Monday, April 27, 2026

Capital Markets: "New Iranian Proposal Helps Bolster Risk Appetites"

From Marc Chandler at Bannockburn Global  Forex:

The breakdown of talks between the US and Iran initially warned of a risk-off session, but a new Iranian proposal appears to have revived the hopes of a resolution. The US dollar is trading softer and equities in Asia Pacific and Europe rose while bond yields were under pressure. The front month crude oil contracts are trading around $2 a barrel higher. 

There are two other developments to note. First, with the Justice Department suspending its probe into the Federal Reserve, Warsh is set to be confirmed as the next Fed chair on Wednesday. When Justice Department made the announcement, the implied chances of a Fed cut by the end of the Beijing’s shadow trade with Iran, sanctioning shipping vessels and a large Chinese refinery. Lastly five G10 central banks meet this week, starting the BOJ tomorrow. None are expected to adjust policy, but hawkish holds are anticipated....

....MUCH MORE 

"Quantum photonics roadmap — how Xanadu and PsiQuantum are looking to transfer qubits through beams of light"

From Tom's Hardware, April 16:

How two companies are using novel approaches to transfer quantum Qubits. 

This article is part of a series documenting quantum computing technologies and their ecosystem – the differing approaches, the key players behind them, and the key technologies that are driving us towards a quantum future. Part one looked at superconducting qubits (materialized in key industry giants such as IBM and Google) and trapped ion qubits (through IonQ and Quantinuum).

In this second part, we’ll be looking at quantum photonics – a light-based technique of defining the quantum unit of computation, the qubit. We’ll take a brief look at the what and the why of quantum photonics, and then materialize it by focusing on two particular companies, their roadmaps, and their technologies: Toronto-based Xanadu Quantum Technologies (which is making a play for public Nasdaq listing this first quarter of 2026 at an estimated 3.6B$ enterprise valuation through a SPAC deal); and the Palo Alto, California-headquartered PsiQuantum (PSIQ.PVT, with an estimated 7B$ valuation buoyed by a 1$ billion worth Series E funding round in late 2025).

Like our previous roadmap analysis, this won’t be a technical article; it’s a technology and roadmap analysis that brings understandable bites on the underlying technologies, their roadmap evolution, current state, and expected next steps. For a better understanding of what quantum computing is all about, Tom’s Hardware has a more explanatory quantum computing article you can familiarize yourself with first.

What is Quantum Photonics?
To answer what quantum photonics actually is, we have to start with the most basic: photonics is the use of light to transmit encoded information. The most widespread application of photonics that’s already a part of our infrastructure today materializes through fiber optic cables: within them, light travels at its speed (which matters for latency) and crucially, without energy losses to electrical resistance.

Because light can contain multiple wavelengths (think colors, ranging through the visible spectrum and beyond), information in fiber optic cables can be encoded in multiple paths within the same ray (a technique known as multiplexing) for increased bandwidth.

This classical approach to photonics uses billions of photons (the essential unit of light) in coherent beams, using other elements such as phase and polarization as data carriers. Classical photonics is already a well-known quantity, with multiple applications in both intercontinental information transit, data center interconnects, and more specifically, inter-chip communication.

The transition towards the quantum realm occurs when you stop looking at light as a beam and focus on the singular elements that compose it: photons. Quantum photonics, then, makes use of single-photon sources and single-photon detectors to encode and decode information through the specific strengths of quantum properties: entanglement (where two entangled photons become a coherent system) and superposition (where the universe of possible information values can be contained in a single qubit until interfered with).

This brings us to the great differentiator in current quantum photonics: the way operations are run on individual photons, and how information is encoded within them. PsiQuantum uses what’s known as a dual-rail encoding approach: informational states are derived from looking at a photon’s “choice” between path A (0) and path B (1) (these paths being known as waveguides). Xanadu approaches it through the lens of continuous-variable encoding: instead of looking at the photon itself, it looks at the photon’s light field and how it’s distributed (across properties like amplitude and phase), ‘squeezing’ them (reducing uncertainty in the amplitude variable at the cost of increased uncertainty in phase) to encode data.

These are two fundamentally different ways of obtaining the result of a photonics-based, large-scale, error-corrected quantum computer, each with its own set of engineering problems. The end-goal, however, is the same: when you can generate, manipulate, and measure individual photons, light stops being a mere transmission medium, and individual particles become the computational substrate itself.

Advantages, challenges, and the mechanics of photonic qubits
Quantum photonics is claimed to have some operational advantages over other approaches: unlike superconducting qubits, photons can be operated on at room temperature, theoretically reducing both installation, running, and maintenance costs.

The natural physical makeup of photons also means that photonic qubits are less susceptible to environmental interference, such as electromagnetic noise and thermal fluctuations. Scaling-wise, photonics-based chips can leverage semiconductor manufacturing infrastructure, and the natural speed of light means that gate times (gate operations being the result of inter-qubit operations towards a useful result) should have a higher operational limit compared to other approaches, such as trapped ions.

There’s always an opportunity cost in each quantum approach, however. In PsiQuantum’s dual-rail approach, identical photons that can be reliably entangled are very hard to generate: minute differences in wavelength, polarization, and spatial modes destroy systemic equilibrium and reliability. Photon generation (which is usually accomplished by shining a laser through a crystal) is a probabilistic operation: sometimes no photon is generated; sometimes, one is; and sometimes, more than that.

All of this leads us to the harsh truth that in quantum photonics - particularly in its dual-rail design - it’s easy to lose more than 90% of the generated photonic qubits (at generation or collection) before they ever get a chance to perform a useful computation. This means that to generate a 100-qubit photonic system, upwards of 10,000 photons must be generated. Everything else is lost.

PsiQuantum’s way of operating on individual photons means there’s no informational backup, such as what you’d get when operating on classical light beams: when the photon is lost, everything is. You can amplify billions of photons when they are a beam, but you can’t do the same for a single photon (a quirk of quantum mechanics known as the no-cloning theorem). And being incredibly small particles, a minute error in the photon’s directionality means that the emitted particle can easily fail to be detected on the other end (think of how a small angular difference at a bullet’s exit compounds on missing the bullseye).

Xanadu’s approach, on the other hand, sidesteps the requirement for photonic “perfection” at generation and is more tolerant to photon loss (the light fields don’t completely vanish on individual photon loss). But it does introduce different error correction challenges – errors are continuous (noise is present in amplitude and phase measurements), while PsiQuantum’s issues are discrete (photon present vs photon absent, resulting in discrete bit flips in calculations).

Clearly, the base technology of photonics can serve very different approaches. PsiQuantum bets that silicon photonics manufacturing can overcome the drawbacks of their dual-rail approach through scale and engineering precision to reduce errors and improve photon measurement reliability, while Xanadu’s intrinsically higher tolerance to process imperfections enables a faster timeline to quantum advantage, or so they hope....

....MUCH MORE, they go deep. 

Possibly also of interest, at Barron's:

"...How to Pretend You Understand Quantum Computing."

"What will be scarce?"

From Ghosts of Electricity substack, April 14:

The economics of structural change and the post-commodity future of work 

Starbucks is a huge company (market cap of $112 billion) that sells one of the most standardized products in the modern economy. Making a cup of coffee or even one of the fancy specialty drinks is very easy to mechanize and reproduce. If the entire economy is soon to be automated, with labor being replaced with increasingly more sophisticated capital, Starbucks should be a canary in the coal mine—the technology for removing labor from its stores and replacing it with automated capital has been around for years. Over the past few years, Starbucks has done exactly that: in efforts to increase thin margins, management has automated more and more of the coffee-making business and instituted tightly mechanized processes for delivering it to customers. But instead of increasing automation, the opposite has happened. After trying to streamline the store experience with fewer workers and more automation, the company concluded that this had been a mistake. CEO Brian Niccol said that ``handwritten notes on cups’’, ceramic cups, and ``the return of great seats’’ had led more customers to ``sit and stay in our cafes’’, showing that ``small details and hospitality drive satisfaction.’’ More baristas are being hired per store and automation is being rolled back.

Economics is the study of decision-making under constraints, i.e., scarcity. If advanced AI brings material abundance—if machines can produce many if not all forms of human production at very low marginal cost—does economics become irrelevant? No, we will still have scarcity, but the kind of scarcity that matters will change. Ultimately the answer to any question about the future economics of advanced AI begins with identifying what becomes scarce. After answering that question, the rest of the analysis is pretty straightforward. In this essay I’m going to explore what becomes scarce when automation can replicate many if not all human production, and what that may mean for the types of jobs that emerge.

Before industrialization, it was difficult to separate a product from the person who made it. The weaver who made your shirt, the baker who made your bread: you personally knew them, and their skill and reputation were tied to the product that they sold. Economic transactions had a distinct social component that was innately linked to the consumption experience. The industrial production process changed this by breaking craft into standardized, repeatable steps. Performed by workers based on predetermined and regularized steps, capitalism produced something new: the commodity form, in which a product’s value lies in the product itself, detached from whoever made it. A table is a table, a phone is a phone. The screen that you’re reading this essay on was designed in one country, manufactured in another, using components from around the world. But none of this matters for the experience of buying and using the device.

Marx described this process in intentionally loaded language. The commodity form, he argued, was built on exploitation: the ability to pay workers less than the value of what they produce. They were able to do this because the capitalist production process was based on alienation: severing workers from the product of their labor, from the process of making it, and ultimately from each other. What had once been a person’s craft became abstract ``labor power,’’ a factor of production to be bought and sold like raw materials. Marx saw this as capitalism’s deepest pathology. But to economists, and to the world writ large, the commodity form was an engine of extraordinary prosperity. If production was no longer tied to specific people, it could be disaggregated, reorganized, shipped across oceans, and scaled in ways that turned few resources into vast riches. Both things were true at once: the commodity form created enormous wealth and prosperity, but it made the human behind any specific product invisible, and ultimately, replaceable.

This is most people’s mental model of what AI will do to the economy. If a machine can produce anything a human can, write the brief, generate the image, compose the song, determine the diagnosis from a radiology scan, then the human will be replaced across all facets of production and jobs will simply disappear. Labor will be replaced with capital. David Autor and Neil Thompson push back on this in an important recent paper. They argue that AI won’t simply eliminate jobs; it will reshape the economic value of human expertise. Their framework distinguishes between expert and inexpert tasks within any given occupation. When automation removes the simpler tasks (as accounting software did for bookkeeping clerks), the remaining work becomes more specialized, wages rise, and fewer workers qualify. When it removes the harder tasks (as inventory management systems did for warehouse workers), the job becomes more accessible, employment expands, and wages fall. Same technology, opposite labor market outcomes, depending on which part of the job gets automated.

But Autor and Thompson also consider a starker possibility: that AI advances to the point where human expertise loses its economic value altogether....

....MUCH MORE 

Sunday, April 26, 2026

U.S. Treasury Secretary Bessent On A.I.: "'a year, maybe 18 months,' before the new technology defines our lives across the board."

That's at the Wall Street Journal, April 24:

The Weekend Interview 

Scott Bessent: Donald Trump’s Economic Engineer
The Treasury secretary looks ahead to the Beijing summit and discusses AI, energy, taxes, bank regulation and more.

Washington
President Trump has a lot of big goals: completing a grand ballroom and a giant arch, putting a covey of his enemies in prison, winning a Nobel Peace Prize. Most of all, he wants the American economy to roar so loudly that no one can deny it’s the greatest financial power in history.

No one has more responsibility for achieving that goal than Scott Kenneth Homer Bessent, star quarterback of Mr. Trump’s economic team in his rookie season in government. According to many of Mr. Bessent’s former Wall Street colleagues, however, his task has been made manifestly harder by Mr. Trump’s tariffs and the Iran war.

The central components of the Treasury secretary’s agenda include restoring growth after the havoc of war, rebalancing global trade, driving down inflation without choking expansion, lifting real wages for the bottom half of earners, and reasserting American dominance in the industries that will determine the next generation of prosperity—chips, artificial intelligence, energy. His portfolio would be daunting even in peacetime. In the aftermath of a regional conflict and amid a trade confrontation with the world, it is a stress test of both policy and temperament.

In several conversations in his office, Mr. Bessent, 63, speaks about all these global challenges the way a trader might talk about a volatile market: with a mixture of confidence and probabilistic hedging. As he learned early from his macroeconomic mentor, George Soros, and has been reminded by Mr. Trump, risk is something not to be feared, but understood and leveraged. “George Soros is willing to take unlimited market risk,” Mr. Bessent says, “but has incredible survival instincts. The president is willing to take unlimited political risk, but knows when to cut.” 

Growth has slowed, but Mr. Bessent insists it will recover. Energy prices will normalize. What he calls the “buffet”—the spread of economic benefits to every household—will still be set out, although delayed from the second quarter of 2026 to the third, perhaps not coincidentally right before the midterm elections that are vitally important to the White House.

China is the most urgent item in Mr. Bessent’s inbox. For all the noise around tariffs, Mr. Bessent’s responsibility is to manage the integrity of the U.S.-China relationship, which will largely define whether the Trump economy is a success. He presents a formulation that sounds simple but contains a dozen tensions: “We have to derisk but not decouple.”

What does that mean? Mr. Bessent sketches a picture that is less rupture than recalibration. Trade continues. American companies still operate in China. The U.S. still sells agriculture, energy, financial services and software. But in three areas—critical minerals, medicines, and semiconductors—America becomes meaningfully independent.

“We’re pretty far along,” he says of rare-earth minerals. “I would say it’s a step function every nine months and probably completely resolved in four years.”

That timeline underscores the central contradiction in Mr. Bessent’s China policy. He insists the coming summit with Xi Jinping is about “stability,” avoiding escalation, keeping the relationship predictable. Yet nearly every concrete move he describes is designed to reduce dependence on the Chinese, thus minimizing Beijing’s leverage.

The recent tariff spiral sharpened the point. As tariffs rose, China deployed nontariff measures, including restrictions on exports of rare-earth magnets. The U.S. responded by applying its own forms of pressure—data controls, technology limitations, student-visa rules. “We have leverage,” Mr. Bessent says, almost casually. “
 
Whether it’s aircraft engines or silicon quartz, the Chinese students, [it] really bothered them.”
 
The deeper view he offers of China is historical, even civilizational. “They believe that they were the Middle Kingdom,” he says, invoking the Qing Dynasty. “I think they want to get back to that equilibrium where the world comes to them.”

This isn’t the language of benign competition but of strategic rivalry and sober mistrust, softened only slightly by the possibility of “peaceful coexistence.” China, he notes, “has never had allies. They have vassal states.”Yet in the same breath, Mr. Bessent argues that the goal of the summit circuit—no fewer than four Trump-Xi meetings this year, including a Xi state visit to the White House in September, the Asia-Pacific Economic Cooperation summit in Beijing in November, and the Group of 20 at Doral, Fla., in December—is to keep relations steady, almost routine. The stakes are “not that high,” Mr. Bessent says, “because everything gets pregamed.” The tension between those two ideas—China as existential competitor and China as manageable counterpart—runs through the entire approach. 
 
But the subtext is clear—Mr. Bessent remains staunchly wary, both culturally and commercially. “We founded the World Bank and the IMF,” he says, “whereas the Chinese just want to be part of it and take it over, and they also formed the Belt and Road and the Asian Infrastructure Bank. But I think the difference is we were in it for more soft-power reasons; they are in it for more hard-power reasons.” 
 
If China is the casino, artificial intelligence is the table stakes. “If we don’t win in AI,” Mr. Bessent says, “then it’s game over.” He speaks with the urgency of someone who believes the timeline has collapsed. It isn’t five years, or even two, but “a year, maybe 18 months,” before the new technology defines our lives across the board.
 
The implications, as he describes them, are both sweeping and oddly mundane. Entire categories of work could be compressed into a fraction of their current cost. Small businesses could operate with a handful of employees and a suite of AI agents. Productivity gains could ripple across the economy in ways that are difficult to predict but impossible to ignore.....
....MUCH MORE 

Malacca Strait: How one volcano could trigger world chaos

From the BBC, 17 January 2023:

It's only a few hundred miles long, but when a natural disaster strikes near the Malacca Strait, the consequences could be global, writes Tom Ough.

Every year, approximately 90,000 ships pass through the narrow sea lane of the Malacca Strait, which links the Indian Ocean to the Pacific. Their cargo – grain, crude oil, and every other commodity under the Sun – comprises an estimated 40% of global trade. Above these ships is one of the busiest air routes in the world, and below them, running along the seabed, is a dense array of submarine internet cables that keep the world online. 

Together, these factors make the Malacca Strait one of the most vital arteries of the global economy. It has been classified as a trade choke point in reports by the World Trade Organization, the US Energy Information Administration and Chatham House, the London-based foreign affairs think-tank.

All of which is to say: nice strait you've got there. Be a shame if something… happened to it.

Researchers are warning that it's only a matter of time before a natural disaster like an earthquake or volcano strikes the region – and when it does, we can expect global consequences.

Alamy Ship-tracking technology reveals just how many travel through the Malacca Strait (Credit: Alamy) 

Ship-tracking technology reveals just how many travel through the Malacca Strait (Credit: Alamy) 

Disruption of key trade routes is a well-established problem, due to crime or human error. Piracy has long bedevilled the area, but the strait, cooperatively policed by Indonesia, Malaysia, Singapore, and Thailand, is generally under control. Still, it is not uncommon for ships to collide here: 10 American sailors died as a result of the USS John McCain running into a Liberian-flagged tanker in 2017. But at 1.7 miles (2.7 km) at its narrowest, the strait is not slender enough to be blocked by an errant container ship in the way that the Suez Canal was by the 400m (1,312ft) Ever Given in 2021

The greatest menaces to the Malacca Strait, which separates the Malay Peninsula from the Indonesian island of Sumatra, lie in the natural world. Of the many intriguing maps of activity in the region, the most arresting is the one that collates the world's active volcanoes and recent earthquakes. Along the coast of Sumatra and the more southerly part of Java, following the course of the Sunda Trench, is a band of earthquake activity, and several volcanoes.

On Java, two volcanoes, Semeru and Merapi, have recently erupted. In the Sunda Strait, which separates Java from Sumatra, is Krakatau, and to the east is Tambora, whose eruption in 1815 caused crop failure as far afield as in Europe and the eastern United States.

The Tambora eruption was magnitude VEI7 in the Volcanic Explosivity Index (VEI), on a logarithmic scale going up to VEI8. An event like 1815 might occur once or twice per millennium. But an eruption need not be of quite so high a magnitude to cause severe problems at a global choke point, especially if it happened at one of the volcanoes closer to the Malacca Strait.

In 2018, researchers at the University of Cambridge's Centre for Risk Studies envisaged the effects of scenarios including a VEI6 eruption at Marapi. The eruption, they suggested, might produce ash clouds and fine tephra – fragments of rock ejected into the air – that waft across the Malacca Strait towards Singapore and Malaysia. The resultant damage to local infrastructure and supply chains, with aviation particularly badly affected, would combine with a global temperature drop of 1C to wipe an estimated $2.51tn (£2tn/€2.3tn) off global GDP over a five-year period. That figure dwarfs the estimated $5bn (£4bn/€4.6bn) that the VEI4 eruption of Eyjafjallajökull, in Iceland, wiped from the global economy.

Marapi's last VEI4 eruption was 2010. A VEI6 eruption at Marapi is lower-probability: its return period, which is the estimated average time between eruptions, is 750 years. Yet the stakes are high enough to merit taking the prospect seriously, says Lara Mani, a volcanologist at the University of Cambridge's Centre for the Study of Existential Risk. And Marapi is one of several active volcanoes in the region. VEI4, VEI5 and VEI6 eruptions, says Mani, "can still really disrupt the strait. And the thing is, when a volcano starts, it doesn't tell you when it's going to stop."....

....MUCH MORE 

And more recently than 2023:

Indonesia/Malaysia/Singapore: "From Gallipoli to the Strait of Malacca: Why maritime choke points still decide the fate of nations" 

Chokepoint: U.S. and Indonesia Jointly Announce Major Defense Agreement

Singapore's Top Diplomat Drops Some F(act)—Bombs On Iran's Position

"DARPA calls for proposals for autonomous underwater drones — gov't looking for a small, cheap autonomous sub that can be developed and built quickly"

From Tom's Hardware, April 26:

The Pentagon wants inexpensive submarine drones, and it wants to get its hands on them as quickly as possible. 

The Defense Advanced Research Projects Agency (DARPA), the U.S. Department of War’s independent research and development agency, just issued a call for proposals to build an autonomous underwater drone. The program, which DARPA calls Deep Thoughts, is looking for the next generation of small autonomous undersea vehicles (AUVs) that can be built using readily available parts that allow for flexibility in the design. It also demands something that can be quickly produced, tested, and iterated on, with a development timeline of months or even weeks. More importantly, the AUV should be easily deployable from various platforms, so that users can launch it from submarines, ships, and even planes or helicopters.

Military drone development has been advancing at breakneck speed, with uncrewed aerial vehicles (UAVs) taking the stage during the ongoing Russia’s invasion of Ukraine. Ukrainian troops have taken advantage of this relatively new technology to blunt Russian armor and halt its advance, while Iran has taken to using its Shahed drones to strike targets in the Middle East when the U.S. started its bombing campaign of the country earlier this year. Chinese military scientists and engineers have also been developing drone swarms, giving individual soldiers the capacity to control up to 200 units.

The U.S. is also working on its own innovations in the UAV space —the U.S. Marine Corp introducing a 3D-printed drone called HANX, allowing units to manufacture and repair drones in-house, while a defense startup is marketing its CobraJet counter-unmanned aircraft systems (C-UAS) to defeat enemy drone swarms at a much more cost-effective way. However, it seems that the Pentagon wants to expand its drone capabilities beyond the sky and into the deep sea....

....MUCH MORE 

 

CURRECTED—What Happens When Sovereigns Crank Up The Issuance Of Short Term Debt?—CORRECTED

First up, to set the scene, a Xitter denizen: 

Continues:

....global macro this year, and finance X has not discussed it once.

Gross borrowing by central governments in emerging market and developing economies crossed $4 trillion in 2025, up from roughly $3 trillion in 2024. That is a 33% year-over-year increase in sovereign issuance from EMDEs in a single year. The OECD area as a whole hit record highs on both bond issuance and outstanding volume, with refinancing requirements accounting for most of the gross borrowing.

Here is what that means structurally. We are watching the largest sovereign bond supply glut in modern history collide with the end of accommodative monetary policy. Under quantitative tightening, central banks have stepped back from debt markets. Retail and foreign investors have stepped in as marginal buyers. Those buyers are more price sensitive and more focused on relative yields. The OECD’s exact language was that this combination has “contributed to higher term premia and steeper yield curves.”

Translation. The bid for long-dated sovereign debt is getting thinner at exactly the moment issuance is hitting records. That is why UK 30-year gilts sit at 5.12%, US 10-year at 4.42%, Colombian TES bonds above 11%, South African RSA at 10.45%. Those are not isolated moves. They are the expression of a structural supply-demand imbalance at the long end that has no precedent in the post-GFC era.

The positioning response from sovereigns themselves is the tell. Per OECD data, many countries are rebalancing issuance toward shorter maturities to limit exposure to higher long-term borrowing costs. This increases refinancing risk downstream but is the only way to get bonds out the door today. The US Treasury has been doing this for two years. The UK, France, and Italy are following. Japan is the outlier that has not yet started. When Japan capitulates, the move gets violent....

....MORE

I cut it at that point because he goes on to extrapolate effects on other assets that I am not sure are correct. But his observation on what the OECD report says about the duration of sovereign issuance leads us to a repost from October 2011, during the Autumn of Occupy Wall Street**:

Correction: The below is the wrong repost, interesting but not the one intended. See after the jump for the "Tale for our time."

Profuse apologies for the brain spasm. I'm hearing good things about ketamine from Elon and AOC, it may be time to give it a whirl. 

New York Fed: Rollover Risk 
An arcane topic that we've visited a few times.*
From the Federal Reserve Bank of New York's Liberty Street blog:

Short-Term Debt, Rollover Risk, and Financial Crises 
One of the many striking features of the recent financial crisis was the sudden “freeze” in the market for the rollover of short-term debt. In this post, based on my paper “Rollover Risk and Market Freezes,” I explain how firms may be unable to borrow overnight against high-quality assets even in the absence of the usual frictions (asymmetric information, adverse selection, or moral hazard) that can cause credit rationing.
Two Freezes
The first such market freeze occurred in the summer of 2007. On July 31, two Bear Stearns hedge funds based in the Cayman Islands and invested in subprime assets failed. The following week, more news of problems with subprime assets hit the markets. On August 9, BNP Paribas halted withdrawals from three investment funds and suspended calculation of their net asset values because it could not “fairly” value the funds’ holdings. This announcement appeared to cause investors in asset-backed commercial paper (ABCP), primarily money market funds, to shy away from further financing of ABCP structures. Since many ABCP vehicles had recourse to sponsoring banks that provided them with liquidity and credit enhancements, if ABCP debt could not be rolled over, the sponsoring banks would have to take assets back onto their balance sheets. In that case, given the assets’ illiquidity, the ability of the banks to raise additional financing would be limited too. Money market funds thus faced the risk that the assets underlying ABCP would be liquidated at a loss. This liquidation and rollover risk produced a freeze in the ABCP market, raised concerns about counterparty risk among banks, and caused the Libor to rise. Providing evidence of such a freeze, Gorton and Metrick (2010) show that during 2007-08, the repo haircuts on a variety of assets rose on average from zero in early 2007 to nearly 50 percent in late 2008. Interestingly, while some of the collateralized debt obligations had a 100 percent haircut and thus no secured borrowing capacity at all during the crisis, equities—which are in principle much riskier assets—had only around a 20 percent haircut.

    The failure of Bear Stearns in mid-March 2008 offers a second example of a market freeze. (A March 20 Securities and Exchange Commission press release provides an interesting discussion of the account.) As an intrinsic part of its business, Bear Stearns relied on day-to-day, short-term financing through secured borrowing. Beginning late on Monday, March 10, rumors about liquidity problems at Bear Stearns eroded investor confidence in the firm. Even though Bear Stearns continued to have high-quality collateral, counterparties became less willing to enter into collateralized funding arrangements with the firm. This resulted in a crisis of confidence and led to a sharp and continuous fall in Bear Stearns’ liquidity, which caused the near-failure of the firm. Furthermore, even at the time of the firm’s sale, the capital ratio of Bear Stearns was well in excess of the 10 percent level used by the Federal Reserve as its standard for well-capitalized banks. As Chairman Bernanke observed, “Until recently, short-term repos had always been regarded as virtually risk-free instruments and thus largely immune to the type of rollover or withdrawal risks associated with short-term unsecured obligations. In March, rapidly unfolding events demonstrated that even repo markets could be severely disrupted when investors believe they might need to sell the underlying collateral in illiquid markets.” 
Why the Freezes?...MORE
HT: FT Alphaville

Correct repost:

In July 2011 it was "The Black Swan Isn't the Debt Ceiling, It is Holders of U.S. Treasuries Asking for Cash Rather Than Rolling the Paper
 
And don't think it can't happen.
Here's TIME Magazine, February 16, 1959:
Business: Bond Failure
The U.S. Treasury offered $9.1 billion in new securities last week to private holders of maturing debt and got a shock. It had hoped to persuade most of the holders of maturing issues, bearing 1⅞% and 2½% interest rates, to trade them in for new Government securities paying 3¾% and 4%. Instead, owners of more than 20% of the old issues demanded to be paid off in cash, the biggest such demand in six months.

To help make up the difference, the Treasury must go to the public this week with a $1.5 billion emergency issue.

The failure of the latest debt "rollover" attempt was a fresh sign of softness in the Government bond market—and of the size of Secretary of the Treasury Robert Anderson's task of refinancing $42 billion of Government securities falling due this year. At a time when most investors want to buy stocks, real estate or other things as a hedge against inflation, Anderson is finding the public increasingly uninterested in bonds.

Furthermore, Wall Streeters thought he had made a mistake in trying to sell securities with one year as the shortest maturity. At a time when investors were trying to figure how high interest rates might go, too many of them did not want to tie up their cash for a year.

Anderson's troubles began last spring when it became clear that the Treasury would have to raise up to $12 billion to cover the Government's deficit for this fiscal year....MORE 
We're racking up $12 Billion every three days.  [2026: $1 Trillion every three months]
***** 
The risk is a buyers strike at the long end.
 
***** 
 
*Back in August 2007, a week after the "Quant-quake", we posted "Liquidity in Business and Markets":
Liquidity is expensive but illiquidity is much more so, 
because it destroys the very existence of a firm"

I don't remember if it was Johannes or Ernst, it was a long time ago that I read Manchester, quoting one of the Schroeder boys on the insolvency of Krupp. That line has stuck with me. Here's the book....

In July 2011 it was "The Black Swan Isn't the Debt Ceiling, It is Holders of U.S. Treasuries Asking for Cash Rather Than Rolling the Paper"

Last Friday: "Too Funny: "GE Capital CEO "sympathetic" to Wall Street protests'":
...Three years ago this month, in the Fall of 2008 no one on earth would touch GE Credit's commercial paper and the entire company was within days of becoming insolvent.

The company had been padding reported earnings by borrowing short and lending long, at one point having over $100 Billion in CP outstanding.
The borrow short/lend long scam is a great way to increase your bonus but in finance it's nothing short of playing Russian roulette....

Even though OWS was three months after the correct repost I will leave this outro up as a parting gift for those readers who have made it this far.

Again, regret the error. 

**Some of our Occupy Wall Street posts: 

The Retired Trader Who Bankrolled #OccupyWallStreet 
"DJ Spooky, Occupy Wall Street, and the Frictions of Radical Chic"  
Some Thoughts on the OccupySesameStreet Protests
#OccupySesameStreet Turns Violent
Breaking--From the OccupySesameStreet Protests: "Three Die After The Electric Company Privatized"--Breaking  
 
Ayatollah Khamenei says Occupy Wall Street could mark the fall of the west
China and GE's Immelt Sympathise with #OccupyWallStreet 
North Korea Comments on #OccupyWall Street   
#OccupyRedSquare Doesn't Go at All Well
 
We Will NOT Be Co-opted: "Luxury Ice Cream Unit of Multinational Unilever Endorses #OccupyWallStreet 
#OccupyWallStreet: The Revolution Will be Televised (and trademarked)
Adbuster Calls on #OccupyWallStreet to Declare Victory and Go Home; "Zuccotti Lung"; and Jay-Z Pulls Occupy T-Shirts from Website 
Today in #OccupyWallStreet News: "I'm a F***ing Journalist, You Motherf***er!
 
"The Occupy Wall Street bank" 
Octopi Wall Street
Banks Much More Successful at Panhandling than #OccupyWallStreet
"Ossify Wall Street: Russell Simmons/Kanye West; Richard Trumka, Tim Robbins Swing By; Jesse Ventura only Gets as Far as Minneapolis". 
Michael "I'm Part of the 99%" Moore Heckled at #Occupy Rally
"Occupy Wall Street in New York running out of cash" 
"Occupy Wall Street leader now works for Google, wants to crowdfund a private militia"

#OccupyWallStreet Proclaims Victory, Announces Plan to Re-launch #OccupyMom'sBasement 
Don't get me wrong, I'm as much into anarcho-capitalism as the next guy, I think I'd do pretty well whatever the ground rules.
It's just that #OWS isn't showing the kind of higher-level cognitive abilities you'll find at, say, MI-6...
 
Good times. 

"Blackstone Raises $69B in Q1, Says AI Infrastructure Driving Returns Across Funds"

From the property mavens at Bangkok's Mingtiandi, April 25:

Blackstone booked $68.5 billion in capital inflows during the first quarter of 2026, in a show of the private equity titan’s fundraising resilience amid market turmoil triggered by the Iran war.

The haul was down only slightly from the previous quarter’s $71.5 billion and brought trailing 12-month inflows to $246.3 billion, according to results released Thursday. First-quarter fundraising was led by $37 billion channelled into credit and insurance strategies, underscoring investor appetite for yield-oriented products during volatile conditions.

“Blackstone delivered outstanding first‑quarter results despite the turbulent environment, highlighted by almost $70 billion of inflows and positive appreciation across nearly all of our flagship strategies,” said chairman and CEO Stephen Schwarzman. “Our all-weather model protects us in these times of disruption while also allowing us to invest where we see the greatest opportunity.”

Returns were supported by what the firm has branded “AI infrastructure”, with data centres and related assets driving performance across multiple strategies. Infrastructure investments posted a 7.8 percent gross return in the quarter and 24.8 percent for the past year, among the strongest showings across asset classes.

Revolutionary Road 
Blackstone is positioning itself at the centre of what Schwarzman described as an AI revolution, pointing to an “extraordinary level of investment” spanning data centres, semiconductors and energy systems.

In an earnings call, Schwarzman traced Blackstone’s early move into the theme back more than a decade, noting that he began engaging with leading figures in artificial intelligence in 2015, well before the current wave of generative AI adoption. That early positioning culminated in the 2021 privatisation of Virginia-based QTS, which Schwarzman said became the “cornerstone” of the firm’s data centre strategy and helped establish its scale in the sector.

Blackstone now counts more than $150 billion in data centre assets globally, including facilities under construction, with a further $160 billion in prospective development pipeline. The firm has been scaling its Asia Pacific data centre platform aggressively, using its control of Sydney-based AirTrunk as a regional backbone....

....MUCH MORE 

Previously from Mingtiandi on data centers:
July 13, 2024 
Asian Property Development: Three Data Center Operators And A Warehouser
The Asian data center business is coming on strong. Three from Mingtiandi (Asian real estate intelligence)

And most recently on Blackstone's infrastructure push:

March 10 - "Blackstone Launching Public Vehicle for Data Center Acquisitions" (BX)

One more self-reverential referential snippet, this time from May 2025's "Infrastructure: Blackstone Is Buying An Electric Utility (BX; TXNM)"
This is something we will see more of, private equity in regulated utilities. It's hard to asset-strip the darn things due to said regulators but boy-oh-boy do they cash flow. Just ask Warren Buffet.... 

"Iran’s Oil Storage Just Hit the Wall" (damage to Iran's oil fields will be permanent)

Two from House of Saud, April 26:

Iran's Kharg Island storage reached capacity April 26 as the US blockade forces well shut-ins that could permanently destroy 300,000-500,000 bpd of production

DHAHRAN — Iran’s Kharg Island oil terminal, which handles more than 90% of the country’s crude exports, reached effective storage capacity on Saturday, April 26, thirteen days after the US naval blockade of Iranian ports took effect. With 31 million barrels of onshore tank space now full and exports at near-zero, Tehran faces a choice it has spent two months trying to avoid: shut in wells that may never fully reopen.

US Treasury Secretary Scott Bessent framed the moment in advance. Storage at Kharg, he said, “will be full and the fragile Iranian oil wells will be shut in.” The arithmetic bore him out. At the blockade’s start on April 13, Kharg held roughly 18 million barrels against 31 million barrels of total capacity, according to Kpler data. Net inflow — production minus the trickle still leaving through Jask and floating transfers — was running at 1.0 to 1.1 million barrels per day. Thirteen days of accumulation consumed the remaining 13 million barrels of headroom.

The storage crisis is not the endgame. It is the trigger for a different and more permanent kind of damage: the destruction of reservoir capacity in Iran’s aging, water-injection-dependent oil fields. The Foundation for Defense of Democracies estimates that forced shut-ins will permanently eliminate 300,000 to 500,000 barrels per day of Iranian production capacity — worth $9 billion to $15 billion in annual revenue, gone not for the duration of the war but for years afterward. For Saudi Arabia, which holds more than half of all OPEC+ spare capacity and is lobbying Washington to end the blockade, the implications for post-war market structure are as large as they are uncomfortable. 

The Storage Math: Thirteen Days From Blockade to Capacity

Kharg Island sits 25 kilometers off Iran’s southwestern coast in the Persian Gulf. A 1984 CIA assessment called it “the most vital” node in Iran’s oil system. That description has not aged. In March 2026, the island accounted for 84% of Iranian crude loadings, according to Kpler, with the Goreh-Jask pipeline terminal on the Gulf of Oman handling just 4.4%.

Before the blockade, Iran was producing approximately 3.68 million barrels per day and exporting 1.5 to 2.15 million bpd through Hormuz, according to Al-Monitor and Bloomberg. Domestic refining capacity absorbs roughly 2.6 million bpd. The gap between production and refining-plus-exports determined how fast Kharg filled.

When the US blockade took effect on April 13, exports through Hormuz dropped to near zero. Bloomberg reported on April 26 that traffic through the strait had become “virtually impossible for the first time in history.” With exports halted, net inflow into Kharg storage ran at 1.0 to 1.1 million bpd — the residual after subtracting refinery intake and the small volumes still trickling through Jask.

Metric Value Source
Kharg total storage capacity 31 million barrels Kpler
Inventory at blockade start (April 13) ~18 million barrels (58%) Kpler (last reported March 7; no subsequent fill between US strikes)
Spare capacity at blockade start (April 13) ~13 million barrels Calculated
Net daily inflow 1.0–1.1 million bpd Al-Monitor, Bloomberg
Days to capacity from April 13 ~12–13 days Calculated
Projected saturation date April 25–26 Calculated

Muyu Xu, senior analyst at Kpler, assessed that Iran had approximately 20 days of onshore storage remaining at current inflow rates and that production reductions would be “gradual over the coming week, with higher likelihood of acceleration into May.” Arne Lohmann Rasmussen, chief analyst at Global Risk Management, said Iran “was expected to run out of storage capacity within approximately one month, but it may already be forced to shut in part of its oil production within a couple of weeks.”

The Nasha: A 30-Year-Old VLCC Buying 48 Hours

Iran’s most visible response to the storage crunch was the reactivation of the Nasha, a very large crude carrier built in 1996 and previously decommissioned. Maritime intelligence sources, including TankerTrackers.com, identified the vessel repositioning toward Kharg Island in mid-April as floating storage. Iranian state media did not acknowledge the deployment.

The Nasha carries approximately 2 million barrels. At 1.0 to 1.1 million bpd of net inflow, that capacity buys roughly 48 hours. Multiple outlets reported the ship was moving so slowly that a voyage expected to take 36 hours stretched to four days — a detail consistent with a vessel that has been idle for years and is operating at minimal crew and mechanical capacity.

Floating storage elsewhere in Iran’s system is already at saturation. Kpler estimates 183 million barrels of Iranian crude sitting on tankers globally; Kenneth Katzman, formerly of the Congressional Research Service, put the figure at 160 to 170 million. Neither figure changes the Kharg arithmetic. The island’s tank farm is the bottleneck between wellhead and tanker, and that bottleneck is now full.

What Happens When You Shut In a Water-Flooded Field?

....MUCH MORE 

Also at House of Saud, April 26:

Iran’s Wellhead Overflow Crisis Hits Its Deadline — and the Damage Is Now Permanent 

TEHRAN — Iran’s onshore oil storage reached functional capacity on or around April 26, triggering the forced shut-in of wells across the country’s aging southwest oil fields — and initiating a process of irreversible underground reservoir damage that no ceasefire, whenever it comes, can undo. The crisis marks a turning point in the war’s economic logic: the IRGC command structure blocking a diplomatic resolution is now actively destroying the physical asset base that any post-war Iranian recovery depends on. 

The distinction matters because it changes what Iran loses. Foregone export revenue — the $435 million per day the Foundation for Defense of Democracies estimates the US naval blockade costs Iran — is a recoverable loss, at least in theory. Tankers sitting at sea can eventually deliver their cargo. But wells forced into prolonged shut-in undergo geological processes that permanently reduce the volume of oil that can ever be extracted from the reservoir. Water pushes into oil-bearing rock. Paraffin clogs tubing. Sand settles into perforations. The field doesn’t recover its pre-shutdown output — not in months, not in years, not ever.... 

....MUCH MORE 

"24,000-year-old frozen ‘zombie worm’ thawed by scientists — then it shockingly started reproducing"

Ummm....wasn't this a movie?

From the New York Post, April 25:

It thawed out — and then it multiplied.

Scientists successfully revived a “zombie worm” that had been frozen for 24,000 years, revealing new insight into how life survives in the most unforgiving environments over extended periods of time.

According to a study published in the scientific journal Current Biology, researchers found that the microscopic organism — identified as a rotifer — is a small, multicellular animal commonly found in freshwater environments that is known for its unusual durability, FOX News reported

The “zombie worm” has been frozen deep within Siberian permafrost since the Late Pleistocene, which was considered to be the final epoch of the Ice Age, ending roughly 11,700 years ago.

Scientists believe the Yedoma formation — an ice-rich, organic-laden permafrost formed during the Ice Age — helped sustain the specimen in a stable, frozen state for tens of thousands of years....

....MUCH MORE 

"The Billion-Barrel Hormuz Oil Shock Is About to Crash Demand"

From Bloomberg, April 25:

The Strait of Hormuz oil shock has yet to crash demand as the rich world borrows from its stocks and pays up to secure supply. Traders are now sounding the alarm that a harsh adjustment is coming.

The longer the vital oil channel doesn’t reopen, traders say, the more consumption is going to have to recalibrate lower to align with supply that’s dropped at least 10%. And for that to happen, people will have buy less, either through prices they can’t afford, or government intervention to force consumption down.

A billion barrels of supply loss is already all-but guaranteed — more than double the emergency inventories that governments released not long after the conflict began at the end of February. Buffers are being used up fast, helping to keep a lid on oil prices for now. But with the closure now in its ninth week, demand destruction that started in less obvious sectors like petrochemicals in Asia, is quietly spreading to everyday markets the world over.

“Demand destruction is happening in places that are not visible pricing centers,” Saad Rahim, chief economist of trader Trafigura Group, told the FT Commodities Global Summit in Lausanne this week. “That adjustment is already happening, but if this continues, it has to get larger and larger. We’re at a critical inflection point.”...

*****

...The most dependent industries and markets — including petrochemicals plants in Asia and the Middle East, and shipments of liquefied petroleum gas, a vital cooking fuel in India — saw an immediate hit when the US and Israel first attacked Iran on Feb. 28.

Now, with a stalemate between US President Donald Trump and his Iranian adversaries dragging on, the impact is increasingly shifting west — and to products that are central to consumers’ everyday lives.

Airlines in Europe and the US are cutting thousands of flights. Analysts are warning of weakness in consumption of gasoline after prices hit $4 a gallon in the US, and diesel — used to power everything from trucks to construction equipment.

Global oil demand is on track to slump the most in five years this month, according to the International Energy Agency, which co-ordinated the emergency measures by major economies to counteract the supply shock.

Trading giant Gunvor Group estimates the loss could double next month to 5 million barrels a day, or 5% of world supplies, and along with other major traders sees a growing risk of economic recession. Other analysts and traders say that the impact has already reached around the 4 million a day mark.

That toll is beginning to take shape. Germany has slashed economic growth forecasts in half, while the International Monetary Fund has trimmed global estimates, citing the war. In the most “severe” of three scenarios modeled by the European Central Bank, Brent prices peak at $145 a barrel and cut the region’s growth in half. Brent crude closed at about $105 a barrel on Friday.....

.....MUCH MORE

Shipping: "Chubb Says U.S. Hormuz Insurance Backstop Stalled as Military Convoys Fail to Materialize"

From gCaptain April 24:

Washington’s headline-grabbing maritime insurance backstop for the Strait of Hormuz appears stuck on the launchpad.

Comments this week from Chubb Chairman and CEO Evan Greenberg suggest the Trump administration’s much-publicized $40 billion maritime reinsurance facility has not stalled for lack of underwriting capacity, but because the military escort concept at its core has yet to materialize.

Speaking during Chubb’s April 22 earnings call, Greenberg disclosed the federally backed program was designed not as a standalone commercial insurance product, but as part of a U.S.-run convoy system intended to support transits through the Gulf. Chubb was tapped to serve as the lead insurance partner in the program....

....MUCH MORE 

Saturday, April 25, 2026

"Iran President Calls on People to Save Energy"

From London's  Asharq Al-Awsat, April 25 (08 Thul-Qi’dah 1447 AH):

Iranian President Masoud Pezeshkian called on his people Saturday to conserve electricity, warning that while there were no shortages at present, the US and Israel aimed to sow "dissatisfaction" among the Iranian people.

"We have asked our dear people, who are now ready and present on the ground, a simple request. And that is to reduce their own electricity and energy consumption," the president said on state TV.

"We do not need people to sacrifice for the time being, but we do need to control consumption. Instead of 10 lights, two lights should be turned on in the house -- what is wrong with that?" he added....

....MUCH MORE 

Also at Asharq Al-Awsat:

Iran Resumes Commercial Flights from Tehran’s International Airport

 

Thought Experiments: "The Social Edge of Intelligence"

From The Ideas Letter, April 16:

AI doesn’t really “think.” Rather, it remembers how we thought together. And we’re about to stop giving it anything worth remembering.

We are on the verge of the age of human redundancy. In 2023, IBM’s chief executive told Bloomberg that soon some 7,800 roles might be replaced by AI. The following year, Duolingo cut a tenth of its contractor workforce; it needed to free up desks for AI. Atlassian followed. Klarna announced that its AI assistant was performing work equivalent to 700 customer-service employees and that reducing the size of its workforce to under 2000 is now its North Star. And Jack Dorsey has been forthright about wanting to hold Block’s headcount flat while AI shoulders the growth.

The trajectory has a compelling internal logic. Routine cognitive work gets automated; junior roles thin out; productivity gains compound year on year. For boards reviewing cost structures, it is the cleanest investment proposition since the internal combustion engine retired the horse, topped up with a kind of moral momentum. Hesitate, the thinking goes, and fall behind.

But the research results of a team in the UK should give us pause. In the spring of 2024, they asked around 300 writers to produce short fiction. Some were aided by GPT-4 and others worked alone. Which stories, the researchers wanted to know, would be more creative? On average, the writers with AI help produced stories that independent judges rated as more creative than those written without it.

So far, so on message: a familiar story about the inevitable takeover by intelligent machines. But when the researchers examined the full body of stories rather than individual ones, the picture became murky. The AI-assisted stories were more similar to each other. Each writer had been individually elevated; collectively, they had converged. Anil R  Doshi and Oliver Hauser, who published the study in Science Advances, reached for a phrase from ecology to explain this: a tragedy of the commons.

Hold that result in mind: individual gain, collective loss. It describes something far more consequential than a writing experiment—it describes the hidden logic of our entire relationship with artificial intelligence. And it suggests that the most successful organizations of the coming decade will be the ones that do something profoundly counterintuitive: instead of using AI to eliminate human interaction by firing droves of workers, they will use it to create more human interaction. IBM has reversed course on its earlier human redundancy fantasies. I bet more will in due course.

I.

Suppose you could travel to Egypt in 3000 BC and copy, in flawless hieroglyphics, the contents of every temple library, every architectural plan, every priestly manual, every commercial ledger. Then suppose you travelled to Mesopotamia and did the same in cuneiform. Consolidate everything you could find in the languages of that era, and then proceed to train a large language model on it. Full transformer architecture, self-attention, the whole enchilada.

The result would be a system capable of a certain kind of intelligence. It could predict floods from astronomical cycles. It could draft administrative correspondence. It could generate plausible religious commentary. But it would have no capacity for what the Greeks would later call the syllogism. It would carry no trace of Roman legal abstraction, and have no conception of the empirical method that wouldn’t emerge for another four millennia.

Now, let’s extend the experiment. Train a new model on the written output of 300 BC Athens: Aristotle, Euclid, Hippocrates, the commercial records of Mediterranean trade, etc. Another on 300 AD Rome, another on 1000 AD Baghdad, another on 1500 AD Florence, and finally one on the full internet-scale text production of the modern world.

Each model in this chain would be qualitatively smarter than the last. But it wouldn’t be smarter because you changed the architecture of the underlying technology (you didn’t). The reason would be that the civilization feeding the tech had changed. The 300 BC model would demonstrate logical inference that its Egyptian predecessor couldn’t approach. The 1500 AD model would handle probability and navigational calculation. And the 2025 model would exhibit the argumentative density, cross-domain reasoning, and multi-perspectival sophistication that characterize today’s frontier systems.

 

Figure 1. Civilizational substrates of intelligence 

What the chain reveals is a dependency the AI industry has largely declined to examine. The underlying intelligence of a large language model isn’t a function of its architecture, its parameter count, or the volume of compute thrown at its training. It is not even about the training data. It is a function of the social complexity of the civilization whose language it digested.

Each epoch advanced the cognitive frontier through something far richer and more complex than the isolated genius of an individual guru or machine. It did so through new forms of collective problem-solving. Think new institutions (the Greek agora, the Roman lex, the medieval university, the scientific society, the modern corporation, and the social internet) that demanded and rewarded ever more sophisticated uses of language.

The cognitive anthropologist Edwin Hutchins studied how Navy navigation teams actually think. In his 1995 book Cognition in the Wild, he wrote something that reads today like an accidental prophecy. The physical symbol system, he observed, is “a model of the operation of the sociocultural system from which the human actor has been removed.”

That is, with eerie precision, a description of what a large language model (LLM) really is, stripped of all the unapproachable jargon and mathematical wizardry. An LLM like ChatGPT is a model of human social reasoning with the human wrangled out. And the question nobody in Silicon Valley is asking with sufficient urgency is: What happens to the model when the social reasoning that produced its training data begins to thin?

II.

In 2024, Ilia Shumailov and colleagues published a paper in Nature with a straight-talking title: AI models collapse when trained on recursively generated data. They demonstrated, with alarming mathematical precision, that language models trained on text generated by other language models start to degenerate partly because the distribution of the output narrows over successive generations. Minority viewpoints, rare knowledge, unusual formulations, and edge-case perspectives gradually vanish. The model converges on a kind of statistical average—fluent, plausible, and hollow. The tails of the distribution disappear first.

Consider what those tails represent. They are the traces of intellectual disagreement, of minority expertise, of Cassandra warnings, of institutional friction, and of the awkward and valuable fact that different people know different things and express them differently. They are, in other words, the signature of social complexity. Model collapse is social mind compression presented as a technical phenomenon.

Around the same time, the AI researcher Andrew Peterson analyzed what he called “knowledge collapse”: the harmful effect on public knowledge due to widespread reliance on AI-generated content. Even with a modest discount on AI-sourced information, public beliefs deviated 2.3 times further from ground truth. When people and organizations rely on AI summaries rather than engaging with primary sources, the diversity of available perspectives narrows.

Similarly, there is a variant of the Dunning Krueger effect, I suggest, that is found in those conversing with service chatbots that spare them the social bruises of hard conversations. When people choose to “ask Grok” to settle messy debates on Twitter/X, they are spreading this syndrome of overconfidence in one’s understanding of complex issues. It is easier to inflate your knowledge and understanding when you don’t have to deal with the social-regulatory feedback of ego-bruising disagreement. Blind spots grow bigger when one is cocooned in a machine-harem of pampering bots. What emerges over time is subtler than the militant ignorance of pre-AI social media. It is a confident, fluent, and remarkably homogeneous form of shallow knowing.

Anthropic, the maker of Claude, another LLM platform, has research results showing that in only 8.7% of user interactions with its platform do users pause to double-check what the bots spew out. That number reinforces something bigger than mere cognitive offloading and delegation. It enables systemic overconfidence which in turn diminishes curiosity, exploration, and knowledge-frontier defiance.

 

Figure 2. Cognitive overloading, overconfidence, underexploration & frontier AI regression 

Meanwhile, a team at Epoch AI estimated that the total stock of quality-adjusted human-generated text available for training is roughly 300 trillion tokens, projected to be exhausted between 2026 and 2032. This is typically framed as a resource depletion problem as though we’re running out of data the way we might run out of water. But that framing misses the deeper point. The reservoir is not just being drained—the springs feeding it are starting to dry up....

....MUCH MORE 

Hungary's Incoming Prime Minister Wants to Put the Austro-Hungarian Empire Back on the Map

Huh, I was just wondering what Eduard Habsburg was up to now that he's no longer Hungary's Ambassador to The Vatican.

Maybe a step or two higher on the Imperial ladder is in his future.*

From Politico.eu, April 22 

Magyar wants to put the Austro-Hungarian Empire back on the map
Hungary’s incoming prime minister wants to forge closer ties with Austria and other Central European nations to wield greater power in Brussels. 

Hungary’s next leader wants to revive Central Europe’s clout by tapping its imperial past.

Prime Minister-elect Péter Magyar says he will deepen ties with neighboring states, especially Austria, building on strong economic links and a shared history rooted in the Austro-Hungarian Empire of the late nineteenth century.

“We used to share a country, and Austria is a key economic partner of Hungary,” Magyar said after his victory over Viktor Orbán in the Hungarian election earlier this month. “I would like to strengthen the relationship between Hungary and Austria for historical but also for cultural and economic reasons.”....

....MUCH MORE 
*Eduard, on our previous visits, came across as fairly well adjusted:

And In Political Commentary...

 ...He seems comfortable in his own skin.

And back in April 2022:

Checking In On His Imperial Royal Highness

Eddie is currently working a side gig as an Ambassador to the Vatican until the Empire is restored.