Anthropic's small models are almost certainly distilled from their larger ones. And their biggest training expense are going to be experimental models that aren't even intended for release, just to test out some idea.
New Constructs takes a similar position on all mega IPOs. Sometimes they're right, but sometimes they're wrong. For example, they insisted Uber's IPO valuation was too high due to unsustainable losses, hidden liabilities, etc. Initially they were proved right when the post-IPO stock price plummeted, but in the long term Uber has performed well, become very profitable, and now trades well above its IPO valuation.
I'm expecting a similar story to play out with Anthropic: The stock price will come down significantly after the IPO, resulting in lots of headlines about the AI bubble bursting. But in the long term it'll climb up again and investors who stick around will do very well.
I don't see how Anthropic can become profitable enough to justify its investments unless they can either stop training models ("Pace the Frontier!!1"), or magically eliminate open source competition so that their volume x margin on inference is high enough to dwarf the training costs.
For the IPO, I assume they're going to try to get everyone to focus on inference - which is profitable in isolation. But I don't know how they'll distract the market from the other half of the equation.
Unlike the dot-com era, this is a bubble that everyone saw coming.
Like dot-com, there are many long-term winners, but cash hungry frontier labs are not among them.
Prediction:
OpenAI, Anthropic, Oracle, and SpaceX[1] go down and assets be sold or companies acquired for a fraction of their valuation. The same goes for most neoclouds. Profitable "old" tech companies like MS, Google, Meta, and Amazon are fine and scoop up the valuable parts for pennies.
Nvidia will be in Cisco's position (Cisco was the world's most valuable company in the dot-com era). Both are good companies that are not going anywhere, but stock prices get decimated when markets collapse (Nvidia liabilities are not high enough to take company down, they are mostly tied to there not being a bubble and data centers are getting built)
[1] Everyone already knows that, according to SpaceX, > 80% of SpaceX's valuation is in AI, not in space stuff, right?
Given https://www.abc.net.au/news/2026-10-10/how-firmus-the-bigges... and the above, I'd say we're already primed for a fall. Given 5 years is a pretty long time (that's 3 US elections cycles where politics can increase uncertainty about AI), and the length it took for the subprime market to create the GFC (see e.g. https://en.wikipedia.org/wiki/File:Subprime_mortgage_origina...) looks to be about 3-5 years, I'd be 99% sure the crash would happen by then (with the 1% covering both the uncertainty in the cycle and something odd happening).
Nvidia probably doesn't really have really serious liabilities as long as it has actually produced all the GPUs it has sold on a buy-and-hold basis.
It's fabless, right? So they haven't even built out wasted manufacturing capacity.
As long as the GPUs they have sold are really sitting in a warehouse in Taiwan or somewhere in the USA, they are making properly concrete money.
The fact that nobody else is making real money, that will eventually come back to bite them, but Nvidia will just see its business shrink; it will have to scale back if the bubble bursts, but it will get out with much of that money intact.
The other parties swimming in money are memory chip makers. And I think list pretty much ends there. They might or might not over commit for future and eat the cost. But they too might be good with these profits even if future fabs lose some money.
Memory demand over time naturally goes up, so even an overcommitment wouldn't last longer than a few years until demand catches up again. SK and Samsung memory margins are utterly ridiculous currently (> 80%).
For September:
> In IT, semiconductor exports rose 262.8 percent to $60.30 billion, exceeding $60.0 billion for the first time as memory demand continued to grow, with export volumes continuing to expand and contract prices maintaining their upward trend.
> So they haven't even built out wasted manufacturing capacity.
According to SEC filings Nvidia has $100 Billion in total commitments. They are mostly purchase obligations, advance supply agreements, and multi-billion-dollar prepayments for fab capacity (wafers, HBM, packaging, substrates and interconnects).
But aren't these for manufacturing things that they have actually sold?
A general rule in the AI bubble appears to be this: Nvidia aren't waiting to get paid for the things they make. Rather, they are being paid very up front for things that cannot be installed.
My prediction is the same. I think MS, Google, and Amazon will be the winners here. They might take a hit when OpenAI and Anthropic blow up, bu they can absorb it, and are well positioned to provide those services in a reasonably sustainable fashion. I suspect the costs of using AI will be considerably higher at that point (subscriptions will be extremely limited or just non-existent). Meta does not benefit in this case since it doesn't provide compute, but they have money to waste (as they did with Metaverse, VR, etc).
> Unlike the dot-com era, this is a bubble that everyone saw coming.
As far as I recall, the dot-com bubble was widely seen as such prior to it bursting. E.g. Greenspan and Buffet were both quite vocal about the irrationality of the values being assigned to companies.
Their inference margins are already high, the thing bringing their net down isn't training per se, it's the fact that they have to train the next iteration right away due to competition, otherwise an extended inference cycle would've eventually recouped training costs.
The bet is that cost per intelligence will keep going down and demand for intelligence will grow at the same time, if this bet holds, a user could get the same or more done with a cheaper model (running-cost wise) while paying the same subscription and the lab gets improved margins.
Open source is a challenge but their current moat is the fact that they're ahead, and as long as they stay ahead they'll be able to charge a premium.
The rush towards open weight models defeats this thesis. There’s no prize for being “ahead.” That’s academically interesting but a terrible business plan. 99% of AI use cases don’t need the latest and greatest model, and businesses increasingly understand this.
That's like saying "forklifts are a terrible idea, because a forklift is excessive for lifting 99% of the items that I can lift". See the problem?
"AI use cases" is a moving target! If you try to define "use cases" by "what AIs today can be used to do", you miss things AIs would do in the future. The more capable and price-performant AIs get, the more there are places where AI has a role.
This is a big part of what the frontier buys you.
The other big part is that going from a local AI to a frontier model often makes the difference between "this use case works 60% of the time, good tech demo" and "this use case works 99% of the time, good business decision". The difference between "clunky and needs human in the loop" and "just works" is worth paying the API price.
The forklift market seems to be in the $90-$95 billion / year while the global passenger car market is $2.9 trillion.
This is the problem.
While the frontier labs will always have a market for AI that can do things the other models can't, if the sliver of work that can be done only by the frontier models is narrow enough, then what they spend to train those frontier models may not let them capture all that much extra revenue.
I absolutely think there will be a market for frontier models pushing further and further.
But it's not yet a given whether or not being ahead on capabilities is going to buy them all that much more higher earnings relative to lower tier providers.
If it stays the case that going from local AI to a frontier model makes the difference between 60% and 99%, then they probably will, but there's nothing to suggest local or open model, or second-tier closed models won't keep moving ahead as well, and eat away at the use cases where only a frontier model will do.
Do you think that human civilization has a finite demand for intelligence? That there is a point that we can hit, and stop there, and say "we've thought of all there is to think about, no more thinking is required?"
Do you think that we are anywhere near that point?
We've already seeing things - like what's happening with AI reverse engineering now. I'm a reverse engineer - and I know that the reason why RE was used as "last resort option" was that expert reverse engineers are rare, expensive, and work slow.
But now that a lot of RE workloads can be tackled by AI instead of a human? The demand for reverse engineering is at a never before seen high. AI made reverse engineering much more viable - and thus, a lot more reverse engineering is happening now.
There are myriads of fields like this - things that go overlooked not because no one wants them, but because the economics of human expertise make them nonviable in most cases. As AI gets better, it can begin to enter those fields.
Except you, of course, need to push the frontier to do it.
It's always disappointing to see comments by arrogant elitists claiming that most people are essentially NPCs. But even if your claim was correct, the demand for inference compute capacity by businesses, governments, and universities is effectively infinite. If there is a limit then there are no signs that we're getting anywhere close to it.
If his claim is correct, and 99% of people are NPCs incapable of any meaningful thinking, that makes the 1% that actually does all the thinking of human civilization very valuable.
And that, in turn, makes AI even more valuable if it can produce thinking on demand.
That is weird claim considering did not reward "highly intelligent" or "knowing stuff" on itself. Super smart people great at whatever jobs they picked have roughly normal salaries.
Researchers specifically were never highly paid. And positions were competitive - there were way more people willing and able to do those positions then positions themselves. Same goes for art btw.
This kind of all depends on being able to continuously make better models indefinitely. I'm not convinced that's possible. If there is a limit, then everybody will get there, and anthropic has no moat at all.
> Do you think that human civilization has a finite demand for intelligence?
No, I don't. But for any given task there is a ceiling above which for that task there is no value in additional intelligence. E.g. it takes very little intelligence (none, in fact) to sort a list. More intelligence does not result in a more sorted list.
And so for a huge proportion of what we do there is a ceiling of value that can be extracted by selling AI tools to do any given task.
Combine that with there being at any given time a ceiling of available capital to be apportioned to buy intelligence to carry out the remaining tasks, and the floor of tasks that non-frontier models can do well enough rising, and there will at any given time be a finite amount of capital that will be accessible to frontier models.
It is by no means given that that slice of capital will grow rapidly enough for frontier providers to be able to create an attractive financial return. That depends on frontier labs being able to continue to deliver sufficiently more value than cheaper models at any given time that enough people won't simply wait.
I'm extremely bullish on AI in terms of its ability to transform society over time, but that does not automatically translate into assuming that the current frontier labs are a safe investment bet.
"Sort a list" doesn't exist by itself. It isn't a terminal goal - it's a step towards something else.
If "sort a list" becomes a trivial task, everything that was bottlenecked on "sort a list" is unbottlenecked, and other parts of the process become bottlenecks instead. Thus, the demand for non-sorting tasks grows. The saturation of low end feeds the value into the high end.
> "Sort a list" doesn't exist by itself. It isn't a terminal goal - it's a step towards something else.
Sometimes it is. But that is also irrelevant. Replace "sort a list" with any given goal and the argument remains the same.
> The saturation of low end feeds the value into the high end.
But that process is not immediate. There's a reason I was careful to include "at any given time" in my comment.
For the purpose of whether or not a frontier lab is a good investment, it doesn't necessarily help them if there is an ever rising demand for intelligence if their market is eaten from below just as fast by cheaper models from competitors catching up.
It could be they manage to out-pace their competitors sufficiently that they will produce returns high enough to justify their valuations.
But irrespective of whether the demand for more and more intelligence continues to rise perpetually if 2nd tier labs hollows out the bottom of their market fast enough, it could equally be that most of the market ends up being low-margin, highly-competitive inference that won't justify their valuations.
Given the size of their valuations, even if they turn out to be tremendously profitable businesses, it's still not a given they'll give a good return on investment for investors getting in now.
I'm not saying they won't. I'm saying we can't easily judge that based on just assuming growth at the high end will continue without understanding what their moat is likely to look like.
> everything that was bottlenecked on "sort a list" is unbottlenecked, and other parts of the process become bottlenecks instead. Thus, the demand for non-sorting tasks grows.
Your assumption here is that the other parts of the process are intelligence. In the real world they usually are not e.g. raw materials, politics, zoning, manual labor, clinical trials, traffic, energy ... And usually those things are such huge bottlenecks that Amdahl's Law renders the speed of delivery of the intelligence part irrelavant.
There is no business model for competing companies to build forklifts that can lift an infinite amount.
That is not to say attempting to do so would not find new use cases for such powerful forklifts. The problem is the cost of building ever increasingly powerful forklifts while the TAM for that power shrinks.
You don't even have to bring in the enormous difference between forklift rusting theta vs gpu theta.
Their competition has the same problem. They're engaged in a giant game of chicken (or giant game of "who runs out of ability to raise more cheap capital first") with respect to overspending on training relative to inference revenue.
So, yes, it's high risk - you're basically betting on who will be in the strongest position when one or more of the competitors are forced to slow spending and the rest are able to ease off on theirs as well as a consequence.
If you think either that Anthropic is in a strong enough position to come out on top or that we'll end up with a detente like with the big cloud providers where they big providers feel they have a strong enough position to beat off upstarts and collectively basically stop competing other than on the margins because they all know they'll earn more by protecting their margins than by internal competition, then the IPO might be worth putting money on.
I think the latter scenario is slightly lower risk, but still risky given how small the moat appears to be vs. the Chinese labs (I say this as I just had Kimi re-design a website in 10 minutes by just giving it the URL to the current one and tell it to replicate everything; they might not be as smart as the frontier models yet, but they're capable enough that they're taking over an increasing proportion of my token budget)
> Open source is a challenge but their current moat is the fact that they're ahead, and as long as they stay ahead they'll be able to charge a premium.
Being ahead isn't much of a moat in a game where playing catch-up is significantly easier than being ahead. Also, how much ahead of Chinese labs are they at best? A year? Two? That's a moat for ants!
> their current moat is the fact that they're ahead
the problem is that they are not ahead. they are ahead on producing one-shot demos, which are useless party tricks, but when it comes to shipping real products these large models are just a big expensive waste of time and what you need is deterministic systems that integrate small efficient purpose built models in the places where they are actually the best solution for the problem.
the anthropic game plan was to wrap the entire software industry up in a magic box called "AI" and then rule the world but these people are delusional and their house of cards is rapidly collapsing. the technology is real, but they didn't invent it and they don't own it. it is kind of amazing to think of a $2T company with zero IP ... they didn't invent a single thing that they are selling, and for the most part they are implementing it worse, and serving it less efficiently than at least a half-dozen other competitors.
If they are a year from AGI, then the private investors can hang on and use their new super intelligence on their own tasks to make themselves considerably more wealthy now and into the future, so why would they want to sell that power to anyone else?
Except the private investors can't, because that AGI belongs to the companies they didn't invest in. And now those companies can reproduce all software and knowledge work of the entire world. Once robotics catch up, labor too.
> These companies believe they're a year from AGI, and that's how they'll be profitable.
What I don't get is that if Company A is a year from AGI (I don't think that's true, but then again, I don't think anyone even has a good definition of AGI), then surely Companies B–ZZ are only a few years (at most!) from AGI as well. There is no moat. Or if there is a moat, the moat is hardware scarcity – but that's systemically outside of the control of these companies.
The problem is RSI. Hypothetically, the first to achieve a sufficiently advanced AGI that can self-improve will see a singularity event that rockets them past all competition exponentially.
It's also weird that most seems to think that if inference is good, it's all good. You still have massive costs in data centers, replacing hardware, upgrading hardware, paying salaries, etc.
You can have 99% margins on what you sell and still go bankrupt.
In intrinsic valuation, the value of the operating assets is determined by ebit(1-t) - reinvestment.
Gross profit doesn’t mean a whole lot if a) your operating income is negative b) your reinvestment needs are mega. You have to make some interesting assumptions Re. Anthropic to get a 2T valuation.
I almost have to hold my nose reading finance posts on here.
People keep talking about the risk of open source models, but if you're outside the HN/SV bubble, no one is using them. Anthropic's revenue is ~$60B supposedly, OpenRouter's revenue is $140M. I know they're not the only place to get open source models from, but they're the most popular and Anthropic is bringing in 400x more revenue than them.
I was hoping you were able to make the numbers work.
I have just not read or listened to much of anything that the numbers work besides some science fiction fantasy on Dwarkesh podcast.
The gpu theta + the frontier model theta + token deflation creates this rolling window that I just don't see how it works given even the most bullish assumptions.
Maybe if the rolling window was expanding a rational argument could be made for the valuation. No one can say with a straight face the rolling window is expanding.
It is like competing biotech firms without patents working on the same drug but with these time decay parameters too.
“So, what you're telling me is that the music is about to stop and we're going to be left holding the biggest bag of odorous excrement ever assembled in the history of capitalism.”
A brilliant line from the movie Margin Call (a fictional portrait of the actual events of the 2008 crisis) that appears likely to get reused in upcoming AI bubble burst movies.
The model is engine, the harness is the car Anthropic are selling.
They are a service company, selling home-grown, mass-produced, conveniently packaged intelligence at a well established price for consumer. Their API pricing might just be for value proposition and tax deduction purposes.
Every tech company, tech department, startup that I know is using claude code to deliver. The boutique deepseeks, qwens, glms and kimis are nice, but ain't production ready in 98% of cases. All the pi's, opencodes, etc are nice, but much less enterprise friendly. And google just outright sucks in comparison. There's a use case for each, but not at the scale Anthropic is doing.
Only real competition - OpenAI - is close, but they're burning money to stay there, which imo is unsustainable long term.
Is Anthropic worth $2T? Can't say. But boy they have a good opportunity to test this, and they may not have a similar chance in the future.
I've tried a bunch of LLMs, and I agree that Claude is currently the best at coding, but the gap isn't huge. Gemini 3.8 Flash is surprisingly good and I'm looking forward to trying Gemini 4. The open weights models like Kimi, GLM, etc. are a little behind in quality I think but not massively.
With harnesses I see little difference between what Zed or Pi gives me and what Claude Code gives me. Enterprise features? The AI can help code those in a week.
AI itself is a great breaker of moats.
The question isn't whether they lead today. It's whether there's any kind of moat. Without a moat, frontier model development is an industry like chip fabrication or large volume manufacturing. Those industries are a red queen's race where if you stop innovating for even a short while you sink. Ask Intel what happened when they decided to coast for a few years.
Chip fabs and bulk manufacturers make a lot of money, sure, but they don't command such a multiple. Anthropic is priced like they're going to be to AI what Google was to web search or Apple is to (US at least) mobile and higher-end PCs.
I don't see it. I think they'll be a big player but that big?
Of course... maybe if they suddenly have that much cash they'll be able to carpet bomb the entire world with AI doom Rationalist ideology and buy their regulatory capture and outlaw their competition.
They made it convenient to get value for the specialist masses and I don't think anyone else managed to achieve it yet. That's their moat.
I've seen firsthand attempts at integrating open source in place of it and they all failed. Time is money and it costs premium. Touching the ground running is a huge advantage. That's why cloud services stuck.
time is money so when the subsidies stop or they magically make inference price an afterthought like cloud did to traffic then it's going to be much more economically better to spend a one-time price setting up a local or a self hosted open model than paying $2000 for a subscription
All the smaller players İ know of have moved production to DeepSeek or Qwen, while they still play with idea/prototyping on Claude or GPT, that's the Western focused players. There are many foreign firms who won't touch either company at all even for that.
Simple reasons being no nonsense nanny refusals & it's cheap/good enough to get the everyday production parts done fast and reliably for next to nothing.
Your experience is not what I see at all, but İ don't work with megacorps or in the Valley anymore, so it's possible those powers will carry the weight to some extent, until they won't or can't.
> The New Constructs report also notes that Anthropic’s assertion that AI could pose “a catastrophic or existential risk to humanity” is another reason why investors should avoid the IPO.
So, we go from an existential threat to basically unprofitable business. I can only see Amodei and Altman just as the next Holmes.
New Constructs is bearish about every tech IPO. Easy to reinforce your bias by selectively looking at instances where they were right, but they also predicted failed IPOs for Spotify (+219%), Uber (+60%), CrowdStrike (+3136%), Cloudflare (+2306%), Palantir (+1991%), Snowflake (+51%), DoorDash (+93%), Robinhood (+187%), ARM (+422%), Instacart (+59%), Reddit (+370%), CoreWeave (+105%), SpaceX (+20%) and lots more.
So whatever your stance on Anthropic this particular analysis is safe to ignore.
You dont need to criticize good research, you can just recognize the market can stay gullible, for longer than you stay solvent.
I like to think you can enjoy the ride wave as you are propped above the heads of an hysterical crowd, as they rush to the abyss...Just find some solid tree branch you can latch on, when they realize where the road ends.
It’s not “good research” when they are wrong >50% of the time. If you invested money in every IPO they told their subscribers to avoid you’d be very rich today.
I feel like the market staying irrational/gullible longer than you can stay solvent argument doesn't really make sense when all you're doing is NOT investing in something. It seems an aphorism more suited to puts and calls, puts especially, than it is to deciding not to invest at all.
> the market can stay gullible, for longer than you stay solvent.
This is essentially just what people say when current reality is different from what they want it to be. Sort of an unfalsifiable escape hatch response to “well observable reality contradicts your claim”
It's usually wise advice when someone thinks they can make money by shorting an overvalued asset. Sure you might eventually be right, but in the meantime you'll go broke.
In the long term, in theory, prices should be tied to value, most most of the time the stock market plays more like a casino.
I agree it makes sense in the context of warning people not to short something. But what I am replying to is a person using it generally, not in the context of shorting, to just say “it only looks like I’m wrong because everyone else is crazy and irrational right now, but they’ll come around eventually”. Not exactly a rigorous argument.
Wise to critique both holistically, which makes it funny when people want to ignore an individual's or group's track record (especially regarding specific mental models or types of analyses) when evaluating a specific argument
I think it's probably a negative for the stock price when the CEO thinks his company shouldn't be developing its main product and believes wiggy and false things about what continuing development means. Investors can put up with a lot of things, but an erratic willingness to undermine core business activities is usually not one of them.
If a weather reporter on TV says it's raining every day, and it's not always raining, I can still criticize them on days when it rains without it meaning I don't think it's raining.
> Track record is extremely relevant when the "argument" is mostly about judgement and subjective opinions.
Ironic given this article is from CNBC, employer of Cramer, host of "Mad Money", who has been so inconsistently wrong that his picks have literally sparked an ETF. Just search using your engine of choice "Inverse Cramer ETF".
I work in finance. Past performance is not a guarantee of future returns, but is a damn good indicator, which is why everyone always wants to see your past performance anyways.
> Past performance is not a guarantee of future returns, but is a damn good indicator,
Unless it's about stock picking, when the winners in one year of doing good stock picking are no better in the next than any other random stock picker.
SJIM lost 15% in a period when the S&P gained 25% (betting against Cramer). LJIM over its lifetime gained 3.7%.
Of course both had too short a lifetime to draw a conclusion due to lack of interest and this was pre-AI so maintaining the positions was difficult. But it’s important to remember that Jim Cramer fails to beat the market, not that he’s an inverse oracle.
WeWork had a massive cost base to offer their service. They had to rent/buy a lot of real estate to serve their customers. None of all the examples you list here except CoreWeave has a comparably high cost base.
All the mayor AI players have to rent/buy a lot of computing power to serve their customers. We're talking costs of 2-5x (or 10x? does anyone actually know?) their revenue. The question is, will they ever be able to pay their cost of revenue and operating expenses? Many people doubt. And we know that they do all sorts of funny book keeping shenanigans like SPVs and delayed deprecation.
What comes on top is, LLMs have no economy of scale. More customers scale linear with higher costs. Will people or companies be willing to pay 5x what they're paying now? Will future frontier models become more cost efficient or less? We simply don't know yet. At this point, it's a gamble.
> None of all the examples you list here except CoreWeave has a comparably high cost base.
Wut? I'm pretty sure SpaceX spends a lot of money shooting rockets into space, and Cloudflare has pretty high infrastructure costs given that a very large portion of all Internet traffic goes through their networks.
True. Cloudflare has a high cost base, but they had and still have a valid business model.
SpaceX is an entirely unique thing, I don't really know what to think of it. I don't see a viable business model there, but I might be wrong. Maybe there is trillions to make in space. Their targets are long shots, but meanwhile they are bleeding money on all their ventures and they ride on the AI wave. The IPO was fairly recent and it might still just implode one day.
You're discussing something entirely different, which is fine, but you're not refuting anything that the parent poster said.
All they were saying is that they're terrible at predicting risk. Examples were given. It doesn't matter why they're bad at predicting risk, they simply are.
True. All I say is that I agree on their take on Anthropic, although I wouldn't word it as strongly as they do. They may be bad at predicting IPOs, but every once in a while they may be right. ;)
>> Many people doubt. And we know that they do all sorts of funny book keeping shenanigans like SPVs and delayed deprecation.
Every time I see Anthropic and other AI companies getting ready to go public, I cannot stop thinking about the entire Enron debacle and all of their "unique" book keeping shenanigans that has far reaching impact, even to this day.
People keep telling me, "Nah this is totally different man, you can't compare the two!" But is it really??
It fundamentally comes to investments/commitments divided by revenue over certain low number of years. Now add in any financing costs, overhead and actually operational costs.
Math ain't looking pretty. Just like it did not look pretty with WeWork. Might have worked, but still not great business to be in.
Being hyperscaler really does look very high capital and questionable margin bussiness at moment. With lot of competition.
You can be right for the wrong reasons and you can be wrong for the right reasons. The economics of many of these businesses are disconnected from their market valuations, and there are examples of investors outright saying "none of this matters, let's meme together" (most notably, GameStop).
In general, the stock market is in a somewhat weird place because most people in the US who have some money just don't have anything else to do with it. It's not a productive suggestion to keep it in savings or treasuries, we don't invest in friends' businesses because we don't have friends, real estate is too expensive, we don't collect art or antiques because that's for old people... so YOLO in the stock market it is.
So yeah, I don't think it's wrong to criticize the Anthropic IPO as nearly impossible to justify by anything other than vague hopes and dreams. But that doesn't mean it won't make you money.
You would think any investor would prefer to be informed that the numbers don't match expectations even if they then decide to go ahead anyway. People like to gamble sometimes even though the likelihood of losing money is very high.
Also known as a broken clock being right two times a day.
The fallacy is assuming ahead of time that they are actually right this time.
If you start assuming they’re right and also admit that their logic doesn’t support that conclusion, there isn’t even any argument left. You’re just implying that you believe one thing is true and anyone who agrees with you, regardless of the reason, is also correct.
It's not that the stock market isn't overvalued. It is that everything else is more overvalued. Especially real estate.
Friends businesses don't need our money, because banks are generous with giving out loans and friends prefer to keep ownership intact while being in debt instead of diluting it.
Are you using lifetime change since IPO and not accounting for years? SpaceX hasn't beat the S&P for example. Uber hasn't. I didn't check them all but some of these seem to contradict your point?
I don't feel like going through the list but Uber definitively botched their IPO. If they are up 60% only since the IPO they are just matching inflation and pretty much below the index.
10 months back 1T made sense, today even that looks expensive and they are eyeing 2T. How much do they expect to grow from here as a 10x growth from 2T is 20T and even a few years later 20T for a company is a lot. Amazon and Google ipoed with lots of room to grow.
I don't understand how people are so certain on how this will play out. We have people basically saying companies like Anthropic offer no value because open source models are free. Then we have others saying once frontier AI labs go RSI FOOM takeoff they'll essentially _become_ the tech industry.
Anthropic raises money from IPO -> How long will that sustain them given the immense cash burn? Forget about gross profit - that's the number they want you to focus on and can be played with. Keep the focus on the cashflows -> if a firm runs out of money its over, who cares what your revenues and gross margins are. We are not talking Amazon level loss's which were paltry AND they were able to raise more than enough to keep going for awhile.
Management of firms who pay rent to LLM models need to reign in costs -> they will use a bundle of chinese +american models (this is already happening look at the data) -> affecting revenues, earnings and cash flows of frontier labs. Given the losses in absolute terms, any stunting of the growth rate would be catastrophic for the story re. valuation.
The frontier model story rests on one giant assumption: lay-offs must happen en masse at some point. It's not happening and in my view won't happen - there simply isn't enough trust. Moreover, do you think firms are going to trust these model providers, given its in their interest to steal IP? lol
I agree it’s not rocket science, but I think there’s more to consider here.
First, a lot of usage can switch to open models (like is happening, I agree), and yet frontier model usage can still grow (like is happening). As long as the market for frontier level intelligence keeps growing, the cost of frontier intelligence is marginally profitable to the user, and the open weight models don’t catch up, I don’t see any reason for frontier level usage to fall. Indeed, we haven’t seen any of that so far, despite the rise in open weight usage. My own product has started using open weight models, but my usage of frontier models also continues to grow, because they keep unlocking new capabilities. Maybe that’ll end, but I’m skeptical. I think the problem space that can benefit from the best intelligence money can buy is unbounded.
Plus the labs can still offer cheap non-frontier models to compete with the open weight models (like Luna and Haiku), and they have a massive advantage in terms of available compute.
Secondly, I don’t think that the big labs need mass layoffs to justify their valuation. That’s perhaps one path, but in my view a more likely one is that we get greater increases in productivity and economic growth, and they capture a large share of that. If global GDP grows 2% faster than it otherwise would over the next decade, that’s an extra $175 trillion in economic value created over the next decade. If it grows 5% above baseline growth, it’s half a quadrillion. GDP in 2036 would be more than $100T higher per year than today. AI companies don’t have to capture very much of that to justify a $2T valuation.
Now, will any of that happen? Who knows, it’s definitely unrealistic and unprecedented, but then again, so is much of what I see happening in the world today. Time will tell.
Most "news" is just a dramatized press release these days. The conditioning of the public to viewing media as authority creates a mental trap where you're told something is important/credible, despite having zero hallmarks of credibility. And we perpetuate this because it's familiar, not correct or accurate.
This is exactly why humanity continues to stumble, despite centuries of evidence as to what doesn't work. We just can't accept that most of what we tell ourselves is reality is just a for-profit (or for-influence) product that masquerades as knowledge or important information.
I thought this was the reason to force an investor account on every american child, so that they can be "forced" to buy into these IPOs, and left holding the worthless stock while a massive amount of wealth is transferred from the system to a select few investors.
I think it's a little early to make that statement. Could be. But at this point I think things like printing press, agriculture, writing ... they're all many times more significant.
I know it’s a hot take, but I disagree. I think the invention of AI (or more specifically, ASI with RSI) will dwarf the printing press, agriculture, writing, etc. in terms of significance.
Now, obviously all these things built on each other, so comparing them like this is a little silly, but in my view, inventing AI is essentially inventing an inventor of fantastical things on par (and beyond) the greatest inventions of humanity, including the ability to self-improve.
To be clear, I don’t think today’s LLMs are there yet, and I take no position on whether they’re a dead end, but in my view ASI has no fundamental barriers that cannot be overcome in time.
"The invention of a magical wish-granting technogenie that has not yet been invented, and may never be invented, and we have no idea how we could get from what we have to inventing it, would be the best thing of all time!"
> I’m buying, this is the greatest invention of all time and Anthropic has garnered a pretty solid lead right now.
Depends on your perspective, but that's definitely true if you're selfish and have been paying people for intellectual labor. Lots of layoffs to fantasize about (even though that represents vast amounts of pain and destruction for many people).
Is it true growth, or circular dealing plus hype? I have little doubt the IPO is nothing but a wealth transfer from retail investors who'll be left holding an empty bag.
I take no position on the correct valuation of Anthropic, but I think if you've used coding agents, it's pretty clear that it's not just hype; they really are a useful technology that can massively increase software engineering productivity.
As far as I know the circular deal fears are more around the chip purchasing agreements, because there is a speculative component to building out datacenters for training which may not produce models that are worth the training cost, but the revenue from inference is real and it has truly grown a lot over the past two years.
> ...it's pretty clear that it's not just hype; they really are a useful technology that can massively increase software engineering productivity
Problem: Anthropic isn't the only provider. You can argue whether they are the "best" provider, but both GLM and DeepSeek exist and are really, really good. I was using Qwen offline on a trans-Atlantic flight on a 128GB MBP and output was totally acceptable.
The benefits of replacing all human payroll will go to AI companies as a whole. AI companies as a whole != Anthropic.
As the article points out, the greatest threat to closed models like Anthropic's comes from cheap open source models. Not from the possibility that AI won't be successful at replacing payroll.
Cancer. Burkitt Lymphoma takes a couple of days to double in size.
It’s important to understand that infinite growth inside a finite system is impossible. At some point growth has to stop, either by eliminating the growing organism or it killing the host.
Well, unlike the economy I can’t grow in size rapidly. (And if I did I’d just have another major problem.)
Induced demand and limitless cheap human-quality labor can possibly grow the pie very fast, though even then, you start running into the earth’s finite resources eventually. But it is possible that they are worth much more than $2 trillion long before that.
But that is why I said you can’t just safely assume 15x multiples to continue.
"The company’s growing operating losses" - yeah, if you see a "research firm" basing your research on the leaked 2025 Anthropic financials and not what happened in 2026 you are on the verge of malpractice.
(I think 2 trillion dollars is an absurd valuation for a product with such hot competition and low switching cost, but if you make the case that Anthropic is losing money based on the 2025 numbers from that Reuters report you're being farcical.)
> which is weird when Anthropic have supposedly claimed two profitable quarters in 2026
Anthropic claimed to be profitable if you dont count some of their largest expenses (like model training). Not the sort of profitable where revenue actually exceeds total expenses
"Anthropic still hasn’t made its prospectus public, so New Constructs hasn’t seen the actual filing. However, the firm cited figures that have been reported, including from the New York Times, which reported in September that the company was on pace to generate $100 billion in annualized revenue by the end of 2026."
Anthropic's annualized revenue run rate reached $65 billion at the end of July 2026, up from just over $5 billion in August 2025 (Anthropic, CNBC)
Anthropic made nearly $4.6 billion in revenue in 2025, 12x more than in 2024 (IPO prospectus, via Reuters, September 2026)
Anthropic's preliminary Q2 2026 revenue was more than $11.5 billion, ahead of OpenAI's $6.7 billion (Bloomberg and The Wall Street Journal, August 2026)
So, the Q2 revenue was $11.5 billion. The claimed $65 billions are "annualized revenue run rate". Please show me where that term is defined reliably. It's a BS marketing term to obfuscate real revenue after the tokenmaxxing hype has ended.
"Anthropic defines “run-rate revenue” in two parts. Use the last 28 days of sales from customers charged on a consumption basis and multiply it by 13. Then, multiply the monthly subscription take by 12, and add the two together."
I think people saying that open source is a threat underestimates how scared large corps are for lagging behind when it comes to AI. There are other risks that are bigger I think like the political risk.
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[ 1.8 ms ] story [ 30.2 ms ] threadKeep all the Mythos/Projects/etc. hype/feature-creep crap in some other entity and value that at $5 tn or something if you wish.
I'm expecting a similar story to play out with Anthropic: The stock price will come down significantly after the IPO, resulting in lots of headlines about the AI bubble bursting. But in the long term it'll climb up again and investors who stick around will do very well.
For the IPO, I assume they're going to try to get everyone to focus on inference - which is profitable in isolation. But I don't know how they'll distract the market from the other half of the equation.
Like dot-com, there are many long-term winners, but cash hungry frontier labs are not among them.
Prediction:
OpenAI, Anthropic, Oracle, and SpaceX[1] go down and assets be sold or companies acquired for a fraction of their valuation. The same goes for most neoclouds. Profitable "old" tech companies like MS, Google, Meta, and Amazon are fine and scoop up the valuable parts for pennies.
Nvidia will be in Cisco's position (Cisco was the world's most valuable company in the dot-com era). Both are good companies that are not going anywhere, but stock prices get decimated when markets collapse (Nvidia liabilities are not high enough to take company down, they are mostly tied to there not being a bubble and data centers are getting built)
[1] Everyone already knows that, according to SpaceX, > 80% of SpaceX's valuation is in AI, not in space stuff, right?
It's fabless, right? So they haven't even built out wasted manufacturing capacity.
As long as the GPUs they have sold are really sitting in a warehouse in Taiwan or somewhere in the USA, they are making properly concrete money.
The fact that nobody else is making real money, that will eventually come back to bite them, but Nvidia will just see its business shrink; it will have to scale back if the bubble bursts, but it will get out with much of that money intact.
For September:
> In IT, semiconductor exports rose 262.8 percent to $60.30 billion, exceeding $60.0 billion for the first time as memory demand continued to grow, with export volumes continuing to expand and contract prices maintaining their upward trend.
https://english.motir.go.kr/eng/article/EATCLdfa319ada/2743/...
Not too shabby for a rainy day fund.
According to SEC filings Nvidia has $100 Billion in total commitments. They are mostly purchase obligations, advance supply agreements, and multi-billion-dollar prepayments for fab capacity (wafers, HBM, packaging, substrates and interconnects).
A general rule in the AI bubble appears to be this: Nvidia aren't waiting to get paid for the things they make. Rather, they are being paid very up front for things that cannot be installed.
> Unlike the dot-com era, this is a bubble that everyone saw coming.
As far as I recall, the dot-com bubble was widely seen as such prior to it bursting. E.g. Greenspan and Buffet were both quite vocal about the irrationality of the values being assigned to companies.
The bet is that cost per intelligence will keep going down and demand for intelligence will grow at the same time, if this bet holds, a user could get the same or more done with a cheaper model (running-cost wise) while paying the same subscription and the lab gets improved margins.
Open source is a challenge but their current moat is the fact that they're ahead, and as long as they stay ahead they'll be able to charge a premium.
"AI use cases" is a moving target! If you try to define "use cases" by "what AIs today can be used to do", you miss things AIs would do in the future. The more capable and price-performant AIs get, the more there are places where AI has a role.
This is a big part of what the frontier buys you.
The other big part is that going from a local AI to a frontier model often makes the difference between "this use case works 60% of the time, good tech demo" and "this use case works 99% of the time, good business decision". The difference between "clunky and needs human in the loop" and "just works" is worth paying the API price.
This is the problem.
While the frontier labs will always have a market for AI that can do things the other models can't, if the sliver of work that can be done only by the frontier models is narrow enough, then what they spend to train those frontier models may not let them capture all that much extra revenue.
I absolutely think there will be a market for frontier models pushing further and further.
But it's not yet a given whether or not being ahead on capabilities is going to buy them all that much more higher earnings relative to lower tier providers.
If it stays the case that going from local AI to a frontier model makes the difference between 60% and 99%, then they probably will, but there's nothing to suggest local or open model, or second-tier closed models won't keep moving ahead as well, and eat away at the use cases where only a frontier model will do.
Do you think that we are anywhere near that point?
We've already seeing things - like what's happening with AI reverse engineering now. I'm a reverse engineer - and I know that the reason why RE was used as "last resort option" was that expert reverse engineers are rare, expensive, and work slow.
But now that a lot of RE workloads can be tackled by AI instead of a human? The demand for reverse engineering is at a never before seen high. AI made reverse engineering much more viable - and thus, a lot more reverse engineering is happening now.
There are myriads of fields like this - things that go overlooked not because no one wants them, but because the economics of human expertise make them nonviable in most cases. As AI gets better, it can begin to enter those fields.
Except you, of course, need to push the frontier to do it.
Much of humanity doesn’t think at all btw - that’s why they’ll never pay for these products and Google search had to be free.
Furthermore two things could be true a) market for frontier is large b) Anthropic still continues to generate net loss’s
What’s your goal here
Interesting. Are you an Anthropic investor?
And that, in turn, makes AI even more valuable if it can produce thinking on demand.
Researchers specifically were never highly paid. And positions were competitive - there were way more people willing and able to do those positions then positions themselves. Same goes for art btw.
I could be wrong, of course.
No, I don't. But for any given task there is a ceiling above which for that task there is no value in additional intelligence. E.g. it takes very little intelligence (none, in fact) to sort a list. More intelligence does not result in a more sorted list.
And so for a huge proportion of what we do there is a ceiling of value that can be extracted by selling AI tools to do any given task.
Combine that with there being at any given time a ceiling of available capital to be apportioned to buy intelligence to carry out the remaining tasks, and the floor of tasks that non-frontier models can do well enough rising, and there will at any given time be a finite amount of capital that will be accessible to frontier models.
It is by no means given that that slice of capital will grow rapidly enough for frontier providers to be able to create an attractive financial return. That depends on frontier labs being able to continue to deliver sufficiently more value than cheaper models at any given time that enough people won't simply wait.
I'm extremely bullish on AI in terms of its ability to transform society over time, but that does not automatically translate into assuming that the current frontier labs are a safe investment bet.
If "sort a list" becomes a trivial task, everything that was bottlenecked on "sort a list" is unbottlenecked, and other parts of the process become bottlenecks instead. Thus, the demand for non-sorting tasks grows. The saturation of low end feeds the value into the high end.
Sometimes it is. But that is also irrelevant. Replace "sort a list" with any given goal and the argument remains the same.
> The saturation of low end feeds the value into the high end.
But that process is not immediate. There's a reason I was careful to include "at any given time" in my comment.
For the purpose of whether or not a frontier lab is a good investment, it doesn't necessarily help them if there is an ever rising demand for intelligence if their market is eaten from below just as fast by cheaper models from competitors catching up.
It could be they manage to out-pace their competitors sufficiently that they will produce returns high enough to justify their valuations.
But irrespective of whether the demand for more and more intelligence continues to rise perpetually if 2nd tier labs hollows out the bottom of their market fast enough, it could equally be that most of the market ends up being low-margin, highly-competitive inference that won't justify their valuations.
Given the size of their valuations, even if they turn out to be tremendously profitable businesses, it's still not a given they'll give a good return on investment for investors getting in now.
I'm not saying they won't. I'm saying we can't easily judge that based on just assuming growth at the high end will continue without understanding what their moat is likely to look like.
Your assumption here is that the other parts of the process are intelligence. In the real world they usually are not e.g. raw materials, politics, zoning, manual labor, clinical trials, traffic, energy ... And usually those things are such huge bottlenecks that Amdahl's Law renders the speed of delivery of the intelligence part irrelavant.
There is no business model for competing companies to build forklifts that can lift an infinite amount.
That is not to say attempting to do so would not find new use cases for such powerful forklifts. The problem is the cost of building ever increasingly powerful forklifts while the TAM for that power shrinks.
You don't even have to bring in the enormous difference between forklift rusting theta vs gpu theta.
That it would be profitable if only there were no competition is not a really strong starting point for an IPO, though, is it?
So, yes, it's high risk - you're basically betting on who will be in the strongest position when one or more of the competitors are forced to slow spending and the rest are able to ease off on theirs as well as a consequence.
If you think either that Anthropic is in a strong enough position to come out on top or that we'll end up with a detente like with the big cloud providers where they big providers feel they have a strong enough position to beat off upstarts and collectively basically stop competing other than on the margins because they all know they'll earn more by protecting their margins than by internal competition, then the IPO might be worth putting money on.
I think the latter scenario is slightly lower risk, but still risky given how small the moat appears to be vs. the Chinese labs (I say this as I just had Kimi re-design a website in 10 minutes by just giving it the URL to the current one and tell it to replicate everything; they might not be as smart as the frontier models yet, but they're capable enough that they're taking over an increasing proportion of my token budget)
So they make a profit on each burger they sell you, but however they keep limiting how many they are willing to sell you?
Being ahead isn't much of a moat in a game where playing catch-up is significantly easier than being ahead. Also, how much ahead of Chinese labs are they at best? A year? Two? That's a moat for ants!
But profitable enough to justify the ludicrous valuation?
I think there will be a few forces driving prices lower if anything.
Everyone is currently looking at their spend on AI and the revenue growth for their own companies that this spend is not yielding.
I also think that if there is any competition, they won’t be able to lock in prices where they stand. Especially with open source models.
the problem is that they are not ahead. they are ahead on producing one-shot demos, which are useless party tricks, but when it comes to shipping real products these large models are just a big expensive waste of time and what you need is deterministic systems that integrate small efficient purpose built models in the places where they are actually the best solution for the problem.
the anthropic game plan was to wrap the entire software industry up in a magic box called "AI" and then rule the world but these people are delusional and their house of cards is rapidly collapsing. the technology is real, but they didn't invent it and they don't own it. it is kind of amazing to think of a $2T company with zero IP ... they didn't invent a single thing that they are selling, and for the most part they are implementing it worse, and serving it less efficiently than at least a half-dozen other competitors.
Hard to run local modals when sam altman continues to drive up the cost of compute.
These companies believe they're a year from AGI, and that's how they'll be profitable.
What I don't get is that if Company A is a year from AGI (I don't think that's true, but then again, I don't think anyone even has a good definition of AGI), then surely Companies B–ZZ are only a few years (at most!) from AGI as well. There is no moat. Or if there is a moat, the moat is hardware scarcity – but that's systemically outside of the control of these companies.
They have not actually demonstrated this, really.
In intrinsic valuation, the value of the operating assets is determined by ebit(1-t) - reinvestment.
Gross profit doesn’t mean a whole lot if a) your operating income is negative b) your reinvestment needs are mega. You have to make some interesting assumptions Re. Anthropic to get a 2T valuation.
I almost have to hold my nose reading finance posts on here.
I have just not read or listened to much of anything that the numbers work besides some science fiction fantasy on Dwarkesh podcast.
The gpu theta + the frontier model theta + token deflation creates this rolling window that I just don't see how it works given even the most bullish assumptions.
Maybe if the rolling window was expanding a rational argument could be made for the valuation. No one can say with a straight face the rolling window is expanding.
It is like competing biotech firms without patents working on the same drug but with these time decay parameters too.
> “I can’t let that bother me,” he said at the time. “I have to stay true to what I think is right.”
Monkey remains true to darts, dartboard.
A brilliant line from the movie Margin Call (a fictional portrait of the actual events of the 2008 crisis) that appears likely to get reused in upcoming AI bubble burst movies.
It's the first film JC Chandor ever directed, off what I understand to be his first feature-length film script.
Another great quote: "I run risk management... it just doesn't seem like a natural place to start cutting."
Yes, it's indeed likely those movies will be made entirely by AI.
They are a service company, selling home-grown, mass-produced, conveniently packaged intelligence at a well established price for consumer. Their API pricing might just be for value proposition and tax deduction purposes.
Every tech company, tech department, startup that I know is using claude code to deliver. The boutique deepseeks, qwens, glms and kimis are nice, but ain't production ready in 98% of cases. All the pi's, opencodes, etc are nice, but much less enterprise friendly. And google just outright sucks in comparison. There's a use case for each, but not at the scale Anthropic is doing.
Only real competition - OpenAI - is close, but they're burning money to stay there, which imo is unsustainable long term.
Is Anthropic worth $2T? Can't say. But boy they have a good opportunity to test this, and they may not have a similar chance in the future.
I think they have a fair chance at this.
With harnesses I see little difference between what Zed or Pi gives me and what Claude Code gives me. Enterprise features? The AI can help code those in a week.
AI itself is a great breaker of moats.
The question isn't whether they lead today. It's whether there's any kind of moat. Without a moat, frontier model development is an industry like chip fabrication or large volume manufacturing. Those industries are a red queen's race where if you stop innovating for even a short while you sink. Ask Intel what happened when they decided to coast for a few years.
Chip fabs and bulk manufacturers make a lot of money, sure, but they don't command such a multiple. Anthropic is priced like they're going to be to AI what Google was to web search or Apple is to (US at least) mobile and higher-end PCs.
I don't see it. I think they'll be a big player but that big?
Of course... maybe if they suddenly have that much cash they'll be able to carpet bomb the entire world with AI doom Rationalist ideology and buy their regulatory capture and outlaw their competition.
I've seen firsthand attempts at integrating open source in place of it and they all failed. Time is money and it costs premium. Touching the ground running is a huge advantage. That's why cloud services stuck.
Simple reasons being no nonsense nanny refusals & it's cheap/good enough to get the everyday production parts done fast and reliably for next to nothing. Your experience is not what I see at all, but İ don't work with megacorps or in the Valley anymore, so it's possible those powers will carry the weight to some extent, until they won't or can't.
So, we go from an existential threat to basically unprofitable business. I can only see Amodei and Altman just as the next Holmes.
So whatever your stance on Anthropic this particular analysis is safe to ignore.
I like to think you can enjoy the ride wave as you are propped above the heads of an hysterical crowd, as they rush to the abyss...Just find some solid tree branch you can latch on, when they realize where the road ends.
This is essentially just what people say when current reality is different from what they want it to be. Sort of an unfalsifiable escape hatch response to “well observable reality contradicts your claim”
In the long term, in theory, prices should be tied to value, most most of the time the stock market plays more like a casino.
…which, in a normal sane world, would affect the stock price?
2 trillion is a lot. I’m skeptical, for the same reasons listed in the report.
Its has nothing to do with Dario, and mostly to do with Chinese open weight models.
I feel like that statement is one of mans' biggest foot-guns in the modern world.
that single sentence has driven the biggest hucksters the world has known to commit the biggest frauds ever perpetrated against man for decades.
In fact track record is perhaps one of the most important things of all when deciding wherever to even engage with the argument in the first.
Ironic given this article is from CNBC, employer of Cramer, host of "Mad Money", who has been so inconsistently wrong that his picks have literally sparked an ETF. Just search using your engine of choice "Inverse Cramer ETF".
I work in finance. Past performance is not a guarantee of future returns, but is a damn good indicator, which is why everyone always wants to see your past performance anyways.
Unless it's about stock picking, when the winners in one year of doing good stock picking are no better in the next than any other random stock picker.
Of course both had too short a lifetime to draw a conclusion due to lack of interest and this was pre-AI so maintaining the positions was difficult. But it’s important to remember that Jim Cramer fails to beat the market, not that he’s an inverse oracle.
All the mayor AI players have to rent/buy a lot of computing power to serve their customers. We're talking costs of 2-5x (or 10x? does anyone actually know?) their revenue. The question is, will they ever be able to pay their cost of revenue and operating expenses? Many people doubt. And we know that they do all sorts of funny book keeping shenanigans like SPVs and delayed deprecation.
What comes on top is, LLMs have no economy of scale. More customers scale linear with higher costs. Will people or companies be willing to pay 5x what they're paying now? Will future frontier models become more cost efficient or less? We simply don't know yet. At this point, it's a gamble.
Wut? I'm pretty sure SpaceX spends a lot of money shooting rockets into space, and Cloudflare has pretty high infrastructure costs given that a very large portion of all Internet traffic goes through their networks.
SpaceX is an entirely unique thing, I don't really know what to think of it. I don't see a viable business model there, but I might be wrong. Maybe there is trillions to make in space. Their targets are long shots, but meanwhile they are bleeding money on all their ventures and they ride on the AI wave. The IPO was fairly recent and it might still just implode one day.
You're discussing something entirely different, which is fine, but you're not refuting anything that the parent poster said.
All they were saying is that they're terrible at predicting risk. Examples were given. It doesn't matter why they're bad at predicting risk, they simply are.
Every time I see Anthropic and other AI companies getting ready to go public, I cannot stop thinking about the entire Enron debacle and all of their "unique" book keeping shenanigans that has far reaching impact, even to this day.
People keep telling me, "Nah this is totally different man, you can't compare the two!" But is it really??
Math ain't looking pretty. Just like it did not look pretty with WeWork. Might have worked, but still not great business to be in.
Being hyperscaler really does look very high capital and questionable margin bussiness at moment. With lot of competition.
In general, the stock market is in a somewhat weird place because most people in the US who have some money just don't have anything else to do with it. It's not a productive suggestion to keep it in savings or treasuries, we don't invest in friends' businesses because we don't have friends, real estate is too expensive, we don't collect art or antiques because that's for old people... so YOLO in the stock market it is.
So yeah, I don't think it's wrong to criticize the Anthropic IPO as nearly impossible to justify by anything other than vague hopes and dreams. But that doesn't mean it won't make you money.
Also known as a broken clock being right two times a day.
The fallacy is assuming ahead of time that they are actually right this time.
If you start assuming they’re right and also admit that their logic doesn’t support that conclusion, there isn’t even any argument left. You’re just implying that you believe one thing is true and anyone who agrees with you, regardless of the reason, is also correct.
I don’t find that persuasive in any way.
Friends businesses don't need our money, because banks are generous with giving out loans and friends prefer to keep ownership intact while being in debt instead of diluting it.
Anthropic IPO prospectus shows AI vision, surging costs
https://news.ycombinator.com/item?id=49886005
None of this sounds credible.
Anthropic raises money from IPO -> How long will that sustain them given the immense cash burn? Forget about gross profit - that's the number they want you to focus on and can be played with. Keep the focus on the cashflows -> if a firm runs out of money its over, who cares what your revenues and gross margins are. We are not talking Amazon level loss's which were paltry AND they were able to raise more than enough to keep going for awhile.
Management of firms who pay rent to LLM models need to reign in costs -> they will use a bundle of chinese +american models (this is already happening look at the data) -> affecting revenues, earnings and cash flows of frontier labs. Given the losses in absolute terms, any stunting of the growth rate would be catastrophic for the story re. valuation.
The frontier model story rests on one giant assumption: lay-offs must happen en masse at some point. It's not happening and in my view won't happen - there simply isn't enough trust. Moreover, do you think firms are going to trust these model providers, given its in their interest to steal IP? lol
Not rocket science mate.
First, a lot of usage can switch to open models (like is happening, I agree), and yet frontier model usage can still grow (like is happening). As long as the market for frontier level intelligence keeps growing, the cost of frontier intelligence is marginally profitable to the user, and the open weight models don’t catch up, I don’t see any reason for frontier level usage to fall. Indeed, we haven’t seen any of that so far, despite the rise in open weight usage. My own product has started using open weight models, but my usage of frontier models also continues to grow, because they keep unlocking new capabilities. Maybe that’ll end, but I’m skeptical. I think the problem space that can benefit from the best intelligence money can buy is unbounded.
Plus the labs can still offer cheap non-frontier models to compete with the open weight models (like Luna and Haiku), and they have a massive advantage in terms of available compute.
Secondly, I don’t think that the big labs need mass layoffs to justify their valuation. That’s perhaps one path, but in my view a more likely one is that we get greater increases in productivity and economic growth, and they capture a large share of that. If global GDP grows 2% faster than it otherwise would over the next decade, that’s an extra $175 trillion in economic value created over the next decade. If it grows 5% above baseline growth, it’s half a quadrillion. GDP in 2036 would be more than $100T higher per year than today. AI companies don’t have to capture very much of that to justify a $2T valuation.
Now, will any of that happen? Who knows, it’s definitely unrealistic and unprecedented, but then again, so is much of what I see happening in the world today. Time will tell.
Most "news" is just a dramatized press release these days. The conditioning of the public to viewing media as authority creates a mental trap where you're told something is important/credible, despite having zero hallmarks of credibility. And we perpetuate this because it's familiar, not correct or accurate.
This is exactly why humanity continues to stumble, despite centuries of evidence as to what doesn't work. We just can't accept that most of what we tell ourselves is reality is just a for-profit (or for-influence) product that masquerades as knowledge or important information.
New findings reveal AI bubble worries are justified: https://www.youtube.com/shorts/xCzCyPoI-eA
I think it's a little early to make that statement. Could be. But at this point I think things like printing press, agriculture, writing ... they're all many times more significant.
Now, obviously all these things built on each other, so comparing them like this is a little silly, but in my view, inventing AI is essentially inventing an inventor of fantastical things on par (and beyond) the greatest inventions of humanity, including the ability to self-improve.
To be clear, I don’t think today’s LLMs are there yet, and I take no position on whether they’re a dead end, but in my view ASI has no fundamental barriers that cannot be overcome in time.
Depends on your perspective, but that's definitely true if you're selfish and have been paying people for intellectual labor. Lots of layoffs to fantasize about (even though that represents vast amounts of pain and destruction for many people).
Is it true growth, or circular dealing plus hype? I have little doubt the IPO is nothing but a wealth transfer from retail investors who'll be left holding an empty bag.
As far as I know the circular deal fears are more around the chip purchasing agreements, because there is a speculative component to building out datacenters for training which may not produce models that are worth the training cost, but the revenue from inference is real and it has truly grown a lot over the past two years.
Is a hypothetical, but is one that's an even higher risk factor for investors.
https://ir.nasdaq.com/news-releases/news-release-details/nas...
The benefits of replacing all human payroll will go to AI companies as a whole. AI companies as a whole != Anthropic.
As the article points out, the greatest threat to closed models like Anthropic's comes from cheap open source models. Not from the possibility that AI won't be successful at replacing payroll.
Cancer. Burkitt Lymphoma takes a couple of days to double in size.
It’s important to understand that infinite growth inside a finite system is impossible. At some point growth has to stop, either by eliminating the growing organism or it killing the host.
Induced demand and limitless cheap human-quality labor can possibly grow the pie very fast, though even then, you start running into the earth’s finite resources eventually. But it is possible that they are worth much more than $2 trillion long before that.
But that is why I said you can’t just safely assume 15x multiples to continue.
I mean, compared to the desired IPO valuation in the trillions, it certainly deserves the "mere" description, but still...
(I think 2 trillion dollars is an absurd valuation for a product with such hot competition and low switching cost, but if you make the case that Anthropic is losing money based on the 2025 numbers from that Reuters report you're being farcical.)
UODATE: I found the actual New Horizons report here - it does acknowledge the 2026 numbers, unlike the linked CNBC story about that report: https://www.newconstructs.com/anthropic-is-the-most-ridiculo...
Anthropic claimed to be profitable if you dont count some of their largest expenses (like model training). Not the sort of profitable where revenue actually exceeds total expenses
"Anthropic still hasn’t made its prospectus public, so New Constructs hasn’t seen the actual filing. However, the firm cited figures that have been reported, including from the New York Times, which reported in September that the company was on pace to generate $100 billion in annualized revenue by the end of 2026."
Anthropic's annualized revenue run rate reached $65 billion at the end of July 2026, up from just over $5 billion in August 2025 (Anthropic, CNBC) Anthropic made nearly $4.6 billion in revenue in 2025, 12x more than in 2024 (IPO prospectus, via Reuters, September 2026) Anthropic's preliminary Q2 2026 revenue was more than $11.5 billion, ahead of OpenAI's $6.7 billion (Bloomberg and The Wall Street Journal, August 2026)
https://explodingtopics.com/blog/anthropic-revenue
So, the Q2 revenue was $11.5 billion. The claimed $65 billions are "annualized revenue run rate". Please show me where that term is defined reliably. It's a BS marketing term to obfuscate real revenue after the tokenmaxxing hype has ended.
That according to "a person familiar with the matter" aka an anonymous source. From https://www.reuters.com/commentary/breakingviews/anthropic-g...
They could have cleared it up, could they not? But silence is more expedient when attempting the most fraudulent IPO of all times.