Ian Welsh

The horizon is not so far as we can see, but as far as we can imagine

Category: AI Page 1 of 3

America’s Losing the AI Race Hard

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On July 21, 2026

32 Comments

Amazing stuff, and sooner than even I expected. China’s Kimi is now about equal to GPT and Claude:

For the first time, a Chinese model Kimi K3 has taken on the Frontend Code Arena and is scoring at or near the frontier on other benchmarks.

And the majors are noticing:

Meanwhile Trump is talking about banning Chinese AI. 

Alternatively, the smart lads at Open AI have a regulatory plan:

I would guess that the Trump Administration will at some point realize that their best strategy here would be to create large amounts of regulatory risk around the use of open-weight Chinese models. You don’t need to “ban open source” (one of the dumber motifs of AI policy discussion). You just need to direct every agency to issue soft law that creates FUD. “A Federal Reserve Advisory Bulletin found that there may be backdoors in Chinese AI models.” It needn’t be that well justified. You just create enough regulatory risk that every regulated enterprise backs off. You probably don’t want to create so much regulatory risk that you scare off the hyperscalers from serving Chinese models; this will just drive startups to sketchier providers. There’s a happy middle ground here. I’d assume they will do some version of this.

Even more fun, the Feds want to approve all AI releases and not allow everyone the full models.

The Trump administration has taken new steps to assert more control over the rollout of future artificial intelligence model releases by dictating which companies and entities are allowed access to the latest frontier models, two people familiar with the matter told CNBC…

….

This week, the administration launched its own program, dubbed “Gold Eagle,” aimed at collaborating with the private sector to find and fix cyber vulnerabilities.

The so-called clearinghouse would put the White House in charge of greenlighting which companies can access new AI models, according to a person familiar with the matter, who spoke on condition of anonymity in order to discuss information that is not public.

China is going to eat America’s lunch on this. If they ban Chinese AI (harder than it seems, given it’s open source) all that means is writing off the rest of the world. And since American models are handicapped, smaller American companies will be stuck with worse AI.

Since Chinese AI is far cheaper, as well, I’d expect American companies to set up subsidiaries overseas to use it, rather than be stuck with American AI.

The entire situation is a complete clusterfuck. Major companies have taken on serious debt in order to build data centers which have a lifecycle of five to seven years, and often less (since new generations of GPUs are much better.)  But the Chinese product is cheaper, open source, lacks nearly as much sovereign risk and I’ll bet multiple models will soon be about as good as Anthropic and OpenAI’s.

Where’s the business case that spending all these trillions of dollars is going to produce enough revenue from US AI to pay for all of it?

There isn’t one. It doesn’t exist.

And that means that, at least in America, this is an AI bubble. All bubbles burst and this will not be an exception. If the government bails them out it will be the last major US bailout.

This is also very likely one of the last major tech revolutions which will start in the US (which it did.) Going forward they China will produce the vast majority of them.

This is the endgame. The turning point where China obtains not just the industrial base but the absolutely undisputed tech lead. From now on China will like America in the 1950s — it’s where almost everything new is created, the dynamic center of the world, and soon people will be competing to move there, because everyone knows it is the future.

 

What I write here is for the benefit of everyone, but alas, I live in capitalism and I, and the site, take money to keep running. If you value the writing here and can, please subscribe or donate.

 

Xi Lays Out His Principles for AI Development

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On July 17, 2026

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There were rumors recently that China was going to put export restrictions on AI. That now seems… unlikely. Here are the principles Xi laid out:

First, adhering to the principle of openness and win-win cooperation while boosting innovation-driven development. Xi highlighted the importance of encouraging open-source, openness, collaboration and sharing to facilitate technological innovation, industrial development and scenario-based application of AI. (My emphasis.)

Second, strengthening risk awareness and ensuring that AI is secure and controllable. Stressing the need to ensure that AI is always under human control, Xi urged all sides to jointly oppose overstretching the national security concept in the field of AI or placing one country’s security over that of others.

Third, encouraging inclusiveness and promoting mutual learning among civilizations. AI development and its application should not erode or undermine the diversity of world civilizations or the uniqueness of cultures of different countries, according to Xi.

Fourth, advocating solidarity and improving global governance. The important role of the United Nations should be recognized, Xi said, calling for further alignment and coordination on AI development strategies, governance rules and technical standards.

I’ve predicted, for a couple years now, that Chinese AI models will be the main models used in most of the world, including in much of the West, assuming they aren’t banned outright, because they’re open and cheap. Costs of running them are about twenty times lower than the US frontier models made by OpenAI and Anthropic. They’re almost as good, and they aren’t that far behind.

The problem with US models is not just that they’re expensive (though that’s huge, there are tons of reports of AI use being cut back) but that they are CLOSED: meaning you can easily be cut off, or have prices raised, or have the model changed on you with no recourse. Open models you can adapt the model, you can run it on your own servers, or various server companies can, will and do run them for you on their servers which you rent.

It’s clear that Xi gets this, and thus that the CPC understands it as well. Open Source isn’t a liability, there’s a reason why Linux runs most of the world’s servers: closed tech is the liability. Open Source is the advantage.

Notice the second bit: on AI always being under control. I wonder if Xi is thinking of Israel and the US for military targeting and how that has possibly contributed to hitting civilian targets like schools. (Possibly because Israel and the US are run by psychopaths and I bet they’d do it anyway. But no human in the loop may make it even worse.)

The third principle is about avoiding US (and Chinese) cultural hegemony. A nice thought, and open source certainly could be adapted to different nations and cultures, so that AI models aren’t all giving the same generic results.

Finally, the fourth principle. I’ve always found it interesting just how much China plays up the United Nations. I don’t know if the respect is genuine, but the words are consistent. Honestly, I think the UN should move its main HQ out of America. America’s been pulling stunts like denying diplomats visas. Not sure if it should go to China (though if it did Shanghai or Hong Kong seem like good fits) but they’d be better stewards than the US, and in any case, if the UN is going to be in the most important great power, that’s now China. (That said, I’d favor something more neutral. Perhaps Singapore.)

China just keeps coming across as smarter, more strategic and more human than the West. It’s sad, in a way, but it is what it is.

And I remain convinced that Chinese AI will be the winner over American.

What I write here is for the benefit of everyone, but alas, I live in capitalism and I, and the site, take money to keep running. If you value the writing here and can, please subscribe or donate.

 

The Old Gray Lady Runs RussiaGate 2: They’re Coming for OpenAI

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On July 10, 2026

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Guest post by Nat Wilson Turner.

New York Times: "China, Russia and Others Seek to Inflame Debate Over A.I. Data Centers"

Thursday’s New York Times brings back their old RussiaGate spirit with a front page banner headline about “foreign interference” and data center opposition.

Here’s a key quote:

…a push by foreign adversaries to seize on what polls have shown is deep ambivalence — verging at times on hostility — about the spread of the data centers needed to power A.I. in the United States and elsewhere.

China, Russia and, to a lesser extent, Iran have sought to use state media outlets to turn the controversy over data centers in the United States into “a domestic fracture point,” according to a new analysis by Alethea, a threat intelligence company, which identified scores of articles and posts on social media this year.

These campaigns, whose impact on public opinion remains to be seen, have raised alarms in Washington, where A.I. is seen as a top issue heading into this year’s midterm elections.

The foreign efforts appear intended to stoke the debate over data centers that has united political figures across the political spectrum — from Senator Bernie Sanders of Vermont, a progressive, to Stephen K. Bannon, the erstwhile adviser to President Trump.

“Foreign actors aren’t manufacturing American debates over the future of A.I., they are exploiting them,” said Jessica Brandt, a former official with the Office of the Director of National Intelligence who tracked foreign influence efforts during the Biden administration.

The goal, she added, is to “deepen our divisions in order to dent our appeal and weaken us from within.”

Interesting sources, some company called Alethea and a former Biden admin DNI spook as our sources.

We’ll come back to them later, but first I’m curious as to why the NYT is only now covering this story when OpenAI put out a press release saying basically the same thing on June 10 except focused solely on China.

After all, OpenAI’s report was convincing enough to sway such luminaries as Senator Tom Cotton (R-AR), Republican Leaders on the House Energy and Commerce Committee, Rep. Brett Guthrie (R-KY), Interior Secretary Doug Burgum, The Bitcoin Policy Institute and prominent tech investor Kevin O’Leary, per WIRED.

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Microsoft To Offer Deepseek Based AI Copilot

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On June 17, 2026

4 Comments

Regular readers will know that for a couple years I’ve been saying that Chinese open source AI would win the AI “war” because it’s cheaper and non proprietary (prices can’t just be raised suddenly, or capacities taken away.)

Over the last few months there’s been a lot of screams coming from regular AI users. OpenAI and Anthropic moved to token based billing, which is to say “you pay based on how much you use.” They still weren’t charging full rate, but they were charging a LOT more and users were not happy. One company spent 500 million by mistake: they forgot to put limits on how much their employees could spend.

Oops.

Nor are ordinary users exempt:

I Went From $3,000/Month on Claude to $5/Week on DeepSeek

And honestly? 80% of my work is identical.

For the past two months, I was burning $3-5K monthly on Claude Code. Every idea from design to development to testing – full end-to-end automation, even simulating users to test my products and provide feedback. Extremely token-intensive.

But Claude’s caching sucked, making it insanely expensive. Then I discovered DeepSeek V4.

The numbers: • Claude: $5 input, $25 output per million tokens •

DeepSeek: $0.28 input, <$1 output (with their current discount) • DeepSeek cached: $0.0002 – literally less than a penny The caching optimization is game-changing.

Once DeepSeek has seen content, it basically stops charging tokens. My result: $5/week vs $1,000/week for the same workload.

So now Microsoft has created their own minor Deepseek fork, and will run it on their servers to power Copilot. You can still use a version run by US labs, but if you can’t afford, or justify that, you can use the Deepseek version.

Driving the news: Microsoft says companies using Copilot Cowork will pay based on how much compute they use.
  • The company tells Axios it is exploring a fine-tuned version of DeepSeek V4, or another open-source model, as a lower-cost alternative to the Anthropic and OpenAI models now powering Copilot Cowork.
  • Microsoft says it expects to make a lower-cost model available in the coming weeks and will confirm its choice then.

Worse than this, there’s beginning to be serious pushback on whether AI is all that useful. Uber’s COO opened the door back in March:

In perhaps the most high-profile example of this growing concern yet, Uber COO Andrew Macdonald acknowledged during a recent podcast appearance that gains in productivity simply weren’t being reflected in the oodles of cash the company has been shelling out on AI.

“That link is not there yet, right?” he told Rapid Response host Bob Safian. “I think maybe implicitly there is more that is getting shipped, but it’s very hard to draw a line between one of those stats and, ‘Okay, now we’re actually producing 25 percent more useful consumer features.'”

“If you’re not actually able to draw a direct line to how much useful features and functionality you’re shipping to your users that trade becomes harder to justify because it’s not free,” he complained. “AI is not free.”

As far as I can tell there’s little evidence that US priced AI is more cost-effective than the employees who were laid off because it was so great. I rather suspect that in most cases, it’s less cost-effective.

But more importantly we have the “it’s better to be wrong with the crowd” effect moving against AI. In almost all positions, including executive ones, if you’re wrong in the same way that everyone else is wrong, it’s no big deal. If you’re wrong against the crowd (say not getting into AI when the rest of your industry is) and it turns out that AI is the next big thing, well, you’re fired.

So much of the AI mania was driven by this and a relentless hype cycle. Now that important people are beginning to push back on it, it’s no longer required to be all-in on AI. And that’s bad for Anthropic and Claude.

AI is not the next coming. It is not going to make it to general AI (not this generation of large language models anyway) and while it does have some utility the US frontier models cost far more to operate than any conceivable return most of their customers will receive. It isn’t the “get rid of three-quarters of your employees” super app corporate leaders were promised.

And to the extent it is useful, well Chinese open source models are more cost effective. As good? Generally no. But they keep catching up, and paying 70 to 97% less makes up for being somewhat behind.

So to the extent that AI is a real industry, odds are high China’s going to win the race. Since the models that will win will be built off open source models that’s not a crisis for anyone, it’s a good thing, far better than a proprietary future.

BUT it does mean that US AI expenditures are probably going to turn out to be the biggest misallocation of resources in centuries: bigger than the housing bubble and bigger than the dot-com bubble (which at least did have a world changing technology behind it.) Not quite the Dutch tulip bubble, but at least the Dutch got lots of pretty flowers of that, instead of massive ugly data centers.

Business is driven by stupid people engaged in group think, especially in the West, far more than most people will admit. Everything Silicon Valley does these days is someone trying to create a monopoly or oligopoly so they can be insanely profitable, while China actually competes on price, and that’s why China keeps eating the West’s lunch.

I’d cry, except that an open source AI world is a far better one than a proprietary one, and every tear some Silicon Valley tech bro cries over a lost opportunity to make a monopolistic buck an angel gets their wings.

What I write here is for the benefit of everyone, but alas, I live in capitalism and I, and the site, take money to keep running. If you value the writing here and can, please subscribe or donate.

 

AI: Make Them Stupid, Then Sell Them Brains

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On June 9, 2026

30 Comments

The evidence on AI’s effect on those who use it has been coming in, and it’s not good. While it doesn’t effect everyone, it seems to effect most people, and the worst affected, it seems, are the young. Olds have the advantage of growing up in world where they had to learn how to do things themselves. To be sure, phones and social media seem to have had a negative effect on attention span and learning ability, but AI is yet another assault, and it hits the young hardest.

This excerpt comes from a larger piece from a university professor on the inability of his students to read. The whole thing is worth reading, and the decline is truly precipitous: fundamentally most of them can’t read an entire book, and struggle even with long articles, and they can’t pull out the arguments made. The bit on AI follows:

Another reason for the decline in student reading capability is increasing reliance on generative AI. In June 2025, Nataliya Kosmyna and colleagues at the MIT Media Lab released a preprint titled “Your Brain on ChatGPT.” They divided 54 participants into three groups writing SAT-style essays — one using ChatGPT, the second group using a search engine, the last group using nothing — and monitored brain activity with a 32-channel EEG. The ChatGPT group showed the lowest neural connectivity of the three, with up to 55 percent reduced connectivity compared with the brain-only group, and “consistently underperformed at neural, linguistic, and behavioral levels.” Eighty-three percent of LLM users could not quote a single line from essays they had written minutes earlier. When the LLM group was forced to write without AI in a follow-up session, their brain activity did not bounce back to baseline; the researchers coined the term “cognitive debt” for the lingering deficit.

The fundamental strategy of a lot of tech startups has been to degrade pre-existing infrastructure by under-pricing, for years if necessary, until the old methods are so diminished that they can start charging monopoly pricing. Uber is the classic example: Ubers were far cheaper than taxis for about a decade. Now they’re often more expensive, if the taxis exist at all. Certainly where I live in Toronto, the Taxis did somewhat survive, and cost less.

But overall the strategy was a success, taxi companies were devastated and Uber’s doing great now. All it took was years of losses and predatory pricing: their model wasn’t superior, their product wasn’t superior except having a good app, but they had far more access to patient money, willing to take losses for years to get to the oligopoly pricing end-state.

Neither Anthropic nor Open AI are remotely profitable. Every single query costs more to run than is charged, even to paying clients. A recent increase in prices, still far below running costs, has hit users with massive bills. There’s no evidence AI is better than humans at most tasks, and the real cost (and sometimes, even subsidized, the current subsidized price) is higher than just having employees. AI is often faster, but it makes mistakes humans don’t, and needs to be checked.

But if you make your employees use it they’re going to be degraded and lose the ability to do their jobs well. The more you do something, the more your body and brain optimize for it. The less you do it, the worse you get.

AI’s strategy for replacing workers is threefold: first, sell executives on getting rid of pesky workers for AI, because it’s supposedly easier to manage.

Second: Subsidize while companies lay off the workers and replace them with AI. Once the workers are gone, jack up prices; and,

Third: by encouraging companies to force workers to use AI and to replace workers with AI in some cases, make the workers less capable: stupider. Over time as more and more people become dependent on AI to think and work for them, they will lose the ability to do the work themselves. AI may be shitty, but it will be better than the dullards AI makes its users into.

It’s an ingenious strategy, really. Make people stupid, and replace them with a product which costs more and is inferior to them for most tasks before they were made stupid.

The longer term issue will be that AI isn’t creative: it uses the embodied creativity of past humans, in terms of their writing and their discoveries to simulate intelligence. But as humans produce less and less new creative work, AI will be reduced to eating its own results, and indications are that leads to model collapse: AI’s are dependent on human, and by making humans redundant and stupid they will themselves become stupider and less effective over time.

We live in a time where we can’t look ahead, ever, at technology and make even the smallest effort to control the end results, it seem. At least in the West. Or, rather, we refuse to deal with obvious negative issues if doing so means a few people won’t be able to get as filthy rich.

Dumb.

And soon we’ll be even dumber.

What I write here is for the benefit of everyone, but alas, I live in capitalism and I, and the site, take money to keep running. If you value the writing here and can, please subscribe or donate.

Western AI Investors Are the Dumbest Money In The World

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On May 27, 2026

34 Comments

Regular readers will know that ever since Deepseek came out, with token costs of three to five percent of US models, and open source which you can run on your own servers, I’ve been saying that China would win the AI war.

Here’s another data point:

I Went From $3,000/Month on Claude to $5/Week on DeepSeek

And honestly? 80% of my work is identical.

For the past two months, I was burning $3-5K monthly on Claude Code. Every idea from design to development to testing – full end-to-end automation, even simulating users to test my products and provide feedback. Extremely token-intensive.

But Claude’s caching sucked, making it insanely expensive. Then I discovered DeepSeek V4.

The numbers: • Claude: $5 input, $25 output per million tokens •

DeepSeek: $0.28 input, <$1 output (with their current discount) • DeepSeek cached: $0.0002 – literally less than a penny The caching optimization is game-changing.

Once DeepSeek has seen content, it basically stops charging tokens. My result: $5/week vs $1,000/week for the same workload.

The Chinese have been optimizing for efficiency. Frontier models are a little better, at each generation, but the Chinese aren’t sitting still on quality either. What will happen is convergence: where all the models are about equally good. Until then, the Chinese models may be 3 months to 6 months behind, but that’s all and when they have the advantage of being, not just 95% cheaper as before but over 99% cheaper, and when they’re open source, so the vendor can’t just increase prices or restrict usage without users having any ability to run the model themselves, well, only an absolute moron would plan on using Anthropic/Claude or Open-AI.

The West is building vast numbers of data centers, far more than the Chinese, because nothing is optimized for efficiency. Our models use far more electricity, far more GPUs, and far more water. Additionally the Chinese are working hard on real-world AI uses: robotic AI, in other words, so that their AI can be used for actual production, and pushing on humanoid robots so they can take care of their old people, do household work and so on: Chinese AI is optimized to do shit work so you can read and write and paint, while Western AI is optimized to do creative work so you can shovel manure, do your own laundry and clean toilets.

I simply cannot fathom; I literally spent 5 minutes repeating to myself, “how can they be so fucking stupid?” what American tech leaders and the people throwing money at American AI companies are thinking. They lose money with every single query. Starbucks just got rid of their inventory AI because it couldn’t tell the difference between oath milk and cow milk even after months of trying to make it work. The only large use-case for American AI is programming and even there quality questions are rife.

But even if it winds up being as great as they say, they’re still going to lose, because it’s not going to be enough better than Chinese AI (if it’s better at all in a few years, which I doubt) to make up a 95 to 99% cost difference plus the safety that open source provides.

We are ruled by morons. Our rich people, whom we celebrate as brilliant, are idiots and fools. The moment Deepseek came out, the response should have been to figure out how it was so much more efficient and add that to American AI. No one even considered it, they just threw hundreds of billions of dollars more money at doing the same thing they were doing before.

You can’t look at American AI, as anyone who uses is, and not realize it’s massively subsidized and that at some point they’re going to have to charge the actual, real cost. As with everything else, the plan is to destroy alternatives, then once they’re damaged beyond repair (like Taxis and “rise sharing”, raise prices.”

But this won’t work with AI because the Chinese aren’t playing along and it’s software that can be run on any server, if you have access, and, again, Chinese models are mostly Open Source and way, way cheaper.

I’m shaking my head as I write this. This is the greatest mis-allocation of resources I’ve seen in my entire life. It makes the housing bubble (out of which we at least got some homes) look brilliant and wise.

Morons. Our leaders are morons. And this isn’t even a case of “well they’ll do well out of it and they don’t care about anyone else”, it’s a case of “they’re going to lose hundreds of billions of dollars.”

One more bailout. Maybe. This is the last time.

And the West is DONE.

Because we aren’t even ruled competent evil people. We’re ruled by utter idiots.

(I wanted to write that they’re the dumbest money in world history, but, alas, that still goes to the Dutch tulip bubble. Though, again, at least they did get a lot of beautiful flowers out of it, which is more than we’re going to get.)

What I write here is for the benefit of everyone, but alas, I live in capitalism and I, and the site, take money to keep running. If you value the writing here and can, please subscribe or donate.

 

The Twin Pillars of the Interregnum of Unreality Are Under Stress

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On April 8, 2026

29 Comments

Guest Post by Nat Wilson Turner

Last Fall, I posited that the US and greater West are in the grips of an Interregnum of Unreality that began when Barack Obama successfully papered over the Great Financial Crisis while addressing none of the causes and leaving the very same banksters whose antics caused the crisis in place.

The Interregnum of Unreality is the legacy of Barack Obama who achieved near-total information dominance via traditional and social media and used that power to promulgate a message that everything was fine, nothing ever happens, the neo-liberal order will never end because it rests on two indestructible pillars:

  1. The perception of American prosperity
  2. The perception of global American military dominance

Thanks to Trump’s impericidal decision to attack Iran in February, kicking off a war he can’t TACO out of, the reputation of American invincibility has taken a beating.

The estimable Aurelian writes in his latest missive of the global political implications of the ass-whipping the American military has taken in the Ramadan War:

That hit is going to be all the larger because of the massive, orchestrated PR campaign that has been going on for more than a generation, presenting the US as the Empire and the Hegemon, its military the unstoppable colossus trampling small countries underfoot. But the test of a hegemon is not how loudly you shout, but whether you can in fact do what you claim. In spite of defeats in Iraq and in Afghanistan, and the ignominious scuttle from the Red Sea, both boosters and critics of the US have been prepared to believe the US had that much power until the last month or so. But now we have price discovery, and it turns out that the US has large and quite capable forces, but it’s not the unstoppable giant ogre that it claimed to be, and never was. The whole “hegemon” thesis, people are beginning to realise, was smoke and mirrors all along: it’s just that now it’s obvious. It’s not just how it is now, it’s how it always was: a traditional result of wars, after all, is to reveal the truth about militaries. No doubt even as I write, pundits are busy composing apologias along the lines of “well, of course by hegemony we just meant Quite a Powerful Nation with a Large Military, actually.” But overselling and underperforming will have their usual political consequences.

He also brings in the second pillar of our interregnum of unreality, the markets:

There’s an interesting comparison to be made with the “Artificial Intelligence” racket, which was similarly hyped, and also expected to somehow guarantee world-dominating status for the US. But in quiet corners away from the hysteria, people who know what they are talking about have been pointing out for several years now that “AI” is a scam, that as an industry it will never be profitable, and that the money, and even more the power and the infrastructure needed, will never be available. And just in the last few weeks, the media are discovering that that’s how it is, and indeed that’s how it always was, if you had bothered to do a few sums. We can add the interesting rider, however, that in a world where generating power is going to have to be rationed, and silicon chips may be scarce, the “AI” scam may come to a swifter and more brutal end than even its worst critics supposed. Exactly what that will do to the US economy I’m not qualified to say, but I imagine it won’t be pretty.

And the damage will not just be financial. Most of the big names of international business, the Musks, the Zuckerbergs, the Altmans and the rest of that lot, treated with fawning reverence by the media and governments of the world, and who have persuaded us that what they think is actually important, will turn out to have empires built on not very much. How badly the poisonous mixture of world depression, financial crisis, and shortage of power and chips will hit them I don’t think anybody knows, but if they survive, their image, and that of the US as a technological leader, will have suffered as badly as the image of its military.

Earlier this week I posted at Naked Capitalism about the deep ties between OpenAI, Oracle and the UAE and that there are indications they are deepening those ties even as the foundations of their partnership are being lit on fire.

The weak links in the AI boom and the Middle East — OpenAI, Oracle, and the United Arab Emirates (UAE) — are strengthening their ties even as the Ramadan War exposes their increasing vulnerabilities.

Spoiler alert: Despite OpenAI’s jarring strategic shifts last week, the UAE is still pouring money down that hole.

Is reality finally intruding on our generation-long delirium?

When Trump failed to calm the markets last week with his ridiculous address to the nation, it seemed that a little reality was peeking through the veils.

But when Iran joined Trump yesterday in claiming that the basic terms of a ceasefire and ensuing negotiations had been reached, the markets roared their approval, with American equities markets posting huge gains.

This despite the ceasefire never taking place and the Strait of Hormuz only being open for a few hours.

As I attempted to document in a post earlier today at Naked Capitalism, “cognitive dissonance and conflicting agendas among key players” has allowed the western media to engage in an orgy of chatter about this ceasefire that never was even as Israel, Iran, and reportedly the UAE all launched strikes at civilians and industrial infrastructure.

One hopes that Trump realizes he went too far in his genocidal threats to destroy Iranian civilization and will at least refrain from implicitly threatening to nuke Iran going forward.

However it’s almost certain he will attempt more attacks on Iran involving US ground forces and equally certain that those attempts will end as disastrously as his first.

We’re seeing a full-on anti-Trump mutiny from leading MAGA media figures and even 70 of the senescent US House Democrats are calling for Trump to be removed from office because Trump’s rhetoric freaked the American mainstream the fuck out.

Democratic 2028 aspirants Rep. Ro Khanna and Sen. Chris Murphy both capitalized on the Trump-triggered panic and ensuing TACO to raise their profiles. Most of rest of the Dem 2028 aspirants have been caught flat footed, trapped by their zionist obligations and inability to recognize the political moment.

The freakouts and cognitive dissonance will continue until they can’t.

And as Aurelian pointed out, the consequences of the Interregnum Ending will be serioius:

For the US, as I’ve indicated, the shock is likely to be existential: Americans have been so misled for so long by their governments and media about their economic and military strength that the sudden discovery of its limits will be brutal and de-stabilising. Above all, a political culture of entitlement, which is used to issuing demands and threats to try to get what it wants, will suddenly have to cope with the US becoming the demandeur, as it is over the current “ceasefire,” obliged to make compromises and sacrifices to get what it needs to keep the country going, and seeing others expand into the strategic space it has vacated. Whether the current political system will survive the shock, and whether it will be capable of actually making the concessions necessary for survival, are very open questions.

Meanwhile the majority of Americans are getting their faces vigorously rubbed in the litter box of reality every time they pump gas and soon the inflationary impact of Trump’s war will resonate throughout the economy.

The longer it takes for the official narrative to adjust to new circumstances, the longer the Interregnum of Unreality continues, the worse the impact will be and the bigger the looming revolutionary moment will seem to be and the more forceful the ensuing crackdown will need to be to snuff it.

Risk and Reward As Perceived in American Strategic Culture

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On March 26, 2026

17 Comments

~by Sean Paul Kelley

How does the way an individual perceives time affect the way they approach risk? And can the way individuals perceive time and risk be applied on a macro scale?

Let’s take a look.

Sociologist Phillip Zimbardo developed a five way typology of how individuals perceive time. People who inhabit certain zones have certain characteristics unique to their typology. Diane Maye, commenting on attitudes toward risk by the US military at The Strategy Bridge writes, “future-oriented people tend to be more successful at achieving their goals, whereas people who frequently reminisce about the past can be overly nostalgic or fearful.” Makes sense, no?

What about those who live in the present? How do they perceive time and more importantly how do they approach risk? This type inhabits what Zimbardo calls the present hedonistic mode, and as Maye elaborates, “[are] more likely to engage in risk-taking behavior.” Maye adds that “the present hedonistic person “lives in and for the moment” and demonstrates a “lack of regard for future consequences.”

I can’t think of anything that describes the outlook of most Americans with more accuracy than this. America is a nation riddled with a present-mind perspective. Our media diet is now totally skewed towards immediate gratification with absolutely zero thought for the future. No one reads long-form essays any longer, much less books. Tik-Tok, X and even the nightly national news is geared towards quippy repartee, not well-informed consideration. Balance and objectivity in reporting just takes too long, especially when you can strike a pose, Right or Left. Such a thing is much easier and much more rewarding to ones endorphin producing centers. Intellectualism is so passé.

Indeed, one of the greatest losses of the last several years was NPRs shift from a medium whose central bias was intellectual, to one that skews left is overtly political. All part and parcel of the slippery slope towards an all pervasive AI-driven society concerned only about its own immediate gratification.

This typology can just as easily be applied to our national approach to such existential matters as voting, domestic economics, and foreign risk, mainly in the context of our conduct of war, best summed up as “bomb first, analyze the loss later.”

The consideration of risk and reward became uncoupled from each other during the Reagan Administration, when the debt markets were restructured drastically by a crucial innovation: MBSs, mortgage-backed securities and junk bonds–supposedly to democratize finance–and the equity markets were deregulated and then a Bull’s ass was set aflame by Greenspan’s long era of easy money. The spread between them only grew worse under Clinton, doubly so under Baby Bush, Obama and aren’t even spoken in the same sentence under our new Maximum Leader, Trump.

Americans, however, are soon going to learn that when you sow the wind, you reap the whirlwind. The consequences of which will be grim.

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