Luu's post includes a (long!) list of specific predictions that aren't "exacerbated"; they're simply wrong.
Luu's point isn't that AI is going to succeed or that the "AI bubble" will never pop. It's that these predictions are all wrong. If you agree "directionally" with Zitron, all that means is that you're skeptical of AI. That's a totally reasonable position to have, but it has nothing to do with whether Zitron's predictions are good or bad.
No, the whole thesis is XYZ likely fail because REVENUE RECORDS is not enough to dig out of hole relative to MAGNITUDE MORE SPEND. Saying Zitron wrong because XYZ made $2 for every $10 it spends revenue needed to justify spending. Fixtaing on the $1-$2 is misdirection/innumeracy, the thesis is in reaching the $10 relative to time, i.e. that $2 has to be $10 in X time, but the current velocity suggest it will not be.
I agree with Zitron directionally on accounting, I in fact disagree with him on AI... I am extremely AI pilled, i.e. I think there is a future where AI is worth trillions and will capture large swatch of economy. The transformation will be extreme, unlike any past revolutions... but the accounting suggest that future isn't coming in time to rescue current AI incumbents from finance blackhole, which some may survive, i.e. bail outs, nationalization... but the $$$ suggest however we get there, there will likely be massive $$$ corrections involved irrespective of adoption.
Someone in deep debt backstopping with maxing credit cards is not dunking on outside observer saying this arrangement ultimately not sustainable. The article is nitpicking over short term micro/liquidity when ultimate macro/solvency. Now maybe there's plenty of credit cards to max out, but systematically someone is going to end up holding the bag, and politically that could be public socializing costs. If folks want to use article to dunk on Zitron short term forecasts, it's whatever, but I think important to point out it doesn't refute his long term thesis around fundamentals, which again does not mean fundamentals cannot be overridden by non market means, but that's also a crux of the long term thesis - in lieu of correction/market clearing, we're going to see non market interventions to save current model from its fundamentals.
It could be "tulip mania" or it could be "the internet".
Luu analyzed the numbers instead of just reacting to hype.
Specifically:
>> Oct 2024: OpenAI's forecast of $3.7B revenue in 2024 and $11.6B in 2025 and $100B in 2029 are absurd, "a statement so egregious that I am surprised it's not some kind of financial crime to say it out loud"
> Wrong (2025 goal exceeded, 2029 TBD but not an egregious financial crime level of implausible)
>> February 2025: Anthropic making $34.5B in revenue 2027 is "is laughable on many levels, chief of which is that OpenAI, which made around twice as much revenue as Anthropic did in 2024, barely made a billion dollars from API calls in the same year."
> Wrong (whether or not they make that in 2027, their 2026 ARR greatly exceeding that makes the 2027 estimate non-laughable)
The numbers being cited is ~100B is well within accounting/ledger maxxxing tricks relative to current pool of investment. Luu is not analyzing number's he's just listing and believing numbers, and analytically entirely avoids the core Zitron thesis... once you tap out of easy investor $$$, FAANG warchest, accounting tricks... where is the rest of the order magnitude more $$$ that justifies existing spent relative to time frame coming from?
Counterargument: As advancements in transistor densities slow down, the rationale for increasing depreciation cycles makes more sense. As the performance gap between new & 5-year-old hardware continues to shrink, then the need to replace older hardware similarly shrinks, justifying longer depreciation cycles.
[1] is a reasonable discussion of DC cost models, which calculates depreciation as part of the annual cost.
> here is the rest of the order magnitude more $$$ that justifies existing spent relative to time frame coming from?
That money comes from long term debt (ie bonds by public companies[3]) and new investment into neo-cloud companies (ie, IPOs like 4).
The justification comes revenue. Eg, the NScale IPO above[4] has $51B in long term contracted revenue with an annual run rate of $500M.
[1] https://epoch.ai/data-insights/ai-datacenter-cost-breakdown
[2] https://www.cushmanwakefield.com/en/united-states/insights/d...
[3] eg https://www.yondrgroup.com/newsroom/press-release/yondr-secu... (but you'll find lots of similar bonds issued)
[4] https://dealroom.co/news/143730-nscale-eyes-september-us-ipo...
You understand that this doesn't follow at all right?
The intermediaries margins can compress.
> opex low - capex premium is ridiculous right now
What does "capex premium" even mean?
Of course you spend more on capex when you build a data center than opex!
High capex matches the expected business model. If opex was high then everyone would be worried!
Investors exuberantly build $10 of housing when there is $5 of demand, builders extract $8, when they normally extract $2 under normal margins, builders raking it, but arrangement is net loses vs world where investors build same housing for $4 and make a profit. Intermediaries margins can compress but what they already extracted for current build out is already built in balance sheet.
>What does "capex premium" even mean? >Of course you spend more on capex when you build a data center than opex!
No. Historically DC opex > capex, i.e. 60-80% goes towards power... because hardware costs were relative low % of TCO. Historically without delulu AI demand, IC producers capturing much less margin and TCO of DC was much lower than it is now. It's not opex vs capex it's TCO. AI is paying $10 vs $4, when demand is $5, $10 isn't sustainable, $4 is.
Now builders will be fine in case of crash, they'll compress margins for next round of buildouts, i.e. bubble bursts, current spend proves not sustainable. This is where the crux of argument is...
Future investors post crash when margins revert towards mean will be spending $4 to supply $5+ of demand. And due to nature of compute deprecatiion (i.e. tulips) they will have more efficient hardware with less opex/capex TCO per unit of compute, with much more sustainable balance sheet. The builders are still fine with their $2 margins, it sucks its not $8. But that leaves the current investors who spent $10 with stranded assets that are not competitive with more efficient $4 future build out, i.e. current investors have balance sheet black hole that cannot compete with none bubble market force.
This does not mean AI is doomed, it just means incumbents from current tranch of bubble driven, stupid high TCO build out is most likely doomed relative to future entrants. Unless incumbant has unassailable moat, or other hedge/cards (i.e. political bailout/intervention). That is the actual argument, Zitron is saying current ecosystem economics not sustainable, not that there is not a future model that isn't sustainable. But it does mean a lot of current players are balance sheet zombies, who _should_ die. But a reasonable disagreement is reality is size of bubble + contagion risk + influence of incumbents i.e. trillion dollar companies is such that they have non market lever (i.e. politics) to save themselves... but someone else is going to be doing the paying for a model that is net loss.
e.g. when he suggested Anthropic may be fudging their revenue numbers / projections - which was actually due to him making some careless mistakes in a spreadsheet
Like one can believe AI is speciation event technology eventually, but still given actual constraints, i.e. literally not enough investors for $$$, not enough hardware, not enough infra over xyz time horizon that these companies carrying stupendous debt and mathematically guaranteed stranded / deprecated compute infra is only digging themselves deeper vs future competitors. Sure AI can eventually capture 30% of GDP and knowledge worker's life time achievement is worth a few $100 of compute or a few pennies in thinking sand. But ultimate winners is probably going to be some future startup that pays pennies for thinking sand not incumbent who paid magnitude more and simply can't operate profitably due to balance sheet.
His point isn't that Google or Meta are doing well or have bright futures. Luu is generally critical of tech giant engineering and product culture. He's critical of Google in particular in this very article.
But the point of the article is that it's not enough to have directionally satisfying vibes. If you made concrete forward-looking predictions and they're catastrophically wrong, that matters. If you make backwards-looking predictions that were literally wrong the moment you published them, that matters even more.
"Did you read the article" is a frowned-upon response on HN. The better way to write that kind of response, per the guidelines, is "the article mentions that". So: the article mentions that.
> it's not enough
It's enough for some of us, like his broad predictions that work on timescale of business cycles seem directionally correct. Even considering we're dealing with fast hardware deprecation cycles it will take years to play out especially with investors and incumbents burning through accumulated war chest. Luu seem oblivious to notion that companies with trillions in market cap can certainly out manipulate fundamental short / medium term market sanity. Part of Zitron's rant I find similarly compelling is the danger of dismissing directionally "satisfying" vibes because $$$ can capture reporting distort reality, which is only going to lead to bigger/more painful correction because directionally "correct" was dismissed as merely directionally "satisfying."
If my cousin kept ranting about my other cousin was going to go bankrupt and fail and it was 3 years later and their income was up 2x I think I’d stop listening.
I worked at Google from 2016 to 2022 and agree with everything he says and you say, modulo the companies who are 2-3x on revenue and profits are going to 0. I worry that both of you have found a real problem but misattributed it, and insisting emotional arguments are the same as rational prevents you from participating in real fixes (ex. metas problem isn’t AI, it’s that they have a god-king CEO who cannot be deposed and monopoly profits. Imagine a twin of you and Zitron but instead of AI it’s 2020-era VR. If they weren’t focused on how their emotional argument was fine, they’d be your compatriots in noticing something’s off in Big Tech. Instead, we don’t hear about them because that battle was fought and lost years ago, and they lost credibility due to imagining Meta was going to 0)
He is not, though. He precisely points to imprecise predictions, decontextualize them so he misses the point of the ones this thread is focused on, analyzes them with even less precise rationales that don't really rebut the prediction, and points suggestively (enough that you seem to have got that suggestion) that this rebuttal destroys the main prediction of every Zitron piece, while saying otherwise several times at the end of the rationale.
Zitron's predictions aren't all very good, but this article isn't either.
But Zitron isn't just blogging about how we're in a bubble. The assertions he makes are not minutiae, he basically continuously says that all the big SW firms are walking corpses. He's not having a rational conversation about the long term prospects for companies who invest in AI. There is a population of people who (rightfully) hate Google et al and want them to fail, and he just stokes their anger and frustration.
He doesn't add anything substantial, and (as the article indicates), even when he brings economic figures into the conversation, he's frequently wrong or misrepresents them.
You think we are in a bubble and that AI won't pay off for the companies investing in it.
While I'm sure there will be companies that invest badly the problem with your prediction is that the public hyperscalers (Google, Amazon and MS especially) are already seeing returns from their AI investments.
Look at the revenue growth - that is actual dollars coming through the door.
...huh? How is it "not rational"? He's saying that, based on the financial information available, it appears AI doesn't actually make very much money given the capital investments. To the point that there may never be AI ROI.
I'm not sure how much this or that "prediction" matters. His arguments would be just as strong without them, perhaps stronger because they wouldn't give folks like Luu something to snipe at.At this juncture, the analysis seems sound. AI costs an absolute fortune and appears to make very little money, comparatively.
Is that irrational? IDGI. One needs look no further than Oracle to see a company in dire financial straits.
Oracle had record revenue and profit in the most recent quarter.
That's quite a long way from "dire financial straits"
https://www.theregister.com/ai-and-ml/2026/07/01/oracle-outl...
It seems like the author of this piece hasn't.
He says:
> Stock market bettors aren't sure they like these odds. The company's stock is down more than 40 percent in the last month
The stock is down because of the increased interest load and the impact of that in the next couple of quarters, not because of doubts over Oracle's viability.
If there were significant doubts over its viability it would be down a lot more than 40%!
- They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers
- Google Search has to compete with LLMs
- Meta hasn't demonstrated a credible argument on how they're planning to use AI. AI 'friends' would kill their business model. Their saving grace ironically is that people absolutely hate interacting with AIs. Same goes for other AI assistants.
- Hyperscalers have to compete for the same hardware as AI companies, driving their costs up
- AI turned out to be excellent at both porting software to more optimized stacks and deleting the 'prestige' of building these ultra-inefficient microservice containerized stuff. I haven't read a single article about somebody bragging about this stuff. When it comes to tech (which is not AI), usually its about Zig, Rust and going native.
- So if customers really start feeling the heat of rising costs, they have a realistic path of optimizing their compute usage by using AI to rewrite the worst-offending components. I think one of the few things in which AI has demonstrated measurable economic value is rewriting software in Rust to be more efficient
Emphasis added, since having a horribly expensive AI infra allows offering enterprise contracts, which is a form of lock-in and has been pretty lucrative for GCP/Azure/AWS.
No. Net income is up quite a bit and profit margins maintained at Microsoft, Amazon, Alphabet, and Amazon. Meta net income is flat, but they are maintaining profit margins.
We'll see when they go public. Until then all these press releases are strategic messaging...
Of course not, but private investors get to see their books and investors are lining up to invest.
If you take this to be his argument, then dan’s numbers are more consistent ed’s claim.
This is about as far from "tweaking their numbers" as you can get. It's a standard way infrastructure-heavy industries structure their investments and people would be asking questions if they didn't do this!
> hyperscalers opted to lengthen the depreciation timelines of their GPUs.
Yes and so they should! GPU depreciation timelines used to be 3 years!!
Google is famously still running 10 year old TPUs at 100% utilization, and 10 year old H100s are worth more now on the second hand market than they were when they were bought.
H100 spot prices have only dropped from $5 in May 24 to $3.20 now despite the release of the B200: https://semianalysis.com/gpu-pricing-index/
I'm pretty sure your claim about TPUs is similarly exaggerated, only a v1 (barely) qualifies and would have no utility today.
I think I was talking about A100 prices (which are still only 6 years old) and conflated a few different things there.
But A100 rental prices have climbed since 2024 (as far back as free account records show on https://semianalysis.com/gpu-pricing-index/).
Coreweave has announced they will keep A100s in use until 2029 which will be 9 years old then. I think that is where I got the 10yo number I had in my head.
On TPUs, I was also wrong on that, but less so. The quote is:
"seven and eight-year-old TPUs have 100 percent utilization."[1]
That was last year, so 8 or 9 year old TPUs now (assuming it is still true). Slight exaggeration there and I wish I'd looked it up before posting.
Despite this, my point (that 3 year depreciation schedules for GPUs was too short) remains correct I think.
[1] https://www.datacenterdynamics.com/en/news/google-says-tpu-d...