70% of AI revenue comes from OpenAI and Anthropic [video]
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What are the advantages of a GPU database?
Analytical queries are dominated by scans, filters, aggregations, and joins over columnar data. Something like `SELECT region, SUM(revenue) FROM sales WHERE year = 2025 GROUP BY region` over a billion rows is very parallelisable: every row gets the same predicate and the same arithmetic. A GPU can throw tens of thousands of threads at that (memory bandwidth is the other half of the story - an H100 has ~3 TB/s of HBM bandwidth versus a few hundred GB/s for a CPU socket, and scans are bandwidth-bound workloads).
You can be thrilled by this exciting technology and all the possibilities it brings without thinking it is going to require this huge capital investment in GPUs. You could radically change billions of lives with a few dozen GPUs.
Do and sync over client to client.
Keep data local again.
Only use cloud for backups of local client encrypted blobs of vectors:data
If you get rid of a lot of the suspect semantics hallucinated up over decades of software development it's not hard to see the geometry of an electronic snowflake. All the language just obfuscates the elegance. Crude meat suit grunts and clicks.
Streamline it all to management of geometric states and access control and put the semantics on the presentation layer. What if we don't need python and go and ruby anymore? Made sense in a pre-gpu everywhere reality. Could just be high school stats classes to generate sets of values. Let go of the obscure linguistic chants.
The data centers are just to serve surveillance purposes. Obfuscated behind politically correct memes of creating jobs.
Chip away at the monolith and atomize the topology
And probably some decently sized states too. Not only commercial actors are up to the job.
These people don't know what they're talking about.
I think he's implying the money in AI is all spending from OpenAI+Anthropic who get it from investors. But those two have annualized revenue of about $26bn and $74bn or about $100bn total which presumably represents actual customer demand for the product.
That's $100bn revenue on about $1tn capex so far which isn't enough to make it profitable in itself but the things growing like crazy so you'd expect that. $100bn is about 0.08% of world GDP so if AI customer demand grows to 1% of GDP that's up 12x from here.
Surely AI is a thing that is here to stay, but I am not at all convinced that the big frontier models are going to be able to return their investment and if it becomes apparent they cannot, then you are almost certainly going to see a massive correction.
Could you provide a citation for this?
For frontier labs, their fund-train-new model play might not be as effective, and a shift of spent of compute cost moving away from training to inference might be a tell-tell sign of the LLM as we know it plateauing out as scale is just not as effective. Open models might also be placing a major pressure on meeting then revenue targets need to sustain the model, lots of customer hosting their own inference to mitigate costs.
If you only move the needle just slightly in the direction of inference, frontier labs will soon loose their alphas. Becoming just another SaaS for inference might not be as attractive unless you are Google/MSF ( IMHO ).
Should this pan out, it could be a scenario where the NeoClouds could soon loose their biggest customers, so I tend to agree with that aspect of Zitron’s view.
Thoughts?
And OpenAI did all of that and is still alive today. Would be good to know this context because if you are out there boldly making doomer predictions month after month then you should also rate your previous ones.
Because one day Ed will be right and he’ll go around and take a victory lap while ignoring he has basically not been right before.
Bold prediction.
With circular deals it’s hard to tell.
From last month: https://www.bloomberg.com/news/articles/2026-07-27/nvidia-s-...
Or from 2025: https://www.cnbc.com/2025/10/15/a-guide-to-1-trillion-worth-...
Hard to imagine a perfectly identical offsetting transaction let alone triangular or circular.
Just like any other technology
No. It was always a pyramid scheme marketed as a "winner takes all" business. But there's no winning. The only winners are those who cash out before it collapses. This is literally Web3 2.0.
[edit] one small difference from web3 is that AI does seem to be at least marginally useful in some narrow verticals (devtools, infosec). That's pretty inconsequential, though. Those verticals can't supply the capital needed to sustain the industry. So on a macro scale that isn't relevant.
When the dust settles I hope we end up in a place where we no longer accept lies and grift as pitchdecks and product briefs. If you have a technology, you demonstrate it, and only after a successful demonstration do you expect funding. We don't need to throw money at vaporware anymore, that's proven itself to be idiotic behavior over and over again.
Web3 on the other hand, none of that. I think it was some sort of crypto scam spinoff.
Re. economics, I think AI will develop a bit like in the movies but hopefully not Terminator 2.
So the whole thing hinges on, at some point in the near future--before the music stops--one of these institutions making a huge breakthrough and discovering AI. But there's no indication we're any closer to that breakthrough now than we were 10, 20, 30, or 50 years ago. They sure do have a lot of compute at their disposal, but there's no clear engineering plan to use it to scale up AI.
If this was a proven technology, there would be a clear path towards making it work. Advancing its industrial applications would be an engineering problem, not a science problem. AI is still science fiction (or at best a speculative theoretical research topic). That's not something sensible people throw money at, unless they've been scammed.
Feels like they want to make a clean headline grabbing argument about how "70% of all the spending is actually just these two companies" and are ending up with a really muddled headline that's just like yeah that's how monopoloies and duopolies work. When there's a lot more insidious circular complicated shenanigans going on that gets collapsed by this framing.
All that is discussed in the video, plus those distinctions. And most important, that AI revenue would not exist...if OpenAI and Anthropic would not be funded, by the same Amazon, Google and Microsoft they are buying it from!
We now have several voices saying the same:
"Aswath Damodaran: Big Tech Has No Idea How AI Pays Off" - https://news.ycombinator.com/item?id=49229981
"Why Wall Street Is Ignoring Big Tech's Debt" - https://news.ycombinator.com/item?id=49230630
Because a lot of isn't real demand, e.g. given away for free or very very cheap.
Because of the low prices lol.
Just look at how OpenAI has lost market share over the past year
Hilarious. You can agree or disagree with Zitron but he really has no business talking about Goldman Sachs. His posts are littered with evidence he has no ability to perform the type of financial analysis he thinks he does.
https://www.wheresyoured.at/exclusive-openai-financials/
Zitron wrote:
> Additional factors – including interest income and interest expense – left it with a net loss of $8.84 billion. It then marked $3.74 billion of losses as “net loss attributable to noncontrolling members capital,” leaving the net loss attributable to the company as $5.09 billion.
> It’s unclear what this means, nor how OpenAI reconciled the removal of $3.74 billion in costs. I will not speculate further.
It is very clear what this means, and no speculation is required if you understand basic consolidation accounting, which you would expect someone in his position to understand.
It's not rocket science: when you have a parent company with entities it doesn't wholly own, the slice of losses belonging to the other equity holders is split out as "noncontrolling interests." Nothing is removed or hidden; the total loss is unchanged, it's just allocated to reflect that the parent company doesn't own the whole. Framing it as OpenAI removing costs implied something sketchy and requiring speculation where there's only routine GAAP accounting.
But it's even worse than this. So many of Ed's claims conflate the foundational R&D and capital expenditures these companies are incurring with the unit economics of their businesses. He seems woefully unable to understand that you could sped gobs of money on the former and still have positive gross margins that scale over time with the latter.
Zitron continually presents things in ways that create a hyperbolic narrative. Turning routine consolidation accounting into an unexplained mystery hinting at some sort of fraud is the perfect example of that. He does it so often and in such a way that I truly believe he just doesn't understand accounting.
It doesn't take a rocket scientist to understand that OpenAI is losing money. But the question ("where's the profit?") assumes that profit is the thing being optimized for. It isn't.
There are basically three buckets here: cost of serving a query, cost of training and capex for capacity.
The first one is unit economics. The other two are bets on the future that get expensed against present revenue. A company can serve every query at a healthy gross margin (OpenAI has improved margins considerably) and still have a $9 billion loss because it spent $12 billion training a model that generates $0 this year.
Zitron constantly blends everything into a pithy "they lose money on everything" narrative, which just isn't accurate. The thing is that OpenAI could have a very different P&L if it chose to, say, stop training the next model.
The problem, obviously, is that if you stop training the next model, the competition might eat you. So right now you have a situation where the the frontier model you spent $12 billion on depreciates in about 18 months, the GPUs depreciate on a schedule nobody agrees on, and you seemingly can't stop the cycle without risking your position in the market.
This is the legitimate bear case, but the problem with Zitron is that he doesn't make it using an argument that is coherent and honest as far as the accounting is concerned. And the accounting is everything.
This phenomenon is known as the J-curve[1], and Uber is a good example of how this can turn out absolutely fine. To some extent, the entire Venture Capital industry exists to finance precisely this dynamic!
Nb. I'm not suggesting OpenAI is fairly valued, or that they will definitely become profitable, but "OpenAI is losing billions of dollars" doesn't really mean anything in and of itself.
[1] https://www.uark.vc/blog/breaking-down-the-j-curve-the-journ... (many other similar such articles exist)
Uber is the antithesis of OpenAI, it’s not a good example. Uber was burning money on acquiring customers. OpenAI is burning money to provide their service (and the R&D they need to continue to have valuable models). They cannot just stop and turn profitable like Uber. The money they burn isn’t invested, it won’t yield a multiple of revenue in the future. It’s consumed for compute and that’s it loo
Of course they can. They could just stop training new models and milk the existing ones. A billion users check in ChatGPT weekly. Software developers wouldn't stop using Codex.
OpenAI is not unlike any other startups who try to build their marketshare early on. No matter how much money they lose, they would be fine as long as they could raise more money than they spend. Uber is exactly the same. HN during 2015-2020 were full of comments predicting Uber's demise.
The number of users they have checking weekly is irrelevant, most of them are free users, unless they find a way to make money from them, but their ads business has been a flop so far.
For context: Uber losses were $12B over 5 years. AWS was $5B invested over 7y.
OpenAI is projected to lose more than $14B just this year!!!
Uber burned through roughly $32 billion in cumulative losses before reaching sustained profitability.
The rough timeline:
- Founded 2009, and lost money every year for about 14 years
- Biggest single-year losses: ~$8.5 billion in 2019 (the IPO year) and ~$9.1 billion in 2022
- 2023 was its first full year of net profitability, earning about $1.9 billion
- Uber has a market cap of $153bn as of today (at a P/E of 16.5)
OpenAI has received substantially more funding than Uber, so its losses will be substantially higher (spending investor money shows up as a loss on your P&L), but again that doesn't mean anything in and of itself.
Broadly speaking, companies that spend 40%+ of revenue on sales and marketing end up being a bit of a drag on society. Eg. Salesforce’ product quality is far lower than winners in other sectors that sit closer to 10-15% of revenue on sales and marketing
Maybe - just as how the city of Sao Paolo implemented a ban on billboards - we can implement a law where a 3 year rolling average of sales and marketing spend cannot exceed 20% of revenue in that period
Or maybe just can you point to some primary sources about this? I am not too bright about this stuff.. I guess I always thought it was usually about having more money than when you started? Or at least about having a story of how you will have more money? Is that not right?
OpenAI isn't a single company. I haven't followed all the details with its structure change/recapitalization, but it's (I believe) a parent sitting on top of an LLC that outside investors like Microsoft hold a large minority stake in.
The rules say that the parent has to report 100% of the LLC's revenue and expenses as if it owned everything and then, at the end, back out the share of the loss that economically belongs to the minority holders.
So $8.84 billion is the whole loss, $3.74 billion is approximately the outside members' proportional share of it, and $5.09 billion is what's left for the parent. Nothing disappeared or was hidden. It's one number presented two ways because two sets of people own it.
Like to be absolutely honest, this point ends up just sounding more alarmist than the claim you took issue with originally. But perhaps I am just misunderstanding.
Let's say I own a lemonade stand. I sell you a 20% stake.
My stand loses $10. When I report my financial results, I report losing $10. Then I report that your share of those losses is $2, and my share is $8. This creates transparency.
So OpenAI really did lose $8.8B or whatever, but some of those losses are 'attributed' to other shareholders/owners of their subsidiaries, because they have a complicated corporate structure. So they report both numbers - the total loss, and then the part they 'own'.
So when Ed says "It’s unclear what this means", he's either terribly uninformed or intentionally misleading his readers into thinking something fishy is going on when it isn't.
Either way, it's bad journalism - if you don't know what it means, shouldn't you try to find out or ask an expert or something and then inform your readers? (And the thing is, it would easy enough to dunk on them for losing $8 billion, without adding these weird insinuations!)
Like its you want to both say that you agree with the overall point here, but also can't trust that very same conclusion because one part in the article reveals an obvious ignorance. Except no one has been able to actually state the exact ignorance here other than the suggestion that Microsoft is in fact the one losing $3 billion dollars, which doesn't really feel very far from Zitron's original implication anyway given all the stuff he writes!
Zitron makes too many "mistakes" like this to be taken seriously. In other words, he just isn't the right person to make the "huge AI bubble" argument because he doesn't understand (or he's being dishonest about) the financials.
I wouldn't consider OpenAI's financials to be pretty. There's circularity in the market that is a bit concerning. And while OpenAI's unit economics have improved it's still questionable as to whether the R&D and capex expenditure ever aligns to the business.
But Zitron is too sure of his argument (without the credibility to support that confidence) and is trying to pretend that there's absolutely nothing of value here. My best guess: there's some "irrational exuberance" and malinvestment but there is something real here and the unwind of the irrational exuberance and malinvestment won't be nearly as painful as Zitron believes for a variety of reasons, including the fact that there just isn't enough leverage in play.
Like I just don't know how to trace this almost moralistic fixation everyone has just about this particular guy.. Everyday we see articles exactly like his by different people (or at least I do), but none attract the same kind of distinct attention.
What even leads you to the concern? Like, why should we think he will be the one conquering the narrative here?
Who else does a detailed financial breakdown like Zitron and thinks things are as corrupt/fishy as him (in particular make specific claims about certain unexplained sums of money)? All the articles I see ultimately just trace back to Zitron. Curious who else you've found.
Except his financial breakdowns almost always get basic points wrong, treat as mysteries things that are clear, cast simple accounting practices in a conspiratorial light, etc.
He's not an accountant or financial analyst and it seems obvious to me that he doesn't even care to educate himself.
- https://io-fund.com/ai-stocks/nvidia-coreweave-nebius-circul...
- https://www.bloomberg.com/news/articles/2026-08-05/microsoft...
Cory Doctorow's feed gives me some pretty diverse but certainly Zitron-adjacent articles every week, one example: https://pluralistic.net/2026/08/01/dare-snot
Oh this guy! https://prospect.org/2026/08/03/ai-bailout-could-be-baked-in...
I can hear the response now that these are all not exactly repeating what Zitron is saying, but I will just leave it up to you all to decide if that is a good faith thing to retort here or not :). Godspeed!
Zitron has become the poster boy for the "AI bubble". His hyperbolic claims make for good content, which I presume is why he gets such a large platform, but they pollute the dialog and make it harder for people to have meaningful conversations about what's going on.
Many discussions of the AI market largely mirror what he says. People who don't understanding basic accounting and who haven't taken the time to educate themselves making bombastic claims about 2008-style bubbles, fraud, etc.
So we end up with discussions like this: simple basic consolidation accounting is misread as fraud. Malinvestment using little to no leverage is predicted to produce financial crises that were caused by 10x and higher leverage. And so on.
So to answer your question ("why should we think he will be the one conquering the narrative here"): his claims already have.
Its like saying David Gerard dominated the crypto backlash, yet I doubt many even know who he is now, and it would seem laughable to give him so much credit these days.
Again, you keep asserting some adult-in-the-room wisdom to your outlook here but only end up offering even crazier pictures of reality! Its a weird a mix, but I do respect it.
This can of course be used to distort the financial picture and this is a significant amount, almost 50% of losses. Is this from the ‘non-profit’ which used to be OpenAI or something else?
Smells like creative accounting to me and the CEO was accused by his board of dishonesty.
https://dart.deloitte.com/USDART/home/codification/broad-tra...
I get that not everyone is an accountant or has had to become educated in accounting matters as part of their work, but you really shouldn't say "smells like creative accounting to me" if you don't have a basic understanding of the subject.
This is like the least interesting thing about OpenAI's financials, and Zitron framing it as some sort of mystery hinting at fraud is one of the least effective ways to make a point given that it's absolutely a nothingburger.
No loss is disappearing or being hidden. This is by-the-book consolidation accounting.
The accounting mechanics are uninteresting, lots of normal accounting rules are abused for nefarious purposes (see Enron et al). What is interesting is why this was done.
Which subsidiary owns the loss and why?
Say Parent Co. controls Subsidiary LLC and owns 60% of it. Minority Corp. owns the other 40%. Subsidiary LLC loses $10 billion.
Consolidation accounting requires Parent Co. to report the full $10 billion loss, as if it owned all of Subsidiary LLC, which it doesn't. Then, on the next line, it attributes the portion belonging to the other owner (Minority Corp.). There are two lines and one loss. Nothing is removed and nothing hidden. This is the definition of disclosure, not obfuscation.
Note that the trigger for applying this is actually control, not ownership interest. My understanding is that OpenAI Foundation controls the public benefit corporation with 26%. And for an LLC, the loss split isn't automatically pro-rata by ownership. It follows the profit-sharing terms in the operating agreement, which is why the there's a Hypothetical Liquidation at Book Value method. Under an old capped-profit waterfall, nobody can verify the exact figure without looking at the operating agreement.
"I can't verify the split" is a very different statement than "it's unclear what this means."
Your "why" question: the reason it works this way is that consolidated statements are meant to show the business as an operating whole because that's what a controlling parent actually runs. You can't operate 60% of a data center or sign 60% of a compute contract. Every line (be it revenue, expenses, assets, etc.) comes in at 100% for that reason. The noncontrolling interest line then answers the separate question of how much of that whole belongs to the parent's own shareholders. One statement answers two questions (what does this enterprise look like versus how much of it is ours).
As for your "who" question, the answer is simple: the other equity holders. Again, OpenAI doesn't own 100% of the entity. My understanding is that Microsoft is one of the other equity holders.
If they own 90% and it is core to the business that’s very different from owning 2% say.
"Also as of closing of the recapitalization, Microsoft holds roughly 27% of OpenAI Group, and the remaining 47% is held by current and former employees and investors."
But this ignores that the capex spent to build more capacity is expected to generate additional future revenue. You don't need to recoup your capex immediately. A better approach would be to amortize the capex and compare revenues to that.
Clearly he assumes revenue won't increase enough to recoup this level of capex (and it's very possible it won't) but IMO it's either a miscalculation of how the financing works or a deliberately misleading framing to compare current small revenues to a big scary capex number.
I'm sure the above is simplified by the way, but I am confident that people who work at Goldman understand the relevant details extremely well.