Anathemata

BREAKING: A robot developed by Caltech and funded by DARPA has successfully built part of a structure in orbit without astronauts, marking what researchers describe as the first autonomous construction of a structure in space. The experiment, called ASTRA, uses a robotic arm to retrieve individual structural tubes and connecting joints, then assemble them into sections of a larger framework directly in orbit. Launched aboard a SpaceX Falcon 9 in March, the system has spent approximately six months in space testing the technology. The robot successfully constructed a new section of a truss structure, demonstrating that spacecraft could eventually assemble large structures from smaller components rather than launching them fully assembled. The experiment is part of DARPA's NOM4D program, which aims to enable construction of enormous structures in orbit, potentially hundreds of meters or even kilometers across. Potential applications include: > Giant space telescopes > Large satellite communications antennas > Orbital solar power stations >Future space infrastructure too large to fit inside conventional rockets The demonstration did not complete the full planned antenna, but establishes an important proof of concept for autonomous orbital construction. The technology could eventually allow the size of structures built in space to exceed the physical limits of the rockets used to launch their components. Link to official report submitted by Caltech: sciencedaily.com/releases/20…

Nuclear Regulators NukeCorp: Good Morning. We want to move a barrel of stuff from here… A. To there… B. Regulator: What if someone shoots the barrel with a tomahawk missile whilst you are moving it? NukeCorp: But why would? I mean who even? Are you serious? Regulator: We’re going to have to see empirical data. Can we see your tomahawk missile barrel-strike test procedure? I presume you have one? NukeCorp: 😖

MIT and Harvard built an AI simulation containing 8.3 billion virtual people, roughly the entire population of planet. They call it MatrAIx. It’s a population-scale simulation running on frontier models, GPT and Claude among them. The longer description took me a while to believe. Start with the dataset, Persona 8B. 8.3 billion synthetic profiles, each one specified across 1,290 dimensions. Background, psychology, spending habits, how comfortable they are with technology, what they do on a Tuesday night, the small behavioral quirks that make one 34-year-old nurse in NYC different from another. A spreadsheet of 8 billion rows would be a curiosity. What they did next is the part that matters. They turned the profiles into agents and dropped them into four environments: surveys, AI chat interfaces, live web browsing, and native desktop and mobile apps. Then they ran real products through the crowd. New features, software updates, pricing changes. And they logged everything. How long an agent paused after seeing a price go up. The exact point at which it gave up on a broken checkout. How much lag it would sit through before closing the app. The number I keep coming back to is 91.5%. That’s how often the agents stayed in character, behaving the way their assigned psychology and demographics said they should. Not perfect. But for billions of agents across four environments, closer than I expected. Here’s what that does to how products get built. Right now, if you want to know whether a feature will land, you ship it to a slice of users and wait. Or you pay a research firm and wait longer. Either way the answer arrives in weeks, from a sample you hope is representative. With something like this, you run the feature past 8 billion simulated reactions overnight. One server. Results by morning, broken down by every one of those 1,290 dimensions if you want them. I have questions about how well a synthetic crowd predicts a real one. 91.5% is persona adherence, not forecast accuracy, and those are different things. But the direction is clear, and it’s coming faster than most product teams are ready for.

Wow, no one could have possibly predicted that late-20th century “historiography” would be less accurate than the ancient sources that they hate so much.

I went to see last night “The Standard of Living”, the play now in London about John Maynard Keynes’s life, and I really enjoyed it. It captures well his life and the times. However I disagree with an important part of the economics, a confusion that is behind the entire economic policy debate in Britain and the rest of Europe today: the confusion between Beveridge and Keynes. The report by William Beveridge (an LSE economist and ex-director) led to an enormous expansion of the welfare state. That is often confused (also in the play) with Keynes’s views, as if the large and continuously growing post-war welfare state had anything to do with demand stabilization. Keynesian demand management is what Andrés Velasco (also an LSE prof), as Finance Minister in Chile, did during the 2000s copper boom: he ran surpluses of 7% of GDP and more in 2006 and 2007 and put the money in a stabilization fund abroad. This was 12% of GDP by the end of 2008, when public debt was 4% of GDP. Public sector workers burned his effigy in Santiago asking for it to be spent. When the copper price collapsed along with the global economy, this surplus allowed him to introduce a massive stimulus package worth 2.8% of GDP, larger relative to the economy than the American one, which allowed him to stabilize Chile’s economy through the financial crisis. “Being a Keynesian means being one in both parts of the cycle,” he told The Economist. Today, very few governments are doing this. It is “whatever it takes” in crisis, and “welfare is untouchable” when the crisis finishes. This leads to a continuous ratchet up of spending that strangles any productive activity. Keynes was in favour of using debt to stimulate demand, but under no circumnstances to finance permanent welfare spending. He wanted an ordinary budget for the state and then a capital budget that would be used for the demand management and that would be invested only in productive capacity. While Beveridge was about social redistribution, an issue of social policy, Keynes was about stabilization. The play and a lot of commentary seem to conflate both things and use demand management to justify permanent structural social policy. I think this is pretty instructive for what’s happening in the UK and in the rest of Europe today. There is a widespread confusion that it’s neoliberalism which is hollowing out the state, when in fact the UK’s public spending burden is at around 45.6% of GDP this year, and the OBR expects it to stay around 45% for ten years running, the longest sustained period of spending this high since the Second World War; EU governments spend 49.5% of GDP (Eurostat, 2025). Outside wartime and the pandemic, the state has never been this large for this long. Neither neoliberalism nor austerity is at fault for the lack of investment. Governments cannot hit the fiscal rules without touching the triple lock, and other welfare entitlements (free transport for the over 60s here in London!) that most MPs consider untouchable. What gets cut all the time to make the numbers add up is infrastructure, energy, grids, R&D, innovation, etc. The UK’s gross fixed capital formation is at 18-19% of GDP, which is the lowest in the G7, and the general government investment is also behind the OECD average. The debate misunderstands the risk of pension sustainability. It is not that at some point in the future pensions become unsustainable. It is that today, their relentless growth eliminates the space to invest in infrastructure, innovation and the rest. Sadly, no party dares to make this argument. And even economists who defend the entrepreneurial or innovative state cannot bring themselves to state the obvious: that there is a huge opportunity cost in having one of every 5 new cars sold in the UK being paid by the state as a disability benefit, or in having free transport for all over 60 year olds.