OpenAI closes funding round at an $852B valuation
cnbc.com
cnbc.com
Anthropic had $19b by end of February 2026 and they added $6b in February alone.[1] This means if they added another $6b in March, they're higher than OpenAI already.
However, I heard that OpenAI and Anthropic report revenue in a different way. OpenAI takes 20% of revenue from Azure sales and reports revenue on that 20%. Anthropic reports all revenue, including AWS's share.[2]
[0]https://www.reuters.com/business/openai-cfo-says-annualized-...
[1]https://finance.yahoo.com/news/anthropic-arr-surges-19-billi...
E.g. what good is 20 billion per year when "OpenAI is targeting roughly $600 billion in total compute spending through 2030". That is $150 billion per year?
the expectation is that they'll eventually make money. they can't raise forever. only startups are not profitable for a few years. but most companies that have existed for a long while have been profitable
and since they're expected to make a LOT of money, everyone wants a piece of that future pie, pushing up the valuation and amount raised to admittedly somewhat delusional levels like here
profit isn't a function of having a killer product, it's a function of having no competition
Industries always consolidate and winners emerge. SOTA LLMs look like a natural monopoly or duopoly to me because the cost to train the next model keeps going up such that it won't make sense for 20 competitors to compete at the very high end.
TSMC is a perfect example of this. Fab costs double every 4 years (Rock’s Law). It's almost impossible to compete against TSMC because no one has the customer base to generate enough revenue to build the next generation of fabs - except those who are propped up by governments such as Intel and Rapidus. Samsung is basically the SK government.
I don’t see how companies can catch OpenAI or Anthropic without the strong revenue growth.
I’ll be polite and call this statement ‘a very debatable’ one.
no, most industries just sell boring generic products, a few industries favor monopolists. Semiconductors are one of them but LLMs are also as far removed from that business as is physically possible.
TSMC makes the most complicated machines humans have ever built, a LLM requires a few dozen nerds, a power plant, a few thousand lines of python and chips. That's why if you're Elon Musk you could buy all of the above and train yourself an LLM in a month.
LLMs are comically simple pieces of software, they're just big. But anyone with a billion dollars can have one, they're all going to be commoditized and free in due time, like search. Copying a lithography machine is difficult, copying software is easy. that's why Google burrowed itself into email, and browsers, and your phone's OS. Problem for openai is they don't have any of that, there's already half a dozen companies that, for 99% of people, do what they do.
Only one company on Earth can make the UV lithography machines TSMC buys for their highest end fabs, and they're not selling to anyone else.
The PRC tried to brute force this supply chain backed by the full might of the Party's blank check, all red tape cut, literally the best possible duplication scenario, and they failed.
It's believable that Meta, ByteDance, etc. can catch up too. It is not certain that scaling will meaningfully increase performance indefinitely, and if it stops soon, they surely will. Furthermore, other market conditions (US political instability) can enable even more labs, like Mistral, to serve as compelling alternatives.
Uber, TSMC, etc. have strong moats in the form of physical goods and factories. LLMs have nothing even remotely comparable. The main moat is in knowledge, which is easy to transfer between labs. Do you think all the money that goes into training a model goes into the actual final training run? No, it is mostly experiments and failed ideas, which do not have to be repeated by future labs and offshoots.
It's certain that it won't. We've already hit diminishing returns.
In this case because it's not clear that anybody has actually figured out how to sell inference for more than it costs
Whether GPT-5 was profitable to run depends on which profit margin you’re talking about. If we subtract the cost of compute from revenue to calculate the gross margin (on an accounting basis),2 it seems to be about 30% — lower than the norm for software companies (where 60-80% is typical) but still higher than many industries.
(They go on to point out that there are other costs that might mean they didn't break even on other costs - although I suspect these costs should be partially amortized over the whole GPT 5.x series, not just 5.0)
https://epochai.substack.com/p/can-ai-companies-become-profi...
https://martinalderson.com/posts/are-openai-and-anthropic-re... (with math working backwards from GPU capacity)
"Most of what we're building out at this point is the inference [...] We're profitable on inference. If we didn't pay for training, we'd be a very profitable company"
https://simonwillison.net/2025/Aug/17/sam-altman/
"There’s a bright spot, however. OpenAI has gotten more efficient at serving paying users: Its compute margin—the revenue left after subtracting the cost of running AI models for those customers—was roughly 70% in October, an increase from about 52% at the end of last year and roughly 35% in January 2024."
https://archive.is/OqIny#selection-1279.0-1279.305 (Note this is after having to pay higher spot rates for compute because of higher than expected demand)
That is not, in fact, "well known", but based entirely on the announcements of the inference providers themselves who also get very cagey when asked to show their work and at least look like they're soliciting a constant firehose of investment money simply to keep the lights on. In particular there's a troubling tendency to call revenue "recurring" before it actually, you know, recurs.
I mean sure, it's self reported.
But the inference prices somewhere like Fireworks or TogetherAI charges is comparable to what Google/AWS/Azure charge for the same model an we know they aren't losing money - they have public accounts that show it, eg:
https://au.finance.yahoo.com/news/wall-street-resets-amazon-...
Fireworks’ gross margin—gross profit as a percentage of revenue—is roughly 50%, according to the same person
https://archive.is/Y26lA#selection-1249.65-1249.173
> In particular there's a troubling tendency to call revenue "recurring" before it actually, you know, recurs.
If someone has a subscription then yes that is pretty normal.
Not if you've substantively changed rate limits 3 times in the last 5 months while still counting those forecast revenues. In most industries that's called rug-pulling.
Profit is money you couldn’t figure out how to spend. During growth, you want positive operating margins with nominal profits. When the company/market matures, you want pure profits because shareholders like money. If you can find a way to invest those profits in new areas of growth, that’s better.
Everyone wants to treat OpenAI like a car wash business where they need to make a profit almost immediately. I don’t know why people can’t understand that the industry is in a rapid growth stage and investing the money is more important than making a profit now. The profits will come later.
The nearly $1T hand wave. Forgive me if I ask how. Might give it some credence if Anthropic and Google weren't pulling even with or surpassing them in various way or markets.
Whats worse is they mostly seem to have retail market name recognition which is arguably the hardest, or maybe the impossible market to make money from.
Whats worse is they mostly seem to have retail market name recognition which is arguably the hardest, or maybe the impossible market to make money from.
Apple is another one that focuses almost exclusively on retail and is also one of the most profitable in history.
Holy crap, is it the year 2000 again?
Profit is the money showing your business is sustainable. Ever since the ZIRP era US companies keep haemorrhaging money at a rate that is physically impossible to recoup.
If OpenAI plans to lose 100+ billion dollars per year for half a decade, what profits are you talking about to offset the losses?
> When the company/market matures, you want pure profits because shareholders like money.
Ah yes. Shareholders like money. And not, you know, basic accounting like "we need money to actually pay salaries, pay for equipment and offices etc. without perpetually relying on seeming endless investor money".
You don’t need profit to offset the losses.
You can simply reduce spending / expenses.
One does not “simply” reduce spending.
Why does stock price go up after mass layoffs?
Company would no longer function of course but why it would matters if the stock price is through the Moon?
Notice I said you should have nominal profits.
> Ah yes. Shareholders like money. And not, you know, basic accounting like "we need money to actually pay salaries, pay for equipment and offices etc. without perpetually relying on seeming endless investor money".
All of these are costs that reduce your profits.
A maximally profitable business fires all employees except shareholders, closes every office, stops all RnD, and leases IP or real estate to others on long-term deals that never need to be renegotiated.
Since everyone is trying to get compute from anywhere they can, including OpenAI going to Google, it's hard to tell what is used internally vs externally.
For example, it's entirely possible that Google's internal roadmap for Gemini sees it using $600b of compute through 2030 as well. In that case, OpenAI needs to match since compute is revenue.
So the same money spent by OpenAI and Google doesn't carry nearly the same amount of risk?
OpenAI doesn't?
I'll also add that Google is already a player in that space so more likely to easily sell it off.
Why are we saying that OpenAI and Anthropic can't do the same?
Openai can't claim either.
Uber was only on a path to monopoly in the US, not world wide. It’s lost to local competitors in most countries. And it can get disrupted by self driving cars soon.
OpenAI’s SOTA LLM training smells like a natural monopoly or duopoly to me. The cost to train the smartest models keep increasing. Most competitors will bow out as they do not have the revenue to keep competing. You can already see this with a few labs looking for a niche instead of competing head on with Anthropic and OpenAI.
Distilling might only be effective in the chat bot dominant era. We are about to move to an agents era.
Furthermore, I’m guessing distilling will get harder and harder. Claude Code leak shows some primitive anti distilling methods already. There’s research showing that models know when it’s being benchmarked. Who’s to say Anthropic and OpenAI aren’t able to detect when their models are being distilled?
Absolutely they will. And this is a huge problem for OAI - given Google is targeting vertical integration, they will acquire a cost-advantage. As long as the model performance is good enough, they will kick OAI and Anthropic out in the long-run.
The valuations of OAI and Anthropic are nonsense. A true valuation would incorporate failure risk, which is natural for startups/fast growing and money losing firms. Anyone who takes them serious is incredibly delusional.
It took them ~14 years to lose that $34 billion. Some projections suggest that OpenAI has lost a third of that in a single quarter. Even the most optimistic projections indicate that they're losing that much every 2-3 years. There's talk that they might lose ~$150B before profitability.
These are just numbers on a page to regular people, but $34 billion and $150 billion are very different numbers.
The problem for OpenAI is that the cost of getting them where they are now has been to high and competitors can now establish themselves for much less money.
The dame Uber that lost close to 30 billion dollars over 10 years to subsidize its price dumping?
No, no we are not treating OpenAI differently than Uber
I remain skeptical of Uber.
Sure, maybe OpenAI and Anthropic will make it work. It's not impossible. But it's far from guaranteed.
Uber generates about $1b in profit yearly now.
Maybe, if you take their word for it, and treat the models as capital assets rather than part of the COGS for the inference product. That's pretty far off from where Amazon was at.
Yes
>before making a profit.
No
Assets are harder to measure. Facebook used to say something silly like every user was worth $100. That sounded ridiculous for a completely free app but over a decade later, the company is worth more than that. Revenue is an easier way of measuring assets than profit.
Profit doesn't really matter. It gets taxed. But it's not about dodging taxes; it's because sitting on a pile of money is inefficient. They can hire people. They can buy hardware. They can give discounts to users with high CLTV. They can acquire instead of building. It's healthy to have profit close to $0, if not slightly negative. If revenues fall or costs increase, they can make up for the difference by just firing people or cutting unprofitable projects.
Also when they're raising money, it makes absolutely no sense to be profitable. If they were profitable, why would they raise money? Just use the profits.
Profit is money you can't find a use for to grow your business, so you give some of it to the government in the form of tax.
Also there is a big difference between operational expenses and capital expenses like building data centers.
I think OpenAI is being very aggressive on the growth vs conservative financial management spectrum but just saying "only profit should matter" is just wrong.
It's what attracts capital investment, which businesses need
As did Amazon, Google, Meta etc etc.
Could be wrong though.
Even a simple shop isn't profitable for months if it needs to buy stock up front, and run some ads to let people know about it. The money for that comes from the shop owners as an investment.
This is the same thing but on a slightly bigger scale, over a longer time frame.
US tech companies just continue operating because "revenue and growth".
US tech companies are some of the most profitable business in history.
Google made over $130B profit last year, Meta 60B.
I'm old enough to have had exactly the same arguments (on Slashdot for Google, here for FB) for both before their IPOs.
It's a uninformed argument and people should know better.
The numbers OpenAI gave in the post would mean a 30x multiple pre-money. And the $20B -> $24B run-rate growth since the start of the year could plausibly mean anything from 110% to 200% annualized growth rate, depending on whether that happened over two or three months. The $24B is a lower bound as well, since they only gave use one significant digit for the monthly revenue.
I think ads is going to massively change this number.
Both will do public reporting only when they IPO[4] and have regulatory requirement to do so every quarter. For private companies[1] reporting to investors there are no fixed rules really[3]
Even for public companies, there is fair amount of leeway on how GAAP[2]expects recognize revenue. The two ways you highlight is how you account for GMV- Gross Merchandise Value.
The operating margin becomes very less so multiples on absolute revenue gets impacted when you consider GMV as revenue.
For example if you consider GMV in revenue then AMZN only trades at ~3x ($2.25T/$~800B )to say MSFT($2.75T/$300B) and GOOG ($3.4T/$400B) who both trade at 9x their revenue.
While roughly similar in maturity, size, growth potential and even large overlap of directly competing businesses, there is huge (3x / 9x) difference because AMZN's number includes with GMV in retail that GOOG and MSFT do not have in same size in theirs.
---
[1] There are still a lot of rules reporting to IRS and other government entities, but that information we (and news media) get is from investors not leaks from government reporting - which would be typically be private and illegal to disclose to public.
[2] And the Big 4 who sign off on the audit for companies prefer to account for it.
[3] As long as it is not explicit fraud or cooking the books, i.e. they are transparent about their methods.
[4] Strictly this would be covered in the prospectus(S-1) few weeks before going public and that is first real look we get into the details.
They aren't reporting anything yet. What we hearing is just from news media who get their leaks/info from investors who get some form of IR reports/ presentation.
The $19b ARR and $6b added in Feb came directly from Anthropic CEO recently.
When we say reporting it means there are statutory submissions with an auditor signing off, with legal liability. As the other reply referenced consequences for doing this incorrectly can be severe - Arthur Anderson is no more after all because of Enron.
A Press Release (of a private entity) does not have to satisfy this high bar.
Press release does mean no constraints, for public companies, disclosure of important information by officers and other insiders have strong controls. Even if its the just a rocket/poop emoji on a casual social media platform. Lawyers have to refile with the SEC in the expected format. Even private companies have restrictions on not claiming things fraudulently to investors, but these are accredited investors with lesser controls than retail.
What we hearing is just from news media who get their leaks/info from investors who get some form of IR reports/ presentation.And? That's not a legislated report; they can use whatever mechanism they want to, without disclosure, to produce numbers.
Lets wait until they are regulated as a public company, then their mechanism has to be both aligned with what legislation requires as well as clearly documented in their report.
That would be fraud against whoever participated in this round, so no. Just because they aren't regulated doesn't mean they are literally free to do whatever they want to close the round.
What makes you think their public announcements are aligned with what they give prospective investors?
All public announcements go through the legal team, regardless of whether it's related to the round or not.
https://www.benzinga.com/markets/tech/26/03/51248353/michael...
More likely than not, most of us are already holding stock in these companies one way or another. All the Mag 7 hold a major chunk of OAI and Anthropic stock anyway, slower entry does not make it less risky for us.
Even if the big tech companies did not hold any stock, they are still the biggest vendors and their own order books is hugely impacted by the AI demand from these two ( and others in this space), either way we are all in this together.
Passive investments are good, but if taken too far as they clearly have been in the last decade they become a scam. Everyone is SIPing into it, and there is infinite liquidity. Until one big whale finally decides they are booking it, then all hell will break loose on the same damn day.
Doubt it.
The world does not allow perfect competition.
What does this have to do with anything?
Plenty of asset managers construct indices to save fees.
However in the long term, economics usually finds the most efficient way.
Maintaining inefficient structures like tariffs or monopolies becomes more and more expensive and eventually untenable and disruptions will occur.
Really feels like 1928
You can just choose not to play the accounting game, and only choose the ones that actually gaap viable as investment opportunities. For example mag7 - tesla are all relatively cheap when they dip.
Some times the best play is just not to play. If you think they are too risky, walk away. There are enough good oppotunities
> mag7 (minus) tesla are all relatively cheap when they dip
Company Ticker P/E Ratio
Apple Inc. AAPL ~33
Microsoft Corporation MSFT ~25
Alphabet Inc. GOOGL ~29
Amazon.com Inc. AMZN ~30
NVIDIA Corporation NVDA ~38
Meta Platforms Inc. META ~28
Tesla Inc. TSLA ~378
How much do these names need to "dip" for you to consider them cheap?
- Growth rate: you can't compare them to the average single digit growth companies or dividend focused companies. Most of these tech companies revenue are still growing at double digit with good moat. Pe is a good measure but it's not absolute. If you believe they sustain their growth then it's a good bet. And you can choose not to buy in their growth stories too. At the end of the day investment is about judgement call
- History benchmark: some of their pe is at historical low. So they are actually cheaper than before.
- Pe ttm and forward pe: how much pe ttm are they at? how much forward pe are they projecting? If forward pe is significantly lower, that means the current analysts consensus is that they will grow in future
- Pe is the a number but it's not everything. You need to consider multiple things to decide if that's undervalued for you. It's highly subjective as different interpretations are common.
- This post is about if you want to play the gaap game with private tech companies. My point is that there are still many public companies that are cheap at certain point. You just need to be patient and be willing to research and wait. For example, meta at around 500 was a buy for me, but since then it has rebounded it's still good but not as undervalued as a few days ago
Real question: What is the real impact of this rule change? To me, it seems so minor. Three months is just a blip in time for any long term investor.
> which corruptly will force us all to buy into these companies
Also, if you don't like the NASDAQ 100 rules, then you don't have to invest in securities that track it. You can trade the basket yourself minus the names that you don't like.
Finally, I would say that S&P 500 index is far more important than NASDAQ 100. To join the S&P 500 index, the name must be profitable for the most recent year. (four quarters). Recall that Uber IPO'd in 2019, but was not profitable until 2023. OpenAI probably will not be profitable when it goes public; thus, it will not join the S&P 500 immediately.
I think the bigger story is SpaceX. It will likely IPO very close to a 1T USD market cap (with a small float: ~10%). And, thanks to StarLink, I assume that SpaceX is now wildly profitable.
Isn't the idea with the indexes that they allow you to intentionally not take an activist position in the market? The exposure is not tied to any underlying market hypothesis. In other words, if we make people form a market hypothesis in order to decide whether or not to hold this index, it has failed in its purpose.
Saying "you can trade the basket yourself minus the names you don't like" is not a real counterargument. Most of us are not going to do that, I'm not going to do that and I'm writing this post right now. John Doe is certainly not doing that.
”Most people” is doing a lot of heavy lifting there; 52% in the US and just 25-30% globally invest their money
That makes a little more sense, because the number of subscribers are so low that tripling won't really make much difference in terms of turning a profit.
Altman and co. get down on their knees and pray that proposition is only transitory in the short run.
LLMs wont disappear, but they wont be large profit generators either. Especially not so whilst there is fierce competition and every dollar of profit is re-invested. The value of an asset is derived upon its potential cash return, net of reinvestment, taxes et al.
Altman is hoping to survive long enough to finance R&D to figure out how to encode the entirety of what humans do, to be able to come good on the asinine aspirations he has put forth that justify its valuation. But it will end in disaster.
Instead of ten, you just need two or three
This is so surface level and boring.
Most of you aren't really clued up on subject areas like Finance to talk about this stuff frankly. As long as a firm is beating its cost of capital, it will reinvest money to generate more growth. What does that mean? Oh. Hiring more people.
I think it's a very, very bad assumption. After trying GLM-5 and Qwen3 on Ollama Cloud, not only were they faster than OpenAI's offerings (by a huge amount) it was just as good if not better at doing what I asked of it.
Claude Code is still superior to anything else but GLM-5 and Qwen3 are easily just as good as GPT-5.X (for coding).
let's not forget that these major LLMs are all the children of corporate hyper-piracy en masse, none of them are ethical even in origin unless you're talking about the pre-product company charter kind of ethics, like google .
You use the term piracy, which potentially hints at ur biases.
American IP laws aren’t universal, and last I checked neither is it popular in Silicon Valley.
Institutions surrounding dealing with IP Piracy is an American strong arm attempt to own the unownable and to use Russel conjugates to make the flagrant attempt seem just.
I do see less quality from reasoning at chatgpt compared to Gemini but otherwise i'm not seeing a year or years gap.
I suspect they have better RL setup for coding that makes their models better at coding than GPT/Gemini in practice.
Also, those $122b raised are not cash-in-hand.
For example, NVIDIA commits to $30b, but OpenAI must build 5gw inference+training capacity using NVIDIA's Ruby Vera systems. NVIDIA's Huang has said[1] that in 1gw of compute, around $35b are NVIDIA hardware. So that $30b investment from NVIDIA goes back to NVIDIA as $175b in revenue. (Besides, NVIDIA gets non-voting shares in OpenAI.)
Deals like these are one of the few ways OpenAI can sustain growing in capacity, but it comes at a huge premium. That's one of the reasons they need the IPO, to get access to cheaper money.
[0]https://finance.yahoo.com/news/openai-is-the-2025-yahoo-fina...
[1]https://www.cnbc.com/2025/09/22/nvidia-openai-data-center.ht...
"Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return."
- Not advancing digital intelligence
- While locking people into a superapp
- Because they are further constrained to generating financial returnsA couple things that stand out to me about this is the use of the phrase "committed capital", which only sounds like a promise that could break from various circumstances, and the valuation of their funding keeps changing so it sounds like a max rather than the valuation every investor invested at.
You're Amazon. You give OpenAI $50B cash investment, they then hand you back the $50B over time because they buy $50B worth of Amazon AWS services (they would use AWS or other equivalent compute anyway). OpenAI pays an additional $1-5B in sales taxes on top of their $50B compute purchase. Now let's say you have $25B opex for said compute. You then have $25B profits, you pay 21% corporate taxes on the profits, so you too owe the government about $5B. Government collects around $6-10B on this whole transaction.
Situation B:
You're Amazon. You let OpenAI use your services by handing them API credentials that unlock what would normally cost $50B worth of services, but no money changes hands. You have zero revenue from the transaction, write off the $25B opex as a tax loss on your other profits elsewhere in the company. You thus pay ~$5B less tax on your other income as a company, and OpenAI also doesn't have to pay sales tax because they didn't actually purchase anything.
It depends how you defined “consumers”. If you mean “those who consume the good subject to the tax, rather than people who resell the good”, yes, ideally.
If you mean “not businesses” or “individuals but not corporations”, then, no.
> Ie companies reverse charge sales tax or omit it entirely.
Generally, the theory of sales taxes is that people (including corporations) pay sales tax on things they consume as a final good rather than use as an intermediate good in production or simply resell. The exact way in which that is determined varies somewhat between jurisdictions with sales taxes, but generally (assuming paper is subject to sales tax in a jurisdiction), if you are buying paper to print books that you sell, you don't pay sales tax, if you are buying paper to print internal documents that you use in running the business, you do pay sales tax.
This is done even in smaller startup funding rounds some times.
"The round totaled $122 billion of committed capital, up from the $110 billion figure that the company announced in February. SoftBank co-led the round alongside other investors, including Andreessen Horowitz and D. E. Shaw Ventures, OpenAI said."
This IPO, if anyone underwrites it, is going to fleece retail so hard. Better make it a SPAC with the help of Chamath and Cantor & Fitzgerald.
They mention this line in different forms a couple of times in the article. It’s clear they’re pretty rattled about Anthropic’s momentum in enterprise, I wonder how confident they really are in this rationale.
ChatGPT uninstalls rose by 295%, downloads fell 13% on day one and a further 5% the next day [2].
One-star reviews spiked 775% overnight, then doubled again the following day [2].
1.5 million users joined the QuitGPT boycott within days [1].
Claude rose to #1 most downloaded app in the App Store and US usage rose by 51% [2].
New customers are now choosing Claude over OpenAI 70% of the time [1].
And much more. I think it was just your bubble that didn’t cancel it.
[1] https://letsdatascience.com/blog/altman-called-the-pentagon-...
[2] https://www.ibtimes.co.uk/openai-backlash-pentagon-partnersh...
Uninstalls up 300%! What's the baseline?
> downloads fell 13% on day one and a further 5% the next day
Dramatic falloff of new downloads after one day (still plenty of new downloads). Day 3 was likely negligible and, I bet, it was back to normal less than a week after when the story left the news cycle.
> 1.5 million users joined the QuitGPT boycott within days
That's both very few people and a completely meaningless number since all it requires is checking a box. Did anyone verify they were actually human?
> Claude rose to #1 most downloaded app in the App Store and US usage rose by 51% [2].
> New customers are now choosing Claude over OpenAI 70% of the time [1].
Which has nothing to do with cancellations.
> And much more. I think it was just your bubble that didn’t cancel it.
Most people in my bubble have no idea any of this happened and are just using free chatgpt tier if they use it at all. That seems much more representative given your provided statistics of the 1.5m person boycott.
The strongest part of my argument goes with your cited 1.5m number. That's not a lot of people, especially when you consider the signing of a petition requires no other action than signing and has no way to verify the signing.
I'm just not seeing how any of this harmed OpenAI more than a government contract helps.
What is going to happen is that the emplyee who tries to sneak OpenAI into our org is going to have two meetings set up by the end of the day, one with IT to ensure the whatever tool they installed is burned out with fire and one with HR to ensure they know the company policy and acknowledge that another fuck-up like this is a firing offense.
iykyk
A linguistic presentation commonly referred to as constrastive negation.
Also AI-Linkedin-Bullshit likes to use "just" additionally and it's mostly along the lines of Y being something much more impactful then X.
Oh, man... I can't wait to see where this is going. Might not be pretty after all.
The milestones aren’t a hard-stop that forbids the previous funding round participants from providing the money if they still choose. It’s just an out.
You're also ignoring that the market changes frequently. If you only raised as much money as you needed for the next 4-6 months with plans to re-raise all the time, you'd have to constantly be sizing your growth plans up or down based on how the market felt about startup investing that month.
Imagine the company having to either do speed hiring or large layoffs every few months to adjust to the size of the fundraising round they were able to get this time around.
Nothing about what you're suggesting would be easier, or easy at all
Funding Round A: VC “A” invests 200M (100M immediately and another 100M if sales grow 10% or whatever)
At 6 months the company will either get the other 100M automatically (meaning they grew sales 10%) or they don’t (meaning they grew less than 10%).
Assuming it’s the later they can then do another round during which they try to get the other 100M. In all likelihood VC “A” won’t be interested (or interested at a lesser amount). They could go ask VC “B” for an investment but it will likely be less than 100M as well because they didn’t grow as much as “the market” anticipated.
Nothing complicated at all.
I’ll give you $1 dollar for your banana today and another dollar in a week when it has ripened. If it’s rotten when I come to get my banana I won’t give you the other dollar. You have your original $1 and you can still try to sell your rotten banana to another HN reader but you probably won’t get another dollar this time.If instead you have a ripe banana I’m sure you could easily find a buyer.
Such a funding structure here isn't all that different: the funding agreement gives OpenAI the right to call on their backers to make certain cash deposits, contingent upon milestones being met. Deep down inside, "money in the bank" doesn't actually exist, it's just mutual agreements backed by force of law.
The first rule of tautology club is...
This is a common structure for large investments. It would be really inefficient for all of these investors and companies to have to have the money sitting in cash to do a deal and then transfer it into the company's bank where it sits and earns interest for years until they can deploy it.
Even VC firms who raise funds work this way. The capital is "committed" but investors don't wire all of the money over right away so it can sit in the VC firm's bank accounts, waiting. The VCs do what's called a "capital call" through which they're legally bound to provide the money they committed when requested, under the terms of the deal.
Also a lot of this "money" is in cloud compute and credits not cash so...
Tell that to Trump and his glorious way of bombing Iran. Nothing against the idea itself, the Mullahs all but asked for it to happen.
But the execution? That was a level of dogshit I haven't seen in the time I was alive lol. Even Russia was better prepared with their invasion of Ukraine.
Both Trump and Netanyahu had a somewhat solid perspective on not getting utterly wasted in the next elections. Instead they go on one of the most ill-prepared wars in modern history, with results that may seriously upend the global economy if not lead us to WW3 outright.
https://techcrunch.com/2026/03/27/why-softbanks-new-40b-loan...
January 26, 2024 - "Japanese investment holding firm SoftBank Group Corp has largely cleared its ownership in e-commerce giant Alibaba Group Holding, concluding one of the most successful deals in China's internet industry and a holding that spanned about 23 years."
"SoftBank, which invested US$20 million into Alibaba when it was still a start-up in 2000, said in a corporate filing on Thursday that it was set to book a gain of 1.26 trillion yen (US$8.5 billion) - about 425 times the value of its initial outlay - for the Tokyo-based firm's 2024 financial year after divesting its [remaining] shares via subsidiary Skybridge."
https://finance.yahoo.com/news/japans-softbank-concludes-run...
I get that people are scared of investing in China. But if I still made single stock investments, I would seriously consider BABA, it seems well positioned.
It makes it hard to say what the valuation of a company is. If the milestones are unlikely to be hit, then it's anyone's guess.
Even VCs don't get all of their fund money delivered into their bank account when they raise a funding round. It's inefficient and undesirable for everyone involved to have to move all of the money up-front, at once.
If you talk to anyone in startup funding or finance they'll be familiar with the term "capital call" which describes how committed capital obligations are delivered at a later date than the initial deal: https://en.wikipedia.org/wiki/Capital_call
This is perhaps because the most common round to raise is a small/early one, and these tend not to have hurdles. Founders that only ever raised these rounds wouldn't necessarily know what happens in later/bigger rounds.
Also, I wonder if capital calls come with hurdles as well? That is, can an LP refuse to put in more money if the VC's recent investments have not done well? I would think not, since it typically takes many years to determine whether investments were good or not.
The whole concept of talking about "runway" is basically calculating how much cash in the bank, that is actually in your bank account, will last. And this arrangement is different, as there are contingencies. In the past, VCs would just give you money in a particular series, and then if your business did well, they'd eventually give you more money in a later series. But it wasn't like they announced it all up front in, say, a Series A, but a big chunk of the money would only be delivered if you met milestones.
Funding doesn't work like that. Investors are giving you money as part of a longer-term deal where they stick around.
Obviously this is 1000x as large so I make no claims to knowing that sum. But it’s routine for startup funding to arrive in bank account.
> Nvidia invested $30 billion
> Microsoft, one of OpenAI’s longtime partners, also participated
There is a lot of non-cash, never-will-be cash, investment here. Credits for compute.
1) For a $100bn round, you won't get a single transfer of $100bn into your checking account, this is normal
2) Sam Altman is a liar and people (correctly) don't really believe him when he starts throwing numbers around
Maybe it makes sustainable sense but in the world of venture capital it seems the most profitable thing to do is lie through a Cheshire grin, every day.
> YC invests $500,000 in every company on standard terms. Our $500K investment is made on 2 separate safes:
> We invest $125,000 on a post-money safe in return for 7% of your company (the "$125k safe")
> We invest $375,000 on an uncapped safe with a Most Favored Nation ("MFN") provision (the "MFN safe")
Michael Burry called out this structural manipulation play recently:
https://www.benzinga.com/markets/tech/26/03/51248353/michael...
... probably will though
What is this about? The title says "OpenAI closes funding round at an $852B valuation". It does not mention $122B.
Edit: the linked page's title is different and indeed states $122B.
Edit: Why did this go from their press release to a news story?
It's now the year 2026. That dead horse has already been beaten.
The valuation seems odd though, you'd expect $840B post-money from that earlier round?
At least they're throwing consumers a bone via the ARK deal. It's crazy how little AI exposure is available to anyone who isn't already wealthy and/or connected.
This is the main reason we see this insane investment into AI imo. If you imagine having lots of money, where should you invest that currently?
Housing market: Seems very overvalued (at least in germany). Also with the current uncertainty and inflation its hard to make an investment that pays back over 20-30 years. So building is also difficult.
Stocks are very volatile currently. Not only since Iran. To me it seems since the financial crisis 2008 investors don't enjoy stocks as before.
Gold: Only if you are paranoid about collapse of society. It doesn't make sense to invest into s.th. without interest rates.
Crypto: Same as gold, but better if you like gamling. I would assume most people who are very rich don't gamble with most of their fortune.
Chip production, too, of course, but it's overflowing with money already, apparently. It's growing though, because there are real actual shortages of stuff like RAM and SSDs, there's money to be made immediately if you can. Chinese RAM manufacturers are building out like crazy.
[1]: https://www.ultimamarkets.com/academy/anduril-stock-price-ho...
[2]: https://www.marketscreener.com/quote/stock/RHEINMETALL-AG-43...
Only viable if you’re okay with the ethical implications of funding war.
This is, sadly, not theoretical, and I'm afraid we'll soon see more of such choices, not fewer.
Anduril is the only company in this sector in the US that has any promise and they aren't even public. Most of us are not going to get our hands on this.
Traditional defense sector looks more like Jeep, or Kodak...
These returns do not qualify as “enjoying stocks”?
https://investor.vanguard.com/investment-products/etfs/profi...
The returns are higher than before 2008, the previous 15 years are unprecedented.
https://www.macrotrends.net/2526/sp-500-historical-annual-re...
Maybe in Europe. The US stock market has nearly tripled since then. Literally the best period of stock growth in history.
https://www.federalreservehistory.org/essays/stock-market-cr...
The good news is that its almost all rich folks money on the line here and a small amount of dumb money. That's very different than, 2008 where it was mostly the indexes that got hit and that's more middle class/upper middle class concentrated.
The only thing I meant to point out was that a very high stock price by itself is no guarantee that there isn't a crisis around the corner. We plugged a lot of holes after 2008 and then reversed a lot of those fixes, I hear retail investors talking about their stocks at birthday parties again. Deja vu... of course this time it will be different. Or not. Let's just say that with the proverbial bull in the earthenware goods store on the loose if we only end up with another financial crisis that might actually not be so bad.
In the roaring twenties stockbrokers allowed clients 10:1 margin. Investors were not as well-informed as they are today. There was no deposit insurance.
The SEC wasn't nearly as powerful as it was in 2024 and there was way more shady shit going on. In that respect, and the repeal of Glass-Steagall we're reverting to the pre-depression era.
It has to be brutal out there for everybody else, if all the money is going to AI.
> At least they're throwing consumers a bone via the ARK deal.
https://www.ark-funds.com/funds/arkvx
The fund is invested in most of the hot tech companies.
If anything being associated with ARK in any form is a big negative signal.
It is deliberate. Period.
It's always been known that you make money in the private markets and pre-IPO companies and retail is the final exit for insiders and early investors.
Retail is not allowed to be early into these companies (Because that would ruin the point of being an insider) and this "exposure" has to be at the near top.
Also, aren't AI businesses losing a lot of money each year? Pretty sure there is some risk involved that is not good for retail.
the whole thing did not yet crash because it seems they can still promise even more without actually delivering definite results
I am from a generation that still sits behind a desktop computer when making "big purchases." I can't even buy a flight on my phone. I am so much less likely to want to have an AI agent do that for me.
Then the idea that daily consumption of these products will drive people to use them more at work... I have a very different life outside of work. My use of AI outside of work is exceedingly different to what I use it for at work.
I sometimes feel wildly out of touch. But sometimes I view this as the VR moment. To me there are some things that I think may always be preferable to do outside of that ecosystem. And for me, a lot of tasks that 'agents' enable are small enough or important enough that I want to do them myself.
I don't think I'll ever be comfortable allowing an agent to call me a taxi, or order food on my behalf. Because the convenience of asking for food isn't worth the chance it'll mess up, and opening an app and looking at a menu is simpler.
I also think we're coming to a moment where we can start identifying the markers of AI generated content on sight. And I think there's a growing animosity to it. I might be comfortable asking AI something, but when I am looking for or searching for other content, seeing AI content markers make me angry at this point.
To finish, I do just sort of straight up hate the idea that we're comparing this moment to the invention of electricity. It's on the face of it absurd.
Do you feel that any technology is comparable in it’s impact?
AI isn’t there yet. You could turn off AI tomorrow and there’d be a shock but people would quickly switch back. You could not do the same for electricity, medicine, combustion engines (or steam engines/turbines), computers, the internet, modern building materials, etc. You try to swap back off any of those and the modern world (literally and figuratively) collapses. Turn off AI, and there’d be a financial collapse but afterwards everything would return relatively easily to an earlier way of doing things (ye know, the way from just 4 years ago, and which is still 99% of how people do things :) )
There are loads of technologies that, despite being decades old, do not qualify. So, no, it’s not “primarily a function of time”. It absolutely is about the utility. We can only be in a position to judge utility when sufficient time has passed, and AI ain’t had enough time yet to prove its utility. Given enough time, it might prove as useful as electricity, or it might just sit alongside computer operating systems - never quite making it onto anyone’s “this changed the world” list, even if it has as much utility as an OS.
It doesn't have to be AI all the way - no one's asking AI to book things on its own and make the payments on their own. What does work is, make AI do the research and you verify and you do the payment. Human in the loop.
To me this is clearly the future - AI has access to all the data sources and can translate your intent by accessing these tools in a loop and use intelligence to automate things.
I see a flight that isn't in my time frame, but is actually like 400 euros cheaper. And I decide in that moment that waking up at 5am is worth the savings.
I'd have not typed that into a prompt. I made that decision at the moment I saw the possibility. I didn't even know that it was an option prior to that moment.
Then I go look at hotels. I have a list of requirements, but I see that one of the hotels that I just glanced at has a really nice long pool, and the amenities look nicer from the images. I change my mind at that exact moment, I can walk 15 minutes more to the beach.
Now it should be even clearer why this is important for food.
In 20 years, we may not be writing UIs for apps anymore. We may just be writing tools for AI agents to consume.
Admittedly openAI is in a better position to do it, but not by much.
Everyone wants to be WeChat in china. No user wants that from them.
Alternatively, you could say browsers are the original super app.
I think the core issue isn’t what underlying technology is used, but rather the service providers. They package their services into mobile apps or WeChat mini programs, and restrict functionality on browsers. For many ordinary people, this provides convenience, but for those who care more about privacy, it’s quite problematic.
WeChat in China covers almost every aspect of life. Even someone like me, who doesn’t want to use it often, can’t avoid it. Some restaurants’ online ordering systems only support scanning via WeChat—that is, WeChat mini programs. People can pay utility bills, call taxis, shop, and make financial investments all within WeChat. Alipay offers similar functions as well.
WeChat is also one of the largest content platforms in China, similar to Medium. Countless creators set up subscription accounts on WeChat and gain more users through readers’ sharing and reposting.At the same time, government information is often released through the WeChat platform.
WeChat is a browser for mobile web applications, a small slice of the web universe gatekept by Tencent. WeChat was modelled after Gmail. So, it is very much like Chrome - you have your communications inbox, and your web apps, in the same app.
I don't let another human do that! When we as a group order lunch, I always want to input mine directly or at least double check the order.
> The OpenAI flywheel is simple. More compute drives more intelligent models. More intelligent models drive better products. Better products drive faster adoption, more revenue and more cashflow.
FTX had a "flywheel". It fell off. Being saddled with hundreds of billions of debt makes this situation ten times worse.
Alphabet’s market cap is $3.5 trillion, compared to OpenAI’s $850 billion reported here.
The only one that is really investing is SoftBank who is pushing for a faster IPO so they hope to make a profit on that and again Google does not offer that opportunity
But I suspect that’ll u-turn hard when the economy implodes
OpenAI charges about 20$/month to tens of millions of users right now. 240/year. About 12 billion per year. That's a market that could grown to billions of people with a long tail probably not paying a lot but being served ads; and a fat high end paying a lot more than that for an ad free/premium experience. They should be able to reach billions of users.
It's why Google is matching investments in AI like this entirely from the profit from ads.
Going to space isn't that expensive. SpaceX bootstrapped with a lot less than that.
They have pieces from paper of folks saying they may put up funds or goods and services in that amount. But it’s important to remember that:
1. While they are “raising” commitments others are backing out of deals (see Disney, various data center things). Big deals announced to major fanfare are falling through.
2. They slashed capital expenditure for the future after previously boasting about all the commitments. This is turning into bonkers math of X + Y - X + Z + W - 1/2 of Y = ? On trying to keep track of what’s actually “raised / real” vs what was PR puffery that folks ran away from later.
3. Circular financing still seems to be going on. Big difference of here’s cash, have fun and various “commitments” and balance sheet games that seem to still be going on.
Net net this all still looks very scary and iffy at best.
Edit: A raise comes with stipulations on what you can use the money for. I don't know if I was being too mean about responding to a parent but before you comment just google what a raise has..
https://thedeepdive.ca/openai-locked-up-40-of-global-ram-wit...
If anything there's a plateau between each model release.
Yesterday I asked claude to fix the color issues of graph. It failed miserably. Opus 4.6 wasn’t able to figure out why the text was grey. It made something up, instead of realizing the problem was simple, oklch wrapped inside a hsl color. hsl(oklch(…)) I easily figured this out by just looking at the css and adding some logs to js.
This is not intelligence. This is a tool that’s smart. Not sentient. AGI won’t be achieved by scaling alone.
The concept of moats just has too much weight put on it around here.
I am very much onboard with AI within my workflow. I just don't really see a future where openai/anthropic are the absolute front runners for devs though. Maybe OpenAI does just have the better vision by targeting the general public instead, and just competing to become the next google before google can just stay google?
What is their next step to ensure local models never overtake them? If i could use opus 4.6 as a local model isntead and wrap it in someone else's cli tool, i 100% do it today. are the future model's gonna be so far beyond in capability that this sounds foolish? the top models are more than enough to keep up with my own features before i can think of more... so how do they stretch further than that?
A side note i keep thinking about, how impossible is a world where open source base models are collectively trained similar to a proof of work style pool, and then smaller companies simply spin off their own finishing touches or whatever based on that base model? am i thinking of thinks too simplistically? is this not a possibility?
Best they can do is to somewhat reliably react to objective signals that they've failed at something (like test failures).
The market for local models is always gonna be a small niche, primarily for the paranoid.
Have you ever heard of industrial espionage? Pr privacy regulations? Or military applications?
(Also the US military runs claude as a local model)
I do not, I self host. My current client is also got rid from AWS packing up nice savings as a result
AI in this context has a very different goal as a tool for individual users.
You wouldn't say that hosting instances of Photoshop on servers and charging for usage is a long term viable business would you? Even if current consumer computers struggled to run Photoshop.
I'd take issue with the statement that it is for the paranoid, but I guess it might be a defense mechanism because of course i am interested in local models. If my new workflow is going to be dependent on 3 companies, I'd prefer if there is a light at the end of the tunnel that breaks us free.
As someone who experiments with local models a lot, I don’t see this as a threat. Running LLMs on big server hardware will always be faster and higher quality than what we can fit on our laptops.
Even in the future when there are open weight models that I can run on my laptop that match today’s Opus, I would still be using a hosted variant for most work because it will be faster, higher quality, and not make my laptop or GPU turn into a furnace every time I run a query.
MacBook Pro laptops are preferred over "gaming" laptops for LLM use because they have large unified memory with high bandwidth. No gaming laptop can give you as much high-bandwidth LLM memory as a MacBook Pro or an AMD Strix Halo integrated system. The discrete gaming GPUs are optimized for gaming with relatively smaller VRAM.
Current multi-GPU training setups assume much higher bandwidth (and lower latency) between the GPUs than you can get with an internet connection. Even cross-datacenter training isn't really practical.
LLM training isn't embarrassingly parallel, not like crypto mining is for example. It's not like you can just add more nodes to the mix and magically get speedups. You can get a lot out of parallelism, certainly, but it's not as straightforward and requires work to fully utilize.
The exchanges are bending head over heels to accommodate these IPOs[1] and make our retirement index funds the exit-liquidity strategy to the thievery of pump and dump actors that buy it low and then sell high? As i understand the way thievery works is:
1. List at many multiples of market valuation on an exchange. So if you company is just 10 billion$ nasdaq and theives collude and say "can make it 100 billion..".
2. Lots of institutional investors and rich billionaires get stock options.
3. All market weighted index funds — aka all *your* low expense ratio ETF money — have to re-balance and buy them, raising their value: the exit-liquidity event
4. Rich A**** get richer by making an profit by selling higher.
[1] https://www.economist.com/leaders/2026/03/31/index-providers...
Which to me seems like a very naked attempt at getting 401k to bag hold
unless you're a private investors in these preIPO, the whole plan is to get big enough, get forced entry into indexes, and leave early with everyone else holding the bag.
That would mean the only way to increase growth would be to charge more per token and to get the existing people to use more tokens. Both of which seem to be only what mature companies do when trying to squeeze the cash cow for all it's worth.
It also explains why they're trying to stuff AI into everything, to keep the numbers up, and to get everyone to try and pay them money.
The growth is there but it’s going to be a marathon, not a sprint. I don’t know why everyone’s in such a goddamn hurry all the time
Its just a matter of Productizing the software to plug and play light office admin work.
This is also what I wonder, what practical applications can you actually do locally on something like a minimum spec NPU?
A couple of such people, after they learned about Claude Cowork, signed up for Anthropic subscriptions and are now using it in their jobs. But overall my impression is that there is still huge potential demand from regular people who use computers for agentic systems with less barrier to entry, and that many will be willing to pay for such systems when more mature and user-friendly ones arrive.
The AI revolution is following a similar adoption curve. Right now many of the tools are only really usable if you are a developer or at least not too shy making AI agents use developer tools on your behalf. That's not going to stay like that for very long. It's going to be a messy transition that will likely take much longer than some people seem to think. But eventually most people doing knowledge work will be leaning heavily on all sorts of AI agents to do their thing. And quite a few will have to learn new skills as most of the stuff they still do manually today just goes away as a thing that you do manually.
Like the mid nineties, these are amazing times for people with a slight head start over everybody else. Which is why there is such an investment frenzy around AI right now. Lots of possibilities where lots of money might be made. And lots of things that won't work out. And lots of people really not seeing the forest for the trees as well. And generally behaving like headless chickens. But the internet in the end proved to be not a fad and it didn't all go back to normal after the hype died and the .com bubble burst.
IMHO, the bubble around AI is not so much the technology but things like data center and energy pricing. The cost of data center production is long term a fraction of current cost (dominated by GPUs costing tens of thousands of dollars). Likewise cheap and plentiful energy to power them is going to eventually cost a lot less. Short term scarcity eats up a lot of billions right now. But you'd be mistaken to confuse that for long term structural cost. Cost is going to come down and that will drive adoption. And that's before you consider edge compute on commodity phones and laptops. There will be billions of devices running small AI agents. Add robotics to the mix and it's a whole new world.
In short, companies like OpenAI and Anthropic are valued so high because all of that is happening right now. Yes, it's a bit of a bubble. But stuff will definitely happen.
Or spend less per token (ie. increase profit margin without raising prices).
But notice that no-one, not a single mention of Deepseek tells me that they are preparing to scare everyone again. Which is why Dario continues to scare-monger on local models.
Sometimes you do not need hundreds of billions of dollars for inference when it can be done locally with efficient software; and Google proved that. But where is the money in that? So continues the flawed belief in infinitely buying GPUs to scale which Nvidia needs you to do.
Only a matter of time for local models to reach Opus level. We are 1 or at most 2 years behind that and Anthropic knows that.
Can confirm. Kimi K2.5 is pretty intelligent and most of the time there's no difference between Opus and Kimi.
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The only way they can manage this type of monetization is a lot of compute to process outputs.
So, the real question here is: Is OpenAI Netscape, or are they Google?
What I want to know is are we in 1994 of the AI bubble or 1999?
Because even after the dotcom bubble popped, it was still much better than it was in 1994.
Wallstreet is already pricing Nvidia to have no growth above the average S&P500 company.
More importantly, do you think that a "pop" means supply of compute is suddenly more than demand?
You’ve written so many posts with glaring flaws. Are you trying to come across as smart? Lmao
What are the flaws?
It seems like its just consumer name recognition at the moment
Last announcement I reckon pre-IPO and the inevitable collapse.
Every joule of human energy is energy that could have been better spent to produce AI slop for other AI agents to consume.
Their latest desperate bid for relevance is a plugin for Claude Code that uses Codex as a second opinion. Please clap.
I cannot really see how they are "far behind," or how some plugin for Claude Code is a "last desperate bid." The tools are close enough to each other that I regularly use Codex one month and Claude Code the next without much disruption, just to try out any new models or features that might be available.
I do not have much visibility into the non-code applications, so maybe it is stickier there.
If/when the AI bubble pops and takes OpenAI down with it, I would not expect Anthropic to come out unscathed either.
OpenAI is floundering and can't sustain their own burn rate. Their competitors are thriving. This is a market and technology that OpenAI largely created and just a few years in they are behind, losing unprecedented amounts of money, and have no clear path to catch up.
Lets be totally clear, they were 3 years ahead 3 years ago and now they are behind. They are literally standing still.
Considering how fast competitors caught up to them, I'm not convinced that OpenAI was years ahead. LLMs and transformers were known technology, it's just that OpenAI accidentally productized it before others did (ChatGPT). This is not an advantage measured in years. Google, for example, could have caught up to them pretty easily (they invented the transformer architecture), I think it mostly came down to mismanagement that they flopped so hard with Bard. The biggest cost was high quality data, Google certainly had that, and a budget for huge training runs. I really don't think OpenAI had any special sauce that made them years ahead.
One confounder here is that LLM scaling has started to hit diminished returns recently, no more GPT3 -> GPT4/o1 jumps in recent times, making it easier to catch up to the SOTA.
That schism within the OpenAI leadership was ugly. And Sam Altman does seem to be a bit snakey to me. But I have no illusions about any company in this space, including Antropic. None of these companies are moral, given what data these models are trained on.
> their competitors caught up and then passed them by
The different models are more capable in different aspects, but they are close enough together that only in a few months they leapfrog each other.
> OpenAI is floundering and can't sustain their own burn rate. Their competitors are thriving.
Google is thriving, sure, but not because of Gemini, it's because of their existing ads business. I would not say that about Anthropic, they seem to be struggling to provide enough compute (with the recent usage limit changes). Hard to know whats happening funding wise in these companies. Saying that their competitors are thriving is a stretch. And again, if the AI bubble pops, Antropic is gonna hurt along with OpenAI. Just not clear to what extent.
Or OpenAI pays off it's investors? Lol.
I am not sure if I believe in the Singularity or not. But it's kind of the best story ever to support the game of musical chairs that is Silicon Valley investing.
Not gonna lie, I hate those announcements lately. It's full bullshit mode, worse than the Dot-com bubble. Numbers don't make any sense, any more, and yet journalist don't ask any real questions...
Ironic, isn’t it?
> I ship code every day. I use Claude, I use GPT, I run llama locally.
Doesn't really strike me as the kind of statement that comes out of a company that can sustain a ~$1T market cap...
-x-
In short, the musical chairs are still playing... Keep on walkin' round, y'all, till the music stops.
/s
I wonder what the bet is here, long term that valuation is going to have to go up even further for this investment to make sense so they're clearly betting that at IPO time they'll be able to convincingly demonstrate AGI or something extremely close to it. That's a pretty risky bet, and meanwhile, whatever they come up with will be a commodity within a year. And that's besides OpenAI no longer being seen as the dominant player or the player with the best edge.
I am so sick of AI writing.
What??
It's going to be pretty hard to get a good answer to whatever you're having difficulties understanding if you can't be bothered to write more than a word.
They raised $122B.
122 / 12*2 = 5 years to get your money back (I simplify, I know revenue <> profit)
They are so big that almost no one can afford to acquire them. It is similar as someone would like to acquire MSFT or AAPL.
WCGW?
Revenue $1.00
COGS (inference) (0.67)
Microsoft (0.20)
Gross margin $0.13
That $0.13 must cover "everything else": R&D, payroll, etc., and ideally leave some profit on the table.
The problem for OpenAI (and other pure AI companies) is that inference is not like software that sells at marginal cost (build once, sell everywhere), but each token costs money. Inference gets cheaper, but newer models require more computing power and consume more tokens. So the gross margin does not improve over time.
Break-even in the future won't come from just growing API usage and subscriber base.