OpenAI resets spending expectations, from $1.4T to $600B
cnbc.com
cnbc.com
For context, that is more than the annual revenue of all but 3 tech companies in the world (Nvidia, Apple, Google), and about the same as Microsoft.
OpenAI meanwhile is projected to make $20 billion in 2026. So a casual 1300% revenue growth in under 4 years for a company that is already valued in the hundreds of billions.
Must be nice to pull numbers out of one's ass with zero consequence.
I'm three of them and I never spent a cent on any llms, I doubt I'm the only one
He is counting on hundreds of husbands: https://xkcd.com/605/
Garbage in, garbage out, same as before.
they'll probably fix it just like they did fix strawberry
their estimates will drop by ~20x which will be their max
as underdog in the race they'll grab fraction of even that
where are they planning to get that much money from? by showing adverts for 14h before you can prompt?
Such a weird sentence. The correct causality should be: It's valued in the hundreds of billions because the investors expect a 1300% revenue growth.
Another example is how Isaac Newton lost money on some other bubble as well: https://www.smithsonianmag.com/smart-news/market-crash-cost-... [ The market crash which cost newton fortune]
So even if NEWTON, the legendary ISAAC NEWTON could lose money in bubble and was left holding umbrellas when there was no rain.
From the book Intelligent investor, I want to get a quote so here it goes (opened the book from my shelf, the page number is 13)
The great physicist muttered that he "could calculate the motions of the heavenly bodies, but not hte madness of the people"
This quote seems soo applicable in today's world, I am gonna create a parent comment about it as well.
Also, For the rest of Newton's life, he forbade anyone to speak the words "South Sea" in his pressence.
Newton lost more than $3 Million in today's money because of the south sea company bubble.
Intelligent investor is a great book though.
[1] eg he wrote more than a million words on alchemy during his lifetime https://webapp1.dlib.indiana.edu/newton/project/about.do
That covers everyone. Especially and including the rationalists. Part of being highly intelligent is being a bit weird because the habits and beliefs of ordinary people are those you'd expect of people with ordinary intelligence.
Anyone involved in small-time investing should be considering that they aren't rational when setting their strategy. Larger investment houses do what they can but even then every so often will suffer from group-think episodes.
The norms of "rational" science hadn't really been established yet. There wasn't really a clear line drawn between alchemy and what we would consider chemistry today.
Newton was also definitely in favour of an empirical/axiomatic basis for science in general. If you read principia he proves almost everything[1] and of course he famously deformed his own eyeballs with wooden gadgets to do his experiments in optics.
[1] In fact pretty much the one thing he doesn't prove is the calculus, which Alex Kontorovich once said in a lecture on youtube that he has a pet theory that the reason that Newton never published the calculus was not the one everyone says about his rivalry with Hooke etc but that he wanted a rigorous proof first (which of course didn't come about until much later with Cauchy, Weierstrass, Dedekind etc for normal calculus and the 1960s for non-standard analysis to prove Newton's fluxions rigorously).
The moral of that story is that being a legend or smart doesn’t count for much in investing.
The marginal investor does.
That is a cost of capital estimate of 40%.
Which points to investors not believing the company will be that profitable.
I am not saying investors don't think they will be profitable just they certainly don't believe that profitable.
> Must be nice to pull numbers out of one's ass with zero consequence.
Seems accurate?
What they are saying is if Microsoft ends up buying the rest of their shares then i.e. Microsoft's total revenue by 2030 will be more than $280 billion.
The tools are good! The main bottleneck right now is better scaffolding so that they can be thoroughly adopted and so that the agents can QA their own work.
I see no particular reason not to think that software engineering as we know it will be massively disrupted in the next few years, and probably other industries close behind.
And even say the latter strategy works - ads are driven by consumption. If you believe 100% openAI's vision of these tools replacing huge swaths of the workforce reasonably quickly, who will be left to consume? It's all nonsense, and the numbers are nonsense if you spend any real time considering it. The fact SoftBank is a major investor should be a dead giveaway.
Evidence? I’m sure someone will argue, but I think it’s generally accepted that inference can be done profitably at this point. The cost for equivalent capability is also plummeting.
Here you go: https://www.wsj.com/livecoverage/stock-market-today-dow-sp-5...
There's no such thing as "profitable inference". A company is either profitable or it isn't.
Let's for a second assume all the labs somehow manage to form a secret OPEC-style cartel that agrees to slow training to a halt, and nobody notices or investigates. This is already hard to imagine with the amount of scrutiny they're under and given that China views this as a military priority. But let's pretend they manage it. These firms also have lots of other costs:
• Staffing and comp! That's huge!
• User subsidies to allow flat rate plans
• Support (including abuse control and handling the escalations from their support bots)
• Marketing
• Legal fees and data licensing
• Corporate/enterprise sales, which is expensive as hell even though it's often worth it
• Debt servicing (!!)
• Generating returns for investors
Inferencing margins have to cover all of those, even if progress stops tomorrow and the RoI to investors has to be likewise very large, so margins can't be trivial. Yet what these firms have said about their margins is very ambiguous. As they're arriving at this statement by excluding major cost components like training, it's not clear what they think the cost of inferencing actually is. Are they excluding other things too like hw depreciation and upgrades? Are they excluding the cost of the corporate sales/support infrastructure around the inferencing?
But also, "profitable inference" IS a thing! "Gross margin" is important and meaningful, even if a company has other obligations that mean it's overall not profitable.
You mention "debt servicing", but OpenAI has no debt. All the money they have raised is equity not debt.
Have any of you tried re-producing an identical output, given an identical set of inputs? It simply doesn't happen. Its like a lottery.
This lack of reproducibility is a huge problem and limits how far the thing can go.
However, we can start by claiming that non-determinism is not necessarily a bad thing - non-greedy token sampling helps prevent certain degenerate/repetitive states and tends to produce overall higher quality responses [0]. I would also observe that part of the yin-yang of working with the agents is letting go of the idea that one is working with a "compiler" and thinking of it more as a promising but fallible collaborator.
With that out of the way, what leads to non-determinism? The classic explanation is the sampling strategy used to select the next token from the LLM. As mentioned above, there are incentives to use a non-zero temperature for this, which means that most LLM APIs are intentionally non-deterministic by default. And, even at temperature zero LLMs are not 100% deterministic [1]. But it's usually pretty close; I am running a local LLM as we speak with greedy sampling and the result is predictably the same each time.
Proprietary reasoning models are another layer of abstraction that may not even offer temperature as knob anymore[2]. I think Claude still offers it, but it doesn't guarantee 100% determinism at temperature 0 either. [3]
Finally, an agentic tool loop may encounter different results from run to run via tool calls -- it's pretty hard to force a truly reproducible environment from run to run.
So, yeah, at best you could get something that is "mostly" deterministic if you coded up your own coding agent that focused on using models that support temperature and always forced it to zero, while carefully ensuring that your environment has not changed from run to run. And this would, unfortunately, probably produce worse output than a non-deterministic model.
[0] https://arxiv.org/abs/2007.14966 [1] https://thinkingmachines.ai/blog/defeating-nondeterminism-in... [2] https://learn.microsoft.com/en-us/azure/ai-foundry/openai/ho... [3] https://platform.claude.com/docs/en/about-claude/glossary
This world of extremes is annoying for people who have the ability to think more broadly and see a world where deterministic systems and non-deterministic systems can work together, where it makes sense.
If the S-curve levels off below that level OpenAI will be an unsuccessful company.
OpenAI and Anthropic aren't building companies that aim to be API endpoints or chatbots forever, their vision is clearly: you will do everything through them.
The gamble is that this change is going to reach deeper into every business it touches than Microsoft Office ever did, and that this will happen extremely quickly. The way things are headed I increasingly think that's not a terrible bet.
Even with the revised numbers, I cannot believe that they’ll have $280bn in revenue by 2030.
[0]: You can tell by the reason the sources are granted anonymity: because the information is private, not because they aren’t authorized to speak on the matter
> After previously boasting $1.4 trillion in infrastructure commitments, OpenAI is now telling investors that it plans to spend $600 billion by 2030.
does the word "commitment" have a different meaning in this context? How do you cut a commitment >50%? OpenAI's partners are making decisions based on the previous commitment because.. OpenAI committed to it. I must be completely wrong because how does this not set off a severe chain reaction?
edit: as others have pointed out, the article is misleading. $1.4T was over 8 years or by 2034. 2030 is halfway to 2034 and $600B is not too far from half of $1.4T.
Just like you and me, Sam Altman can say anything he likes to say. To pump the investors' confidence, to make the US administration believe he's serious about AGI, or just to make himself feel good. It's not legally binding in any way.
You should never read it as "OpenAI committed to..." but as "Altman said these words..." and words mean very little today.
A trillion here, a trillion there and all the AI companies are also telling us they're planning on wiping out 2/3 of jobs in the next 10 years? Nothing about the economics of the AI boom makes any sense.
I'm not saying it's not possible, but if we wipe out 2/3 of jobs with AI, who is going to be buying *all the stuff*?
Unemployed people aren't much of a demographic, and you can't just say UBI because that doesn't make sense either. You think the billionaires are going to allow themselves to be taxed heavily enough to support UBI just so that there's a market for people to buy stuff from them? That's nonsense.
Not trying to creep anybody out, but I just don't see a stable outcome for a society that doesn't need 2/3 of the population.
They will have no choice. Proletariat must not be hungry and agitated. Free legal MJ for everyone!
If you want some light reading: 1984, brave new world, and atlas shrugged will mostly get you caught up on current events.
Everyone else has been less explicit, likely because it's just not politically a good idea to keep pronouncing it.
It's part of Anthropics marketing though. Maybe to push the idea you can't beat us so join us?
what if… MBAs turned from economics to a religion and no one noticed?
Money is just a proxy for access to resources. If a machine that is capable of replacing almost all jobs is really created then money will matter much less than access to said machine. Taken to the extreme to make the point, if you had a genie that could grant your every wish, what would you need money for ?
The things that a magic AI Genie will never be able to give you no matter how far into the AGI/Singularity things get. Such as Land, Energy, Precious Metals, Political and Social Capital, etc.
Energy, Precious Metals etc are not obtained with Money. They are obtained with human work and effort, all of which we are now saying is doable by the machine.
It's a domestic robot that can do full maintenance on another domestic robot.
Self replicating machines are the genie that grants you more wishes. They are the genie that can turn that land, energy, and precious metals into copies of themselves.
And if they were, then the machine will just do all that for them. That's the point. The things you mentioned don't need intrinsically need money. The machine can fix or create whatever car, replace whatever roof, and build whatever house.
Well they should be, because actually putting 2/3rds of the workforce out of work in a short, sudden fashion is probably not going to end well for them.
> The things you mentioned don't need intrinsically need money. The machine can fix or create whatever car, replace whatever roof, and build whatever house.
What machine is this? It certainly doesn’t exist and won’t in the short timeframe these AI companies are predicting everyone is gonna be laid off. Maybe, maybe if the timeframe for “no one has a job anymore” happens over say, 100 years, things might go slowly. Over two or three years? Heads will roll.
Maybe. The ruling elite being a small fraction compared to the downtrodden masses is hardly a new manifestation. Regardless, money won't be the primary issue. Again it's just (intrinsically) worthless paper. All of its current value is a social construction and new ones could take its place if necessary.
Then when the labor market is nice and hollowed out, the tokens will go up in price several-fold.
I don’t imagine they’re pretty.
> "People enjoy products and services." ???
WTF does that even mean? Folks are so deluded with all of these "right around the corner" solves that AI has in store that they fail to realize how out of whack the numbers game has played out. In any other reality people would be scrutinizing Sam Altman at every angle. But because of some magical AI sauce the incomprehensible numbers now magically make sense.
But for a lot of us: it doesn't. If you're going to claim hundreds of billions in revenue, just a few short years from now, you better have a really fucking great product today. Not in 6 months, not in a year - but right now.
SaaS has not been displaced. Workers have not been displaced (other than shifting their salaries to AI spend which does not equate to worker replacement). Where does madness end? The only thing that makes sense is an implosion that will ripple all the way through many other markets which will now take years to fix.
(1) matan - mathematical analysis, as a reference to a widely known and hard to learn university course.
Easy - a greater portion of the world's resources can go toward the luxury market for the wealthy. This is already the trend.
It's dark but certainly not impossible to have a smaller and smaller group doing all the spending and keep spending the same, and to keep stability by force using technology.
I want no part of it.
Like rather than Dilbert writing code, he gets promoted to pointy haired boss and manages an AI which writes the code.
OpenAI...not so sure, they need an IPO soon while public still is high off the double bull run post 2020
I saw a report that previous capacity pricing was $28/MWh/day. Latest numbers have shot up to $300.
Thats a weekly metric on https://openrouter.ai/rankings flagship chatgpt 5.2 model is at #16
PMF is now evolving when competitor models are either smarter or cheaper.
Is this like Windows and MacOS not being in the top 10 of distrowatch.com?
And there's a reason that OpenRouter has an OpenAI compatible layer highlighted not deep in docs, but on their Quickstart page: https://openrouter.ai/docs/quickstart#using-the-openai-sdk
The number of projects accessing OpenAI directly, who might only reach for OpenRouter once an alternative is desired, is unknowable (since OpenAI doesn't share usage statistics), but likely meaningful.
There are so many plausible explanations for why a particular model is or is not ranked in the top 10 by this metric.
Maybe people using OpenAI models are so happy that they don't care about other models and have no need for OpenRouter. Maybe OpenAI models produce fewer tokens, or are more expensive per token.
Your conclusion might be correct, but citing the number of tokens seen by OpenRouter is not very strong evidence.
I use openrouter.ai as the benchmark because it's the foundational API layer for innovator apps that are always the quickest to adopt new tech.
But I don't think either are very meaningful when there are actual benchmarks to measure the quality of models on specific tasks.
If they didn't appropriately account for risk that the expectation would not pan out, well, that's on them.
Extraordinary claims and all.
If we see a continuation or even a slowdown of the current trend, the technology overhang, lagging productization, and catch up from the slow adoption of AI by businesses probably gets them part of the way there, but I don't know about 1000% growth at this point... Seems kinda like they're banking on another breakthrough no? And if they don't get the breakthrough, the downside risks such as a competitor of some sort destroying their margin can't exactly be ignored...
https://www.cnbc.com/quotes/ORCL
Remember this press conference?
This looks very much like a careful move to deflate the bubble without popping it, but we’ve likely passed that point.
90% chance in 6-12 months spending expectations drop to $0.
But this time draw it for spending expectations.
I'm not an AI booster, and I don't see "sustainable" in the current markets, but I'd take the other side of that bet!
The great physicist muttered that he "could calculate the motions of the heavenly bodies, but not the madness of the people"
There seems to be a lot of madness happening in the world again as well. A lot of OpenAI claims make no sense except if we consider the world to have gone mad.
The bubbly nature of openAI and just doing whatever they think like doing with 0 regards to anything or everything including financials is a form of madness.
I was reading another comment and actually opened up the Intelligent Investor book to read the quote from there. I highly recommend that book although truth be told that I haven't read more than the first 50-100 pages as I quickly felt like passive investment is a great vehicle personally.
I feel that Sam is saying what investors want to hear, but the coding work it is capable of and how it improved with using the terminal (TerminalBench) in such a short time is something that I'm sure can't be seen by short term revenue projections. I'm sure the other AI companies are having the same speedups, but it's real.
The usual limit is of course the slop output that is not well modularized that makes it hard to do bigger things, and codex is terrible at refactoring into the right direction (it has no taste).
3x YoY growth in revenue is just not hard to imagine with this kinds of models, I think they have to get out with more expensive parallel working agents and higher-than-pro subscriptions, but it is coming I'm sure.
Open source models catch up quickly and eventually even large models could be run locally.
Will it continue to transform the economy radically? Yes.
Will that translate to the model-makers somehow capturing the entire value of the transformed economy? No.
There were a few key moments that revealed this. When OpenAI initially declared "there is no moat," I wasn't sure whether to believe them. GPT 3.5 and 4 were so much better than the competition, it felt like them saying that they had no moat was some sort of attempt to avoid regulation or scrutiny. But then, lo and behold, Claude and Gemini caught up; there really was no moat.
But up until then, while it was clear that there was no moat around OpenAI, it was unclear if there was a moat around big tech. Mistral was meh. Even Meta's were meh. We also had no idea how much these models actually cost to run. It wasn't until the "DeepSeek moment," and especially once these open source models actually started being hosted on third party services, that it became clear that this was actually a competitive landscape.
And as has already been demonstrated, because the interface for all of these models is just plain language, the cost of switching models is basically non-existent.
AI made “basically zero” difference in U.S. economic growth last year. https://www.youtube.com/watch?v=zZHN0-ZNe_4&t=399s
Both numbers are fictional. No one really expects any of this to be true.
The people who claim to believe this are simply lying.
Seeing the same setup in 2008 and now. Enjoy your subsidized $200/month codex because its going to go up in the future.