Ian Welsh

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

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American “AI” Is “No Win” For Society

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On November 13, 2025

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Let’s lay out the big picture for LLM style AI.

It is is statistical prediction of what should be the next word or symbol. That is why it required so much data to train and why, even if we had the tech, we couldn’t have created it 20 years ago: not enough data in digital format. It is not intelligent. It is not conscious. It is just an algo trained with a TON of data and which used massive amounts of processing power (and thus electricity) to produce results. Hallucinations are part of the tech, they cannot be eliminated, which means that LLM “AI” will always make mistakes and many will almost certainly be the sort of mistakes trained humans rarely make.

The current build-out in the US involves only a few companies, all in a huge circle jerk, and they make up 40% of the entire public stock market’s value. Neither Open AI nor Anthropic actually make a profit, and it costs more to do a query than is made even from paying customers, let alone all the free ones. There is absolutely no question in my mind that they are in a bubble.

The maximalist claim for “AI” is that it will become so smart it can replace at least 40% of jobs. (Or smart enough.) The more realistic claim is that it’s good for some things and can replace some workers by making those who remain more efficient. Plus, after all, most tech companies don’t care if their products are shit as long as they make money. See Google for “who cares what you think, it’s us or no one. You’ll use our product no matter how shit it is.” (Ironically, Search is one of the few things AI is better at than incumbents.)

So here’s the thing: no matter whether AI is a real tech or not, it’s in a bubble. (The internet was real, it had a bubble.) No one actually knows who’s going to make money from AI. The big internet winners (Amazon, Facebook, Google) came after the dot-com bust. The Feds may backstop and/or bailout, if they do, it will hurt everyone not involved.

If I am wrong about AI and the maximalist claims are true then what will happen is a massive replacement of tens of millions of workers. Since those people will now have almost no income, that will lead to a classic demand depression. A great depression like the one in the 1930s. The only way out would be a massive guaranteed annual income. Given our rulers and ideology, we’d probably have food riots long before they realized they were risking their own throats.

If it is a real tech, but not that big a deal, it will lead to a shittier economy where even more mistakes are made, and it’s even harder to find a human being to fix anything. Which is what tech wants: they want everything automated and certainly they don’t want to have real customer service.

And, if it is a real tech, as I have noted before, China is actually going to win. Their models are 20 to 30 times cheaper to run, and are open source. If your business uses AI you will use open source if  you have half a brain, because with open source one of two major providers (Anthropic/Open AI) can’t just raise prices or change the model. To use closed source would be so stupid that even most American CEOs will not do it. Certainly no one with sense outside American vassal swarm will be so stupid.

So:

  1. Maximal AI leads to a great depression.
  2. Moderate AI leads to a shittier economy and shittier projects.
  3. There’s a bubble either way
  4. At the end of it China’s AI models will be used far more than American ones anyway. The US has already “lost” the AI race and can’t even see that. (Why? Fundamentally because they’re greedy and want to become billionaires of trillionaires. Genuine open source AI won’t print nearly as many rich people.

America can’t win at anything that matters any more, because the people who lead America are stupid, liars and so greedy they can’t think of anything but money. (See Trump, who is the avatar of all these vices.)

 

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Trump Has Achieved Biden Levels Of Delusion And Denial

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On November 11, 2025

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I mean…

Not to mention firing BLS workers because he didn’t like the stats, which even Biden didn’t do. Given how dubious most BLS stats relating to inflation already are, that’s some impressive cope.

The fact is that prices keep going up, and if you aren’t in the golden ponzi scheme of AI, the economy sucks.

Rosenberg Research did some analysis:

If they aren’t in expansion, they’re in contraction. Also known as a recession, even if they didn’t shade it.

Some further supporting data:

 

Sure doesn’t look like those tariffs are causing manufacturing to flood back into America, does it? Data centers and power station building are both AI related, and as for hospitals: a protected oligopoly, or it was until the ACA subsidies were cut. That’s not likely to be good for the health “industry”, which would be wonderful except that people will die and suffer as a result. “Get rid of part of the shitty way we provide health care now without replacing it with something else.”

Anyway, unless you’re in a monopoly/oligopoly, and have some control, or you’re connected to the AI spigot, the economy is ass. And remember, major tech companies are engage in mass layoffs, so just working for tech companies won’t protect you: the reverse is true. Unless you’re actively working on AI, you’re first to the gallows, since their workers are where they’re starting with the replacements.

For decades I warned coders, “engineers”, that their days of being king shit of turd island, pretending their skills were super special, would eventually come to an end. The moment senior management could figure out how to replace them, it would. And unless you’re truly at the very top of your field, you’re always replaceable—mediocre isn’t as good as average, but it’s usually a LOT cheaper.

Anyway, the end days are nigh. There isn’t much left of the middle class in America, with little left for the rich to steal. The US either changes its politics radically (and Trump was always a billionaire whose policies are good for billionaires} or America continues its descent to unutterable shithole for about 80% of its population.

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Did Burry, Altman, Friar, Huang, Karp and Sacks Just Pop the AI Bubble?

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On November 7, 2025

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The stock market bubble inflated by AI hype since late 2022 might finally be popping. If this week’s reversals turn into a sustained downtown, analysts might look back at the actions of tech executives and Trump adminstration figures this week as the straw that finally broke the camel’s back.

The warnings have been coming for a while.

Ed Zitron (on the business side) and Gary Marcus (on the technical side) have been warning about the AI bubble for years now.

Even rubes such as myself noticed when 7 AI-fueled stocks exceeded 50% of NASDAQ’s market cap.

OpenAI CEO Sam Altman has been warning of an AI stock market bubble since August.

Dumbass META boss Mark Zuckerberg started saying bubble a month or so later.

JPMorgan’s Michael Cembalest noted that AI-related stocks have accounted for 75 percent of S&P 500 returns and 80 percent of earnings growth since ChatGPT launched in November 2022.

Harvard economics prof Jason Furman pointed out in late September that U.S. GDP growth in the first half of 2025 would have been 0.01% without AI capex investment.

Yet Another Bad News Cycle for AI

Meanwhile the litany of bad headlines for AI continued.

This is just a sampler and just from this week:

The Big Short Comes For AI

On Monday, November 3, legendary short seller Michael Burry shorted Nvidia, the chipmaker at the heart of the AI/LLM mania, and Palantir, the AI-powered government contractor.

As of Friday, he’s up about $1B.

Going for That Government Money

That’s when the AI hucksters blinked.

Well, Sam Altman had already blinked, flipping out at podcaster Brad Gerstner and walking out after a testy exchange:

Brad Gerstner: “How can a company with $13 billion in revenues make $1.4 trillion of spend commitments? You’ve heard the criticism, Sam.”

Sam Altman: If you want to sell your shares, I’ll find you a buyer. Enough.

I think there’s a lot of people who talk with a lot of breathless concern about our compute stuff or whatever that would be thrilled to buy shares. We could sell your shares or anybody else’s to some of the people who are making the most noise on Twitter about this very quickly.

We do plan for revenue to grow steeply. Revenue is growing steeply. We are taking a forward bet that it’s going to continue to grow and that not only will ChatGPT keep growing, but we will be able to become one of the important AI clouds, that our consumer device business will be a significant and important thing, that AI that can automate science will create huge value.

We carefully plan. We understand where the technology, where the capability is going to grow and how the products we can build around that and the revenue we can generate. We might screw it up. This is the bet that we’re making and we’re taking a risk along with that. A certain risk is if we don’t have the compute, we will not be able to generate the revenue or make the models at this kind of scale.

Palantir CEO Alex Karp went on CNBC’s “Squawk Box” on Tuesday and was asked about Burry’s bet:

“The two companies he’s shorting are the ones making all the money, which is super weird. The idea that chips and ontology is what you want to short is batshit crazy. He’s actually putting a short on AI. … It was us and Nvidia. I do think this behavior is egregious and I’m going to be dancing around when it’s proven wrong. It’s not even clear he’s shorting us. It’s probably just, ‘How do I get my position out and not look like a fool?’”

Wednesday OpenAI CEO Sam Altman went on the Conversations with Tyler podcast and openly called for a government backstop:

“ When something gets sufficiently huge … the federal government is kind of the insurer of last resort, as we’ve seen in various financial crises … given the magnitude of what I expect AI’s economic impact to look like, I do think the government ends up as the insurer of last resort.”

That same day, OpenAI’s CFO Sarah Friar echoed the same message at a Wall Street Journal technology conference.

The Journal led its story with “OpenAI Chief Financial Officer Sarah Friar said that …the company hopes the federal government might backstop the financing of future data-center deals.”

As OpenAI ramps up its spending on data center capacity to unheard of levels, the company is hoping the federal government will support its efforts by helping to guarantee the financing for chips behind its deals, Friar said. The depreciation rates of AI chips remain uncertain, making it more expensive for companies to raise the debt needed to buy them.

“This is where we’re looking for an ecosystem of banks, private equity, maybe even governmental, the ways governments can come to bear,” she said. Any such guarantee “can really drop the cost of the financing but also increase the loan-to-value, so the amount of debt you can take on top of an equity portion.”

Friar said OpenAI could reach profitability on “very healthy” gross margins in its enterprise and consumer businesses quickly if it weren’t seeking to invest so aggressively.

“I’m not overly focused on a break-even moment today,” she said. “I know if I had to get to break-even, I have a healthy enough margin structure that I could do that by pulling back on investment.”

OpenAI is losing money at a faster pace than almost any other startup in Silicon Valley history thanks to the upside-down economics of building and selling generative AI. The company expects to spend roughly $600 billion on computing power from Oracle, Microsoft, and Amazon in the next few years, meaning that it will have to grow sales exponentially in order to make the payments. Friar said that the ChatGPT maker is on pace to generate $13 billion in revenue this year.

Friar realized immediately she’d screwed up and went to LinkedIn to course correct:

Unfortunately for Friar, she couldn’t take it back nor did she address the other dumb things she said at the WSJ confab, per Bloomberg:

“I don’t think there’s enough exuberance about AI, when I think about the actual practical implications and what it can do for individuals. We should keep running at it.”

Regarding charts like this that argue that many of the AI industry’s recently announced deals are just a circular money-go-round, Friar said:

“We’re all just building out full infrastructure today that allows more compute to come into the world. I don’t view it as circular at all. A huge body of work in the last year has been to diversify that supply chain.”

Thursday, Nvidia CEO Jensen Huang flagrantly linked the fortunes of Amercian AI companies to American national security, telling the Financial Times that “China is going to win the AI race.”

The Nvidia chief said that the west, including the US and UK, was being held back by “cynicism”. “We need more optimism,” Huang said on Wednesday on the sidelines of the Financial Times’ Future of AI Summit.

Huang singled out new rules on AI by US states that could result in “50 new regulations”. He contrasted that approach with Chinese energy subsidies that made it more affordable for local tech companies to run Chinese alternatives to Nvidia’s AI chips. “Power is free,” he said.

Gary Marcus was on it fast, pointing out that he’d been warning that the AI bros would go for government funding since January:

Former Blackrock ace Edward Dowd quickly called out the scam as well.

Dowd also warned that:

A cluster of 3 Hindenburg Omens and Altman & Jenson signaling the end is near on the AI bubble by asking for taxpayer assistance does not bode well for the short term on $SPX.

Should Trump green light government assistance and we get a pump it will likely be faded as it will not be nearly enough. Congress has true purse strings.

The stink of desperation is in the air to keep the headline indices afloat with 7 AI stocks. Ends badly at some point.

Sam Altman went into backtracking mode too.

I’d quote the whole thing but it’s mostly bullshit and Altman is a known liar (just check out this 62 page deposition from OpenAI co-founder Ilya Sutskever which references Altman’s “consistent pattern of lying”).

Altman’s claims were complicated when this October 27 letter from OpenAI’ Chief Global Affairs Officer to Michael Kratsios, Executive Director of the U.S. government’s Office of Science and Technology Policy emerged. The letter says (via Simp for Satoshi):

The Administration has already taken critical steps to strengthen American manufacturing by extending the Advanced Manufacturing Investment Credit (AMIC) for semiconductor fabrication. OSTP should now double down on this approach and work with Congress to further extend eligibility to the semiconductor manufacturing supply chain; grid components like transformers and specialized steel for their production; AI server production; and AI data centers. Broadening coverage of the AMIC will lower the effective cost of capital, de-risk early investment, and unlock private capital to help alleviate bottlenecks and accelerate the AI build in the US.

Counter the PRC by de-risking US manufacturing expansion. To provide manufacturers with the certainty and capital they need to scale production quickly, the federal government should also deploy grants, cost-sharing agreements, loans, or loan guarantees to expand industrial base capacity and resilience.

Altman spoke to Reuters to “clarify”:

OpenAI has spoken with the U.S. government about the possibility of federal loan guarantees to spur construction of chip factories in the U.S., but has not sought U.S. government guarantees for building its data centers, CEO Sam Altman said on Thursday.

Altman said the discussions were part of broader government efforts to strengthen the domestic chip supply chain, adding that OpenAI and other companies had responded to that call but had not formally applied for any financing. He said the company believes taxpayers should not backstop private-sector data center projects or bail out firms that make poor business decisions.
…
Tech officials argue that these investments are tantamount to a national security asset for the U.S. government [Reuters supplies no source for this argument. Nat], given AI’s growing role in the U.S. economy. OpenAI has committed to spend $1.4 trillion building computational resources over the next eight years, Altman said Thursday.

Regardless of Altman’s backpedaling, the whole thing became moot after the Trump administration shut down talk of AI bailouts.

Trump Tech Czar Slams That Door Shut

David Sacks, the White House’s AI czar (and founding member of the PayPal mafia alongside Elon Musk and Peter Thiel) was quick to shut this talk down, tweeting Thursday morning:

I have to wonder if Sacks’ statement — which was a political must following GOP losses in Tuesday’s elections — might not be a Lehman Brothers moment for AI and the larger stock market bubble.

Ed Zitron’s latest report won’t stop the bleeding:

Based on analysis of years of revenues, losses and funding, from 2023 through 1H2025, OpenAI took in $28.6bn in cash and lost $13.7bn.

It was just reported that OpenAI ended 1H 2025 with $9.6bn in cash.

OpenAI has burned $4.1bn more than we thought.

And as long as we’re risking 2008 flashbacks, never forget that in 2023 the infamous Larry Summers joined the OpenAI board. I’m shocked Larry hasn’t already saved the day.

Sarcasm aside, this may be the beginning of the end for the Interregnum of Unreality that I posited began in 2008.

The Next Big Crash Is On Its Way

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On October 1, 2025

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Ever since Greenspan took over the Fed and the 87 crash when they figured out their playbook, the US has only had unavoidable stock market crashes. The Fed is always there to juice markets higher and to jump in at the least sign of a normal (pre-Greenspan) market correction.

But sometimes the irrational stupidity overwhelms even the Fed, because they are both stupid and ideologically unwilling to ever force a correction. This happened twice: the dot-com boom and crash and the Mortgage backed security boom and crash (if we bundle shitty mortgages based on lies together, they become not shitty, because we’re pretending they aren’t all basically the same thing!)

Now we’re going to get the AI Boom crash. I’m well over 90% on this. The AI booms is in the “wildly stupid over-claiming” stage. It’s not that token based AI isn’t a real tech, or that it doesn’t have some uses, but the claims of it completely changing everything (replacing a third of the workforce, acting without human help to run things, being able to cure cancer and make huge theoretical breakthroughs) are obvious over-reaches. So far every academic study that comes in shows that AI isn’t even good at the one thing everyone anecdotally agreed it was good at: writing code. Right now it seems to mainly be a good way to cheat at university, to have a fake relationship, or to bypass Google’s shitty search (which is what I use it for.) It hallucinates, the hallucinations cannot be removed because they are integral to the tech, and the code it produces, even when it works, is a huge mess that will cause massive maintenance issues.

In addition:

  • Since it doesn’t actually mostly reason, it requires data sets bigger than all the data in the world if it is to keep improving;
  • If it uses the data it itself produces, it experiences model collapse.
  • None of the American AI companies make money per query. Every query costs more than they can charge.
  • It requires a vast build-out of energy and data centers, of the “over a trillion dollars” variety. There literally isn’t enough money to pay for OpenAI and Anthropic’s dreams, and there isn’t a product at the end of it that could pay back all that money.
  • About 40% of the US stock market is now based around NVidia and the AI companies.
  • NVidia has now invested in Open AI, so that they can turn around and buy more NVidia cards.
  • The Chinese offer an open source AI which is almost as good and with costs somewhere between one fifteenth and one-thirtieth as much, so that it might actually be profitable AND since it’s open source, Trump can’t have a mini-stroke and decide to cut you off at his whim.

It’s my annual fundraiser. This allows us to cover the changeover of hegemony from America to China, environmental collapse, internal US fascism, what a better society would look like, Gaza, AI, the coming stock market crash and various other issues. As of this writing we’ve raised about $2,700 out of a $12,500 goal, from over 25 people. It’d be great if you can help out (please don’t donate if your financial situation is dire.) You can Subscribe or Donate here or contact me at admin-at-ianwelsh-dot-net if you need another way to donate (mail, usually. A lot of cash apps don’t work in Canada.)

Throwing all this money at AI if it really was the epochal “tech to end all techs, the singularity, dude” that the tech-bros claim it is might make sense. But I don’t see the evidence that this is the case, and even if it is, why not use the Open Source Chinese variety?

In fact, my guess is that this version of AI, based on this model and this generation of chips, is not even as big a deal as the internet was. Everyone was right that the internet was going to be HUGE, they just over-invested before it was and before people knew who the winners (Google, Facebook, Amazon) were going to be.

But so far AI doesn’t even look as important as the internet, but the spend is way larger than the internet build-out of the turn of the millennium.

But even if AI turns out to be a HUGE deal, it’s going to crash out of this bubble and we’ll find out later who can make money doing what.

The Fed will paper the AI market crash over, making hundreds of billions or even a trillion out of thin air to save the rich from their own stupidity and greed. Again. But this will be the LAST crash the Fed will be able to save the capitalists from. The one after will either wipe the capitalists out, wipe out America, or both.

“AI” Insanity. Does This Industry Make Sense?

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On September 3, 2025

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AI’s a weird industry. So far almost no one is making any money, certainly not the major Western AI companies: Anthropic and OpenAI. Every query costs more than the revenue it generates. The primary beneficiary has been NVidia: they’re making money hand over fist, and suppliers of data centers and power have big customers in AI. But AI itself doesn’t make money. (Not Western, anyway. Deepseek, which is 20 to 30 times cheaper, probably is.

The energy required for Western AI is huge, and it’s mostly dirty energy. AI requires mostly 24/7 energy, which means renewables are out. It needs nuclear or carbon intensive sources like coal and natural gas and turbines. MIT did a massive dig into this in March.

The researchers were clear that adoption of AI and the accelerated server technologies that power it has been the primary force causing electricity demand from data centers to skyrocket after remaining stagnant for over a decade. Between 2024 and 2028, the share of US electricity going to data centers may triple, from its current 4.4% to 12%.

AI companies are also planning multi-gigawatt constructions abroad, including in Malaysia, which is becoming Southeast Asia’s data center hub. In May OpenAI announced a plan to support data-center buildouts abroad as part of a bid to “spread democratic AI.” Companies are taking a scattershot approach to getting there—inking deals for new nuclear plants, firing up old ones, and striking massive deals with utility companies.

Nature came up with this chart. As they note, it’s lower bound, because if it was too high, AI companies would have said so.

AI’s a lot more intensive than traditional methods. For example, AI vs. a Google search (granted Google search sucks, but that’s because Google wants it to suck.)

It’s long been noted that one of the biggest issues with climate change is that we can expect it to reduce the amount of fresh water available. AI gobbles that:

AI is also thirsty for water. ChatGPT gulps roughly a 16-ounce bottle in as few as 10 queries, calculates Shaolei Ren, associate professor of electrical and computer engineering at UC Riverside, and his colleagues.

 

 

But here’s the kicker:

ChatGPT 5 power consumption could be as much as eight times higher than GPT 4 — research institute estimates medium-sized GPT-5 response can consume up to 40 watt-hours of electricity

Whoa! That kind of puts paid to rising by 10% a year and other such assumptions. It doesn’t look like new models are scaling linearly.

We have a climate change problem already: lots of extreme weather, disrupted rainfall patterns and massive wildfires. The permafrost is bubbling and releasing methane and arctic temperatures are absurd (hitting 30 celcius in some cases).

Now if this tech was truly transformative, if it made everything so much better, maybe it would be worth it. But so far, with a few exceptions (mostly running thru millions of combinations to assist research) it seems like it’s better search, automatic image generation, a great way for students to cheat and may make programming faster. (There’s some dispute about this, one study found it made coders slower.) So far agents are duds, unable to even run a vending machine.

On the downside, even AI boosters claim it’s likely to put vast numbers of people out of work if it does work, wiping out entire fields of employment, including SFX, illustrators, artists, writers, customer service and perhaps most entry level jobs. We’re told AI has a small but existential risk of wiping out humanity. It gobbles water and energy and causes pollution.

What, exactly, are we expecting to get from AI (other than NVidia making profits) that is worth the costs of AI? Does it make sense to be rushing forward this fast, and in this way? Deepseek has shown AI doesn’t have to use so many resources, but Western AI companies are doing the opposite of reducing their resource draw. Eight times as much energy? How much more energy with GPT-6 use?

It seems like we’re unable to control our tech at all. This used to be the killer argument “well, there’s no controlling it, so why even try?”

But China’s AI uses way less energy. Apparently China can control it, and we can’t? So it’s not about “can’t”, it’s about “won’t”. Using less resources would mean less money sloshing around making various Tech-bros rich, I guess, and we can’t have that.

And all this for an industry where the primary actors, OpenAI and Anthropic aren’t even making money.

Perhaps we could be using these resources in a better way? China is spending their money on producing three-quarters of the world’s renewable energy, and ramping up nuclear power. Their carbon emissions are actually down. Their economy is growing far faster than ours. They’ve almost completely moved over to electric cars, they have high speed trains, and their space program is going gangbusters. All this while reducing rent by over a third in the past five years.

You don’t have to be an AI skeptic to think “maybe this is a misallocation of resources?” Is it really going to change everything so much so that it “makes America great again”? Is western AI so much better than Chinese to make that difference even if AI is as big a deal as its greatest boosters say?

Maybe the US and Europe should be concentrating on more than just AI? Not letting China continue to march ahead in almost every field, while putting almost all the marbles on one big project that they barely have a lead in anyway?

I don’t want to overstate this issue. The amount of energy and water used doesn’t come close to, say, expected increases in air conditioning. (Though if increases in draw continue to ramp up similar to GPT-5 we’ll see. And, the more energy we use, the more air conditioning we need thanks to fairly obvious feedback.) But still, what are we getting for it?

Just some things to think about.

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The Best Short Summary of Why China Is Winning & the West Fading

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On June 2, 2025

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It’s about living in reality:

The main difference between American and Chinese society today is less that one has more dumb people and one has more smart people and more that within public life, being stupid is relentlessly shamed as stupid in one and being smart is relentlessly shamed as stupid in the other.

These days, American society assigns intelligence credentials based not on who can demonstrate a meticulous, well-developed understanding of how anything works, but on who can give the smartest sounding, post-hoc rationalization for the half-baked ideas people desperately want to be true.

If you do the former, and it yields answers people don’t like, they’ll reach deep into their bag of fantasyland narratives to try to invalidate your credibility. If you provide the latter, you’re celebrated — not only as a genius, but a champion. When things don’t work as promised?

They’ll have already sunk so much personal credibility and self esteem into the fantasy they’d rather burrow deeper into delusion than backtrack. In other words, “smart” is whatever helps nurse fragile self esteems rather than whatever helps them understand and work with reality.

In Chinese society today, intelligence is still very much a consequential trait that demands its keep via real, effective results. In the US, it’s turned into another fake self esteem signifier in a culture that’s long stopped caring about anything but fake self esteem signifiers.

I observed this a long time ago, personally. I had predicted the financial crisis, right down to the month. I had been right about Iraq and a variety of other important issues. I was discussing the “Arab Spring,” and said, “It isn’t over till the army votes.”

There was argument back and forth, and I said, in effect, “Look, I have a track record, and so do you. I’m usually right, and you’re usually wrong.”

The response was furious, and I was booted off that particular forum.

In my last major blog role as managing editor, I was able to increase traffic by 60 percent in less than a year, and I felt onto most of it after the election of Barack Obama. Other Netroots sites were bleeding readers, but not us. I could say exactly what had been done to increase traffic. But the publisher was sure they knew better, so I left. That site no longer exists.

People who were for the Iraq war, who made claims that it would work and be easy are now major pundits. Both Matt Yglesias and Ezra Klein were for the war. Indeed, Yglesias wanted to take out all of Iraq, Iran, and North Korea. A study in the L.A. Times found that media figures against the war were fired, laid off, or had their careers stagnate. Those who were for it had their careers prosper.

A correspondent once did a serious search on who had been right, in public and in advance, about the financial crisis. The number was in the 40s. That means that almost no economists, the people who, you know, study this stuff and claim to know something, predicted an obvious bubble. You only had to look at a couple charts. It wasn’t rocket science.

For most of my life, development economists claimed that free trade without protection for local industry was how countries should industrialize and that they should move to cash crops and sell commodities. Every country that tried this failed. The ones who succeeded at industrializing did so behind some form of protection for new industry: China, Japan, South Korea, Taiwan, and so on. They certainly didn’t double down on commodities. The only thing that has ever worked is exactly what development economists advised against.

Fools like Francis Fukuyama became famous and wealthy by saying nonsense things like how “democracy and capitalism are two sides of the same coin” and “the end of history has arrived.” Those of us who warned that it mattered where industry was, and that sending your industry to other countries was the equivalent of shipping away your power and prosperity, were sneered at.

Climate change has, for decades, come in “over,” which is to say worse, than the consensus predictions. Almost every single bad event has happened sooner than the IPCC said it would. You’d think, after a while, they’d ask themselves, “Why are we getting this wrong all the time?” and self-correct. If you can’t figure out why, just look at the windage, make your predictions, then add the average error rate. “Events usually happen X percent sooner than our models predict, so here’s the dates taking that into account.”

It’s not rocket science.

Most Western pundits thought that Ukraine would “win” a war against Russia. No. Pundits told us over and over again that NATO expansion wouldn’t cause a war. Wrong. Pundits told us that Russia was weak compared to NATO and that GDP accurately measured their strength. Pundits thought that sanctions would collapse the Russian economy, not taking into account that China had a veto over that, and a reason to use it.

In every single case, the discourse had, and has been, seized by what people want to believe, or what oligarchs want people to believe. They want people to believe what pays, not what is true. There are no consequences for being wrong and no self-awareness. I am bad at electoral predictions. So when I make one, I always note that I suck and am probably a negative indicator. (I thought Harris would win, for example, though I did get the Canadian election right.)

Now, it isn’t entirely true that there’s no accountability in the West. There is. There is only one rule that the West insists always be followed:

The rich must keep becoming richer, no matter the cost to anyone or anything else.

Because that is the only form of Western accountability, the West will keep losing, because richer rich and higher inequality do not cause or even correlate with any of the main constituents of power, prosperity, or technological progress

Our entire discourse system, our entire media, and our entire elite class have zero accountability outside of ensuring the rich get richer.

At this they have succeeded and at nothing else.

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China Is Going to Win the AI Race

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On May 28, 2025

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Yeah, it doesn’t seem that way, but it’s how it will turn out. What China’s doing is embracing actual open AI (unlike the company named Open AI). Open source and open standards. Everyone outside North America and maybe Europe is going to prefer that, and those who set the standards control the tech. On top of that, American AI is frighteningly expensive; no one in the US is making any money. Every query costs more to produce than is earned, even from customers who are paying, let alone all the free accounts.

Deepseek is much less expensive per query, however. The idea of capitalism is to, y’know, make money? There’s a limit to how much money Softbank can throw at AI if it doesn’t start providing at least some returns.

Further, American-style AI requires massive amounts of energy, and guess who produces the equipment needed to quickly build more generation capacity? (If you need more than one guess, you haven’t been paying attention.)

Every hyper-scale or “AI-ready” data-centre campus needs its own sub-station and a bank of step-down transformers big enough to deliver 50-150 MVA per site. Add the grid-side upgrades that utilities must make to back-feed those loads, and each incremental gigawatt of GPU capacity pulls several hundred megavolt-amps (MVA) of new LPT demand.

Roughly 80 percent of U.S.’s large power transformers (LPT≥100 MVA) are imported and lead-times have ballooned from 50 weeks (2021) to 120-210 weeks (2024), and the lone domestic GOES mill provides only a fraction of what new AI loads will require.

China dominates both finished-unit exports and nearly half of global GOES output; it also supplies critical sub-components such as tap-changers and bushings. GOES now fall under Beijing’s 25 percent retaliatory-tariff list and new export-licence regime.

Export licensing is China’s retaliation for the US “don’t sell China chips or lithography machines” regime. I’m sure they won’t drag their feet or outright deny exports to the US, when the US has explicitly restricted “AI” chips to attempt to cripple China’s AI industry. I mean, turnabout isn’t fair play, amiright?

Thing is, China has proved very good at using what they can get, or make themselves, and they’re making fast progress on chips, with the possibility of creating a new class of chips which out-performs anything the US has looking very likely. The US, on the other hand, cannot ramp up production of transformers on any reasonable timescale.

Reap, sow. Fuck around, find out, etc.

As for AI destroying all jobs, well, no. It makes mistakes too often, and in anything that matters even a one or two percent serious error rate is unacceptable.

I, at least, will laugh myself sick when Silicon Valley gets its lunch eaten by the Chinese on AI. I mean, it’s sad, because Silicon Valley bros are so humble, never brag and never lord it over anyone else. It’s not like they’re assholes whose entire business model is based on gouging and taking value from everyone else, and it’s not like modern “AI” is based on the most vast theft of other people’s work in history.

And them Chinese, man, who do they think they are? Embracing open licenses and open standards and actually trying to make a profit, like they have real competitive markets or something? Commies can’t do Capitalism better than America!

 

This blog has always been free to read, but it isn’t free to produce. If you’d like to support my writing, I’d appreciate it. You can donate or subscribe by clicking on this link.

AI Will Degenerate In Much The Same Way Google Did

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On January 30, 2025

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If you’re old enough to remember search before and after Google, you remember how good Google search was at the beginning.

Google used links to rank what to show to searchers. In the old web, before Google, every link was, in essence, an endorsement. We linked to what we thought was good, that other people should read.

It was a pristine “state of nature” system.

But the minute Google became dominant in search, everyone started manipulating links and metadata and everything else to get Google to send them more traffic. Links were no longer organic, no longer endorsements, but attempts to manipulate the algo. The more that was true, the more it became necessary to engage in “search engine optimization”, and the more algorithmic search engines sucked. Of course, Google also self-sabotaged, by trying to optimize search results so that Google would make the most money possible.

I recently read a regular traveler saying he never reads travel blogs and magazines any more, because AI is so much better. I’m sure he’s right.

But AI is better because it’s reading all the travel blogs and magazines, sorting and summarizing. AI being better, readership is cratering, and so the blogs and magazines will slowly die off. Travel’s one of those activities where you need relatively recent information, where was great to stay years ago isn’t very helpful. So, as the blogs and magazines die, the AI’s results will slowly get worse, until they’re crap scraped from official websites of hotels, museums and other travel destinations, since that’s all that will remain.

AI, in other words, in this and other ways, many of them similar, will destroy the ecosystem required for it to be good, same as Google did.

This is “eating the seedcorn/destroying the soil’s fertility” type of stupidity. If you destroy an ecosystem you’re dependent on (and we’re all dependent on some ecosystems) then whatever you’re doing is only short term viable.

So enjoy AI as an alternative to search for now (but always check its source, because it does hallucinate) but understand this is a moment in time, a moment which is destroying what makes it possible.

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