Oh! What’s his reputation?
The people who are completely sold on the belief that AI providers are running at a profit believe him to be utterly, totally and completely wrong in every one of his predictions.
The people who are completely sold on the belief that AI providers are running at a loss they can never recover from believe him to be utterly, totally and completely correct in every one of his predictions.
The reality is that it's not his predictions that matter, but his data, which is almost always correct as of time of writing. If you ignore his opinions, the data presented on liabilities, spend, revenue, loans, commitments, etc across Coreweave, Stargate, Oracle and all of the usual AI companies is, as far as I can tell, correct.
IOW, when it comes to his opinions, it's all about your priors. His data is good, though.
Yeah, I think that he does well with sources and data. I also think that his editorialising can be off-putting for lots of people. I kinda enjoy it, but accept that I have niche tastes.
He's not even good at that, here's him not understanding what ARR means and fumbling a simple calculation and refusing to fix it.
https://x.com/binarybits/status/2031392856401666362
Not only not understanding ARR, he simply doesn't do data analysis properly - he misses some few months and days in his calculation to prop up his point. This is a mistake chatgpt would have caught.
Can you share me the official meaning of ARR? Preferably on a GAAP basis. Should be no problem, right?
This is something Ed clearly doesn't understand https://x.com/edzitron/status/2031124650474852382
And you haven't addressed the fact that he doesn't do simple data calculations - see his blog https://www.wheresyoured.at/the-beginning-of-history
Can you be more specific on his incorrect calculations please?
The miscalculations are pretty clearly pointed out in the tweet I linked earlier.
This is (historically) a recipe for fraud and badness. If ARR is important enough to be reported, then there should be a GAAP definition.
Do you use calendar month or four week rolling? Do you account for seasonality? How do you recognise revenue? (My sense is that Anthropic do sketchy things with credits, as the consumer ones last for like 180 days and then expire).
ARR is a really, really, really easy metric to make sound like whatever you want which is why I am sceptical of it.
EDIT: I looked at the tweet which is a screenshot of a supposed sheet that Ed built. Unless you have a source for the sheet then I'll need to assign this relatively low credibility (don't know the user, it's a screenshot with no link).
It’s here in the blog.
> This is (historically) a recipe for fraud and badness. If ARR is important enough to be reported, then there should be a GAAP definition.
This is orthogonal to Ed misunderstanding ARR.
> I’m a reporter who has written about technology, economics, and public policy for more than a decade. Before I launched Understanding AI, I wrote for the Washington Post, Vox.com, and Ars Technica. I have a master’s degree in computer science from Princeton.
> I’m working on Understanding AI full-time, and I have no outside investors or donors. Since I started it in 2023, paying subscribers have accounted for a large majority of my income (you can see full details on my source of income on my disclosure page). Their support allows me to work on the newsletter full-time.
Passes my credibility check because I've read a lot of his work, and he's been around the block a few times in journalism circles.
Do you have a link to his blog where he gets the ARR wrong?
True, I haven't much of his posts, but the one or two I recall reading with ARR in it didn't seem to have fumbled the calculations.
I think the question is more about whether people believe this is a sound business in the long term, which imo isn't possible to tell based on these numbers yet.
It's funny, because you can both believe that these entities are bleeding money on every token and also believe that "financial engineering" will bail them out when they IPO despite this fact.
The fundamentals of running a business that sells products or services for more than the cost to produce them seem increasingly decoupled from the financial success of the company and its owners.
After this supposedly being the reveal for his bubble-bursting massive revelation that will send the industry flying and lead to journalists kicking in his door for interview requests and exposés, I think... well, not that anymore. I thought "the frontier labs are losing money" was rather universally understood, and this really isn't even as bad as the stuff that's publicly visible; the fact that they keep raising hundreds of billions of dollars that they'll one day supposedly be required to show returns on?
I mean, the fact that lots of expenses are not scaling with revenue (sales and marketing 5xed versus revenue 3xing) and that the losses are very very large is important. More importantly, these are audited figures which haven't been seen before.
https://www.ft.com/content/e15b0d7e-ff6b-4f16-ba7a-4068feddb... this uses the same sources and answers more honestly and Ed Zitron doesn't touch on this.
> As OpenAI’s worth rose, the increased value of those investor rights created a roughly $30bn charge, added the person. The charge is not expected to recur following the restructuring, they said.
> Stripping out the charge and other non-cash expenses, such as stock-based compensation of staff and computing credits from Microsoft, OpenAI’s losses were $8bn, according to the person.
Whom would you trust? FT or Ed Zitron?
And none of my points have anything to do with the once off losses. I'm observing that a bunch of costs appear to be scaling with revenue or above revenue, which does not bode well for future profitability.
Also, as an aside, stripping out equity grants is really misleading for a private, high growth tech company.
Once expectation stabilises these losses won’t happen because the valuation will remain constant. A lot of people were paid really high equity grants simply because they started low. You can’t expect them to be paid the same amount each time.
FT themselves point this out and who you believe is up to you.
My original point around equity is that if you pay a substantial fraction of comp in this form, then leaving it out of expenses is pretty bizarre.
Is it your contention that the equity grants are the cause of their increasing losses?
I believe that this is probably not true at all, it's more likely to be S&M (salespeople scale as N not log(N) like engineering/product) particularly given that the product requires tuning for lots of companies (hence all the FDE hires).
More generally, the training costs seem to be increasing which is bad for their future profitability.
Also it should be obvious that you shouldn’t extrapolate stock based compensation in a scale up. People make a one time bounty but that is not recurring obviously.
As OpenAI’s worth rose, the increased value of those investor rights created a roughly $30bn charge, added the person. The charge is not expected to recur following the restructuring, they said.
Stripping out the charge and other non-cash expenses, such as stock-based compensation of staff and computing credits from Microsoft, OpenAI’s losses were $8bn, according to the person.
I presume that this is what you're talking about, right?
That doesn't actually disagree with what I noted above using the (more detailed) figures from Ed's article. I noted that their revenue scaled by about 3x, while many costs (cost of revenue, sales & marketing, r&d) scaled by either equal (r&d) or greater than their revenue scaled. That's the point I was (apparently badly) making, nothing to do with the stock based compensation causing their losses. In any case, the loss was actually driven by treatment of the non-profit shares.
> Also it should be obvious that you shouldn’t extrapolate stock based compensation in a scale up. People make a one time bounty but that is not recurring obviously.
Correct, in some sense this is a once-off, however, most tech companies continue granting stock over time, so it's definitely worth including in actual margins. (This is a more general point that's not exclusive to Open AI).