Speaker 1: Media. Hello, and welcome to a very special episode of
Speaker 1: Better Offline. I'm, of course, your host ed ze trunk.
Speaker 1: For years, I've been hunting down the core details behind
Speaker 1: open aiyes costs and revenues, and today I'm going to
Speaker 1: bring you some of them. A lot of what I
Speaker 1: say today is going to be reflected in my newsletter,
Speaker 1: which I'll link to in the notes. Based on documents
Speaker 1: viewed by my newsletter, I'm able to report open aiy's
Speaker 1: inference spend on Microsoft asure in addition to its payments
Speaker 1: to Microsoft as part of its twenty percent revenue share agreement,
Speaker 1: which was reported in October twenty twenty four by The Information.
Speaker 1: In simple terms, that last bit means that Microsoft receives
Speaker 1: twenty percent of open eyes revenue in addition to whatever
Speaker 1: it spends on GPUs and servers. As a reminder, influence
Speaker 1: is the process through which a model creates an output,
Speaker 1: which I'll be reminding you of a few times because
Speaker 1: it's actually kind of important. Now a few notes. I
Speaker 1: don't have open AI's training spend, nor do I have
Speaker 1: information on the entire extent of open AI's revenues, as
Speaker 1: it appears that Microsoft shares some percentage of its revenue
Speaker 1: from being as well as twenty percent of the revenue
Speaker 1: Microsoft receives from selling open AI's models on as you.
Speaker 1: What I do have, as I've mentioned, is its inference spend.
Speaker 1: And if you're new to this, like I said, this
Speaker 1: means all the computation's open ai does when processing requests
Speaker 1: sent to its services like chat, GPT, and Sora. Now,
Speaker 1: before publishing, I asked a financial time supporter to help
Speaker 1: corroborate some of the data in the documents. They reached
Speaker 1: out to Microsoft and open Ai, who both declined to comment. Now,
Speaker 1: the following will be a lot of numbers, and it
Speaker 1: might be easier for you to read them. However, I'm
Speaker 1: going to try and make things as easy and clear
Speaker 1: as possible, because the documents I've seen call into question
Speaker 1: what we actually knew about open AI's business and the
Speaker 1: sustainability of said business. To keep things simple, all the
Speaker 1: years in this piece are calendar years. Microsoft has fiscal years.
Speaker 1: I'm not going to play that game. It's impossible to
Speaker 1: follow along with nobody thinks this way. Now we've done that,
Speaker 1: let's get to him. According to the document's view by
Speaker 1: my newsletter, open Ai spent five point oh two billion
Speaker 1: dollars on inference alone with Microsoft Azure in the first
Speaker 1: half of calendar year twenty twenty five. This is a
Speaker 1: pattern that has continued through the end of September twenty
Speaker 1: twenty five, by which point open ai had spent eight
Speaker 1: point six seven billion dollars just on inference. Open AI's
Speaker 1: inference costs have risen consistently over the past eighteen months too.
Speaker 1: For example, open ai spent three point seven six billion
Speaker 1: dollars on inference in twenty twenty four, meaning that open
Speaker 1: ai has already more than doubled its inference costs in
Speaker 1: just the first nine months of twenty twenty five. These
Speaker 1: costs are dramatic and significantly higher than has been previously reported.
Speaker 1: According to the Information, open AI's computer run models, which
Speaker 1: I understand to mean inference, was two billion dollars in
Speaker 1: twenty twenty four. Additionally, an April twenty twenty five piece
Speaker 1: from the Information stated that open AI's inference costs for
Speaker 1: twenty twenty five would be around six billion dollars, or
Speaker 1: roughly two billion dollars less than open ai appears to
Speaker 1: have spent through the end of September. I want to
Speaker 1: be clear as well, I'm just reporting what these documents
Speaker 1: have said. This is not a statement about the information.
Speaker 1: They do great reporting. But then there's the issue of
Speaker 1: the revenue share. As I've previously stated, the following numbers
Speaker 1: are based on the revenue share paid to Microsoft as
Speaker 1: part of its deal with open Ai, where it gives
Speaker 1: Microsoft twenty percent of its revenues. According to the documents,
Speaker 1: Microsoft received four hundred and ninety three point eight million
Speaker 1: dollars in revenue share payments in twenty twenty four from
Speaker 1: open Ai, implying revenues for twenty twenty four for open
Speaker 1: Ai of at least two point four to six nine
Speaker 1: billion dollars, or around one point twenty three billion dollars
Speaker 1: less than the three point seven billion dollar number that's
Speaker 1: been previously reported in multiple outlets. Similarly, for the first
Speaker 1: half of twenty twenty five, Microsoft received four hundred and
Speaker 1: fifty four point seven million dollars as part of its
Speaker 1: revenue share agreement, implying open AI's revenues for that six
Speaker 1: month period or at least two point twenty seven three
Speaker 1: billion dollars or around two billion dollars less than the
Speaker 1: four point three billion dollars previously reported for that period.
Speaker 1: Through September, Microsoft's revenue share payments total eight hundred and
Speaker 1: sixty five point eight million dollars, implying open AI's revenues
Speaker 1: are at least four point three to two nine billion
Speaker 1: dollars through the end of Q three twenty twenty five.
Speaker 1: To be clear, and I'm going to say this, Microsoft
Speaker 1: also pays open Ai a cut of bing's revenues under
Speaker 1: certain circumstances I could not confirm, as well as a
Speaker 1: cut of about twenty percent of all open ai models
Speaker 1: sold through a zore. Just to be clear, Microsoft is
Speaker 1: the only party that can sell open AI's models other
Speaker 1: than open Ai. I don't have the details on those payments,
Speaker 1: like I said, but I am skeptical that they can
Speaker 1: account for the massive difference between those numbers that have
Speaker 1: been leaked and the ones in the documents in question.
Speaker 1: I do not know, nor will I speculate on why
Speaker 1: these differences are so distinct. What was important about today
Speaker 1: was getting you these numbers and shedding light on the
Speaker 1: differences I see between the story told about open ai
Speaker 1: and the reality of its spend and potential revenues. You've
Speaker 1: also I probably noticed that this podcast is a bit
Speaker 1: of a different tone to the usual no insults, no jokes,
Speaker 1: haven't called anyone clammy, haven't even said a swear word
Speaker 1: for the first time in maybe one hundred episodes. The
Speaker 1: reason simple. These numbers are serious and seriously different to
Speaker 1: those reported. Open AI's costs are dramatically higher than previously
Speaker 1: reported in thought, and based on the extrapolations from Microsoft's
Speaker 1: revenue share, its implied revenues are also seemingly dramatically lower
Speaker 1: than we knew. The ramifications of these numbers are severe.
Speaker 1: Open AI's influence costs are incredibly high, absorbing any and
Speaker 1: all revenues and seemingly scaling with every increase in chat
Speaker 1: GPT's user numbers. As revenue goes up, so does their
Speaker 1: inference costs. Conversely, if these implied revenues are indicative of
Speaker 1: the larger financial picture, open ai is not as successful
Speaker 1: as company as we previously believed. In any case, the
Speaker 1: reality of the AI bubble is becoming clearer. Inference, the
Speaker 1: process of creating outputs for a model appears to be
Speaker 1: an incredibly burdensome cost. And if these implied revenue is
Speaker 1: there any indicator the actual business of selling generative AI
Speaker 1: services and models doesn't really seem to be as good
Speaker 1: a business as we thought either. It's all looking a
Speaker 1: little bleak out there. I don't want to editorialize too
Speaker 1: much because I want this information to sit on its
Speaker 1: own own self. But it's it's strange being here. It's
Speaker 1: strange getting these numbers and seeing them myself, and I
Speaker 1: have to wonder how things work out from here. I
Speaker 1: truthfully have no idea, but I do know I'll be
Speaker 1: happy to do this every week, and I will tell
Speaker 1: you what happens now. These numbers allow us to kind
Speaker 1: of see the real picture of the AI bubble, and
Speaker 1: I have to wonder what other companies look like now
Speaker 1: that I've seen these numbers. Email me contact me Esitron
Speaker 1: dots seventy six on signal. If you ever want to
Speaker 1: tell me anything, do you ever want to show me anything.
Speaker 1: I'm always interested to hear, and I'm honored to do
Speaker 1: this