c. 13kg.
  • Iberian Warrior: c. 13kg (Medium infantry)
  • Celtiberian Warrior: c. 11.5kg (Medium Infantry)
  • Hellenistic thureophoroi: c. 10.5kg (Medium Infantry)
  • Roman veles: c. 8kg (Light infantry).13

Some observations emerge from this exercise immediately. First combat role – which I’ve derived from how these troops are used and positioned in ancient armies, not on how much their kit weighs – clearly connects to equipment weight. There is a visible ‘heavy infantry range’ that starts around 15kg and runs upward, a clear ‘medium’ range of lightly-armored line-but-also-skirmish infantry from around 14kg to about 10kg and then everything below that are ‘lights’ that aren’t expected to hold part of the main infantry line.14

But I’d argue simply putting these weights together exposes some real problems in both the extreme orthodox and extreme heterodox views. On the one hand, the idea that hoplite equipment was so heavy that it could only function in the phalanx is clearly nonsense: the typical hoplite was lighter than the typical Roman heavy infantryman who fought in a looser, more flexible formation! Dismounted knights generally fought as close-order heavy infantrymen, but certainly could fight alone or in small groups and maneuver on the battlefield or over rough terrain and they are heavier still. So the idea that hoplites were so heavily equipped that they must fight in the extremely tight orthodox phalanx (we’ll come to spacing later, but they want these fellows crowded in) is silly.

On the other hand hoplites are very clearly typically heavy infantry. They are not mediums and they are certainly not lights. Can you ask heavy infantrymen to skirmish like lights or ask light infantrymen to hold positions like heavies? Well, you can and they may try; the results are generally awful (which is why the flexible ‘mediums’ exist in so many Hellenistic-period armies: they can do both things not-great-but-not-terribly).15 So do I think soldiers wearing this equipment generally intended to fight in skirmish actions or in truly open-order (not that Roman combat spacing, while loose by Greek standards, is still ‘close order’)? Oh my no; across the Mediterranean, we see that the troops who intend to fight like that even a little are markedly lighter and those who specialize in it are much lighter, for the obvious reason that running around in 18kg is a lot more tiring than running around in 8kg or less.

So the typical hoplite was a heavy infantryman but not the heaviest of heavy infantry. If anything, he was on the low(ish) end of heavy infantry, probably roughly alongside Hellenistic peltastai (who were intended as lighter, more mobile phalangites)16 but still very clearly in the ‘heavy’ category. Heavier infantry existed, both in antiquity and in the middle ages and did not suffer from the lack of mobility often asserted by the orthodox crowd for hoplites.

But of course equipment is more than just weight, so let’s talk about the implications of some of this kit, most notably the aspis.

The Aspis

Once again, to summarize the opposing camps, the orthodox argument is that hoplite equipment – particularly the aspis (with its weight and limited range of motion) and the Corinthian helmet (with its limited peripheral vision and hearing) – make hoplites ineffective, almost useless, outside of the rigid confines of the phalanx, and in particular outside of the ‘massed shove othismos‘ phalanx (as opposed to looser phalanxes we’ll get into next time).

The moderate heterodox argument can be summed up as, “nuh uh.” It argues that the Corinthian helmet is not so restricting, the aspis not so cumbersome and thus it is possible to dodge, to leap around, to block and throw the shield around and generally to fight in a more fluid way. The ‘strong’ heterodox argument, linking back to development, is to argue that the hoplite’s panoply actually emerged in a more fluid, skirmish environment and the phalanx – here basically any close-order, semi-rigid formation fighting style – emerged only later, implying that the hoplite’s equipment must be robustly multi-purpose. And to be clear that I am not jousting with a straw man, van Wees claims, “the hoplite shield did not presuppose or dictate a dense formation but could be used to equally good effect [emphasis mine] in open-order fighting.”17

The short version of my view is that the moderate heterodox answer is correct and very clearly so, with both the orthodox and ‘strong’ heterodox arguments having serious defects.

But first, I want to introduce a new concept building off of the way we’ve already talked about how equipment develops, which I am going to call appositeness which we can define as something like ‘situational effectiveness.’ The extreme orthodox and heterodox arguments here often seem to dwell – especially by the time they make it to public-accessible books – in a binary can/cannot space: the hoplite can or cannot move quickly, can or cannot skirmish, can or cannot fight with agility and so on.

But as noted above real equipment is not ‘good’ or ‘bad’ but ‘situationally effective’ or not and I want to introduce another layer of complexity in that this situational effectiveness – this appositeness – is a spectrum, not a binary. Weapons and armor are almost invariably deeply compromised designs, forced to make hard trade-offs between protection, reach, weight and so on, and those tradeoffs are real, meaning that they involve real deterioration of the ability to do a given combat activity. But ‘less’ does not mean ‘none.’ So the question is not can/cannot, but rather how apposite is this equipment for a given function – how well adapted is it for this specific situation.

You can do almost any kind of fighting hoplite armor, but it is very obviously adapted for one kind of fighting and was very obviously adapted for that kind of fighting when it emerged: fighting in a shield wall. And that has downstream implications of course: if the aspis is adapted for a shield wall, that implies that a shield wall already existed when it emerged (in the mid-to-late 8th century). Now we may, for the moment, leave aside if we ought to call that early shield wall a phalanx. First, we ought to talk about why I think the hoplite’s kit is designed for a shield wall but also why it could function (less effectively) outside of it.

So lets talk about the form of the aspis. The aspis is a large round shield with a lightly dished (so convex) shape, albeit in this period with a flat rim-section that runs around the edge. The whole thing is typically about 90cm in diameter (sometimes more, sometimes less) and it is held with two points of contact: the arm is passed through the porpax which sits at the center of mass of the shield and will sit against the inside of the elbow of the wear, and then holds the antelabe, a strap near the edge of the shield (so the wearer’s elbow sits just to the left of the shield’s center of mass and his hand just to the left of the shield’s edge). That explains the size: the shield pretty much has to have a radius of one forearm (conveniently a standard ancient unit called a ‘cubit’) and thus a diameter of two forearms, plus a bit for the rim, which comes to about 90cm.

Via Wikimedia Commons, a Corinthian black-figure alabastron (c. 590-570) showing hoplites in rows, which really demonstrates just how big the aspis can be. A 90cm shield is a really big shield although the artist here has certainly chosen to emphasize the size.

In construction, the aspis has, as mentioned, a wooden core made of a wood that offers the best strength at low weight (e.g. willow, poplar, not oak or ash) covered (at least for the better off hoplites) with a very thin (c. 0.25-0.5mm) bronze facing, which actually does substantially strengthen the shield. The result is, it must be noted, a somewhat heavy but very stout shield.

And here is where I come at this question a bit differently from my peers: that description to me demands comparison but the aspis is almost never compared to other similar shields. Two things, however, should immediately stand out in such a comparison. First, the aspis is an unusually, remarkably wide shield; many oblong shields are taller, but I can think of no shield-type that is on average wider than 90cm. The early medieval round shield, perhaps the closest comparison for coverage, averages around 75-85cm wide (with fairly wide variation, mind you), while the caetra, a contemporary ancient round shield from Spain, averages around 50-70cm. The famously large Roman scutum of the Middle Republic is generally only around 60cm or so wide (though it is far taller). So this is a very wide shield.

Via Wikimedia Commons, an Attic black-figure Kylix (c. 560) which gives us a good look at the two-point grip of the aspis (though note this aspis is something of a diplyon-hybrid with two small cutouts!).

Second, the two-points-of-contact strap-grip structure is a somewhat uncommon design decision (center-grip shields are, globally speaking, more common) with significant trade-offs. As an aside, it seems generally assumed – mistakenly – that ‘strap-grip’ shields dominated European medieval shields, but this isn’t quite right: the period saw a fair amount of center-grip shields, two-point-of-contact shields (what is generally meant by ‘strap grip’) and off-center single-point of contact shields, with a substantial portion of the latter two supported by a guige or shield sling, perhaps similar to how we generally reconstruct later Hellenistic version of the aspis supported by a strap over the shoulder. So the pure two-point-of-contact porpax-antelabe grip of the aspis is actually fairly unusual but not entirely unique.

But those tradeoffs can help give us a sense of what this shield was for. On the one hand, two points of contact give the user a strong connection to the shield and make it very hard for an opponent to push it out of position (and almost impossible to rotate it): that shield is going to be where its wearer wants it, no matter how hard you are hitting it. It also puts the top of the dish at shoulder level, which probably helps keeping the shield at ‘ready,’ especially because you can’t rest the thing on the ground without taking your arm out of it or kneeling.

On the other hand the two-point grip substantially reduces the shield’s range of motion and its potential to be used offensively. Now this is where the heterodox scholars will point to references in the ancient sources to war dances intended to mimic combat where participants jumped about or descriptions of combatants swinging their shield around and dodging and so on,18 and then on the other hand to the ample supply of videos showing modern reenactors in hoplite kit doing this.19 To which I first say: granted. Conceded. You can move the aspis with agility, you can hit someone with it, you can jump and dodge in hoplite kit. And that is basically enough to be fatal to the orthodox argument here.

But remember our question is appositeness: is this the ideal or even a particularly good piece of equipment to do that with? In short, the question is not ‘can you use an aspis offensively’ (at all) but is it better than other plausible designs at it. Likewise, we ask not ‘can you move the aspis around quickly’ but is it better at that than other plausible designs. And recall above, when the aspis emerged, it had competition: we see other shield designs in early Archaic artwork. There were alternatives, but the aspis ‘won out’ for the heavy infantryman and that can tell us something about what was desired in a shield.

In terms of offensive potential, we’re really interested in the range of strikes you can perform with a shield and the reach you can have with them. For the aspis, the wearer is limited to variations on a shove (pushing the shield out) and a ‘door swing’ (swinging the edge at someone) and both have really limited range. The body of the shield can never be more than one upper-arm-length away from the shoulder (c. 30cm or so)20 so the ‘shove’ can’t shove all that far and the rim of the shield can’t ever be more than a few centimeters in advance of the wearer’s fist. By contrast a center-grip shield can have its body shoved outward to the full extension of the arm (almost double the distance) and its rim can extend half the shield’s length in any direction from the hand (so striking with the lower rim of a scutum you can get the lower rim c. 60cm from your hand which is c. 60cm from your body, while a center-grip round shield of c. 80cm in diameter – smaller than the aspis – can project out 40cm from the hand which is 60cm from the body).

So that two-point grip that gives the shield such stability is dropping its offensive reach from something like 60 or 100cm (shove or strike) to just about 30 or 65cm or so (shove or strike).21 That is a meaningful difference (and you can see it represented visually in the diagram below). Again, this is not to say you cannot use the aspis offensively, just that this design prioritizes its defensive value over its offensive value with its grip and structure.

And then there is the question of coverage. Can you swing an aspis around, left to right, blocking and warding blows? Absolutely. Is it good at that? No. It is not and I am always surprised to see folks challenge this position because have you seen how a center-grip round shield is used? And to be clear, we know the Greeks could have used center-grip shields because center-grip dipylon shields show up in Archaic Greek artwork (though many diplyon shields have the same two-point grip-system as aspides as well): they had the other option and chose not to use it.22 With a two-point porpax-antelabe grip, the aspis‘ center of mass can never be more than an upper-arm’s length (again, c. 30cm) away, which really matters given that the average male might be c. 45cm wide. In practice, of course, it is hard to get an elbow much further than the center of one’s chest and that is basically the limit for how far to the right the center of the aspis can be. Likewise, there’s a real limit to how far you can cock your elbow backwards.

By contrast, the center-point of a center-grip shield can be wherever you fist can be, which is a lot wider of a set of places: you can get a center-grip shield all the way to the far side of your body, you can pull it all the way in to your chest or push your entire arm’s length into the enemy’s space. Moreover, with just a single point of contact, these shields can rotate around your hand. You can see the difference in coverage arcs below which honestly also understates how much easier it is to move a center-group shield into some of these extreme positions because it isn’t strapped to your arm.

Note: We’re going to return to the ‘side on’ vs. ‘straight on’ question in a future post, but I’ve provided both for now. The heterodox school (van Wees, op. cit., 168-9) supposes a side-on stance but in practice hoplites must have been transitioning frequently between side-on and straight-on simply to use their weapons (you bring your back leg forward when striking to get your whole body into the blow) or to march (these guys did not run sideways into battle, even if they might turn sideways as they reached the enemy). However I will note that you can see very clearly that it is only in the ‘straight on’ (or nearly so) position that Thucydides’ statement about the tendency of hoplites to drift right-ward to seek to protect their unprotected right side makes any sense (Thuc. 5.71.1), something Thucydides says “all armies do so” (ἅπαντα τοῦτο) and so must have been a general feature of the warfare he knew.

So the aspis‘ design has significantly compromised offensive potential, mobility, maneuverability and the range of coverage on the sides. What it gains is a stout design, a very stable grip and an unusually high amount of width and we know they chose these trade-offs because the aspis replaced other shield designs that were present in the Archaic, at least for this kind of combatant (the emerging hoplite). The question then is why and here certainty is impossible because the Greeks do not tell us, but we can approach a plausible answer to the question in two ways: we can ask in what situation would those positive qualities – stoutness, stability and width – be more valuable or we could look at how similar shields (large round shields) are used in other cultures.

A very wide shield that covers a lot of space in which the combatant is not is not particularly useful in skirmishing or open-order fighting (cultures that do that kind of fighting tend to drift towards either large oblong shields or small buckler-style shields). But that extra width is really handy if the goal is to create an unbroken horizontal line of protection without having to crowd so tightly with your buddies that you can’t move effectively. A hoplite can ‘join shields’ with his mates even with a file width of 90cm, which is certainly closed-order, but not absurdly tight – a Roman with a scutum has to pull in to about 60-65cm of file width to do the same. Where might you value stoutness over mobility or range of motion? Well, under conditions where you expect most strikes to come from a single direction (in front of you), so you are more concerned about your ability to meet those strikes effectively than your ability to cover angles of attack that aren’t supposed to be threatened in the first place – such as, for instance, a situation where that space is occupied by a buddy who also has a big shield. In particular, you might want this if you are more worried about having your shield shifted out of position by an enemy – a thing that was clearly a concern23 – than you are about its offensive potential or rapid mobility (or its utility for a shoving match).

What is the environment where those tradeoffs make sense? A shield wall.

Alternately, we could just ask, “what contexts do we tend to see large, solid and relatively robust round shields” and the answer is in shield walls. Or we might ask, “where do we see infantry using two-point grip shields (like some kite shields, for instance)” and find the answer is in shield walls.

I thus find myself feeling very confident that the aspis was designed for a shield wall context. Which, given how weapons develop (see above) would suggest that context already existed to some degree when the aspis emerged in the mid-to-late 8th century, although we will leave to next time working out what that might have looked like.

A Brief Digression on the Corinthian Helmet

We can think about the Corinthian helmet in similar terms. Victor Davis Hansen, who can only compare Corinthian helmets to modern combat helmets – because again a huge problem in this debate is that both sides lack sufficient pre-modern military comparanda – suggested that hoplites wearing the helmet could “scarcely see or hear” which essentially forced hoplites into a dense formation. “Dueling, skirmishing and hit-and-run tactics were out of the question with such headgear.”24 The heterodox response is to dispute the degree of those trade-offs, arguing that the helmets don’t inhibit peripheral vision or hearing and are not as heavy as the orthodox camp supposes.25 That dispute matters quite a lot because again, as we’ll get to, the ‘strong’ heterodox position is that hoplite equipment didn’t develop for or in a shield-wall formation, but for skirmishing, so if the Corinthian helmet is a bad helmet for skirmishing, that would make its emergence rather strange; we’ll come back to the question of early Archaic warfare later. Strikingly, there is a lot of effort in these treatments to reason from first principles or from other later ancient Greek helmets but the only non-Greek comparandum that is regularly brought up is the open-faced Roman montefortino-helmet – other closed-face helmets are rarely mentioned.

Via Wikimedia Commons, a relatively early design (c. 630) Corinthian helmet, showing the minimal nose protection (albeit there was some more here before it was broken off) and very wide gap over the face. The punch-holes are presumably to enable the attachment of a liner.
Via Wikimedia Commons, a sixth century Corinthian helmet (so the ‘middle’ stage of development) – the face gap is not yet fully closed, but we have the fully developed nose guard and more curved overall shape.

So does the Corinthian helmet limit vision? It depends on the particular design but a general answer is ‘perhaps a bit, but not an enormous amount.’ The eye-slits in original Corinthian helmets (as opposed to sometimes poorly made modern replica) are fairly wide and the aperture is right up against the face, so you might lose some peripheral vision, but an enormous amount. The impact to hearing is relatively more significant, but what I’ve heard from reenactors more than once is that it only gets bad if you make noise (which then is transmitted through the helmet), but that can include heavy breathing.26 Of course the best evidence that the impact to hearing was non-trivial (even if the wearer is still able to hear somewhat) is that later versions of the helmet feature cutouts for the ears. Breathing itself is a factor here: the width of the mouth-slit varies over time (it tends to close up as we move from the Archaic towards the Classical), but basically any obstruction of the front of the face with a helmet is going to be felt by the wearer when they are engaged in heavy exertion: if you are running or fighting your body is going to feel just about anything that restricts its ability to suck in maximum air.

Via Wikipedia, a 13th century German great helm, showing the narrowness of the vision-slits and the breaths (breathing holes).

But those drawbacks simply do not get us to the idea that this was a helmet which could only be used in a tight, huddled formation for the obvious reason that other, far more enclosed helmets have existed at other points in history and been used for a wider range of fighting. 13th century great helms also have no ear cutouts, feature even narrower vision-slits and use a system of ‘breaths’ (small circular holes, typically in patterns) to enable breathing, which restrict breathing more than at least early Corinthian helmets (and probably about the same amount as the more closed-front late types). Visored bascinets, like the iconic hounskull bascinet design likewise lack ear-cut outs, have breaths for air and notably move the eye aperture forward away from the eyes on the visor, reducing the area of vision significantly as compared to a Corinthian helmet. And yet we see these helmets used by both heavy infantry (dismounted knights and men-at-arms) and cavalry in a variety of situations including dueling.27

Via Wikipedia, a hounskull visored bascinet. The visor was attached via hinges so that it could be swung open (some designs have them swing upwards, others have two points of contact and swing horizontally). The large bulge beneath the eyes served in part to make breathing easier, creating a larger air pocket and more space for the breaths.

Which puts us in a similar place as with the aspis: the Corinthian helmet is a design that has made some trade-offs and compromises. It is capable of a lot – the idea that men wearing these were forced to huddle up because couldn’t see or hear each other is excessive – but the choice has clearly been made to sacrifice a bit of lightness, some vision, a fair bit of hearing and some breathing in order to squeeze out significantly more face and neck protection (those cheek pieces generally descend well below the chin, to help guard the neck that Greek body armor struggled to protect adequately). That is not a set of compromises that would make sense for a skirmisher who needs to be able to see and hear with maximum clarity and who expects to be running back and forth on the battlefield for an extended period – and indeed, skirmishing troops often forgo helmets entirely. When they wear them, they are to my knowledge invariably open-faced.

Via Wikimedia Commons, an early classical (and thus ‘late’) Corinthian helmet design (c. 475). The face has almost totally closed off and the eye-gaps have narrowed, although there is still a decently wide cutout to avoid harming peripheral vision.

Instead, when we see partially- or fully-closed-face helmets, we tend to see them in basically two environments: heavy cavalry and shield walls.28 Some of this is doubtless socioeconomic: the cavalryman has the money for expensive, fully-enclosed helmets while the poorer infantrymen must make do with less. Whereas I think the aspis was clearly developed to function in a shield wall (even though it can be used to do other things) I am less confident on the Corinthian helmet; I could probably be persuaded of the idea this began as a cavalryman’s heavy helmet, only to be adopted by the infantry because its emphasis on face-protection was so useful in the context of a shield wall clashing with another shield wall. What it is very obviously not is a skirmishers helmet.29

Conclusions

As you have probably picked up when it comes to equipment, I find the ‘orthodox’ position unacceptable on almost every point, but equally I find the heterodox position unpersuasive on every point except the ‘soft’ gradualism in development (the Snodgrass position) which I think has decisively triumphed. Of the entire debate, this is often the part that I find most frustrating because of the failure of the scholars involved to really engage meaningfully with the broader field of arms-and-armor study and to think more comparatively about how arms and armor develop, are selected and are used.

On the one hand, the idea that the hoplite, in full or nearly-full kit, could function as a skirmisher, “even in full armour, a hoplite was quite capable of moving back and forth across the battlefield in the Homeric manner” or that the kit could be “used to equally good effect in open-order fighting” is just not plausible and mistakes capability for appositeness.30 Hoplite equipment placed the typical hoplite very clearly into the weight-range of ‘heavy infantry,’ by no means the heaviest of heavy infantry (which fatally undermines the ‘encumbered hoplite’ of the orthodox vision) but also by no means light infantry or even really medium infantry except if substantial parts of the panoply were abandoned. Again, I could be sold on the idea that the earliest hoplites were, perhaps, ‘mediums’ – versatile infantry that could skirmish (but not well) and fight in close order (but not well) – but by the early 600s when the whole panoply is coming together it seems clear that the fellows with the full set are in the weight range for ‘heavies.’ We’ll talk about how we might imagine that combat evolving next time.

Moreover, key elements of hoplite equipment show a clear effort to prioritize protection over other factors: shield mobility, offensive potential, a small degree of vision, a larger but still modest degree of hearing, a smaller but still significant degree of breathing, which contributes to a larger tradeoff in endurance (another strike against the ‘skirmishing hoplite’). The environment where those tradeoffs all make sense is the shield wall. Which in turn means that while the ultra-rigid orthodox vision where these soldiers cannot function outside of the phalanx has to be abandoned – they’re more versatile than that – the vision, propounded by van Wees, that the hoplite worked just as well in open-order is also not persuasive.

Instead, it seems most plausible by far to me that this equipment emerged to meet the demands of men who were already beginning to fight in shield walls, which is to say relatively31 close-order formations with mutually supporting32 shields probably already existed when the hoplite panoply began to emerge in the mid- and late-8th century.

Tossing Texas’ Redistricting Maps

A political minute ago, Texas was starting a nationwide range war by redrawing its congressional maps to tilt results in next year’s elections for Republicans to keep majorities for Donald Trump. Texas officials made the gerrymandering goal explicit.

In response, California voters turned out in droves to “fight fire with fire” by redrawing districts for Democrats, and other states were panting hard about what to do.

The politicos now are wondering if it was all a bad dream, or whether this gerrymandering to help Republicans keep the upper hand in Washington in fact will help Democrats.

On Tuesday, three federal court judges in El Paso threw over the redrawing tables, deciding 2-1 that the new maps violated prohibitions on redistricting along racial lines. The new maps had taken mixed-race districts and sought to resort them using voting precincts by race, according to a Justice Department analysis used as evidence.

Under time constraints, Texas officials said immediately that they will file emergency appeals to the Supreme Court – a body that specifically has ruled for political partisanship in redistricting but not race.

“The public perception of this case is that it’s about politics,” U.S. District Judge Jeffrey V. Brown, a Trump appointee, said in the majority opinion, joined by U.S. District Judge David Guaderrama, an Obama appointee. Judge Jerry Smith, a Reagan appointee, dissented in an attack on the rush to issue a decision and the other judges. The 160-page opinion said that “substantial evidence shows that Texas racially gerrymandered the 2025 map” and thus was unconstitutional. Judge Jerry Smith, a Reagan appointee, dissented in an attack on the rush to issue a decision and the other judges

In the meantime, Texas must use existing maps without the bias of extra Republican votes, all with practical deadlines that 2026 lines must be in place early next month.

The decision only affects Texas, but the other states considering redrawn maps are listening.

Gauging Political Impact

Clearly, the mid-terms have politicians of all stripes unnerved. This month’s elections in several states showed positive results for Democrats and spell trouble for tight majorities in both houses of Congress. Democratic majorities will prove problematic for Trump’s broad policy changes and his aggregation of power.

Trump shows dropping popularity in the face of tariffs and rising prices, health care insurance rate woes, the antagonism to the military aggressiveness of the migrant mass deportation campaign and the Epstein case fallout.

So, Texas acted in August to redraw district lines in expectation that states with yet more registered Republicans might pick up five GOP congressional seats. Missouri, Ohio and North Carolina threatened more pro-Republican districts redraws, Virginia said it may follow with tit-for-tat Democratic districts.  Indiana Republicans said the redistricting question was beneath them and defied Donald Trump and JD Vance.

In a show of irony, Trump’s Justice Department has challenged the California redistricting maps in court on similar grounds but with opposite political impact (Three other challenges have been rejected by courts). But redistricting was not ordered by state politicos; it was a ballot measure by voters. In Virginia, proposed changes would be a change in state constitution, not a drawing whim of a partisan legislature.

Democracy Docket, which aligns with Democrats and whose founder represented the successful litigants in Texas, has a useful map and explanations about redistricting. The various moving parts make it difficult to know whether any of the perceived party gains are realistic. Plus, redrawing “safe” districts to create new would-be majority districts necessarily requires diluting the safety margin in the original districts.

But numerically, the Republican push to redistricting for electoral gain in 2026 actually could end up helping Democrats.


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Electron launches confidential commercial satellite

Electron launch

Rocket Lab launched a payload for an undisclosed commercial customer Nov. 20, just hours after the company announced plans for the launch.

The post Electron launches confidential commercial satellite appeared first on SpaceNews.

Eric Hanushek on the import of schooling quality declines

 My recent research at Stanford University translates the achievement declines into implications for future economic impacts. Past evidence shows clearly that people who know more earn more. When accounting for the impact of higher achievement historically on salaries, the lifetime earnings of today’s average student will be an estimated 8 percent lower than that of students in 2013. Because long-term economic growth depends on the quality of a nation’s labor force, the achievement declines translate into an average of 6 percent lower gross domestic product for the remainder of the century. The dollar value of this lower growth is over 15 times the total economic costs of the 2008 recession.

Here is the full Op-Ed, noting that Eric compares this decline to the effects of an eight percent income tax surcharge.  I have not read through this work, though I suspect these estimates will prove controversial when it comes to causality.  In any case, file this under “big if true,” if only in expected value terms.

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ESA unveils Thales Alenia Space-led consortium for its Argonaut lunar lander

An illustration of ESA's Argonaut lunar lander. Credit: ESA - P. Carril

MILAN — The European Space Agency has tapped a consortium led by Thales Alenia Space Italy to develop its Argonaut lunar lander and has outlined a division of labor for the program across several European firms. Thales Alenia Space Italy will act as the Lunar Design Element (LDE) prime contractor and ensure that all subsystems […]

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Janus Henderson invests in Starlab Space

Illustration of Starlab, a commercial space station under development by Voyager Space, which went public in January 2025. Credit: Voyager Space

Starlab Space has secured funding from an investment group as development of its proposed commercial space station reaches a critical phase.

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Blue Origin announces New Glenn upgrade plans

New Glenn 9x4

A week after successfully launching and landing the current version of New Glenn, Blue Origin announced a series of upgrades to the vehicle.

The post Blue Origin announces New Glenn upgrade plans appeared first on SpaceNews.

The Brittle Grip of Ultra-Wealth

Just before I began writing this post, I saw this article from The Washington Post about the rise of billionaires in American politics. Given Bezos’s ownership and the recent shift in its editorial policies I’m mildly surprised they published it. The key points aren’t terribly surprising. But it brings them together in one place — the vast growth in billionaire giving over the first quarter of this century, the rapid trend from a relatively even partisan split to overwhelming giving to Republicans. It is among other things the story of billionaires becoming increasingly class conscious. It’s always been true that money buys influence in American politics. In some ways, it was even greater and more brazen in the past since there wasn’t even the pretense of limits on giving or disclosure.

But the role of billionaire ownership of the political process has not only grown rapidly in recent years. Public recognition of that fact has, too, which has — perhaps paradoxically or perhaps not — spurred the drive for even tighter ownership. It’s no exaggeration to say that the deca-billionaire or even centi-billionaire class — setting aside those who might command a mere few billion dollars — act now as a kind of post-modern nobility, a class which does not rule exclusively but interacts with politics in a fundamentally different way from the rest of society.

This article meshes with a different New York Times article I read yesterday and which I had already planned to mention. It pivots off the big Mohammed bin Salman shindig in Washington. We’re used to the standard story about how Saudi wealth brings all the boys to the yard. That’s still mostly true. This article notes that it’s not quite as true. Or to put it more specifically, bin Salman is actually running tight on cash to finance his genuinely audacious and ambitious plans for his country.

Bin Salman has been running Saudi Arabia for a decade. His rule, whatever its horrors, has been genuinely revolutionary in a Saudi context. It’s a genuine revolution from above. He’s trying to leverage Saudi’s vast oil wealth to build a post-carbon, high-value-add first world future for the country. And a big part of that is not just buying up assets that are still domiciled abroad, like buildings, teams, and equity assets in foreign companies. A lot is supposed to be invested in building new industries, heavily tilted toward tech and emerging technologies, in Saudi Arabia.

But that requires huge sums of money, and the returns from the last decade have been hit or miss at best. There have been a lot of boondoggles that are going nowhere. There’s a futuristic, high-tech robot city in the desert which seemed bogged down in delays and cost overruns. The Times doesn’t make the point quite explicitly but a number of the key investments have been in things that key players think are cool. The sovereign wealth fund’s governor, Yasir al-Rumayyan, has invested a huge amount of money in building an international golf league in part, the Times implies, because he’s super into golf. The article similarly suggests that Saudi’s recent acquisition of a controlling interest in game maker Electronic Arts is in part because bin Salman is hugely into video games.

Saudi Arabia’s attempt to buy its way into a high-tech future not wedded to extraction economies is a complex subject that is far from exhausted by any one article or my limited understanding of the topic. But there’s a common thread between these two articles, and that is the insecurity of ultra-wealth which lurks behind and drives its increasingly aggressive ventures into the political world. It’s a topic I’ve come back to again and again over the years, most notably in a series (“The Brittle Grip”) which started in this post from mid-2012. A major way many of us understand the current moment is as an authoritarian assault on civic democratic government in the United States and indeed around the world. And it’s very much that. But it’s also an effort by those who have had a vast run-up in wealth over the last quarter century wanting to use that wealth to lock in that wealth by the acquisition of direct political power. This is absolutely the arc of the titans of Silicon Valley, almost all of whose leaders have now become either supporters of the oligarchic right or decided to make common cause with it in order to avoid having lawless political power attack them and their assets. This is overwhelmingly driven by the wealth generated by network effects lock-in, which produces vast levels of surplus wealth which look unbreakable by anything but government anti-trust intervention. It is sort of common knowledge, or common assumption, that the current mad dash for the commanding heights of AI represents the final goal of lock-in. Whatever one thinks of AI, it’s critical to see how tightly the Trump White House is allied with the tech companies in clearing the way for the current incumbents to dominate the future AI economy.

None of what I’ve said here is terribly new. But I note it as a way to place back at the center of our attention the insecurity of ultra-wealth as a core driver of our current politics, the tightly bound together mixture of insecurity and aggression which is at the center of everything.

Trump DOJ Defies Another Court Order in Abrego Garcia Case

GREENBELT, MD—If the Justice Department had brazenly defied a judge’s order a year ago the way it did again today in the Abrego Garcia case, it would have been a banner headline and the buzz of legal circles.

But 10 months into the Trump II presidency, it’s become all too normal for his Justice Department to refuse to comply with direct court orders, to engage in bad faith charades in court, and to dare judges to do anything about it.

The case of Abrego Garcia — the El Salvadoran man wrongfully deported to his home country in March in violation of a immigration judge’s order — may be where the Trump administration has been most persistently defiant for the longest time. It’s refusal to correct its error and bring him back sparked a constitutional clash that landed at the Supreme Court, and it only brought him back after indicting him for unrelated crimes.

You don’t have to get too deep into the weeds to understand the significance of what happened today.

The Trump administration wants to deport Abrego Garcia to somewhere in Africa, most recently Liberia. At one point Costa Rica was on the table, and Abrego Garcia is now willing to accept deportation there, but the Trump administration says Costa Rica has withdrawn its offer.

U.S. District Judge Paula Xinis wanted to get a definitive, binding account from the Trump administration on its claim that Costa Rica did in fact withdraw the offer, something more than just taking the administration’s word for it. Toward that end, and to try to head off another debacle in court, Xinis held a conference call with the parties on Monday ahead of today’s hearing and admonished DOJ lawyers.

She pointed out that the government had defied a separate order of hers in October — “no other way to sugar coat it,” she said — by putting on a witness who had no direct personal knowledge of the subject of his testimony. More than a single act of defiance, the administration had engaged in a pattern of producing non-responsive witnesses, Xinis said.

“It’s a strategy on your part on behalf of your client since day one,” she scolded the DOJ attorneys on the call.

This time Xinis tried to close off any avenues of escape for the government and to force it to bring a viable witness, not a cipher, with no involvement in the Abrego Garcia case, no knowledge of the negotiations with the third countries, and no authority to bind the government, as had happened on, by her count, three prior occasions.

So following the conference call, Xinis issued an order memorializing her instructions to DOJ lawyers. In short, Xinis ordered them to produce ICE official John E. Cantú to testify in person about the substance of a declaration he had already submitted in the case. His testimony would have to bind the Department of Homeland Security, she directed, and the government and DOJ lawyers were to make a good faith effort to prepare him to testify based on his personal knowledge and/or knowledge that he obtained from others.

Despite Xinis efforts, things went off the rails very quickly in court today.

When Deputy Assistant Attorney General Jonathan D. Guynn — questioning his own witness, I should emphasize — pointed Cantú to each of three different passages from his declaration and asked what they meant, Cantú was unable to say.

After the third dead end, Judge Xinis intervened: “Did you write this declaration?”

“With help from counsel,” Cantú said.

“When you say you don’t know what these words mean, were they just relayed to you?” Xinis asked.

“They were just relayed to me,” Cantú said, “then meeting over.”

Not surprisingly, things got rougher on cross examination by Abrego Garcia lawyer Sascha Rand. The gist of Cantú’s testimony was that he had had no prior involvement with the Abrego Garcia case before now and had only been in his current position since Nov. 3. He was told what to put in his declaration by a State Department attorney in a five-minute call and simultaneous email on Nov. 7. Most (though not all) of the portions of the declaration critical for today’s hearing were verbatim what he’d received from the State Department lawyers.

Rand asked Cantú if anyone had given him a copy of Xinis’ Monday order for him to testify. No, Cantú said.

Xinis jumped in again: “Did you have any conversations with anyone about my order that the witness would bind DHS?”

“No, your honor,” Cantú said.

She later asked if Cantú has any independent knowledge of whether anyone from State has been in touch with Costa Rica. No, Cantú said.

Cantú ultimately testified he had no independent knowledge about any of the critical sections of the declaration.

While Cantú was still on the stand, Judge Xinis declared, “The witness has zero information about the content of the declaration.” Catching herself, she turned to Cantú: “That’s no shade on you, Mr. Cantú. You’ve been candid and I appreciate that.”

Xinis proceeded to hear arguments from both sides over pending motions, but took no punitive action for the government’s conduct today. To this point, her modus operandi has been to stay focused on the more pressing issues related to Abrego Garcia’s detention and deportation.

As the four-hour hearing wound down, Judge Xinis again lamented Cantú’s testimony.

“Poor Mr. Cantú knew nothing about anything,” Xinish said. “Today was a zero, in my view.”

Abrego Garcia attorney Andrew Rossman agreed: “It’s been a parade of less-than-memorable witnesses, your honor.”

Fun Stunt to Promote ‘Pluribus’: An Ask Me Anything on Reddit With Carol Sturka

“Carol Sturka”, actress Rhea Seehorn’s fictional protagonist of the new Apple TV series Pluribus, is on Reddit right now — at 12n ET / 9am PT — doing an AMA in character. Sturka is a fantasy novelist, and Apple Books has an 11-page excerpt of her “new” novel Bloodsong of Wycaro. Unclear whether it’s Seehorn writing the in-character responses, but it’s definitely Seehorn in the confirmation photo. Reminiscent of some of the promotional fun Apple has had for Severance.

Both my wife and I are loving Pluribus so far. I highly recommend watching the first episode without even knowing the premise, if you can.

 ★ 

‘Pixar: The Early Days’ — Never-Before-Seen 1996 Interview With Steve Jobs

The Steve Jobs Archive:

To mark Toy Story’s 30th anniversary, we’re sharing a never-before-seen interview with Steve from November 22, 1996 — exactly one year after the film debuted in theaters.

Toy Story was the world’s first entirely computer-animated feature-length film. An instant hit with audiences and critics, it also transformed Pixar, which went public the week after its premiere. Buoyed by Toy Story ’s success, Pixar’s stock price closed at nearly double its initial offering, giving it a market valuation of approximately $1.5 billion and marking the largest IPO of 1995. The following year, Toy Story was nominated for three Academy Awards en route to winning a Special Achievement Oscar in March. In July, Pixar announced that it would close its television-commercial unit to focus primarily on feature films. By the time of the interview, the team had grown by 70 percent in less than a year; A Bug’s Life was in production; and behind the scenes, Steve was using his new leverage to renegotiate Pixar’s partnership with Disney.

Kind of a weird interview. The video quality is poor, and whoever was running the camera zoomed in and out awkwardly. It’s like ... just a VHS tape? But it’s also weird in a cool way to get a “new” Steve Jobs interview in 2025, and Jobs, as ever, is thoughtful and insightful. Well worth 23 minutes of your time.

There’s a particularly interesting bit at the end when Jobs discusses how Pixar was half a computer company (with extraordinary technology) and half a movie studio (with extraordinary filmmaking talent), but eventually they had to choose between the two industries for how to pay their employees to motivate them to remain at Pixar. The Hollywood way would be with contracts; the Silicon Valley way would be with stock options. Jobs chose the Silicon Valley path for Pixar.

 ★ 

Reflections on Progress Conference 2025

TL;DR

  • Check out videos of the conference talks, articles from well known writers, and a new Big Think special issue on progress.
  • The second annual progress conference was a great success. Progress Conference 2026 will be October 8th-11th in Berkeley. More info early next year!

This is the best conference I have ever been to. The attendees quality, the venue and the operations details are top notch. Will be a forever attendee from now on!

You will meet more excellent people and get to think about more challenging ideas in 48 hours than in any other environment/event.

If building a great culture is the really hard part, Progress Conference gives us a solid foundation to build on. The quality of ideas is extremely high and overflowing, but it’s the openness, honest discussions, and friendliness that makes it so energizing.

We’re about a month past the second annual Progress Conference. The 2025 conference was bigger than 2024: more days and more people, bringing together over 350 builders, academics, policy makers, investors, and writers who care about progress. Many attendees said it was yet again one of the best (or the best!) conference they had ever attended.

Attendees are extremely likely to recommend the conference to a friend or colleague, with an average rating of 9.3/10 and an excellent net promoter score of +83. We also received dozens of pages of feedback, even more than last year, giving us lots of ideas on how to keep improving the event.

It costs a lot of people’s time and money to get together. Why have an in-person conference in the age of video meetings, chatbots, and endless social media? In-person gatherings are necessary to build community and grow a movement. Here are the goals we had for the conference, and what people had to say about them:

Meet great people

It’s 2 days of living in the future. You meet people who are at the frontier of emerging fields and fill up on inspiration and ideas.

I really liked meeting the other attendees + spending time with them; very useful. A very orthogonal slice of people to those with whom I typically interact professionally, which makes it thought-provoking and high marginal value.

It was the best blend of academics/policy oriented folks/investors/entrepreneurs of all the conferences I’ve been to this year.

Catalyze new projects

Really really impressive work putting on such a great event. I came away with dozens of ideas, memories and contacts that I suspect will be paying dividends for many years!

Thanks for building this movement. The ideas and connections from these conferences have fueled my organization over the last year.

Be energized and inspired

THE BUZZ! Gosh I had so many wonderful conversations. It was amazing to be in a space filled with the greatest minds, working on such critical problems, without ugly ego. Still grinning from the experience.

If building a great culture is the really hard part, Progress Conference gives us a solid foundation to build on. The quality of ideas is extremely high and overflowing, but it’s the openness, honest discussions, and friendliness that makes it so energizing.

All I can say about the progress conference is that I always felt both welcome & certain I was the dumbest person in the room, which is an incredibly fortunate situation to be in. The conference sets the tone of my personal year: will I have done something meaningful enough to share next year?

Sharing ideas

Our other core goal for the event is to share ideas. You can watch videos of the talks, read articles and blog posts from the event, and browse the latest Big Think special issue on progress (just published!)

Videos of conference talks will be published over the next several weeks. We’ll post on the RPI YouTube channel (2025 specific playlist here) and on social media. Two plenary interviews are already available:

The buzz continued after the event, with many writers sharing ideas inspired by the conference. We’ve collected essays, blog posts, and social media commentary here. A few highlights:

  • Kevin Kohler on A Culture of Progress: “Mokyr would be a great speaker for the Progress Conference. Still, the agenda that brings together frontier entrepreneurs, science and tech policy leaders, and authors is more future-oriented and action-oriented than disinterested historical analysis. In that sense, the Progress Conference is not the annual meeting of Industrial Revolution scholars, rather it is a modern form of the ‘culture of growth’ that **Mokyr studied as part of the Industrial Revolution. Lighthaven is kind of an ‘enlightenment salon’ of the singularity. Loose networks of substacks are a modern take on the ‘Republic of Letters’.”
  • Ruy Teixeira on Democrats Could Learn a Lot from the Progress Movement: “Here are my impressions: 1. There was more political diversity than among abundance advocates who tend to lean a bit left and mostly aspire to be a faction within the Democratic Party. The progress movement/studies umbrella includes such people but also many who lean right and/or libertarian and don’t have much use for the Democrats. 2. There was an entrepreneurial, as opposed to technocratic, feel to the crowd and many of the discussions, not least because there were quite a few startup founders and VCs present. That’s not to say there weren’t quite a few policy wonks too, but the entrepreneurial vibe helped give a sense of people creating progress, rather than twisting policy dials to help it along. 3. There was a fierce and generalized techno-optimism to the crowd that far surpassed what you see in Democratic-oriented abundance circles where it tends to be focused on favored goals like clean energy. These are people who deeply believe in the potential of technological advance and the process of scientific discovery that leads to such advance—‘the endless frontier’ if you will.”
  • Zvi Mowshowitz on Dan Rothschild’s thread about our conference badges: “There’s basically no reason for everyone not to outright copy this format, forever.”

Big Think just published The Engine of Progress, exploring the people and ideas driving humanity forward. This special issue featuring original reporting and essays from many conference attendees and RPI fellows, and much more. Here are some of our favorite pieces:

Building a culture of progress

At the Roots of Progress Institute, our programs are dedicated to building the progress community and movement.

The annual progress conference is becoming a must-attend, central event for the progress community. But there is clearly much more room to grow: the conference sold out in June, five months before the event, and there were hundreds of interested, qualified people that we wish we’d had space to include.

As we plan out more events for 2026, we are thinking about how to include many more people in our RPI events, and how to gather smaller groups at functional events aimed at solving specific questions or kickstarting projects.

A personal reflection: I joined RPI this year to organize the second annual conference (and more events to come). It’s energizing to be around so many people who believe that progress is possible and worthwhile, and that the work can be done with taste, craft, and thoughtfulness. I became a father just a few weeks before this conference, and now I feel like I have a lot more skin in the game. We can build a future that we want our grandchildren to live in!


Save the date for Progress Conference 2026: October 8th-11th at Lighthaven in Berkeley, CA.

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Friday assorted links

1. Those semi-new service sector jobs how to get people to leave a cult.

2. What was Alice Munro actually writing about?  So often people are writing about themselves.

3. The New Yorker on Paul Collier and Britain.

4. Claims about LLMs and stock returns.

5. Live version of “I Hear a Symphony,” you can skip the thirty second intro.

6. The Harvard endowment’s single biggest public investment is now Bitcoin.

The post Friday assorted links appeared first on Marginal REVOLUTION.

       

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Q3 GDP Tracking: Close to 4%

From BofA:
Since our last weekly publication, 3Q GDP tracking remains unchanged at 2.8% q/q saar. [November 14th estimate]
emphasis added
From Goldman:
We boosted our Q3 GDP tracking estimate by 0.1pp to +3.8% (quarter-over-quarter annualized). Our Q3 domestic final sales estimate stands at +2.7%. [November 19th estimate]
GDPNowAnd from the Atlanta Fed: GDPNow
The GDPNow model estimate for real GDP growth (seasonally adjusted annual rate) in the third quarter of 2025 is 4.2 percent on November 21, unchanged from November 19 after rounding. After recent releases from the US Census Bureau, the US Bureau of Labor Statistics, and the National Association of Realtors, a slight decrease in the nowcast of third-quarter real personal consumption expenditures growth was offset by an increase in the nowcast of third-quarter real gross private domestic investment growth from 4.8 percent to 4.9 percent. [November 21st estimate]

Some second-order effects of unaffordable housing

This is one of the best, most interesting, and most important papers I have seen of late:

Housing affordability has declined sharply in recent decades, leading many younger generations to give up on homeownership. Using a calibrated life-cycle model matched to U.S. data, we project that the cohort born in the 1990s will reach retirement with a homeownership rate roughly 9.6 percentage points lower than that of their parents’ generation. The model also shows that as households’ perceived probability of attaining homeownership falls, they systematically shift their behavior: they consume more relative to their wealth, reduce work effort, and take on riskier investments. We show empirically that renters with relatively low wealth exhibit the same patterns. These responses compound over the life cycle, producing substantially greater wealth dispersion between those who retain hope of homeownership and those who give up. We propose a targeted subsidy that lifts the largest number of young renters above the “giving-up threshold.” This policy yields welfare gains that are 3.2 times those of a uniform transfer and 10.3 times those of a transfer targeted to the bottom 10% of the wealth distribution, while also increasing homeownership rate, raising work effort, and reducing reliance on the social safety net.

That is from Seung Hyeong Lee of Northwestern and Younggeun Yoo of University of Chicago.  Via the excellent Kevin Lewis.

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Glonzo Has Broken Republican Containment

On the left, construed broadly, we’re worried about things like the constitutional order. Meanwhile, on the right, well, there’s this (boldface mine):

Take the recent flare-up on the right over the online activity of Thomas Crooks, who attempted to kill Trump last year in Butler, Pennsylvania. Ever since the assassination attempt, Republicans have fumed over the FBI saying Crooks left behind only a slim online profile. That made it harder to blame Democrats or any kind of organized leftist network for the shooting. The frustration crested this past week as Tucker Carlson accused law enforcement agencies of systemically covering up, or outright lying to the public about, Crooks’s background.

The anger grew so intense that Kash Patel’s FBI launched a “rapid response” account on X, seemingly aimed in large part at rebutting Carlson. On X, Patel insisted the FBI took the investigation into Crooks seriously.

But as is often the case with conspiracists, a direct attack on a load-bearing belief is not necessarily going to convince proponents that the belief is wrong. On Benny Johnson’s show, Rep. Tim Burchett (R-Tenn.) argued that Crooks was likely “groomed” as part of some CIA mind-control experiment.

CIA mind control. Okey dokey. Don’t worry, it gets dumber:

On Friday, meanwhile, Carlson unveiled what he purported were copies of some of Crooks’s online profiles. The Carlson segment was soon echoed in follow-up reports by the New York Post and InfoWars personality Breanna Morello.

The reporting appears to be mostly nonsense. The Post, for example, makes much of Crooks having an account on the art social-network site DeviantArt to suggest he might have a “furry fetish,” in an attempt to link the assassination attempt to a broader belief in MAGA that crazed furries—people who dress up as animals—are out to kill Trump supporters. But even the Post concludes Crooks isn’t connected to any actual furry art. DeviantArt hosts all kinds of bad art, not just furries!

Complicating matters further, Megyn Kelly claimed Monday that the furry stuff was actually an FBI-planted distraction meant to obscure Carlson’s suggestions that the shooter was recruited by shadowy forces.

When the Republican Party loses power, I just don’t know what we do with this. This is absolutely bonkers, and when the loudest voices in the Republican firmament are this divorced from reality (‘It’s the furries wot done it guv!’), I just don’t know how we have a body politic at all. Because this isn’t a deranged ideology, like racism, it’s just a mass communicable psychotic break.

Links 11/20/25

Links for you. Science:

Bird Flu’s Back, And This Time Fewer People Are Keeping Tabs On It
Experts Warn The Government Shutdown Is Affecting You In A Major, Unexpected Way
Fat AND Sassy? A Three-Legged Lizard Really Can Have It All
A Fundamental ‘Constant’ of the Universe May Not Be Constant At All, Study Finds
Advanced 2.5 Million-Year-Old Tools May Rewrite Human History
arXiv Changes Rules After Getting Spammed With AI-Generated ‘Research’ Papers

Other:

Dick Durbin Says We Don’t Understand How the Senate Works. He’s both right and wrong about that, but in neither case does it work to his credit. (excellent)
What Did Men Do to Deserve This? (excellent, deceptive title)
The Future of Advertising Is AI Generated Ads That Are Directly Personalized to You (https://mikethemadbiologist.com/2025/08/11/ai-is-very-good-at-mediocrity/)
The Most Frustrating Thing About the Shutdown Cave
Inside the Trump family’s global crypto cash machine. The U.S. president’s family raked in more than $800 million from sales of crypto assets in the first half of 2025 alone, a Reuters examination found, on top of potentially billions more in unrealized “on paper” gains. Much of that cash has come from foreign sources as Donald Trump’s sons have touted their business on an international investor roadshow.
‘A Slap in the Face’: Federal Employees Feel Betrayed by Democrats’ Shutdown Cave
Booooooo! Boooooooo!!! (related post)
16 Thoughts On The Dem Shutdown Cave
Día de los Muertos in New Orleans
Josh Shapiro Is Done Lying Low
What’s It All About Then
D.C. Journalist’s Nightmare Song
I Don’t Like Being Lied To
THE REAL DEMOCRATIC DIVIDE IS BETWEEN FIGHTERS AND CAVERS
Senate Democrats Just Made a Huge Mistake
Donald Trump is Joe Biden now
Marjorie Taylor Greene flees Trump’s sinking ship
Eight Senate Dems Caved, and Caved Too Early
How to Be a Good Citizen When Your Country Does Bad Things
12 Reasons Why Trump, 79, May Be Losing The Plot
Six election results that didn’t make the headlines
Conservation groups blast Trump’s pick to lead key environmental agency
The Busiest “Rail Line” You’ve Never Heard Of Is In the Suburbs of Atlanta
Japan deploys the military to counter a surge in bear attacks
Trump’s Economy Is Looking More and More Like Saudi Arabia’s
Progressive group calls for Sen. Chuck Schumer to resign over shutdown vote
Taking GLP-1s to Get Ahead at Work
Did the Off-Year Elections Settle the Democrats’ Big Debate?
Master of the House: The Pelosi Paradox. How the Strongest Speaker Made Congress Weak
Democrats Have to Get Out of a Normal Democracy Mindset. By folding in the government shutdown in exchange for virtually nothing, eight Democratic senators aid Trump’s authoritarian takeover rather than oppose it

AI as Cyberattacker

From Anthropic:

In mid-September 2025, we detected suspicious activity that later investigation determined to be a highly sophisticated espionage campaign. The attackers used AI’s “agentic” capabilities to an unprecedented degree­—using AI not just as an advisor, but to execute the cyberattacks themselves.

The threat actor—­whom we assess with high confidence was a Chinese state-sponsored group—­manipulated our Claude Code tool into attempting infiltration into roughly thirty global targets and succeeded in a small number of cases. The operation targeted large tech companies, financial institutions, chemical manufacturing companies, and government agencies. We believe this is the first documented case of a large-scale cyberattack executed without substantial human intervention.

[…]

The attack relied on several features of AI models that did not exist, or were in much more nascent form, just a year ago:

  1. Intelligence. Models’ general levels of capability have increased to the point that they can follow complex instructions and understand context in ways that make very sophisticated tasks possible. Not only that, but several of their well-developed specific skills—in particular, software coding­—lend themselves to being used in cyberattacks.
  2. Agency. Models can act as agents—­that is, they can run in loops where they take autonomous actions, chain together tasks, and make decisions with only minimal, occasional human input.
  3. Tools. Models have access to a wide array of software tools (often via the open standard Model Context Protocol). They can now search the web, retrieve data, and perform many other actions that were previously the sole domain of human operators. In the case of cyberattacks, the tools might include password crackers, network scanners, and other security-related software.

Realtor.com Reports Median Listing Price Down Year-over-year

What this means: On a weekly basis, Realtor.com reports the year-over-year change in active inventory, new listings and median prices. On a monthly basis, they report total inventory. For October, Realtor.com reported active inventory was up 15.3% YoY, but still down 13.2% compared to the 2017 to 2019 same month levels. 

Here is their weekly report: Weekly Housing Trends: U.S. Market Update (Week Ending Nov. 15, 2025)
Active inventory climbed 12.6% year over year

The number of homes active on the market climbed 12.6% year-over-year, as the streak of annual gains stretched past two years in length. There were about 1.1 million homes for sale last week, marking the 29th week in a row over the million-listing threshold. Active inventory is growing due to both new listings hitting the market, but mostly listings taking longer to sell in this weak 2025 sales year.

New listings—a measure of sellers putting homes up for sale—rose 1.7% year over year

New listings edged up on an annual basis, the second straight week of gains and a return to more typical levels after last week’s surge. Mortgage rates held in the low 6.2s range last week the low-6% range, which may be enticing some homeowners to make a move.

The median listing price fell 0.4% year-over-year

he median list price dropped compared to the same week one year ago. Adjusting for home size, price per square foot fell 1.0% year-over-year, dropping for the 11th consecutive week. Price per square foot grew steadily for almost two years, but the weak sales activity has finally caught up and shaken underlying home values despite stable prices.

Viewpoint diversity on swastikas and vaccines: one close call and one further descent

The canary was revived after being found gasping for breath in the coal mine...

The Washington Post reports this morning:

In reversal, Coast Guard again classifies swastikas, nooses as hate symbols By Hari Raj and Victoria Bisset
 

"The U.S. Coast Guard issued a new, more stringent policy on hate symbols including the swastika Thursday night, prohibiting “divisive or hate symbols or flags.”  


 Here's the WaPo's story from yesterday: 

U.S. Coast Guard will no longer classify swastikas, nooses as hate symbols 

"Though the Coast Guard is not part of the Defense Department, the service has been reworking its policies to align with the Trump administration’s changing tolerances for hazing and harassment within the U.S. military. In September, Defense Secretary Pete Hegseth directed a review and overhaul of those policies, calling the military’s existing standards “overly broad” and saying they jeopardize troops’ combat readiness." 

########

But viewpoint diversity is alive and well at the CDC: see this from Statnews

Under RFK Jr., CDC reverses course on stance that vaccines don’t cause autism
It’s the latest move by Kennedy and his allies to raise doubts about childhood shots  By Chelsea Cirruzzo, Helen Branswell, and Daniel PayneNov 

"The Centers for Disease Control and Prevention on Wednesday publicly reversed its stance that vaccines do not cause autism, over the objections of career staff and counter to years of scientific evidence." 


Systems design 3: LLMs and the semantic revolution

Long ago in the 1990s when I was in high school, my chemistry+physics teacher pulled me aside. "Avery, you know how the Internet works, right? I have a question."

I now know the correct response to that was, "Does anyone really know how the Internet works?" But as a naive young high schooler I did not have that level of self-awareness. (Decades later, as a CEO, that's my answer to almost everything.)

Anyway, he asked his question, and it was simple but deep. How do they make all the computers connect?

We can't even get the world to agree on 60 Hz vs 50 Hz, 120V vs 240V, or which kind of physical power plug to use. Communications equipment uses way more frequencies, way more voltages, way more plug types. Phone companies managed to federate with each other, eventually, barely, but the ring tones were different everywhere, there was pulse dialing and tone dialing, and some of them still charge $3/minute for international long distance, and connections take a long time to establish and humans seem to be involved in suspiciously many places when things get messy, and every country has a different long-distance dialing standard and phone number format.

So Avery, he said, now they're telling me every computer in the world can connect to every other computer, in milliseconds, for free, between Canada and France and China and Russia. And they all use a single standardized address format, and then you just log in and transfer files and stuff? How? How did they make the whole world cooperate? And who?

When he asked that question, it was a formative moment in my life that I'll never forget, because as an early member of what would be the first Internet generation… I Had Simply Never Thought of That.

I mean, I had to stop and think for a second. Wait, is protocol standardization even a hard problem? Of course it is. Humans can't agree on anything. We can't agree on a unit of length or the size of a pint, or which side of the road to drive on. Humans in two regions of Europe no farther apart than Thunder Bay and Toronto can't understand each other's speech. But this Internet thing just, kinda, worked.

"There's… a layer on top," I uttered, unsatisfyingly. Nobody had taught me yet that the OSI stack model existed, let alone that it was at best a weak explanation of reality.

"When something doesn't talk to something else, someone makes an adapter. Uh, and some of the adapters are just programs rather than physical things. It's not like everyone in the world agrees. But as soon as one person makes an adapter, the two things come together."

I don't think he was impressed with my answer. Why would he be? Surely nothing so comprehensively connected could be engineered with no central architecture, by a loosely-knit cult of mostly-volunteers building an endless series of whimsical half-considered "adapters" in their basements and cramped university tech labs. Such a creation would be a monstrosity, just as likely to topple over as to barely function.

I didn't try to convince him, because honestly, how could I know? But the question has dominated my life ever since.

When things don't connect, why don't they connect? When they do, why? How? …and who?

Postel's Law

The closest clue I've found is this thing called Postel's Law, one of the foundational principles of the Internet. It was best stated by one of the founders of the Internet, Jon Postel. "Be conservative in what you send, and liberal in what you accept."

What it means to me is, if there's a standard, do your best to follow it, when you're sending. And when you're receiving, uh, assume the best intentions of your counterparty and do your best and if that doesn't work, guess.

A rephrasing I use sometimes is, "It takes two to miscommunicate." Communication works best and most smoothly if you have a good listener and a clear speaker, sharing a language and context. But it can still bumble along successfully if you have a poor speaker with a great listener, or even a great speaker with a mediocre listener. Sometimes you have to say the same thing five ways before it gets across (wifi packet retransmits), or ask way too many clarifying questions, but if one side or the other is diligent enough, you can almost always make it work.

This asymmetry is key to all high-level communication. It makes network bugs much less severe. Without Postel's Law, triggering a bug in the sender would break the connection; so would triggering a bug in the receiver. With Postel's Law, we acknowledge from the start that there are always bugs and we have twice as many chances to work around them. Only if you trigger both sets of bugs at once is the flaw fatal.

…So okay, if you've used the Internet, you've probably observed that fatal connection errors are nevertheless pretty common. But that misses how incredibly much more common they would be in a non-Postel world. That world would be the one my physics teacher imagined, where nothing ever works and it all topples over.

And we know that's true because we've tried it. Science! Let us digress.

XML

We had the Internet ("OSI Layer 3") mostly figured out by the time my era began in the late 1900s, but higher layers of the stack still had work to do. It was the early days of the web. We had these newfangled hypertext ("HTML") browsers that would connect to a server, download some stuff, and then try their best to render it.

Web browsers are and have always been an epic instantiation of Postel's Law. From the very beginning, they assumed that the server (content author) had absolutely no clue what they were doing and did their best to apply some kind of meaning on top, despite every indication that this was a lost cause. List items that never end? Sure. Tags you've never heard of? Whatever. Forgot some semicolons in your javascript? I'll interpolate some. Partially overlapping italics and bold? Leave it to me. No indication what language or encoding the page is in? I'll just guess.

The evolution of browsers gives us some insight into why Postel's Law is a law and not just, you know, Postel's Advice. The answer is: competition. It works like this. If your browser interprets someone's mismash subjectively better than another browser, your browser wins.

I think economists call this an iterated prisoner's dilemma. Over and over, people write web pages (defect) and browsers try to render them (defect) and absolutely nobody actually cares what the HTML standard says (stays loyal). Because if there's a popular page that's wrong and you render it "right" and it doesn't work? Straight to jail.

(By now almost all the evolutionary lines of browsers have been sent to jail, one by one, and the HTML standard is effectively whatever Chromium and Safari say it is. Sorry.)

This law offends engineers to the deepness of their soul. We went through a period where loyalists would run their pages through "validators" and proudly add a logo to the bottom of their page saying how valid their HTML was. Browsers, of course, didn't care and continued to try their best.

Another valiant effort was the definition of "quirks mode": a legacy rendering mode meant to document, normalize, and push aside all the legacy wonko interpretations of old web pages. It was paired with a new, standards-compliant rendering mode that everyone was supposed to agree on, starting from scratch with an actual written spec and tests this time, and public shaming if you made a browser that did it wrong. Of course, outside of browser academia, nobody cares about the public shaming and everyone cares if your browser can render the popular web sites, so there are still plenty of quirks outside quirks mode. It's better and it was well worth the effort, but it's not all the way there. It never can be.

We can be sure it's not all the way there because there was another exciting development, HTML Strict (and its fancier twin, XHTML), which was meant to be the same thing, but with a special feature. Instead of sending browsers to jail for rendering wrong pages wrong, we'd send page authors to jail for writing wrong pages!

To mark your web page as HTML Strict was a vote against the iterated prisoner's dilemma and Postel's Law. No, your vote said. No more. We cannot accept this madness. We are going to be Correct. I certify this page is correct. If it is not correct, you must sacrifice me, not all of society. My honour demands it.

Anyway, many page authors were thus sacrificed and now nobody uses HTML Strict. Nobody wants to do tech support for a web page that asks browsers to crash when parsing it, when you can just… not do that.

Excuse me, the above XML section didn't have any XML

Yes, I'm getting to that. (And you're soon going to appreciate that meta joke about schemas.)

In parallel with that dead branch of HTML, a bunch of people had realized that, more generally, HTML-like languages (technically SGML-like languages) had turned out to be a surprisingly effective way to build interconnected data systems.

In retrospect we now know that the reason for HTML's resilience is Postel's Law. It's simply easier to fudge your way through parsing incorrect hypertext, than to fudge your way through parsing a Microsoft Word or Excel file's hairball of binary OLE streams, which famously even Microsoft at one point lost the knowledge of how to parse. But, that Postel's Law connection wasn't really understood at the time.

Instead we had a different hypothesis: "separation of structure and content." Syntax and semantics. Writing software to deal with structure is repetitive overhead, and content is where the money is. Let's automate away the structure so you can spend your time on the content: semantics.

We can standardize the syntax with a single Extensible Markup Language (XML). Write your content, then "mark it up" by adding structure right in the doc, just like we did with plaintext human documents. Data, plus self-describing metadata, all in one place. Never write a parser again!

Of course, with 20/20 hindsight (or now 2025 hindsight), this is laughable. Yes, we now have XML parser libraries. If you've ever tried to use one, you will find they indeed produce parse trees automatically… if you're lucky. If you're not lucky, they produce a stream of "tokens" and leave it to you to figure out how to arrange it in a tree, for reasons involving streaming, performance, memory efficiency, and so on. Basically, if you use XML you now have to deeply care about structure, perhaps more than ever, but you also have to include some giant external parsing library that, left in its normal mode, might spontaneously start making a lot of uncached HTTP requests that can also exploit remote code execution vulnerabilities haha oops.

If you've ever taken a parser class, or even if you've just barely tried to write a parser, you'll know the truth: the value added by outsourcing parsing (or in some cases only tokenization) is not a lot. This is because almost all the trouble of document processing (or compiling) is the semantic layer, the part where you make sense of the parse tree. The part where you just read a stream of characters into a data structure is the trivial, well-understood first step.

Now, semantics is where it gets interesting. XML was all about separating syntax from semantics. And they did some pretty neat stuff with that separation, in a computer science sense. XML is neat because it's such a regular and strict language that you can completely validate the syntax (text and tags) without knowing what any of the tags mean or which tags are intended to be valid at all.

…aha! Did someone say validate?! Like those old HTML validators we talked about? Oh yes. Yes! And this time the validation will be completely strict and baked into every implementation from day 1. And, the language syntax itself will be so easy and consistent to validate (unlike SGML and HTML, which are, in all fairness, bananas) that nobody can possibly screw it up.

A layer on top of this basic, highly validatable XML, was a thing called XML Schemas. These were documents (mysteriously not written in XML) that described which tags were allowed in which places in a certain kind of document. Not only could you parse and validate the basic XML syntax, you could also then validate its XML schema as a separate step, to be totally sure that every tag in the document was allowed where it was used, and present if it was required. And if not? Well, straight to jail. We all agreed on this, everyone. Day one. No exceptions. Every document validates. Straight to jail.

Anyway XML schema validation became an absolute farce. Just parsing or understanding, let alone writing, the awful schema file format is an unpleasant ordeal. To say nothing of complying with the schema, or (heaven forbid) obtaining a copy of someone's custom schema and loading it into the validator at the right time.

The core XML syntax validation was easy enough to do while parsing. Unfortunately, in a second violation of Postel's Law, almost no software that outputs XML runs it through a validator before sending. I mean, why would they, the language is highly regular and easy to generate and thus the output is already perfect. …Yeah, sure.

Anyway we all use JSON now.

JSON

Whoa, wait! I wasn't done!

This is the part where I note, for posterity's sake, that XML became a decade-long fad in the early 2000s that justified billions of dollars of software investment. None of XML's technical promises played out; it is a stain on the history of the computer industry. But, a lot of legacy software got un-stuck because of those billions of dollars, and so we did make progress.

What was that progress? Interconnection.

Before the Internet, we kinda didn't really need to interconnect software together. I mean, we sort of did, like cut-and-pasting between apps on Windows or macOS or X11, all of which were surprisingly difficult little mini-Postel's Law protocol adventures in their own right and remain quite useful when they work (except "paste formatted text," wtf are you people thinking). What makes cut-and-paste possible is top-down standards imposed by each operating system vendor.

If you want the same kind of thing on the open Internet, ie. the ability to "copy" information out of one server and "paste" it into another, you need some kind of standard. XML was a valiant effort to create one. It didn't work, but it was valiant.

Whereas all that money investment did work. Companies spent billions of dollars to update their servers to publish APIs that could serve not just human-formatted HTML, but also something machine-readable. The great innovation was not XML per se, it was serving data over HTTP that wasn't always HTML. That was a big step, and didn't become obvious until afterward.

The most common clients of HTTP were web browsers, and web browsers only knew how to parse two things: HTML and javascript. To a first approximation, valid XML is "valid" (please don't ask the validator) HTML, so we could do that at first, and there were some Microsoft extensions. Later, after a few billions of dollars, true standardized XML parsing arrived in browsers. Similarly, to a first approximation, valid JSON is valid javascript, which woo hoo, that's a story in itself (you could parse it with eval(), tee hee) but that's why we got here.

JSON (minus the rest of javascript) is a vastly simpler language than XML. It's easy to consistently parse (other than that pesky trailing comma); browsers already did. It represents only (a subset of) the data types normal programming languages already have, unlike XML's weird mishmash of single attributes, multiply occurring attributes, text content, and CDATA. It's obviously a tree and everyone knows how that tree will map into their favourite programming language. It inherently works with unicode and only unicode. You don't need cumbersome and duplicative "closing tags" that double the size of every node. And best of all, no guilt about skipping that overcomplicated and impossible-to-get-right schema validator, because, well, nobody liked schemas anyway so nobody added them to JSON (almost).

Today, if you look at APIs you need to call, you can tell which ones were a result of the $billions invested in the 2000s, because it's all XML. And you can tell which came in the 2010s and later after learning some hard lessons, because it's all JSON. But either way, the big achievement is you can call them all from javascript. That's pretty good.

(Google is an interesting exception: they invented and used protobuf during the same time period because they disliked XML's inefficiency, they did like schemas, and they had the automated infrastructure to make schemas actually work (mostly, after more hard lessons). But it mostly didn't spread beyond Google… maybe because it's hard to do from javascript.)

Blockchain

The 2010s were another decade of massive multi-billion dollar tech investment. Once again it was triggered by an overwrought boondoggle technology, and once again we benefited from systems finally getting updated that really needed to be updated.

Let's leave aside cryptocurrencies (which although used primarily for crime, at least demonstrably have a functioning use case, ie. crime) and look at the more general form of the technology.

Blockchains in general make the promise of a "distributed ledger" which allows everyone the ability to make claims and then later validate other people's claims. The claims that "real" companies invested in were meant to be about manufacturing, shipping, assembly, purchases, invoices, receipts, ownership, and so on. What's the pattern? That's the stuff of businesses doing business with other businesses. In other words, data exchange. Data exchange is exactly what XML didn't really solve (although progress was made by virtue of the dollars invested) in the previous decade.

Blockchain tech was a more spectacular boondoggle than XML for a few reasons. First, it didn't even have a purpose you could explain. Why do we even need a purely distributed system for this? Why can't we just trust a third party auditor? Who even wants their entire supply chain (including number of widgets produced and where each one is right now) to be visible to the whole world? What is the problem we're trying to solve with that?

…and you know there really was no purpose, because after all the huge investment to rewrite all that stuff, which was itself valuable work, we simply dropped the useless blockchain part and then we were fine. I don't think even the people working on it felt like they needed a real distributed ledger. They just needed an updated ledger and a budget to create one. If you make the "ledger" module pluggable in your big fancy supply chain system, you can later drop out the useless "distributed" ledger and use a regular old ledger. The protocols, the partnerships, the databases, the supply chain, and all the rest can stay the same.

In XML's defense, at least it was not worth the effort to rip out once the world came to its senses.

Another interesting similarity between XML and blockchains was the computer science appeal. A particular kind of person gets very excited about validation and verifiability. Both times, the whole computer industry followed those people down into the pits of despair and when we finally emerged… still no validation, still no verifiability, still didn't matter. Just some computers communicating with each other a little better than they did before.

LLMs

In the 2020s, our industry fad is LLMs. I'm going to draw some comparisons here to the last two fads, but there are some big differences too.

One similarity is the computer science appeal: so much math! Just the matrix sizes alone are a technological marvel the likes of which we have never seen. Beautiful. Colossal. Monumental. An inspiration to nerds everywhere.

But a big difference is verification and validation. If there is one thing LLMs absolutely are not, it's verifiable. LLMs are the flakiest thing the computer industry has ever produced! So far. And remember, this is the industry that brought you HTML rendering.

LLMs are an almost cartoonishly amplified realization of Postel's Law. They write human grammar perfectly, or almost perfectly, or when they're not perfect it's a bug and we train them harder. And, they can receive just about any kind of gibberish and turn it into a data structure. In other words, they're conservative in what they send and liberal in what they accept.

LLMs also solve the syntax problem, in the sense that they can figure out how to transliterate (convert) basically any file syntax into any other. Modulo flakiness. But if you need a CSV in the form of a limerick or a quarterly financial report formatted as a mysql dump, sure, no problem, make it so.

In theory we already had syntax solved though. XML and JSON did that already. We were even making progress interconnecting old school company supply chain stuff the hard way, thanks to our nominally XML- and blockchain- investment decades. We had to do every interconnection by hand – by writing an adapter – but we could do it.

What's really new is that LLMs address semantics. Semantics are the biggest remaining challenge in connecting one system to another. If XML solved syntax, that was the first 10%. Semantics are the last 90%. When I want to copy from one database to another, how do I map the fields? When I want to scrape a series of uncooperative web pages and turn it into a table of products and prices, how do I turn that HTML into something structured? (Predictably microformats, aka schemas, did not work out.) If I want to query a database (or join a few disparate databases!) using some language that isn't SQL, what options do I have?

LLMs can do it all.

Listen, we can argue forever about whether LLMs "understand" things, or will achieve anything we might call intelligence, or will take over the world and eradicate all humans, or are useful assistants, or just produce lots of text sludge that will certainly clog up the web and social media, or will also be able to filter the sludge, or what it means for capitalism that we willingly invented a machine we pay to produce sludge that we also pay to remove the sludge.

But what we can't argue is that LLMs interconnect things. Anything. To anything. Whether you like it or not. Whether it's bug free or not (spoiler: it's not). Whether it gets the right answer or not (spoiler: erm…).

This is the thing we have gone through at least two decades of hype cycles desperately chasing. (Three, if you count java "write once run anywhere" in the 1990s.) It's application-layer interconnection, the holy grail of the Internet.

And this time, it actually works! (mostly)

The curse of success

LLMs aren't going away. Really we should coin a term for this use case, call it "b2b AI" or something. For this use case, LLMs work. And they're still getting better and the precision will improve with practice. For example, imagine asking an LLM to write a data translator in some conventional programming language, instead of asking it to directly translate a dataset on its own. We're still at the beginning.

But, this use case, which I predict is the big one, isn't what we expected. We expected LLMs to write poetry or give strategic advice or whatever. We didn't expect them to call APIs and immediately turn around and use what it learned to call other APIs.

After 30 years of trying and failing to connect one system to another, we now have a literal universal translator. Plug it into any two things and it'll just go, for better or worse, no matter how confused it becomes. And everyone is doing it, fast, often with a corporate mandate to do it even faster.

This kind of scale and speed of (successful!) rollout is unprecedented, even by the Internet itself, and especially in the glacially slow world of enterprise system interconnections, where progress grinds to a halt once a decade only to be finally dislodged by the next misguided technology wave. Nobody was prepared for it, so nobody was prepared for the consequences.

One of the odd features of Postel's Law is it's irresistible. Big Central Infrastructure projects rise and fall with funding, but Postel's Law projects are powered by love. A little here, a little there, over time. One more person plugging one more thing into one more other thing. We did it once with the Internet, overcoming all the incompatibilities at OSI layers 1 and 2. It subsumed, it is still subsuming, everything.

Now we're doing it again at the application layer, the information layer. And just like we found out when we connected all the computers together the first time, naively hyperconnected networks make it easy for bad actors to spread and disrupt at superhuman speeds. We had to invent firewalls, NATs, TLS, authentication systems, two-factor authentication systems, phishing-resistant two-factor authentication systems, methodical software patching, CVE tracking, sandboxing, antivirus systems, EDR systems, DLP systems, everything. We'll have to do it all again, but faster and different.

Because this time, it's all software.

The Firefly and the Pulsar

The Firefly and the Pulsar

We’ve now had humans in space for 25 continuous years, a feat that made the news last week and one that must have caused a few toasts to be made aboard the International Space Station. This is a marker of sorts, and we’ll have to see how long it will continue, but the notion of a human presence in orbit will gradually seem to be as normal as a permanent presence in, say, Antarctica. But what a short time 25 years is when weighed against our larger ambitions, which now take in Mars and will continue to expand as our technologies evolve.

We’ve yet to claim even a century of space exploration, what with Gagarin’s flight occurring only 65 years ago, and all of this calls to mind how cautiously we should frame our assumptions about civilizations that may be far older than ourselves. We don’t know how such species would develop, but it’s chastening to realize that when SETI began, it was utterly natural to look for radio signals, given how fast they travel and how ubiquitous they were on Earth.

Today, though, things have changed significantly since Frank Drake’s pioneering work at Green Bank. We’re putting out a lot less energy in the radio frequency bands, as technology gradually shifted toward cable television and Internet connectivity. The discovery paradigm needs to grow lest we become anthropocentric in our searches, and the hunt for technosignatures reflects the realization that we may not know what to expect from alien technologies, but if we see one in action, we may at least be able to realize that it is artificial.

And if we receive a message, what then? We’ve spent a lot of time working on how information in a SETI signal could be decoded, and have coded messages of our own, as for example the famous Hercules message of 1974. Sent from Arecibo, the message targeted the Hercules cluster some 25,000 light years away, and was obviously intended as a demonstration of what might later develop with nearby stars if we ever tried to communicate with them.

But whether we’re looking at data from radio telescopes, optical surveys of entire galaxies or even old photographic plates, that question of anthropocentrism still holds. Digging into it in a provocative way is a new paper from Cameron Brooks and Sara Walker (Arizona State) and colleagues. In a world awash with papers on SETI and Fermi and our failure to detect traces of ETI, it’s a bit of fresh air. Here the question becomes one of recognition, and whether or not we would identify a signal as alien if we saw it, putting aside the question of deciphering it. Interested in structure and syntax in non-human communication, the authors start here on Earth with the common firefly.

If that seems an odd choice, consider that this is a non-human entity that uses its own methods to communicate with its fellow creatures. The well studied firefly is known to produce its characteristic flashes in ways that depend upon its specific species. This turns out to be useful in mating season when there are two imperatives: 1) to find a mate of the same species in an environment containing other firefly species, and 2) to minimize the possibility of being identified by a predator. All this is necessary because according to one recent source, there are over 2600 species in the world, with more still being discovered. The need is to communicate against a very noisy background.

Image: Can the study of non-human communication help us design new SETI strategies? In this image, taken in the Great Smoky Mountains National Park, we see the flash pattern of Photinus carolinus, a sequence of five to eight distinct flashes, followed by an eight-second pause of darkness, before the cycle repeats. Initially, the flashing may appear random, but as more males join in, their rhythms align, creating a breathtaking display of pulsating light throughout the forest. Credit: National Park Service.

Fireflies use a form of signaling, one that is a recognized field of study within entomology, well analyzed and considered as a mode of communications between insects that enhances species reproduction as well as security. The evolution of these firefly flash sequences has been simulated over multiple generations. If fireflies can communicate against their local background using optical flashes, how would that communication be altered with an astrophysical background, and what can this tell us about structure and detectability?

Inspired by the example of the firefly, what Brooks and Walker are asking is whether we can identify structural properties within such signals without recourse to semantic content, mathematical symbols or other helpfully human triggers for comprehension. In the realm of optical SETI, for example, how much would an optical signal have to contrast with the background stars in its direction so that it becomes distinguishable as artificial?

This is a question for optical SETI, but the principles the authors probe are translatable to other contexts where discovery is made against various backgrounds. The paper constructs a model of an evolved signal that stands out against the background of the natural signals generated by pulsars. Pulsars are a useful baseline because they look so artifical. Their 1967 discovery was met with a flurry of interest because they resembled nothing we had seen in nature up to that time. Pulsars produce a bright signal that is easy to detect at interstellar distances.

If pulsars are known to be natural phenomena, what might have told us if they were not? Looking for the structure of communications is highly theoretical work, but no more so than the countless papers discussing the Fermi question or explaining why SETI has found no sign of ETI. The authors pose the issue this way:

…this evolutionary problem faced by fireflies in densely packed swarming environments provides an opportunity to study how an intelligent species might evolve signals to identify its presence against a visually noisy astrophysical environment, using a non-human species as the model system of interest.

The paper is put together using data from 3734 pulsars from the Australia National Telescope Facility (ATNF). The pulse profiles of these pulsars are the on-off states similar to the firefly flashes. The goal is to produce a series of optical flashes that is optimized to communicate against background sources, taking into account similarity to natural phenomena and trade-offs in energy cost.

Thus we have a thought experiment in ‘structure-driven’ principles. More from the paper:

Our aim is to motivate approaches that reduce anthropocentric bias by drawing on different communicative strategies observed within Earth’s biosphere. Such perspectives broaden the range of ETI forms we can consider and leverage a more comprehensive understanding of life on Earth to better conceptualize the possible modes of extraterrestrial communication… Broadening the foundations of our communication model, by drawing systematically from diverse taxa and modalities, would yield a more faithful representation of Earth’s biocommunication and increase the likelihood of success, with less anthropocentric searches, and more insights into deeper universalities of communication between species.

The authors filter the initial dataset down to a subset of pulsars within 5 kpc of Earth and compute mean period and duty cycle for each. In other words, they incorporate the rotation of the pulsar and the fraction in which each pulse is visible. They compute a ‘cost function’ analyzing similarity cost – how similar is the artificial signal to the background – and an energy cost, meaning the less frequent the pulses, the less energy expended. The terms are a bit confusing, but similarity cost refers to how much an artificial signal resembles a background pulsar signal, while energy cost refers to how long the signal is ‘on.’

So if you’re an ETI trying to stand out against a background field of pulsars, the calculations here produce a signal background period of 24.704 seconds and a duty cycle of ~0.004 (meaning that the signal is ‘on’ for 0.4 percent of the period). Such signals appear at the edge of the pulsar distribution – they would be signals that stand out by being relatively rare and also brief in contrast to the rest of the pulsar population. They would, in other words, serve as the optimal beacon for ETI attempting to communicate.

I spare you the math, which in any case is beyond my pay grade. But the point is this: A civilization trying to get our attention while broadcasting from a pulsar background could do so with a signal that has a long pulsar period (tens of seconds) and a low duty cycle. This would be sufficient to produce a signal that becomes conspicuous to observers. Now we can think about generalizing all this. The pulsar background is one of many out of which a possible signal could be detected, and the principles can be extended beyond the optical into other forms of SETI. The broad picture is identifying a signal against a background, proceeding by identifying the factors specific to each background studied.

Any time we are trying to distinguish an intentional signal, then, we need to optimize – in any signaling medium – the traits leading to detectability. Signals can be identified by their structural properties without any conception of their content as long as they rise above the noise of the background. Back to the fireflies: The paper is pointing out that non-human signaling can operate solely on a structure designed to stand out against background noise, with no semantic content. An effective signal need not resemble human thought.

Remember, this is more or less a thought experiment, but it is one that suggests that cross-disciplinary research may yield interesting ways of interpreting astrophysical data in search of signs of artificiality. On the broader level, the concept reminds us how to isolate a signal from whatever background we are studying and identify it as artificial through factors like duty cycle and period. The choice of background varies with the type of SETI being practiced. Ponder infrared searches for waste heat against various stellar backgrounds or more ‘traditional’ searches needing to distinguish various kinds of RF phenomena.

It will be interesting to see how the study of non-human species on Earth contributes to future detectability methods. Are there characteristics of dolphin communication that can be mined for insights? Examples in the song of birds?

The paper is Brooks et al., “A Firefly-inspired Model for Deciphering the Alien,” available as a preprint.

Not in our name

Black and white photo of a line of people marching on a city street holding signs protesting against the draft for the Vietnam War.

The gravest of all decisions, to go to war, happens without the consent of the people. This is a great flaw in democracy

- by Vincenza Falletti

Read on Aeon

Attack, defend, pursue—the Space Force’s new naming scheme foretells new era

A little more than a century ago, the US Army Air Service came up with a scheme for naming the military’s multiplying fleet of airplanes.

The 1924 aircraft designation code produced memorable names like the B-17, A-26, B-29, and P-51—B for bomber, A for attack, and P for pursuit—during World War II. The military later changed the prefix for pursuit aircraft to F for fighter, leading to recognizable modern names like the F-15 and F-16.

Now, the newest branch of the military is carving its own path with a new document outlining how the Space Force, which can trace its lineage back to the Army Air Service, will name and designate its “weapon systems” on the ground and in orbit. Ars obtained a copy of the document, first written in 2023 and amended in 2024.

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Thinkie: Influence Diagram

Pattern: you have a big, complicated system that’s acting up & you’d like to regain influence over it

Transformation: diagram the effects you observe in the system & their influence on each other

Thinkie: Influence Diagram follows from Thinkie: Separate Observation From Judgement. We aren’t rushing to take action. More probably we have stepped back from t…

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Nano Banana Pro does Marginal Revolution

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Via Rohit Krishnan.

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My very fun Conversation with Blake Scholl

Here is the audio, video, and transcript.  This was at a live event (the excellent Roots of Progress conference), so it is only about forty minutes, shorter than usual.  Here is the episode summary:

Blake Scholl is one of the leading figures working to bring back civilian supersonic flight. As the founder and CEO of Boom Supersonic, he’s building a new generation of supersonic aircraft and pushing for the policies needed to make commercial supersonic travel viable again. But he’s equally as impressive as someone who thinks systematically about improving dysfunction—whether it’s airport design, traffic congestion, or defense procurement—and sees creative solutions to problems everyone else has learned to accept.

Tyler and Blake discuss why airport terminals should be underground, why every road needs a toll, what’s wrong with how we board planes, the contrasting cultures of Amazon and Groupon, why Concorde and Apollo were impressive tech demos but terrible products, what Ayn Rand understood about supersonic transport in 1957, what’s wrong with aerospace manufacturing, his heuristic when confronting evident stupidity, his technique for mastering new domains, how LLMs are revolutionizing regulatory paperwork, and much more.

Excerpt:

COWEN: There’s plenty about Boom online and in your interviews, so I’d like to take some different tacks here. This general notion of having things move more quickly, I’m a big fan of that. Do you have a plan for how we could make moving through an airport happen more quickly? You’re in charge. You’re the dictator. You don’t have to worry about bureaucratic obstacles. You just do it.

SCHOLL: I think about this in the shower like every day. There is a much better airport design that, as best I can tell, has never been built. Here’s the idea: You should put the terminals underground. Airside is above ground. Terminals are below ground. Imagine a design with two runways. There’s an arrival runway, departure runway. Traffic flows from arrival runway to departure runway. You don’t need tugs. You can delete a whole bunch of airport infrastructure.

Imagine you pull into a gate. The jetway is actually an escalator that comes up from underneath the ground. Then you pull forward, so you can delete a whole bunch of claptrap that is just unnecessary. The terminal underground should have skylights so it can still be incredibly beautiful. If you model fundamentally the thing on a crossbar switch, there are a whole bunch of insights for how to make it radically more efficient. Sorry. This is a blog post I want to write one day. Actually, it’s an airport I want to build.

And;

COWEN: I’m at the United desk. I have some kind of question. There’s only two or three people in front of me, but it takes forever. I notice they’re just talking back and forth to the assistant. They’re discussing the weather or the future prospects for progress, total factor productivity. I don’t know. I’m frustrated. How can we make that process faster? What’s going wrong there?

SCHOLL: The thing I most don’t understand is why it requires so many keystrokes to check into a hotel room. What are they writing?

What are they writing?

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How ASML Got EUV

I am pleased to cross-post this piece with Factory Settings, the new Substack from IFP. Factory Settings will feature essays from the inaugural CHIPS team about why CHIPS succeeded, where it stumbled, and its lessons for state capacity and industrial policy. You can subscribe here.

An EUV tool at Lawrence Livermore National Lab in the 1990s.

Moore’s Law, the observation that the number of transistors on an integrated circuit tends to double every two years, has progressed in large part thanks to advances in lithography: techniques for creating microscopic patterns on silicon wafers. The steadily shrinking size of transistors — from around 10,000 nanometers in the early 1970s to around 20-60 nanometers today — has been made possible by developing lithography methods capable of patterning smaller and smaller features.1 The most recent advance in lithography is the adoption of Extreme Ultraviolet (EUV) lithography, which uses light at a wavelength of 13.5 nanometers to create patterns on chips.

EUV lithography machines are famously made by just a single firm, ASML in the Netherlands, and determining who has access to the machines has become a major geopolitical concern. However, though they’re built by ASML, much of the research that made the machines possible was done in the US. Some of the most storied names in US research and development — DARPA, Bell Labs, IBM Research, Intel, the US National Laboratories — spent decades of research and hundreds of millions of dollars to make EUV possible.

So why, after all that effort by the US, did EUV end up being commercialized by a single firm in the Netherlands?

How semiconductor lithography works

Briefly, semiconductor lithography works by selectively projecting light onto a silicon wafer using a mask. When light shines through the mask (or reflects off the mask in EUV), the patterns on that mask are projected onto the silicon wafer, which is covered with a chemical called photoresist. When the light strikes the photoresist, it either hardens or softens the photoresist (depending on the type). The wafer is then washed, removing any softened photoresist and leaving behind hardened photoresist in the pattern that needs to be applied. The wafer will then be exposed to a corrosive chemical, typically plasma, removing material from the wafer in the places where the photoresist has been washed away. The remaining hardened photoresist is then removed, leaving only an etched pattern in the silicon wafer. The silicon wafer will then be coated with another layer of material, and the process will repeat with the next mask. This process will be repeated dozens of times as the structure of the integrated circuit is built up, layer by layer.

Early semiconductor lithography was done using mercury lamps that emitted light of 436 nanometers wavelength, at the low end of the visible range. But as early as the 1960s, it was recognized that as semiconductor devices continued to shrink, the wavelength of light would eventually become a binding constraint due to a phenomena known as diffraction. Diffraction is when light spreads out after passing through a hole, such as the openings in a semiconductor mask. Because of diffraction, the edges of an image projected through a semiconductor mask will be blurry and indistinct; as semiconductor features get smaller and smaller, this blurriness eventually makes it impossible to distinguish them at all.

The search for better lithography

The longer the wavelength of light, the greater the amount of diffraction. To avoid eventually running into diffraction limiting semiconductor feature sizes, in the 1960s researchers began to investigate alternative lithography techniques.

One method considered was to use a beam of electrons, rather than light, to pattern semiconductor features. This is known as electron-beam lithography (or e-beam lithography). Just as an electron microscope uses a beam of electrons to resolve features much smaller than a microscope which uses visible light, electron-beam lithography can pattern features much smaller than light-based lithography (“optical lithography”) can. The first successful electron lithography experiment was performed in 1960, and IBM extensively developed the technology from the 1960s through the 1990s. IBM introduced its first e-beam lithography tool, the EL-1, in 1975, and by the 1980s had 30 e-beam systems installed.

E-beam lithography has the advantage of not requiring a mask to create patterns on a wafer. However, the drawback was that it’s very slow, at least “three orders of magnitude slower than optical lithography”: a single 300mm wafer takes “many tens of hours” to expose using e-beam lithography. Because of this, while e-beam lithography is used today for things like prototyping (where not having to make a mask first makes iterative testing much easier) and for making masks, it never displaced optical lithography for large-volume wafer production.

Another lithography method considered by semiconductor researchers was the use of X-rays. X-rays have a wavelength range of just 10 to 0.01 nanometers, allowing for extremely small feature sizes. As with e-beam lithography, IBM extensively developed X-ray lithography (XRL) from the 1960s through the 1990s, though they were far from the only ones. Bell Labs, Hughes Aircraft, Hewlett Packard, and Westinghouse all worked on XRL, and work on it was funded by DARPA and the US Naval Research Lab.

For many years X-ray lithography was considered the clear successor technology to optical lithography. In the late 1980s there was concern that the US was falling behind Europe and Japan in developing X-ray lithography, and by the 1990s IBM alone is estimated to have invested more than a billion dollars in the technology. But like with e-beam lithography, XRL never displaced optical lithography for large-volume production, and it’s only been used for relatively niche applications. One challenge was creating a source of X-rays. This largely had to be done using particle accelerators called synchrotrons: large, complex pieces of equipment which were typically only built by government labs. IBM, committed to developing X-ray lithography, ended up commissioning its own synchrotron (which cost on the order of $25 million) in the late 1980s.

Part of the reason that technologies like e-beam and X-ray lithography never displaced optical lithography is that optical lithography kept improving, surpassing its predicted limits again and again. Researchers were forecasting the end of optical lithography since the 1970s, but through various techniques, such as immersion lithography (using water between the lens and the wafer), phase-shift masking (designing the mask to deliberately create interference in the light waves to increase the contrast), multiple patterning (using multiple exposures for a single layer), and advances in lens design, the performance of optical lithography kept getting pushed higher and higher, repeatedly pushing back the need to transition to a new lithography technology. The unexpectedly long life for optical lithography is captured by Sturtevant’s Law: “the end of optical lithography is 6 – 7 years away. Always has been, always will be.”

Advances in optical lithography lenses over time, via Bruning 2007. In addition to more complex lenses, shorter wavelengths of light were used.

The rise of EUV

In the early 1980s, Hiroo Kinoshita, a researcher at Japan’s Nippon Telephone and Telegraph (NTT), was researching X-ray lithography, but was becoming disillusioned by its numerous difficulties. The X-ray lithography technology being used was known as “X-ray proximity lithography” or XPL. Whereas in optical lithography light passed through a lens to reduce the image size projected onto the silicon wafer, because no known materials could make a reduction lens for X-rays, X-rays were projected directly onto the wafers without any sort of lens reduction. In part because of the lack of reduction — which meant that any imperfections in the mask wouldn’t be scaled down when projected onto the wafer — making masks for XPL proved exceptionally difficult.

However, while it’s not possible to focus X-rays with a lens, it is possible to reflect certain X-ray wavelengths with a mirror. A normal mirror will only reflect X-rays at very shallow angles, making it very hard to use them for a practical lithography system (the requirement of a shallow angle would make such a system gigantic); at steeper angles, X-rays will simply pass through the mirror. However, by constructing a special mirror from alternating layers of different materials, known as a “multilayer mirror”, light near the X-ray region of the spectrum can be reflected at much steeper angles. Multilayer mirrors use layers of different materials with different indices of refraction (how much light bends when entering it) to create constructive interference — each layer boundary reflects a small amount of light, which (when properly designed) adds together with the reflection from the other layers. (Anti-reflective coatings use a similar principle, but instead use multiple layers to create destructive interference to eliminate reflections.)

The first multilayer mirrors that could reflect X-rays were built in the 1940s, but they were impractical because the mirrors were made from gold and copper, which quickly diffused into each other, degrading the mirror. But by the 1970s and 80s, the technology for making these constructive interference-creating mirrors had dramatically improved. In 1972 researchers at IBM successfully built a 10-layer multilayer mirror that reflected a significant fraction of light in the 5 to 50 nanometer region, and in 1981 researchers at Stanford and the Jet Propulsion Laboratory built a 76-layer mirror from alternating layers of tungsten and carbon. A few years later researchers at NTT also successfully built a multilayer tungsten and carbon film, and based on their success Kinoshita, the researcher at NTT, began a project to leverage these multilayer mirrors to create a lithography system. In 1985 his team successfully projected an image using what were then called “soft X-rays” (light in roughly the 2 nanometer to 20 nanometer range) reflected off of multilayer mirrors for the first time.2 That same year, researchers at Stanford and Berkeley published work showing that a multilayer mirror made from molybdenum and silicon could reflect a very large fraction of light near the 13 nanometer wavelength. Because X-rays in a lithography tool will bounce off of multiple mirrors (a modern EUV tool might have 10 mirrors), reflecting a large portion of them is key to making a lithography tool practical; too little reflection and the light will be too weak by the time it reaches the wafer.

Initially people in the field were skeptical about the prospects of a reflective X-ray lithography system. When presenting this research in Japan, Kinoshita noted that his audience was “highly skeptical of his talk” and that they were “unwilling to believe that an image had actually been made by bending X-rays”. The same year, when Bell Labs researchers suggested to the American government that soft X-rays with multilayer mirrors could be used to create a lithography system, they received an “extremely negative reaction”; reviewers argued that “even if each of the components and subsystems could be fabricated, the complete lithography system would be so complex that its uptime would be negligible.” When researchers at Lawrence Livermore National Lab, after learning of Kinoshita’s work, presented a paper on their own soft X-ray lithography work in 1988, reception was similarly negative. One paper author noted that “You can’t imagine the negative reception I got at that presentation. Everybody in the audience was about to skewer me. I went home with my tail between my legs…”

Despite the negative reactions, work on soft X-ray lithography continued to advance at NTT, Bell Labs, and Livermore. Kinoshita’s research group at NTT designed a new two-mirror soft x-ray lithography system, and used it to successfully print patterns with features 500 nanometers wide. When presenting this work at a 1989 conference in California, a Bell Labs researcher named Tania Jewell became extremely interested, and “deluged” Kinoshita with questions. The next year, Bell Labs successfully printed a 50 nanometer pattern using soft X-rays. The 1989 conference, and the meeting between NTT and Bell Labs, has been called the “dawn of EUV”.

Work on soft X-ray lithography continued in the 1990s. Early soft X-ray experiments had been done with synchrotron radiation, but a synchrotron would be difficult to make into a practical light source for high-volume production, so researchers looked for alternative ways to generate soft X-rays. One strategy for doing this is to heat certain materials, such as xenon or tin, enough to turn them into a plasma. This can be done using either lasers (creating laser produced plasma, or LPP) or electrical currents (creating discharge produced plasma, or DPP). Development of LPP power sources began in the 1990s, but creating such a system was enormously difficult. Turning material into a plasma generated debris which reduced the life of the extremely sensitive multilayer mirrors, and a “great deal of effort [was] put into designing and testing a variety of debris minimization schemes”. One strategy that proved to be very successful was to minimize the amount of debris by creating a “mass limited target”: minimizing the amount of material to be heated into plasma by emitting it as a series of microscopic droplets. Over time, these and other strategies allowed for longer and longer mirror life.

Another major challenge was manufacturing sufficiently precise multilayer mirrors. In 1990, mirrors could be fabricated with at most around 8 nanometers of precision, but a practical soft X-ray lithography system demanded 0.5 nanometer precision or better. NTT had obtained its first multilayer mirrors from Tinsley (the US firm that had built the ultra-precise mirrors for the Hubble Space Telescope), and with NTT’s encouragement Tinsley was able to fabricate mirrors of 1.5 to 1.8 nanometer accuracy in 1993. Similar work on mirror accuracy was done at Bell Labs (with assistance from researchers at the National Institute of Standards and Technology), and during the 1990s the precision of multilayer mirrors continued to improve.

As work on it was proceeding, a change in name for soft X-ray technology was suggested. “Soft X-ray” was thought to be too close to X-ray proximity lithography, which worked on different principles (ie: it had no mirrors) and had developed a negative reputation thanks to its difficult development history. So in 1993 the name was changed to Extreme Ultraviolet Lithography, or EUV. The wavelengths being used were at the very bottom of the ultraviolet spectrum, and the name created associations with “Deep Ultraviolet Lithography” (DUV), a lithography technique based on 193-nanometer light, which was then being used successfully.

Organizational momentum behind EUV continued to build. In the early 1990s Sandia National Labs, using technology developed for the Strategic Defense Initiative, partnered with Bell Labs to demonstrate a soft X-ray lithography system using a laser produced plasma. In 1991, Japanese corporations Nikon and Hitachi also began to research EUV technology. That same year, the Defense Advanced Research Projects Agency (DARPA) began to fund lithography development via its Advanced Lithography Program, and by 1996 Sandia National Labs and Lawrence Livermore lab had committed around $30 million to EUV development (with a similar amount contributed by several private companies). In 1992, Intel committed $200 million into the development of EUV, most of which funded research work at Sandia, Livermore and Bell Labs. In 1994, the US formed the National EUV Lithography Program, made up of researchers from the national labs (Livermore, Berkeley, and Sandia), and led by DARPA and the DOE.

EUV-LLC

In 1996, congress voted to terminate DOE funding for EUV research. Without funding to keep the research community together, the national lab researchers would be reassigned to other tasks, and much of the knowledge around EUV might dissipate. At the time, there were still numerous difficulties with EUV, and it was far from obvious it would be the successor lithography technology: a 1997 lithography task force convened by SEMATECH (a US semiconductor industrial consortium) ranked EUV last of four possible technologies behind XPL, e-beam lithography, and ion projection lithography.

Despite the uncertainty, Intel placed a bold bet on the future of EUV, and stepped in with around $250 million in funding to keep the EUV research program alive. It formed a consortium known as EUV-LLC, which contracted with the Department of Energy to fund EUV work at Sandia, Berkeley, and Livermore national labs. Other major US firms, including Motorola, AMD, IBM, Micron also joined the consortium, but Intel remained the largest and most influential shareholder, the “95% gorilla”. Following the creation of EUV-LLC, Europe and Japan formed their own EUV research consortiums: EUCLIDES in Europe and ASET in Japan.

When EUV-LLC was formed, US lithography companies had been almost completely forced out of the global marketplace. Japanese firms Nikon and Canon held a 40% and 30% share of the market, respectively, and third place was held by an up-and-coming Dutch firm called ASML, which held 20% market share. The members of EUV-LLC, not least Intel, wanted a major foreign lithography firm to join the consortium to help ensure EUV became a global standard However, the prospect of funding the development of advanced semiconductor technology, only to hand that technology over to a national competitor (especially a Japanese competitor who had so recently been responsible for decimating the US semiconductor industry), wasn’t an easy sell. Nikon declined to participate in EUV-LLC in part due to the resulting controversy, and Canon was ultimately prevented from joining by the US government.

ASML, however, was different. Being located in the Netherlands, it was considered “neutral ground” in the semiconductor wars between the US and Japan. Intel, whose main concern was that it could itself get access to the next generation of lithography tools regardless of who produced them, strongly advocated that ASML be allowed to procure a license. (One executive at the US lithography company Ultratech Stepper complained that Intel had “done everything in their power to give the technology to ASML on a silver platter.”) In 1999, ASML was allowed to join EUV-LLC and gain a license for its technology, provided that it used a sufficient quantity of US components in the machines it built and opened a US factory — conditions that it never met.

Left outside of the EUV-LLC consortium, Nikon and Canon never successfully developed EUV technology. And neither did any US firms. Silicon Valley Group, a US lithography tool maker which had licensed EUV technology, was bought by ASML in 2001, and Ultratech Stepper, another US licensee, opted not to pursue it. ASML, in partnership with German optics firm Carl Zeiss, became the only lithography firm to take EUV technology across the finish line.

Conclusion

Over the next several years, EUV-LLC proved to be a huge success, and when the program ended in 2003, it had met all of its technical goals. EUV-LLC had successfully built a test EUV lithography tool, made progress on both LPP and DPP light sources, developed masks that would work with EUV, created better multilayer mirrors, and filed for over 150 patents. Thanks in large part to Intel’s wager, EUV would ultimately become the lithography technology of the future, a technology that would entirely be in the hands of ASML.

This future took much longer to arrive than expected. When the EUV-LLC program concluded in 2003, US semiconductor industry organization SEMATECH stepped in to continue funding work on commercialization. ASML shipped its first prototype EUV lithography tool in 2006, but with very weak DPP power sources. A US company, Cymer (later acquired by ASML), was developing a better power source using a laser-produced plasma, but working out the problems with it took years and required further investment from Intel. Making defect-free EUV masks proved to be similarly difficult. EUV development proved to be so difficult that ASML ultimately required billions of dollars in investment from TSMC, Samsung, and Intel to fund its completion: the three companies invested $1 billion, $1 billion, and $4 billion, respectively in ASML in 2012 in exchange for shares of the company. ASML didn’t ship its first production EUV tool until 2013, but development work on things like the power source (often funded by the US) continued for years afterwards. Intel, worried about the difficulties of getting EUV into high-volume production, made the ultimately disastrous decision to try and push optical lithography technology one more step for its 10 nanometer process.

But today, after decades of development, EUV has arrived. TSMC, Intel, and Samsung, the world’s leading semiconductor fabricators, are all using EUV in production. And they are all using lithography tools built by ASML for it.

An important takeaway from the story of EUV is that developing a technology that works, and successfully competing with that technology in the marketplace, are two different things. Thanks to contributions from researchers around the world, including a who’s who of major US research organizations — DARPA, Bell Labs, the US National Labs, IBM Research — EUV went from unpromising speculation to the next generation of lithography technology. But by the time it was ready, US firms had been almost entirely forced out of the lithography tools market, leaving EUV in the hands of a single European firm to take it across the finish line and commercialize.

1

Modern semiconductor processes often have names that imply smaller sizes — TSMC’s 7 nm node, Intel’s 10 nm node — but these are essentially just names that don’t correspond with actual feature sizes.

2

Definitions for what light is considered to be “soft x-ray” don’t seem especially consistent. One article notes that “the terms soft X-ray and extreme ultraviolet aren’t well defined.”

Friday: No Major Economic Releases

Mortgage Rates Note: Mortgage rates are from MortgageNewsDaily.com and are for top tier scenarios.

Friday:
• At 10:00 AM ET, University of Michigan's Consumer sentiment index (Final for November).

Blue Origin revealed some massively cool plans for its New Glenn rocket

One week after the successful second launch of its large New Glenn booster, Blue Origin revealed a roadmap on Thursday for upgrades to the rocket, including a new variant with more main engines and a super-heavy lift capability.

These upgrades to the rocket are “designed to increase payload performance and launch cadence, while enhancing reliability,” the company said in an update published on its website. The enhancements will be phased in over time, starting with the third launch of New Glenn, which is likely to occur during the first half of 2026.

A bigger beast

The most significant part of the update concerned an evolution of New Glenn that will transform the booster into a super-heavy lift launch vehicle. The first stage of this evolved vehicle will have nine BE-4 engines instead of seven, and the upper stage four BE-3U engines instead of two. In its update, Blue Origin refers to the new vehicle as 9×4 and the current variant as 7×2, a reference to the number of engines in each stage.

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Thursday 20 November 1662

All the morning sitting at the office, at noon with Mr. Coventry to the Temple to advise about Field’s, but our lawyers not being in the way we went to St. James’s, and there at his chamber dined, and I am still in love more and more with him for his real worth. I broke to him my desire for my wife’s brother to send him to sea as a midshipman, which he is willing to agree to, and will do it when I desire it. After dinner to the Temple, to Mr. Thurland; and thence to my Lord Chief Baron, Sir Edward Hale’s, and back with Mr. Thurland to his chamber, where he told us that Field will have the better of us; and that we must study to make up the business as well as we can, which do much vex and trouble us: but I am glad the Duke is concerned in it. Thence by coach homewards, calling at a tavern in the way (being guided by the messenger in whose custody Field lies), and spoke with Mr. Smith our messenger about the business, and so home, where I found that my wife had finished very neatly my study with the former hangings of the diningroom, which will upon occasion serve for a fine withdrawing room. So a little to my office and so home, and spent the evening upon my house, and so to supper and to bed.

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The future of war is the future of society

Photo by АрміяІнформ via Wikimedia Commons

The most prophetic post I’ve ever written wasn’t about economics — well, not directly at least. It was about military technology. I’m not much of an expert in that subject, but I managed to make some predictions that were unpopular at the time but which have been borne out spectacularly in the years since. The original article, written for Quartz, was in 2013, but right now I can only find this republished version from 2020. Here’s what I wrote:

The human race is on the brink of momentous and dire change. It is a change that potentially smashes our institutions and warps our society beyond recognition. It is also a change to which almost no one is paying attention. I’m talking about the coming obsolescence of the gun-wielding human infantryman as a weapon of war…

You may not even realize you have been, indeed, living in the Age of the Gun…But imagine yourself back in 1400. In that century…the battlefield was ruled not by the infantryman, but by the horse archer—a warrior-nobleman who had spent his whole life training in the ways of war. Imagine that guy’s surprise when he was shot off his horse by a poor no-count farmer armed with a long metal tube and just two weeks’ worth of training. Just a regular guy with a gun…

For centuries after that fateful day, gun-toting infantry ruled the battlefield…But sometime in the near future, the autonomous, weaponized drone may replace the human infantryman as the dominant battlefield technology. And as always, that shift in military technology will cause huge social upheaval.

The advantage of people with guns is that they are cheap and easy to train…The hand-held firearm reached its apotheosis with the cheap, rugged, easy-to-use AK-47; with this ubiquitous weapon, guerrilla armies can still defy the mightiest nations on Earth…

But another turning point in the history of humankind may be on the horizon. Continuing progress in automation, especially continued cost drops, may mean that someday soon, autonomous drone militaries become cheaper than infantry at any scale.

Note that what we call drones right now are actually just remote-control weapons, operated by humans. But that may change…Sometime in the next couple of decades, drones will be given the tools to take on human opponents all by themselves…meanwhile, technological advances and cost drops in robotics continue apace. It is not hard to imagine swarms of agile, heavily armed quadrotor drones flushing human gunmen out of buildings and jungles[.]

That was twelve years ago. At the time, when I floated this idea on Twitter, people jumped to scoff at it. They told me that electronic warfare would be too powerful for drones to overcome, that drones wouldn’t have the firepower to dominate the battlefield, and so on. They pointed out — quite correctly — that when it comes to military technology, I don’t have any expertise.

And yet as of 2025, my prediction has been utterly vindicated. Reports from the battlefield in Ukraine tell of a battlefield so completely dominated by drone warfare that experts are forced to go out of their way to argue that traditional artillery still has a role. Here’s Michael Kofman (my favorite Ukraine expert):

Drones continue to be responsible for most daily casualties, with the front line defined by overlapping drone and artillery fire engagement zones 20-25km from the forward line of troops. This is commonly referred to as the ‘kill zone.’..Drone units work to suppress and displace the opponent’s drone crews further from the front…[L]onger range drones strike artillery, logistics, and enemy drone teams further in the rear…

On the Russian side Rubicon formations remains a leading problem for drone operators, not only the drone companies themselves, but because they train other Russian drone units to replicate their approaches focused on AFU logistics, drone crews, and intercepting ISR…One of the observed changes is the balance of casualties in the AFU has shifted from infantry to supporting roles, drone operators, logistics, etc. There is very little infantry forward, and in many AFU brigades infantry now bears less of the casualties…

Most units now have a UGV platoon, company, or battalion. These require greater skill and training to employ, but hold considerable promise, reducing casualties…The airspace has become even more contested for longer-range ISR, with both sides establishing dense tactical radar coverage to detect drones, and one way attack munitions…

Artillery remains important to suppressing enemy forces and shaping how they attack, especially in bad weather, which is more prevalent this time of year. Fog, wind, and rain significantly degrade drone operations[.]

Other reports all tell the same story.

The drone is increasingly regarded as the infantryman’s basic weapon. The U.S. Army is ordering a million drones to equip its soldiers (a war would require many, many times that). Drones are replacing artillery, now having the capability to take out infantry, tanks, artillery, and basically anything else at a fairly long range. Strike drones are supplementing bombers and long-range missiles as a way of dealing damage behind the lines; Ukraine’s drone strikes are degrading Russia’s oil industry from thousands of miles away.

And drone technology is still in its infancy. Currently, drones are still piloted by humans. This makes them subject to electronic warfare that jams the link between pilot and drone, forcing them to use spools of fiber-optic cable to maintain a secure connection. And it means that drone operators have to stay somewhat near the front, exposing them to enemy strikes. Skilled human operators are a valuable resource that limits the amount of drones that can be used at once.

This is about to change. Advances in AI are going to enable drones to behave autonomously — the “killer robots” out of a science fiction novel. In fact, Ukraine has already experimented with autonomous drone swarms. Drones are going to first supplement and then replace boats, fighter jets, submarines, and every other manned weapon of war. Human infantry, and human-crewed vehicles, will become obsolete due to their sheer expense. Soldiers and big vehicles cost a lot; drones cost much less.

All of these predictions are fairly obvious and easy to make. AI is only getting better. And machines are generally cheaper than humans, who are only going to get more expensive over time.1 Those two facts are all I really needed2 in order to predict the rise of drones back in 2013, and neither has changed since then.

What happens next is harder to foresee. Obviously, everyone will look for ways to shoot down swarms of drones. At first this will involve very fast guns, like Rheinmetall’s Skyranger. A drone is cheap, but a bullet is cheaper. Even cheaper, eventually, will be a puff of light; laser weapons are being developed that can shoot down drones cheaply, quickly, and very accurately. Eventually, we may see big battleships and tanks bristling with point defense lasers force their way through swarms of drones, while defenders try to take them out with big fast missiles.

Maybe that will result in the return of WW2-style maneuver warfare. Or maybe missiles will cheaply take down any big vehicle, creating static battlefields more like World War 1 (or the current Ukraine War), where the only way to win is to have your economy produce more drones than the enemy. Recall that I’m not actually an expert in military technology, so I can’t say how this will shake out. I’m not sure if anyone knows yet.

But what I do think is very likely is that the organization of human societies will have to change.

Take a look at the long-term history of warfare. Our numbers are pretty patchy, but as far as we can tell, there have been three really big waves of warfare over the last millennium:

  1. The Mongol conquests in the 1200s (and follow-up conquerors in the 1300s like Timur)

  2. The Thirty Years’ War and the fall of the Ming Dynasty in China in the 1600s

  3. The World Wars and communist revolutions of the 1900s

People argue a lot over why there were these three big outbreaks of war all over the world. Some blame climate change, while others blame patterns of trade, population growth, and so on. But I think one big plausible factor is military technology.

Each of the three waves of war coincides with a dominant package of military technology. The Mongols ran circles around their opponents with stirrup-equipped horses, and outranged them with recurved bows. The wars of the 1600s represented the peak of gunpowder warfare, while the wars of the 20th century were the peak of industrial warfare — planes, tanks, metal ships, and so on.

Interestingly, none of those big wars happened right after the key technologies were introduced. There was always a substantial lag. Most of the bow and stirrup technologies that made the Mongols so fearsome were invented a millennium earlier by the Xiongnu (the predecessor of the Huns). Cannon and muskets were invented a century before the cataclysms of the 1600s. The World Wars saw rapid innovation, but the machine gun, the howitzer, the ironclad battleship, and other key technologies were pioneered earlier. There were constant incremental improvements in all of these technologies, of course, but it’s unlikely that they reached some special threshold of lethality that caused wars to suddenly get much much bigger and deadlier.

Instead, what changed were the societies that made use of the weapons.

There were plenty of steppe empires before the Mongols, but they usually weren’t able to overcome densely populated, settled civilizations like China. Only once Genghis Khan implemented reforms like meritocracy, writing, and so on were the steppe warlords able to break through and conquer the world. Mongol tactics — especially the ability of mounted units to remain separate for days and then all converge on the same place at the same time — required sociocultural innovations to prevent defection/betrayal and ensure cooperation among highly mobile subcommanders.

Similarly, firearms and artillery saw wide adoption by the 1400s, but it wasn’t until the 1600s that gunpowder armies grew to truly massive size — hundreds of thousands of men instead of tens of thousands. That increase in size drove much of the higher death toll of the wars of the 1600s, since those giant armies had to live off the land, which caused famines and massacres (the battlefield death toll was higher too, obviously).

Those big armies required lots of money, which required lots of financing — better tax collection and more bank loans. Paul Kennedy notes that the countries that won wars in the gunpowder era tended to be the ones that were the best at tax collection. Charles Tilly argues that gunpowder-era wars made the modern state, because the regimes that survived were the ones that developed complex bureaucracies in order to collect more taxes to fund their wars.

The World Wars were also made possible by innovations in social organization — modern corporations, even larger bureaucracies, modern supply and logistics, and continuous research and development. Those social innovations emerged partly as a way to make countries more effective in war — if you didn’t develop those things, you were liable to be conquered.

It’s likely that all three eras of warfare required innovations in persuasion, ideology, and communication as well. Genghis Khan had to convince a plethora of fractious steppe warlords to all stick together and cooperate. The great powers of the 1600s used a combination of religion and local loyalties — often communicated using the printing press — to help motivate their large armies to fight. In the 20th century wars, ideologies like communism, fascism, and democracy were key, and radio was an important new tool. All of those ideological changes changed society as well.

It was these social changes that allowed wars to get so big and cataclysmic in each era. So it might seem like the changes I’m describing are a bad thing — and in fact, I do think it’s a distinct possibility that we’ll see a cataclysmic global drone war sometime in the future. But from any one country’s point of view, those social changes were absolutely necessary, since the only thing worse than winning a war is losing a war.

And historically, warfare acted as a vector for the beneficial spread of both physical and social technologies. Countries in the early modern period had to adopt modern fiscal systems in order to be able to resist conquerors who already had those systems in place. Industrial production spread not just because it made citizens wealthier, but because you needed it to make guns, ammunition, railroads, and so on.

In other words, it’s very difficult for countries to resist the changes that new dominant packages of military technologies necessitate. In the 1700s and 1800s, you either learned to be a gunpowder empire, or you got conquered and enslaved. In the 20th century, you had to become a modernized industrial state, or you got plowed under. If there is a single driving irresistible force of History, I think it must be the innovations that we use to kill each other.

Right now, we’re in the middle of a revolution in military affairs that will be just as profound as the Industrial Revolution, the introduction of gunpowder, or the rise of steppe warfare. The two great inventions of our time — AI and the electric tech stack — are rapidly eclipsing industrial warfare. That will probably make war more capital-intensive, as human labor is increasingly removed from the equation (and because AI is very capital-intensive). It will almost certainly make it more knowledge-intensive, as understanding of how to apply AI effectively becomes decisive.

These changes are going to force our society to change and adapt. The America that won World War 2 didn’t look like the America of Thomas Jefferson’s time. And if we want to remain powerful and secure, the America of the 21st century won’t look like Roosevelt’s America, either. It can’t.

Right now, China looks like it’s outpacing other societies in terms of adapting itself to the new requirements of war. Possibly alone of all countries, it has mastered every part of the drone supply chain:

China’s emphasis on manufacturing, while perhaps not economically efficient, has also probably prepared it better for prolonged capital-intensive war. Right now, they would be able to out-produce the rest of the world in terms of drones. If we are to match them, we’re going to need to make better use of industrial policy to patch the holes in our supply chains, stop wrecking those supply chains with tariffs on our allies, and form closer partnerships with those allies so that we can achieve the scale to match China.

China also seems to be adapting the new communications technologies of social media more effectively than many of its rivals — or at least, more effectively in terms of warfighting ability. We scoff at China’s massive system of internet thought control, but it’s possible that this is the only way to keep a modern nation from fracturing and spiraling into chaos in the age of social media. I hope there are ways to hold together a modern nation-state without resorting to centralized thought control. But we really need to start looking for those techniques, instead of just assuming that stability will somehow naturally reemerge from the chaos of X and TikTok.

Most of all, America — and Europe, and other developed countries — must prepare for dramatic, wrenching change. These days we often find ourselves looking backward — resisting the adoption of new technologies, blocking development, and wallowing in nostalgia for the glory days of the 20th century. But the kind of society we had then will not serve us as well in an age when flying robots rule the battlefield. Just as Thomas Jefferson’s America gave way to Franklin D. Roosevelt’s, we must find a way to preserve the core benefits and advantages of our liberal democracy while transitioning to the next thing.

Right now, I don’t think either Americans or Europeans are mentally prepared for that change. I hope it doesn’t take a catastrophic defeat in a major war in order to wake us up.


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1

The cost of a human soldier goes up with both lifetime earnings and with the subjective value that society places on each human life. Both of those things go up as economies grow.

2

Technically, I also had to know that explosives carried by drones would win the battle against new kinds of armor. But that’s just obvious from basic physics. It takes a huge amount of energy

What Happens Next?

I recently published three very controversial articles here—warning readers about the growing backlash against AI. I called special attention to the vulnerability of Meta’s stock.

I took a lot of heat for this straight talk. But let’s look at what actually happened in the aftermath.

Since August 8—when I published “Is This What a Bubble Looks Like at the Top?”—Meta’s stock has collapsed. It’s down a staggering $180 per share. And the decline has accelerated since October 30, when I published “The Bubble Just Burst.”

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During that same period the NASDAQ is down a stunning 1,400 points.

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That raises the obvious question: What happens next?

Read more

3I/ATLAS: A View from Planet Earth

Now outbound after its perihelion or closest approach to the Sun Now outbound after its perihelion or closest approach to the Sun


Falcon 9 Starlink mission marks 100th launch of the year from Florida’s Space Coast

A Falcon 9 rocket rises from a fog bank on Nov.20, 2025, making the 100th launch of the year from Florida’s Space Coast. Image: John Pisani/Spaceflight Now.

A Falcon 9 rocket lifted off from the Kennedy Space Center Thursday evening on a milestone mission marking the 100th launch from the Space Coast this year.

The Starlink 6-78 mission, carrying 29 satellites for SpaceX’s internet service, soared spaceward at 10:39 p.m. EST (0339 UTC), the Faclon 9 rocket rising from a fog bank that had blanketed the area around launch complex 39A.

Earlier this month, missions by the three major launch companies operating from the spaceport broke the record of 93 liftoffs that was set in 2024. SpaceX has chalked up the lion’s share of the 100 launches so far in 2025 with 93 flights of its Falcon 9 rocket. United Launch Alliance has made five launches, four by its workhorse Atlas 5 rocket and one of its new Vulcan vehicle. Blue Origin flew its New Glenn rocket for the first time in January and for a second flight on Nov. 13.

The Eastern Range, operated by the Space Force’s Space Launch Delta 45 wing, is the busiest spaceport in the world, accounting for more than a third of all orbital launches in 2025.

bital launch attempts from Cape Canaveral by year 1957-2025. Data as of Nov. 20, 2025.

Until 2020, the annual launch rate from the pads at Cape Canaveral Space Force Station and NASA’s Kennedy Space Center only twice exceeded 25 orbital launches in a year. SpaceX, with its partially reusable Falcon 9 rocket, has driven the dramatic increase in launch cadence, accounting for 91 percent of launches from Florida.

Thursday’s Starlink delivery mission used Falcon 9 first stage booster B1080, which first flew in 2023 and is launching for a 23rd time. Eight minutes after launch, it landed on the drone ship ‘Just Read the Instructions’, stationed in the Atlantic Ocean about 365 miles downrange, east of the Bahamas.

Deployment of the Starlink satellites will come about one hour and five minutes after launch. This latest batch of V2 Starlinks will join more than 9,000 satellites already in orbit.

The Starlink 6-78 mission heads on a south-easterly trajectory after departing Kennedy Space Center. Image: Michael Cain/Spaceflight Now.

Building more with GPT-5.1-Codex-Max

Building more with GPT-5.1-Codex-Max

Hot on the heels of yesterday's Gemini 3 Pro release comes a new model from OpenAI called GPT-5.1-Codex-Max.

(Remember when GPT-5 was meant to bring in a new era of less confusing model names? That didn't last!)

It's currently only available through their Codex CLI coding agent, where it's the new default model:

Starting today, GPT‑5.1-Codex-Max will replace GPT‑5.1-Codex as the default model in Codex surfaces. Unlike GPT‑5.1, which is a general-purpose model, we recommend using GPT‑5.1-Codex-Max and the Codex family of models only for agentic coding tasks in Codex or Codex-like environments.

It's not available via the API yet but should be shortly.

The timing of this release is interesting given that Gemini 3 Pro appears to have aced almost all of the benchmarks just yesterday. It's reminiscent of the period in 2024 when OpenAI consistently made big announcements that happened to coincide with Gemini releases.

OpenAI's self-reported SWE-Bench Verified score is particularly notable: 76.5% for thinking level "high" and 77.9% for the new "xhigh". That was the one benchmark where Gemini 3 Pro was out-performed by Claude Sonnet 4.5 - Gemini 3 Pro got 76.2% and Sonnet 4.5 got 77.2%. OpenAI now have the highest scoring model there by a full .7 of a percentage point!

They also report a score of 58.1% on Terminal Bench 2.0, beating Gemini 3 Pro's 54.2% (and Sonnet 4.5's 42.8%.)

The most intriguing part of this announcement concerns the model's approach to long context problems:

GPT‑5.1-Codex-Max is built for long-running, detailed work. It’s our first model natively trained to operate across multiple context windows through a process called compaction, coherently working over millions of tokens in a single task. [...]

Compaction enables GPT‑5.1-Codex-Max to complete tasks that would have previously failed due to context-window limits, such as complex refactors and long-running agent loops by pruning its history while preserving the most important context over long horizons. In Codex applications, GPT‑5.1-Codex-Max automatically compacts its session when it approaches its context window limit, giving it a fresh context window. It repeats this process until the task is completed.

There's a lot of confusion on Hacker News about what this actually means. Claude Code already does a version of compaction, automatically summarizing previous turns when the context runs out. Does this just mean that Codex-Max is better at that process?

I had it draw me a couple of pelicans by typing "Generate an SVG of a pelican riding a bicycle" directly into the Codex CLI tool. Here's thinking level medium:

A flat-style illustration shows a white, round-bodied bird with an orange beak pedaling a red-framed bicycle with thin black wheels along a sandy beach, with a calm blue ocean and clear sky in the background.

And here's thinking level "xhigh":

A plump white bird with an orange beak and small black eyes crouches low on a blue bicycle with oversized dark wheels, shown racing forward with motion lines against a soft gradient blue sky.

I also tried xhigh on the my longer pelican test prompt, which came out like this:

A stylized dark gray bird with layered wings, a yellow head crest, and a long brown beak leans forward in a racing pose on a black-framed bicycle, riding across a glossy blue surface under a pale sky.

Also today: GPT-5.1 Pro is rolling out today to all Pro users. According to the ChatGPT release notes:

GPT-5.1 Pro is rolling out today for all ChatGPT Pro users and is available in the model picker. GPT-5 Pro will remain available as a legacy model for 90 days before being retired.

That's a pretty fast deprecation cycle for the GPT-5 Pro model that was released just three months ago.

Via Hacker News

Tags: ai, openai, generative-ai, llms, evals, pelican-riding-a-bicycle, llm-release, gpt-5, codex-cli

Pundit Brain Continues to Afflict Nation

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When I was a young man, I went on lots of job interviews, and usually didn’t perform very well. The artificiality of the exercise always made me profoundly uncomfortable; one interviewer even said to me, “You hate this, don’t you?” Every once in a while, though, I’d say something clever enough to make an impact.

Which is what happened when, at the age of 24 and with a couple of jobs as a campaign grunt under my belt, I was interviewing at a political consulting firm when I mentioned that one of the conclusions I had come to after way too much phone banking and door knocking was that those of us in the politics business have a real problem when it comes to voters: We know way more than voters do, and that makes it hard for us to understand them.

We think about politics all the time, we understand the basics of how voting works, we know how a bill becomes a law, and we may even have a grasp of some policy issues. But as you learn when you spend time talking to them, most voters understand little if anything about these things. That means that the political professionals have a very hard time getting inside their heads and seeing things from their perspective, which is essential to crafting strategies that will persuade them.

My interviewer seemed impressed, as though this was an insight he hadn’t thought of before, and I got the job. Later I wound up in grad school and learned that political scientists had spent decades investigating the sources, details, and implications of widespread voter ignorance.

“Ignorance” isn’t a very nice word, and the charitable way this is often described is that while some people find politics interesting and pay a lot of attention to it, most people don’t. They’re worried about their jobs, their kids, and whatever else is going on in their lives, so most of them don’t come home after a long day and turn on cable news to find out what happened in today’s House Rules Committee meeting. They learn about what’s happening in drips and drabs, but most of it is at a very superficial level, and that’s fine with them. It isn’t a matter of being dumb; the same person who doesn’t know who the Speaker of the House is might be able to tell you what’s going on with their favorite football team at an extraordinary level of detail and subtlety, because that happens to be something they care about.

This is something every political scientist knows. Yet somehow, lots of important people who work in politics and write about politics for a living continue to believe that voters see the political world in the same way they do. In particular, they think that like them, voters have rationally organized views about policy that assemble into coherent ideological systems, and therefore parties and candidates can improve their performance by moving toward or away from the “center,” tweaking their positions and the emphasis of their communication to maximize their performance with the elusive “median voter.”

It has always been thus

For all the years I’ve been around politics, people have been debating whether Democrats should move to the center or go left to mobilize their base. We’re still having that debate today. The underlying premise is that voters themselves have a discernible ideology and will respond if candidates position themselves closer to that position. Yet since at least the 1960s, political scientists have been wrestling with the lack of ideology among the electorate. The most influential early work in this area was an article by Philip Converse called “The Nature of Belief Systems in Mass Publics,” which argued that only a sliver of voters had coherent ideological beliefs. He classified only 3% of voters as “Ideologues,” while another 12% were “Near-Ideologues”; the rest arrived at their positions on issues through group affiliation, a response to whatever was happening at the time, or completely randomly. Here’s his key table:

In the ensuing decades, other scholars built a mountain of research on the implications of Converse’s study. A lot of it could be understood as apologetics, endeavoring to explain that even though voters might not know very much, they can still make reasonable decisions either individually or collectively. Many books have been written making this argument (see here or here or here).

The fact that most people don’t know very much about policy or politics doesn’t necessarily mean that adjusting your ideology will never work; voters still have feelings about issues, and all else being equal, a candidate would seem to be in the best position if they align with the feelings of the maximum number of voters. But all else is never equal, and the pursuit of the median voter may never have been more fruitless than it is today.

That brings me to some excellent recent work showing how important it is to keep in mind that voters are nothing like pundits and political professionals. First, Adam Bonica and Jake Grumbach took on the central claim of many a centrist pundit and moderate Democratic advocacy group, that there is clear evidence that moderate candidates perform better than those whose issue positions are farther from the center. Sure, your AOC types might succeed in places where the electorate is overwhelmingly left-leaning, but overall it’s better to tack to the center. Bonica and Grumbach find that it just isn’t true:

The small to nonexistent effects of moderation in the modern era shouldn’t be surprising. Decades ago when “all politics was local,” a candidate’s moderation likely carried significant benefits. In the Trump era, by contrast, elections are driven by national tides, candidate charisma, and anti-establishment credibility—qualities that neither political consultants nor academics know how to manufacture.

This point is central to this story: All politics is now national. This has been evident for a few years now; I wrote back in 2019 about research by Emory’s Alan Abramowitz showing that the benefits of both moderation and incumbency in House elections were disappearing. Voters are essentially deciding which party they’re mad at or which party they think should be in charge in Washington and voting accordingly, regardless of what the specific candidates in their district are saying.

Which is perfectly rational! It makes much more of a difference who controls the House than whether my member of Congress is a little more to the right or the left, so it would be logical to ignore their particular positions and just choose by party. When you layer on the fact that few voters are even thinking ideologically, you get the kind of ever-shifting electoral results we’ve been seeing.

That brings us to this piece by G. Elliott Morris, in which he uses survey data to show that “Most Americans tell us they want a party that improves their general standard of living, and don’t use ideological language at all when describing what their ideal political party would stand for.” Here’s one of his charts:

That “moderate” group looks pretty small. In any case, there are a couple of important things to understand about the “affordability” that’s on everyone’s mind. The first is that it is the top concern right now, and it will certainly be a concern for a while. But not forever; if at some future date the economy is doing great and we’ve also had first contact with an alien species, the top issue on voters’ minds will probably be “What to do about the aliens.”

The second is that affordability as an issue is neither liberal nor conservative. It’s good for Democrats now because Republicans are in charge, and people blame whoever’s in charge for whatever they don’t like. It was bad for Democrats a year ago because the president was a Democrat. If Democrats win in 2026 and 2028 and people still feel economically precarious, it’ll be bad for Democrats again. I may think Democrats’ ideas about making life more affordable are better than Republicans’ ideas, but voters without firm party commitments will mostly vote against the party in charge if they’re unhappy, whichever party that is.

The lack of ideological thinking among the electorate presents a kind of emotional problem for Democrats, precisely because they care about policy. It’s what they want to talk about, and they think it matters. Which it does — when it comes time to govern. And sometimes, talking about policy during a campaign can convince people that you have ideas to address their main concerns, but most of the time it doesn’t much matter what the precise content of those ideas is.

And after all, if voters had clear and coherent ideological beliefs, we wouldn’t need to have campaigns at all; candidates could just put out a set of policy papers, and the wise and informed voters would choose whichever platform they prefer. The very fact that we spend so much time arguing about ridiculous fake issues and micro-controversies while being inundated with inane campaign ads shows that the voters aren’t particularly rational. It’s not an ideal world, but it’s the one we live in.

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Old Rock & Roll on a Rainy Night

Never heard this before. Boy were they hot, 23 years ago. Mature. And if my calculations are right, Mick was 60 (didn’t realize he was such a harmonica meister). And Bobby! And Ronnie! Woulda loved to have been there. A sweet spot in time. Had me dancing in the kitchen.

Then serendipitedly the same rainy night, I stumbled across this Scottish band from Glasgow, circa 1974, live at the Rainbow Theater in London, maybe my favorite music venue in the world. (Saw the Kinks there one night, Joe Cocker another night.) These guys were a combo of blues, rock and roll and vaudeville. Pretty unique.

Their version of Framed cracked me up, I liked the original version of this R&B song by the Platters (written by Lieber and Stoller) so much when I was 19 that I memorized all the words, (still can recite them). This version is like a Celtic tribute…

The Vibecession Deepens

A graph of purple and white text

AI-generated content may be incorrect.

My big discovery yesterday: I can’t do serious thinking and writing when jet-lagged and very tired. Whaddya know. So just a brief post this morning, before a busy day here in [country and city redacted]. I’ll be doing a full primer for Sunday but can’t promise much before then.

But here’s a bit of a preview. I noted last week that the Biden era vibecession — people feeling bad about an economy that looked good by standard measures — has persisted under Trump. In fact, public perceptions of the economy appear to be plumbing new depths.

Honestly, I’m surprised. One factor in poor economic sentiment under Biden was partisanship. People’s reported perception of the economy is strongly affected by whether their preferred party is in power:

A graph of a political party

AI-generated content may be incorrect.

Source: University of Michigan

This is true for both parties, but historically Republicans have tended to cheer harder and boo louder than Democrats. So other things equal we would have expected average sentiment to improve under Trump II.

Now, things aren’t equal. Objectively, the economy is worse in important ways than it was a year ago. Still, the extent of the plunge in perceptions is remarkable.

It may be that Trump is — bear with me here — actually paying a price for telling Americans not to believe their own eyes. As I’ve written recently, it’s important not to engage in false equivalence. Biden and company told Americans that their incomes were outpacing inflation, which was true but not what people wanted to hear. Trump keeps insisting that grocery prices are way down, which is simply a lie. And people may be noticing.

The absolute absurdity of the Trump team’s efforts to explain away bad economic news may also be taking a toll. Remember when Scott Bessent was supposed to be the adult in the room? Now he’s blaming migrants taking diseased cattle with them for high beef prices.

I also wonder whether Trump’s other problems — from Epstein to the deep unpopularity of ICE’s actions — are bleeding over to economic sentiment. Political consultants like to imagine that the public makes clear distinctions between issues: “kitchen table” versus democracy versus corruption. In reality public opinion is much more of a gestalt in which bad or good feelings on different issues merge.

I’ll try to parse all of this Sunday. Now, off to perform.

MUSICAL CODA

Nano Banana Pro aka gemini-3-pro-image-preview is the best available image generation model

Hot on the heels of Tuesday's Gemini 3 Pro release, today it's Nano Banana Pro, also known as Gemini 3 Pro Image. I've had a few days of preview access and this is an astonishingly capable image generation model.

As is often the case, the most useful low-level details can be found in the API documentation:

Designed to tackle the most challenging workflows through advanced reasoning, it excels at complex, multi-turn creation and modification tasks.

  • High-resolution output: Built-in generation capabilities for 1K, 2K, and 4K visuals.
  • Advanced text rendering: Capable of generating legible, stylized text for infographics, menus, diagrams, and marketing assets.
  • Grounding with Google Search: The model can use Google Search as a tool to verify facts and generate imagery based on real-time data (e.g., current weather maps, stock charts, recent events).
  • Thinking mode: The model utilizes a "thinking" process to reason through complex prompts. It generates interim "thought images" (visible in the backend but not charged) to refine the composition before producing the final high-quality output.
  • Up to 14 reference images: You can now mix up to 14 reference images to produce the final image.

[...] These 14 images can include the following:

  • Up to 6 images of objects with high-fidelity to include in the final image
  • Up to 5 images of humans to maintain character consistency

There is also a short (6 page) model card PDF which lists the following as "new capabilities" compared to the previous Nano Banana: Multi character editing, Chart editing, Text editing, Factuality - Edu, Multi-input 1-3, Infographics, Doodle editing, Visual design.

Trying out some detailed instruction image prompts

Max Woolf published the definitive guide to prompting Nano Banana just a few days ago. I decided to try his example prompts against the new model, requesting results in 4K.

Here's what I got for his first test prompt, using Google's AI Studio:

Create an image of a three-dimensional pancake in the shape of a skull, garnished on top with blueberries and maple syrup.

A very detailed quality photo of a skull made of pancake batter, blueberries on top, maple syrup dripping down, maple syrup bottle in the background.

The result came out as a 24.1MB, 5632 × 3072 pixel PNG file. I don't want to serve that on my own blog so here's a Google Drive link for the original.

Then I ran his follow-up prompt:

Make ALL of the following edits to the image:
- Put a strawberry in the left eye socket.
- Put a blackberry in the right eye socket.
- Put a mint garnish on top of the pancake.
- Change the plate to a plate-shaped chocolate-chip cookie.
- Add happy people to the background.

It's the exact same skull with the requested edits made - mint garnish on the blueberries, a strawberry in the left hand eye socket (from our perspective, technically the skull's right hand socket), a blackberry in the other, the plate is now a plate-sized chocolate chip cookie (admittedly on a regular plate) and there are four happy peo ple in the background.

I'll note that it did put the plate-sized cookie on a regular plate. Here's the 24.9MB PNG.

The new model isn't cheap. Here's the API pricing: it's 24 cents for a 4K image and 13.4 cents for a 1K or 2K image. Image inputs are 0.11 cents (just over 1/10th of a cent) each - an earlier version of their pricing page incorrectly said 6.7 cents each but that's now been fixed.

Unlike most of Google's other models it also isn't available for free via AI Studio: you have to configure an API key with billing in order to use the model there.

Creating an infographic

So this thing is great at following instructions. How about rendering text?

I tried this prompt, this time using the Gemini consumer app in "thinking" mode (which now uses Nano Banana Pro for image generation). Here's a share link - my prompt was:

Infographic explaining how the Datasette open source project works

This is a great opportunity to test its ability to run searches (aka "Grounding with Google Search"). Here's what it created based on that 9 word prompt:

Described by Gemini 3 Pro: A technical architecture diagram titled "How Datasette Works: From Raw Data to Explorable API," illustrating a workflow from left to right. 1. "RAW DATA SOURCES" include "CSV", "JSON", "Excel (XLSX)", and "Log Files". 2. These flow into "DATA PREPARATION & CONVERSION" using tools "csvs-to-sqlite" and "sqlite-utils" to create a "SQLite DATABASE". 3. This feeds into the central "DATASETTE APPLICATION CORE," a stack comprising "Data Ingestion (Read-Only)", "Query Engine (SQL)", "API Layer (JSON)", and "Web UI Rendering". 4. A "PLUGIN ECOSYSTEM" connects below the core, listing "Vega Charts", "Cluster Maps", "Full-Text Search", and "Custom Renderers". 5. To the right, the core branches into "OUTPUT & INTERFACES": an "Interactive Web Interface (Explore, Filter, Facet)", a "JSON API (Programmatic Access)" showing a snippet {"data": [...]}, and a "SQL EDITOR Custom SQL Queries" showing SELECT * FROM.... 6. The API output connects to "PUBLISHING & DEPLOYMENT" via a terminal command datasette publish cloudrun my.db leading to deployment targets "Heroku", "Google Cloud Run", "Fly.io", and "Vercel".

That's a pretty extraordinary result for such a simple prompt. The text is all spelled correctly and rendered without glitches. The content is solid too - it even included logos for the most popular publish platforms, and a tiny thumbnail of the Datasette UI which is close-enough for an infographic.

"Data Ingestion (Read-Only)" is a bit off. Everything else looks great to me.

Here's the thinking trace for that image generation process:

Initiating Datasette Infographic

I'm starting a detailed infographic about the Datasette project. I plan to use Google Search to gather specific information about its core processes, which I will then visualize in a multi-panel diagram.

Developing the Datasette workflow

I am visualizing the Datasette workflow as described in the search results. I'm focusing on the conversion of data from different formats into a SQLite database, which is then presented as a web application complete with a user interface and JSON output.

Visualizing Datasette Workflow

I've sketched out the initial structure for the infographic, focusing on a flowchart style. The key components include data input from diverse sources, conversion to SQLite, the Datasette core application, its main features (web UI, JSON API, SQL querying), ecosystem plugins, and finally, deployment options. I aim for clear icons and labels to represent each step. Now I will focus on refining the flow and clarifying the relationships between the parts.

Defining Core Datasette Stages

I've sketched out the initial infographic structure. I have identified the key components, focusing on visual representation of the data flow and the key benefits and features of the system. I have made updates to the flowchart with clear icons and labels. Now I'm working to expand the data input section and refine the visual representation of each step.

Constructing Datasette Infographic

I am translating the current Datasette workflow outline into visual elements. The input section will show icons for different data formats. I've sketched the data conversion stage with clear illustrations of the necessary tools. I will add a depiction of the Datasette core application, showcasing its interfaces and functions. The plugin ecosystem and deployment options will follow. Now, I am refining the visual representation.

Analyzing Datasette's Architecture

I'm currently working on representing the Datasette open-source project's architecture visually. I've broken it down into key components: raw data processing, SQLite conversion, core application functionalities, plugin integration, and deployment methods. I'm focusing on creating a clear, linear representation to show the workflow.

Mapping the Datasette Flow

I've crafted a comprehensive graphic to illustrate Datasette's operation. It spans the data ingestion, SQLite conversion, main application features, plugin interactions, and deployment stages, aiming for clarity and a logical flow.

Detecting generated images with SynthID

This note from the announcement post caught my eye:

We believe it's critical to know when an image is AI-generated. This is why all media generated by Google's tools are embedded with our imperceptible SynthID digital watermark.

Today, we are putting a powerful verification tool directly in consumers' hands: you can now upload an image into the Gemini app and simply ask if it was generated by Google AI, thanks to SynthID technology. We are starting with images, but will expand to audio and video soon.

Last night I used Nano Banana Pro to generate a fake photograph of raccoons stealing our food delivery, then scrubbed out the little diamond icon using the Apple Photos "cleanup" tool. I uploaded that Gemini app and asked "Was this image created with AI?":

Screenshot of a mobile chat interface displaying a conversation about AI image detection. The user has uploaded a photo showing two raccoons on a porch; one raccoon reaches inside a paper bag a bench while the other stands on the ground looking up at it. The conversation title reads "AI Image Creation Confirmed". The user asks, "Was this image created with ai?" The AI response, labeled "Analysis & 1 more", states: "Yes, it appears that all or part of this image was created with Google AI. SynthID detected a watermark in 25-50% of the image."

It replied:

Yes, it appears that all or part of this image was created with Google Al. SynthID detected a watermark in 25-50% of the image.

Presumably that 25-50% figure is because the rest of the photo was taken by me - it was just the raccoons that were added by Nano Banana Pro.

Tags: google, ai, datasette, generative-ai, llms, gemini, text-to-image, llm-release, nano-banana

Quoting Nicholas Carlini

Previously, when malware developers wanted to go and monetize their exploits, they would do exactly one thing: encrypt every file on a person's computer and request a ransome to decrypt the files. In the future I think this will change.

LLMs allow attackers to instead process every file on the victim's computer, and tailor a blackmail letter specifically towards that person. One person may be having an affair on their spouse. Another may have lied on their resume. A third may have cheated on an exam at school. It is unlikely that any one person has done any of these specific things, but it is very likely that there exists something that is blackmailable for every person. Malware + LLMs, given access to a person's computer, can find that and monetize it.

Nicholas Carlini, Are large language models worth it? Misuse: malware at scale

Tags: ai-ethics, generative-ai, nicholas-carlini, ai, llms

Hotels: Occupancy Rate Decreased 4.1% Year-over-year

Hotel occupancy was weak over the summer months, due to less international tourism.  The fall months are mostly domestic travel and occupancy is still under pressure! 

From STR: U.S. hotel results for week ending 15 November
The U.S. hotel industry reported negative year-over-year comparisons, according to CoStar’s latest data through 15 November. ...

9-15 November 2025 (percentage change from comparable week in 2024):

Occupancy: 60.9% (-4.1%)
• Average daily rate (ADR): US$154.41 (-0.5%)
• Revenue per available room (RevPAR): US$93.97 (-4.6%)

The Veteran’s Day calendar shift drove a double-digit decline in group demand, resulting in lower performance levels across the U.S.
emphasis added
The following graph shows the seasonal pattern for the hotel occupancy rate using the four-week average.

Hotel Occupancy RateClick on graph for larger image.

The red line is for 2025, blue is the median, and dashed light blue is for 2024.  Dashed black is for 2018, the record year for hotel occupancy. 

The 4-week average of the occupancy rate is tracking behind last year and close to the median rate for the period 2000 through 2024 (Blue).

Note: Y-axis doesn't start at zero to better show the seasonal change.

The 4-week average will decrease seasonally until early next year.

On a year-to-date basis, the only worse years for occupancy over the last 25 years were pandemic or recession years.

SSC introduces streamlined ground station service

SSC Go

Swedish Space Corp. has rolled out a new ground station service designed to provide streamlined support for operators of small satellites and constellations.

The post SSC introduces streamlined ground station service appeared first on SpaceNews.

Thursday assorted links

1. Reddit thread on Beatriz Villaroel.

2. “Reading about the St. Louis Hegelians, a group of American orthodox Hegelians who thought they could dialectically prove St. Louis, Missouri was good

3. Suisun City and California Forever (NYT).

4. The male boom in Orthodox Christianity in the U.S. (NYT).

5. More on Harvard graduate cutbacks.

6. Paul Ekman, RIP.  And more here.

7. GPT-5.1 has been released, pretty quietly.

8. Summers will not finish the semester teaching at Harvard.

The post Thursday assorted links appeared first on Marginal REVOLUTION.

       

Comments

 

Space Force roadmap set to define what the service needs and why

Chief of Space Operations Gen. Chance Saltzman says work on the service’s “objective force” analysis is nearly complete, publication likely in 2026

The post Space Force roadmap set to define what the service needs and why appeared first on SpaceNews.

The ultimate backup: why humanity needs a lunar seed vault — now

The entrance to the Svalbard Global Seed Vault. Credit: Svalbard Global Seed Vault

Humanity is losing the genetic diversity that sustains life on Earth at a pace that should alarm every nation. According to the UN Food and Agriculture Organization, about 75% of the world’s crop varieties have disappeared in the last century. According to Marie Haga, former Executive Director of the Global Crop Trust, it’s closer to […]

The post The ultimate backup: why humanity needs a lunar seed vault — now appeared first on SpaceNews.

Voyager Technologies acquires Estes Energetics

The deal strengthens domestic access to energetics and propellants at a time of rising demand for munitions

The post Voyager Technologies acquires Estes Energetics appeared first on SpaceNews.

Reimagining space stations for the commercial age

Marshall Smith

In this episode of Space Minds, host Mike Gruss sits down with Marshall Smith, CEO of Starlab Space for a fireside chat at the Johns Hopkins University Bloomberg Center, the next installment of the Center’s Discovery Series.

The post Reimagining space stations for the commercial age appeared first on SpaceNews.

Industry expects Germany to increase ESA contributions

Pleyer

With ESA members set to decide on the agency’s budget for the next three years, all eyes on how much Germany will offer to support an ambitious series of programs.

The post Industry expects Germany to increase ESA contributions appeared first on SpaceNews.

Visa restrictions are bad for Indians—but maybe not for India

Remittances may fall, but opportunities are opening up

Economists get cold feet about high minimum wages

Governments are pushing the policy to its limits

Can the Chinese economy match Aruba’s?

Xi Jinping has lofty goals for 2035. But China faces a real problem

How James Comey’s Vindictive Prosecution Claim Fared In Court

ALEXANDRIA, VA—This morning’s hearing on James Comey’s motion to dismiss for vindictive and selective prosecution was largely overshadowed by the revelation that the indictment may not be valid because it was botched by interim U.S. Attorney Lindsey Halligan. You can read my initial report from court here.

It would be an epic way for the weaponized prosecution of Comey to end: the Trump loyalist with no prosecutorial experience so badly mishandling the basic nuts and bolts of grand jury practice that no indictment ever attached to Comey.

But a botched indictment only indirectly gets at the heart of the bad faith and ill motive that is driving the Comey prosecution, so let’s run through some of the highlights of the nearly hour-long argument that preceded U.S. District Judge Michael Nachmanoff pressing prosecutors for answers on their mishandling of the grand jury. Instead of recounting the arguments from both sides — former deputy Solicitor General Michael Dreeben for Comey and Nathaniel Lemons for the government — I want to zoom in on what most interested the judge and where his questions were most focused.

Is General Animus Toward Comey From Trump Enough?

The judge wanted to know whether the vindictive motive for the prosecution had to be in retaliation for exercising a constitutional right — in Comey’s case, his First Amendment right to freely criticize Trump — or if a claim of vindictive prosecution could be sustained if the retaliation was based merely on general animus toward the defendant. Comey’s position was that both were viable, and, ultimately, under questioning from Nachmanoff, Lemons agreed. That opens the door for Nachmanoff to consider all manner of Trump invective aimed at Comey. Dreeben seized on that concession, arguing that the basic legal framework was not in dispute.

Was There a DOJ Declination Memo?

Nachmanoff wanted to know from both sides if the Justice Department had issued a declination memo — a written explanation for why Comey should not be charged — like it had in the Letitia James case. Comey doesn’t know, and in the most contentious part of the hearing on the motion to dismiss, Lemons refused to say, claiming he didn’t have permission from DOJ higher-ups.

Nachmanoff, incredulous that a counsel of record in the case couldn’t answer whether there had been a declination memo, peppered Lemons with questions: You didn’t check to see if there was a declination memo? Did you seek out a declination memo? Did you seek to find out whether a prosecution memo was prepared? Did someone instruct you not to answer?

Lemons revealed that he didn’t have permission from deputy Attorney General Todd Blanche’s office to answer the question on the grounds that it was privileged work-product. The most he would say was that there had been lots of internal discussions and a “draft memo.”

For his part, Dreeben seemed on guard about the potential lack of a declination memo, I suspect because it’s better for his case if line prosecutors had recently recommended in writing against pursuing charges, like they did in the James case, and Halligan ignored them. But the judge seemed to be getting at a different point, which he expanded on later in the hearing.

If Halligan was appointed interim U.S. attorney on Sept. 22 and brought the Comey case to the grand jury on Sept. 25, then “what independent evaluation could she have done in that time frame?” the judge asked. The existence, or lack thereof, of declination and prosecution memos would help determine whether Halligan had really exercised independent judgment. Lemons demurred that that was a question to be ascertained if the judge ordered a discovery phase on the vindictive prosecution claim.

What About These Trump Remarks That You Didn’t Cite?

Nachmanhoff pushed both sides to address comments from Trump that he made to reporters the day after he posted on social media his notorious message to Attorney General Pam Bondi demanding she pursue the prosecution of Comey, James, and Sen. Adam Schiff. Noting that James had cited these remarks in her brief and Comey had not, Nachmanoff read most of them out loud:

“No, I just want people to act,” Trump said. “They have to act and we want to act fast. You know, they were ruthless and vicious. I was impeached twice. I was indicted five times. It turned out to be a fake deal. And we have to act fast! One way or the other. One way or the other. They’re guilty, they’re not guilty, we have to act fast. If they’re not guilty, that’s fine. If they are guilty, or if they should be charged, they should be charged. And we have to do it now.”

Dreeben seemed concerned that the judge was treating those remarks like a walk back of the social media post, but later when Nachmanoff pressed Lemons about the same remarks it became clear that the judge saw them as especially damning evidence against the government.

At one point, when Lemons argued that Comey’s vindictive prosecution claim was based entirely on anonymous sources, news reports, and conjecture, the judge brought him up short.

“You’re not saying these are not the words of the president?” Nachmanoff asked, citing the quote above. Lemons beat a hasty retreat.

A few moments later, the judge again brought Trump’s remarks up about “acting fast” and “guilty or not guilty,” asking Lemons: “How is that consistent with your practice when deciding whether to bring a case before the grand jury?”

Then, still focused on the Trump remarks that Comey hadn’t cited, Nachmanoff interrupted Lemons to ask his most pointed question about the vindictive prosecution claim: How is that consistent with the Justice Manual that you only bring cases if you believe the defendant will be found guilty beyond a reasonable doubt and the conviction upheld on appeal?

Lemon retreated to saying that even if Trump had improper motive, Comey had to prove that Halligan had the improper motive in her own mind. At which point, the judge made Comey’s case for him, telling Lemons that Comey’s argument is that Trump gave the order to prosecute in the social media post and reiterated it in follow up remarks.

At that moment in the hearing, Nachmanoff sounded convinced that the bar had been cleared for a successful vindictive prosecution claim.

Newsletter: NAR: Existing-Home Sales Increased to 4.10 million SAAR in October

Today, in the CalculatedRisk Real Estate Newsletter: NAR: Existing-Home Sales Increased to 4.10 million SAAR in October

Excerpt:
The fourth graph shows existing home sales by month for 2024 and 2025.

Existing Home Sales Year-over-yearSales were up 1.7% year-over-year compared to October 2024. The last 2 months of 2025 will have more difficult year-over-year comparisons.
...
Year-to-date, sales are essentially unchanged compared to last year - and 2024 was the lowest level of sales since 1995! Sales this year will be close to last year.

Will this be the lowest level of sales in 30 years?
There is much more in the article.

NAR: Existing-Home Sales Increased to 4.10 million SAAR in October

From the NAR: NAR Existing-Home Sales Report Shows 1.2% Increase in October
Month-over-month

• 1.2% increase in existing-home sales – seasonally adjusted annual rate of 4.10 million in October

• 0.7% decrease in unsold inventory – 1.52 million units equal to 4.4 months' supply

Year-over-year

• 1.7% increase in existing-home sales

• 2.1% increase in median existing-home sales price to $415,200
emphasis added
Existing Home SalesClick on graph for larger image.

This graph shows existing home sales, on a Seasonally Adjusted Annual Rate (SAAR) basis since 1994.

Sales in October (4.10 million SAAR) were up 1.2% from the previous month and were up 1.7% compared to the October 2024 sales rate.  

The second graph shows nationwide inventory for existing homes.

Existing Home InventoryAccording to the NAR, inventory decreased to 1.52 million in October from 1.53 million the previous month.

Headline inventory is not seasonally adjusted, and inventory usually decreases to the seasonal lows in December and January, and peaks in mid-to-late summer.

The last graph shows the year-over-year (YoY) change in reported existing home inventory and months-of-supply. Since inventory is not seasonally adjusted, it really helps to look at the YoY change. Note: Months-of-supply is based on the seasonally adjusted sales and not seasonally adjusted inventory.

Year-over-year Inventory Inventory was up 10.9% year-over-year (blue) in October compared to October 2024.

Months of supply (red) decreased to 4.4 months in October from 4.5 months the previous month.

I'll have more later. 

What HHS Secretary’s “Kiddie Killer” Kennedy’s ‘Gold Standard’ Science Actually Looks Like

Yesterday, the CDC, under the guidance of HHS Secretary “Kiddie Killer” Kennedy, updated its “Autism and Vaccines” page:

Screenshot 2025-11-20 at 8.21.35 AM

Like science denialists of all stripes, you’ll notice that they flipped the ‘null hypothesis.’ Rather than assuming vaccines do not cause autism, and then requiring evidence to demonstrate that they do, the corrupted CDC under Kennedy, starts with the false premise that vaccines do cause autism. Not only does this fly in the face of existing evidence, but, just by random chance leading to a false association, we would expect the occasional small-sample size study to find a spurious link, meaning that it will impossible to “rule out the possibility that vaccines cause autism.” This isn’t ‘gold standard science’, it’s a rigged game.

You also might notice that there’s no mention on the page of the massive benefits of vaccination in preventing childhood mortality and disability.

Naturally, this was done without notifying the relevant, in terms of actual expertise, CDC personnel. The chef’s kiss in this microbiological nightmare is the following disclaimer at the bottom of the page:

* The header “Vaccines do not cause autism” has not been removed due to an agreement with the chair of the U.S. Senate Health, Education, Labor, and Pensions Committee that it would remain on the CDC website.

I would like to wish every Republican senator who voted to confirm Kennedy–all but two of them–a hearty fuck you (and no Democrats voted for him).

Also, everyone who voted for Trump or sat out the election because they’re too fucking saintly to live in the real world owns this crap.

Impeach Kennedy. Impeach him now.

Weekly Initial Unemployment Claims Decrease to 220,000

The DOL reported:
In the week ending November 15, the advance figure for seasonally adjusted initial claims was 220,000, a decrease of 8,000 from the previous week's level. The 4-week moving average was 224,250, a decrease of 3,000 from the previous week's average.
emphasis added
The following graph shows the 4-week moving average of weekly claims since 1971.

Click on graph for larger image.

The dashed line on the graph is the current 4-week average. The four-week average of weekly unemployment claims decreased to 224,250.

The graph includes all the missing weeks while the government was shutdown.

September Employment Report: 119 thousand Jobs, 4.4% Unemployment Rate

From the BLS: Employment Situation
Total nonfarm payroll employment edged up by 119,000 in September but has shown little change since April, the U.S. Bureau of Labor Statistics reported today. The unemployment rate, at 4.4 percent, changed little in September. Employment continued to trend up in health care, food services and drinking places, and social assistance. Job losses occurred in transportation and warehousing and in federal government.
...
The change in total nonfarm payroll employment for July was revised down by 7,000, from +79,000 to +72,000, and the change for August was revised down by 26,000, from +22,000 to -4,000. With these revisions, employment in July and August combined is 33,000 lower than previously reported.
emphasis added
Employment per monthClick on graph for larger image.

The first graph shows the jobs added per month since January 2021.

Total payrolls increased by 119 thousand in September.  Private payrolls increased by 97 thousand, and public payrolls increased 22 thousand (Federal payrolls decreased 35 thousand).

Payrolls for July and August were revised down by 33 thousand, combined.  The economy lost jobs in both June and August.

Year-over-year change employment The second graph shows the year-over-year change in total non-farm employment since 1968.

In September, the year-over-year change was 1.31 million jobs.  

Year-over-year employment growth is slowing sharply.



The third graph shows the employment population ratio and the participation rate.

Employment Pop Ratio and participation rate The Labor Force Participation Rate increased to 62.4% in September, from 62.3% in August. This is the percentage of the working age population in the labor force.

The Employment-Population ratio was increased to 59.7% from 59.6% in August (blue line).

I'll post the 25 to 54 age group employment-population ratio graph later.



unemployment rateThe fourth graph shows the unemployment rate.

The unemployment rate was increased to 4.4% in September from 4.3% in August.

This was above consensus expectations, however, July and August payrolls were revised down by 33,000 combined.  

Overall another weak report.

I'll have more later ...

Scam USPS and E-Z Pass Texts and Websites

Google has filed a complaint in court that details the scam:

In a complaint filed Wednesday, the tech giant accused “a cybercriminal group in China” of selling “phishing for dummies” kits. The kits help unsavvy fraudsters easily “execute a large-scale phishing campaign,” tricking hordes of unsuspecting people into “disclosing sensitive information like passwords, credit card numbers, or banking information, often by impersonating well-known brands, government agencies, or even people the victim knows.”

These branded “Lighthouse” kits offer two versions of software, depending on whether bad actors want to launch SMS and e-commerce scams. “Members may subscribe to weekly, monthly, seasonal, annual, or permanent licenses,” Google alleged. Kits include “hundreds of templates for fake websites, domain set-up tools for those fake websites, and other features designed to dupe victims into believing they are entering sensitive information on a legitimate website.”

Google’s filing said the scams often begin with a text claiming that a toll fee is overdue or a small fee must be paid to redeliver a package. Other times they appear as ads—­sometimes even Google ads, until Google detected and suspended accounts—­luring victims by mimicking popular brands. Anyone who clicks will be redirected to a website to input sensitive information; the sites often claim to accept payments from trusted wallets like Google Pay.

Organ procurement centers (OPOs) are responding to changes in their performance evaluations (by Bae, Sweat, Melcher and Ashlagi in JAMA Surgery)

 Here

Bae H, Sweat KR, Melcher ML, Ashlagi I. Organ Procurement Following the Centers for Medicare and Medicaid Services Performance Evaluations. JAMA Surg. Published online November 19, 2025. doi:10.1001/jamasurg.2025.5074 

"In 2024, 4639 patients died in the United States while waiting for a transplant from deceased donors.1 Organ procurement organizations (OPOs) are government contractors responsible for identifying potential donors in a geographical region, recovering their organs, and implementing the offering processes to patients on the waiting list. In 2020, 10% of potential donors—individuals younger than 76 years with inpatient death and organs suitable for transplant—became organ donors, suggesting an opportunity to increase donation and transplant rates.2

"Toward this goal, the Centers for Medicare and Medicaid Services issued a final rule in December 2020 to increase transparency of OPO performances by monitoring several metrics. OPOs are placed into 3 tiers based on donation rate and donor age–adjusted transplant rates, although acceptance of organ offers is up to patients and transplant centers. OPOs that perform poorly on both metrics are placed into tier 3 and are at risk of decertification in 2026.3 This longitudinal study examines changes in OPOs’ organ recovery practices following the initial report released in September 2021, focusing on the number and quality of organs recovered and the resulting transplant rates. 

 

 

 

 

 

 

 "The findings suggest that the 2021 release of the report on OPO performance was associated with increased organ recovery among low-performing OPOs, narrowing the gap in organ donation with high-performing OPOs. Even though the gap in the transplant rate has narrowed, much of it is linked to increased organ recovery from older donors, which may limit improvements in transplant rates. This is despite an increase in organs placed out of sequence by low-performing OPOs."

Confidently Wrong

If you’re going to challenge a scientific consensus, you better know the material. Most of us, most of the time, don’t—so deferring to expert consensus is usually the rational strategy. Pushing against the consensus is fine; it’s often how progress happens. But doing it responsibly requires expertise. Yet in my experience the loudest anti-consensus voices—on vaccines, climate, macroeconomics, whatever—tend to be the least informed.

This isn’t just my anecdotal impression. A paper by Light, Fernbach, Geana, and Sloman shows that opposition to the consensus is positively correlated with knowledge overconfidence. Now you may wonder. Isn’t this circular? If someone claims the consensus view is wrong we can’t just say that proves they don’t know what they are talking about. Indeed. Thus Light, Fernbach, Geana and Sloman do something clever. They ask respondents a series of questions on uncontroversial scientific topics. Questions such as:

1. True or false? The center of the earth is very hot: True
2. True or false? The continents have been moving their location for millions of years and will continue to move. True
3. True or false? The oxygen we breathe comes from plants: True
4. True or false? Antibiotics kills viruses as well as bacteria: False
5. True or false? All insects have eight legs: False
6. True or false? All radioactivity is man made: False
7. True or false? Men and women normally have the same number of chromosomes: True
8. True or false? Lasers work by focusing sound waves: False
9. True or false? Almost all food energy for living organisms comes originally from sunlight: True
10. True or false? Electrons are smaller than atoms: True

The authors then correlate respondents’ scores on the objective (uncontroversial) knowledge with their opposition to the scientific consensus on topics like vaccination, nuclear power, and homeopathy. The result is striking: people who are most opposed to the consensus (7, the far right of the horizontal axis in the figure below) score lower on objective knowledge but express higher subjective confidence. In other words, anti-consensus respondents are the most confidently wrong—the gap between what they know and what they think they know is widest.

In a nice test the authors show that the confidently wrong are not just braggadocios they actually believe they know because they are more willing to bet on the objective knowledge questions and, of course, they lose their shirts. A bet is a tax on bullshit.

The implications matter. The “knowledge deficit” approach (just give people more fact) breaks down when the least-informed are also the most certain they’re experts. The authors suggest leaning on social norms and respected community figures instead. My own experience points to the role of context: in a classroom, the direction of information flow is clearer, and confidently wrong pushback is rarer than on Twitter or the blog. I welcome questions in class—they’re usually great—but they work best when there’s at least a shared premise that the point is to learn.

Hat tip: Cremieux

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Angles of love

Black-and-white photo of hands framing the sky with a modern building in the background.

What is love to you? An artist focuses on the hands and gestures of his subjects as they reflect on this boundless question

- by Aeon Video

Watch on Aeon

Our phosphorescent world

Photo of rugged limestone formations at sunset with a partly cloudy sky and sea visible in the background.

This life-giving element, stored in rock and organic material, moves around Earth in an ancient cycle we have just broken

- by Jack Lohmann

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Mexico facts of the day

I have been expecting this for a long time, but it came more quickly than I thought:

Mexico is now the world’s top buyer of U.S. goods, according to data released by the U.S. government on Wednesday, outpacing Canada for the first time in nearly 30 years.

The data highlighted how Mexico and the United States have, despite periodic political tensions, become deeply intertwined in business, and how much global trade patterns have shifted in a short period. Only two years ago, Mexico became the country that sold the most goods to the United States, surpassing China.

“Mexico is the United States’ main trading partner,” said Marcelo Ebrard, Mexico’s economy minister, during the president’s daily news conference on Wednesday.

Here is more from the NYT.  Via Brian Winter.  As I have been telling people for decades now, visiting Mexico, learning about Mexico, and learning Spanish are very good investments in understanding the world, most of all if you live in the USA.

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American democracy is very much alive, though not in all regards well

The Democrats who won in the November elections are all going to assume office without incident or controversy.

The Supreme Court is likely to rule against at least major parts of the Trump tariff plan, his signature initiative.  Trump already has complained vocally on social media about this.  He also preemptively announced that some of the food tariffs would be reversed, in the interests of “affordability.”

National Guard troops have been removed from Chicago and Portland, in part due to court challenges.  The troops in WDC have turned out to be a nothingburger from a civil liberties point of view.

Here is an account of November 18 and all that happened that day:

* House votes 427-1 to release the Epstein files, a veto-proof+ majority

* A federal judge blocked GOP redistricting map in Texas, meaning net net with CA measure passed, Democrats could pick up seats for 2026, KARMA!

* A federal appeals court, including two Trump appointed judges, rejected Trump’s defamation lawsuit against CNN over the term “Big Lie,” finding the case meritless

* Corporate Public Broadcasting agree to fulfill its $36 million annual contract with NPR, after a judge told Trump appointees at CPB that their defense was not credible

* A NY judge dismissed Trump’s calling of New York’s law barring immigration arrests in state and local courthouses.

The Senate also sided with the House on the Epstein files.  Nate Silver and many others write about how Trump is now quite possibly a lame duck President.

I do not doubt that there are many bad policies, and also much more corruption, and a more transparent form of corruption, which is corrosive in its own right.  But it was never the case that American democracy was going to disappear.  That view was one of the biggest boo-boos held by (some) American elites in recent times, and I hope we will start seeing people repudiating it.

I think the causes of this error have been:

1. Extreme dislike of the Trump administration, leading to emotional reactions when a bit more analysis would have done better.

2. Pessimism bias in the general sense.

3. Recency bias — for the earlier part of the term, Congress was relatively quiescent.

4. Cognitive and emotional inability to admit the simple truth of “democracy itself can lead to pretty bad outcomes,” thus the need to paint the status quo as something other than democracy.

5. The (largely incorrect) theory of good things happening in politics is “good people will them,” so from that starting point if you see bad people willing bad things you freak out.  The understanding was never “spontaneous order” enough to begin with.

Any other?

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Google Scholar Labs

Brings AI to Google Scholar, find it here.  Via Joshua Gans.  And yes this does mean that the academics also are, or at least ought to be, writing for the AIs.

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Thursday: Existing Home Sales, September Employment Report, Unemployment Claims

Mortgage Rates Note: Mortgage rates are from MortgageNewsDaily.com and are for top tier scenarios.

Thursday:
• At 8:30 AM ET, The initial weekly unemployment claims report will be released.  The consensus is for 223K initial claims.

• Also at 8:30 AM, Employment Report for September.   The consensus is for 43,000 jobs added, and for the unemployment rate to be unchanged at 4.3%.

• Also at 8:30 AM, the Philly Fed manufacturing survey for November. The consensus is for a reading of 2.0, up from -12.8.

• At 10:00 AM, Existing Home Sales for October from the National Association of Realtors (NAR). The consensus is for 4.08 million SAAR, up from 4.06 million in September.

• At 11:00 AM, the Kansas City Fed manufacturing survey for November.

Widespread Rain from Texas to the Central Appalachians; Heavy to Excessive Rainfall in Southern California and the Southwest

Group Chats in ChatGPT Now Available Worldwide

OpenAI:

Early feedback from the pilot has been positive, so we’re expanding group chats to all logged-in users on ChatGPT Free, Go, Plus and Pro plans globally over the coming days. We will continue refining the experience as more people start using it.

That didn’t take long — the initial rollout limited to Japan, New Zealand, Korea, and Taiwan started just three days ago.

 ★ 

CPHC Central North Pacific Outlook


Central North Pacific 2-Day Graphical Outlook Image
Central North Pacific 7-Day Graphical Outlook Image


ZCZC HFOTWOCP ALL
TTAA00 PHFO DDHHMM

Tropical Weather Outlook
NWS Central Pacific Hurricane Center Honolulu HI
Issued by NWS National Hurricane Center Miami FL
800 PM HST Fri Nov 21 2025

For the central North Pacific...between 140W and 180W:

Tropical cyclone formation is not expected during the next 7 days.

$$
Forecaster Gibbs
NNNN


NHC Atlantic Outlook


Atlantic 2-Day Graphical Outlook Image
Atlantic 7-Day Graphical Outlook Image


ZCZC MIATWOAT ALL
TTAA00 KNHC DDHHMM

Tropical Weather Outlook
NWS National Hurricane Center Miami FL
100 AM EST Sat Nov 22 2025

For the North Atlantic...Caribbean Sea and the Gulf of America:

Tropical cyclone formation is not expected during the next 7 days.

$$
Forecaster Gibbs
NNNN


NHC Eastern North Pacific Outlook


Eastern North Pacific 2-Day Graphical Outlook Image
Eastern North Pacific 7-Day Graphical Outlook Image


ZCZC MIATWOEP ALL
TTAA00 KNHC DDHHMM

Tropical Weather Outlook
NWS National Hurricane Center Miami FL
1000 PM PST Fri Nov 21 2025

For the eastern and central North Pacific east of 180 longitude:

Tropical cyclone formation is not expected during the next 7 days.

$$
Forecaster Gibbs
NNNN