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I don't think Zitron has been right about anything in the last 5 years. But he talks a good talk.
Every post about Zitron here seems to have a comment like yours at the top.

Another thing those comments have in common is that they offer no logical or rational explanation of why he is supposedly wrong.

It's quite hard work to research why wrong. His always writing 10000 words doesn't help. I'd say he's over skeptical of AI being a real thing and he cherry picks the financials. (earlier comment from me with some details https://news.ycombinator.com/item?id=49073112)
I cannot understand why people listen to him? I feel like I must be living in an alternate universe to a substantial amount of people? It's bananas...
The problem with his work is that a lot of the conclusions he comes to are a step too far, but the problems he identifies with how money is moving or how much datacenters cost or how no one has ever built a 1GW datacenter and we're expected to believe they can build a bunch of them, or even a 10GW data center - those are real.
I am not so sure that those are actual problems? I mean, "they're problems" - but everyone is still acting like it's 1996! The world is changing fast...

And if he can consistently be so wrong on those things, and has no real education in the field, then why the hell should I listen to him when he's screaming FUD at the top of his lungs?

It reminds me of the gold guys who constantly talk about how the dollar crash is mere months away. One day that is likely true, but when those guys predict it month after month and get it wrong all of those times, I don't really take their theses seriously.

There's certain figures he gives that paint the picture well enough without him having to really even make the argument. For example, in his piece "The More You Buy, The More You Lose"[1], a few paragraphs in, he says: "Hyperscalers will have sunk over $1.3 trillion dollars into generative AI by the end of 2026, and have plans to spend a trillion dollars more next year. On a very rational level, nothing that large language models (LLMs) have done, do or will do in the future can or will ever bring in the more than $2 trillion (or more) in brand new revenue that will be required to make any of this worth it."

He explains some more numbers in the following paragraphs (that aren't needed to make my point), but the problem isn't even that AI can't make any money, it's that the scale of the money spent is so colossal, what they would need to do to actually make it back is insane! They'd need to actually replace most of the workers in the world because that is such a ridiculous, unimaginable amount of money! It outclasses all of their combined revenue significantly, and remember, these companies don't tell us how much money they make from AI (anymore), they bundle it in with other things, and if it was good, you know they'd be shouting it from the rooftops how much they were making.

I also don't take seriously any of his predictions that have dates attached to them - after all, the market can remain irrational longer than you can remain solvent. I don't trust his timing, but the numbers don't lie.

[1] https://www.wheresyoured.at/the-more-you-buy-the-more-you-lo...

> It's bananas...

Actually, it's lemons (https://en.wiktionary.org/wiki/Zitron).

Sorry, I couldn't resist:)

Boooooooo! <the dad joke make me smile, but insert Zoidberg meme here>
Well he's saying what a lot of people desperately want to believe.
this strikes me as a much more plausible answer, thanks. A LOT of people are really scared about the future. That's kind of stupid for a lot of reasons, but I suppose you're right, selling people what they want to hear has a long history.
Even if we don't consider economics, the reason "AI" has not increased white collar productivity is because it's not necessary for knowledge work beyond aggregating information for research. Knowledge work has always been a lot more arguing than "doing".

Google was already the default option for this, and Google Gemini is a genuine improvement for Google Search. Google (and Apple) have sidestepped all the drama by just improving their existing products. Sometimes that's the right call in the shorter term, and this is one of those times.

Yes, and the scary thing is, when Google starts selling ads in Gemini results, you wont be able to see them, it will be a bigger business that Google Search ever was.

Update: Perhaps this is what Zitron doesn't want to say out loud, (and why investors are confused), the return on investment is going to come from having the largest mind control machine the world has even known.

> the return on investment is going to come from having the largest mind control machine the world has even known

This is what Google already was and continues to be. They didn't need OpenAI and Anthropic as foils to maintain that position or expand Google Cloud. If anything, they did all this work with Gemini despite what's happening on the sidelines.

OpenAI secured their multinational defense contract with Project Stargate. I can easily see the extremely high demand to get rid of so many contractors with security clearances. No government believes that the risk of another Snowden-like whistleblower is worth the mediocre intelligence summaries.

The loser will be Anthropic unless Microsoft buys them out for a lowball price at the last minute in an attempt to make Copilot less terrible. For everyone else, it's business as usual.

There's just no easy way to see what makes LLMs able to duplicate the profits of the entire existing tech sector of the economy. This is the return they need to make based on what they're currently expensing and projecting. Couple that with the circular financing agreements and it's just preposterous. Zitron may have been first and most outspoken to this argument, but like all bubbles it's an open secret.
LLM advertising consuming all current advertising dollars plus more is realistic. That's a solid chunk of the entire tech center it eats right there.
I don't fully agree with Zitron on all his points but it's very hard to disprove the larger points will somehow resolve themselves. One point that I think will determine the future, moreso with data centers, is politics. Laws are not unchangeable and making decisions that determine the next 5-10 years of action based on the current law is a recipe for disaster. "Buying" a politician still has to account for the fact they can be voted out.
> making decisions that determine the next 5-10 years of action based on the current law is a recipe for disaster.

How else can one make business decisions? Or any long term decision, financial or otherwise.

If you are correct, which I fear you may be, then we, in the West generally, are now living in a low trust society.

Which is not a good thing at all, and should be of utmost concern.

I feel like it’s been understood that we live in a low trust society for a while now. If not for all of us, at least for a LOT of us.
Let us assume a person cannot change society, they simply do not have the leverage, even if they are a billionaire or most politicians. This is a systems problem, requiring enormous investment of time and resources to change trajectories of. Therefore, the choices available are to continue to live in a low trust society, or move to a high trust society and minimize your exposure to low trust society impact on your life. It's unfortunate. I would very much like to be wrong, please correct me if I am mistaken.

https://www.visualcapitalist.com/mapped-where-people-trust-e...

https://ourworldindata.org/grapher/self-reported-trust-attit...

This data conflicts with my image of Japan and China, and I wonder where the discrepancy lies.
I cannot speak to China, but my recent personal experience is that Japan is high trust throughout Tokyo, Kyoto, and Osaka. Would love to hear about the trust situation in China from anywhere who has recent ground truth.
The propagandised idea that living in China means living under an oppressive communist regime, runs counter to the countries wild success at pretty much everything it does.
Hey, remember Naomi Wu? She used to post a lot here. I wonder whatever happened to her?
Good point. We can always point to Naomi Wu as an real life example of why China is NOT living in the future. She is a good example of why we would never want to replicate what China is doing
I don't think success directly translates into high trust.

I think of China as a hypercompetitive place, which to me should mean lower trust.

In a newly evolving situation, you have to assume that it's possible that the laws will change. Typically the way you account for this is hedging or keeping reserves to adapt.
All day every day you make decisions based on things you think you can safely assume, and things you know you can't assume.

The most likely behavior of a political office is just one of the things you know you can not safely assume, that's all.

What laws do you think will change
So right towards the end Zitron says it isn't clear what Google, MS and Amazons plan is. But he just finished explaining that Anthropic and Open AI are paying for them to build data centers, and implied that on face value, this was to rent the data centers back to Anthropic and Open AI.

Seems to me they are just bleeding them dry so that when the money runs out for Anthropic and Open AI, they will be left with data centers that the can run their own (or open) models.

If you read more of Zitron's work, he says that there's little demand for the AI compute power outside of OpenAI and Anthropic. If they are bled dry, then the hyperscalers will not have enough customers for the data centers which they have blown so much capex spend on and will have to soon go into debt to ensure they can be built. The GPUs and the high bandwidth memory they use have little use other than to run and train these LLMs.
So his big insight is that if you take away the two largest customers the demand is much lower? Wow, such informative.

>The GPUs and the high bandwidth memory they use have little use other than to run and train these LLMs.

It's compute, and can be used to compute anything.

"It's compute, and can be used to compute anything."

Do you know anyone that needs trillions of dollars of compute?

It's GPU compute, which is a lot more niche. There are only so many things you can render or simulate and only so many people/companies who want to render or simulate something. Not even remotely enough to create enough demand to saturate a trillion dollars worth of GPU data centres.
There is a famously counterintuitive conjecture about demand and supply named "Jevon's paradox". For compute it held so far.
> little demand for the AI compute power outside of OpenAI and Anthropic.

I think every other business is going to slowly wake up to how powerful machine learning can be, and or, how important it will be to run your own models you can trust.

I don't doubt that there is a bubble, but once the hardware is built, there will be plenty of customers.

I guess if you overpay for hardware, you can be undercut by data centers built after the bubble pops, but that might just mean your return on investment is slower.

I don't think so. AI is a general purpose tech and you have many companies still doing discoveries on how to apply the technology in a useful way. It's an expensive solution in search of a problem. Not to mention no one wants to pay the actual cost of what it takes to deliver the technology. The whole business model is unsustainable.
The business model has not been discovered yet.
Go have a look at that Seedance thread. Movies and TV will be completely AI in the future.
and he wrong on all of those accounts. but he’s got the best gig, he has been writing literally one same article for years, gets LLM to shuffle the words and publishes it under a different title :)
Now, now, let's be fair. I don't think LLMs are used for writing or editing the articles in any way.

(Each reader can decide themselves whether what you wrote is unfair to Zitron or to LLMs.)

look at his articles from 202_ and compare them with 2026. the year will be 2078 and he will still hussle money out of his subscribers talking about exact same thing over and over again… this is like “experts” predicting a market crash. market will crash, eventually. it always does, eventually. so if you say every day until it does, you are guaranteed to be the one that predicted the crash, eh?

reminds me of a “riddle” my Dad told me when I was a kid which asks “why does the native american rain dance always works, 100% of the time always produces rain?” to which I replied that not only do I not know but also that it cannot possibly be true. he smiled and said “it always produces rain because they do not stop dancing until the rain starts.” #dadwisdom

His follow-up point was, "that seems like a ridiculously nice double-dipping situation" until you realize that money depends on only two "unsustainable" customers, spending other people's money, that now have to become absurdly massive to ever make this work.
Another view of that is, hedging their bets. Which businesses do all the time.
The chimp brain cant handle unpredictability for too long. Just keep pushing people into unpredictable situations or specifically try getting someone to say I dont know constantly. Beyond a point story generation starts, to feel sane within an "I dont know" reality.

Truth is things are unpredictable. Predictability of anything hasnt increased.

Stories/Lies exist for cope. Cause of chimp brain dynamics responding to unpredictability.