New Constructs is bearish on every tech IPO. Easy to reinforce your bias by selectively looking at instances where they were right, like WeWork, 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.
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.
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.
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.
> 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 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.
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 define good or bad research, based on my time horizon and the time-value-of-money. For example its irrelevant for me how much money Tesla makes, since I judge there only two possible outcomes for the company: bankruptcy or assimilation.
the peak of tulip mania was in 1637, people who invested in 1636 and got out in early 1637 would probably have made good money.
I believe the analogy here is that investing in the Tesla IPO would have made a lot of money, yes, but at some point in a future implied to be not so far off, staying in Tesla should lead to losing all that money.
I sort of feel like that will probably prove to be true. Was it a bad idea to invest in the IPO, no, but it wasn't a bad idea to invest in tulips either, until it became a very bad idea.
"The company’s growing operating losses" - yeah, if you are 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.)
"The company grew revenue twelvefold in 2025 to ~$4.6 billion. According to the New York Times, Anthropic is on pace to generate $100 billion in annualized revenue by the end of 2026."
It does lean into those 2025 figures when talking about Anthropic's losses though, which is weird when Anthropic have supposedly claimed two profitable quarters in 2026.
> 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
$2 trillion is a lot of money and certainly doesn’t seem a safe bet at that price. But also, their revenue went from <$0 in 2024 to $4b in 2025 to what will likely be >15x that in 2026. Has anything ever grown that fast before?
If you carry that forward even one year, and I’m not saying you certainly can, they’re outselling NVIDIA.
I get it, there are risks, scalability issues, low cost competitors, etc. $2 trillion is a big number, but it’s tiny compared to all human payroll.
I’m not buying it either but I dont think anyone who does failed an IQ test.
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.
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.
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’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).
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.
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.
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)
> 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.
It's a sort of weird chicken game in that there's a meta-chicken game going on too — they are both, sort of separately, betting that the outcome of their chicken game will be too devastating for the US economy for it to be allowed to happen.
(I say "sort of separately". But the one guy used to work for the other guy. You know how people who split up from partners spend the next few years trying to shake their ex-partner's framing of the world? They know each other's thinking; they are aligned where this meta-chicken game is concerned)
They don't need it to actually be devastating. They just need sufficient fear of it.
Especially if it is finely calibrated enough that they get to continue at a slower pace, but end up with enough expensive red tape to slow down upstart competition more because of high compliance costs.
If they can't beat OpenAI etc., the second best is to near-freeze market shares in place at a lower rate of investment - hence my comparison to cloud providers where none of the big providers makes too large reductions in prices etc. because they all know they'll all lose on a price war.
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.
> 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.
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.
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.
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.
Except that’s simply not how it works. Companies just have one forklift. Yes it’s too much for most use cases but you don’t have a garage full of different sized forklifts. There’s a big cost to keeping all these extra forklifts on standby.
Models, however, are completely interchangeable on demand. That’s why companies are building these realtime internal marketplaces to route tokens to different models. Anthropic may win the occasional “bleeding edge” use case but the money is in the day to day use cases that get routed to the cheap-but-works options. There’s zero cost to having all the forklift sizes at your disposal and only using the size needed when it’s truly needed.
Anthropic is trying to sell the biggest baddest forklift in a world where companies can swap out cheaper ones easily and on demand. Hence why Anthropic doesn’t appear to have a viable business model in its current form.
The biggest, baddest forklift in the world is a crane.
And crane, despite being bigger, more powerful and more awesome (they lift skyscrapers and do things nothing else can do), the Forklift is actually more useful to more people.
I think the argument carries solid weight. Making bigger and better things doesn't necessarily lead to bigger and better businesses.
Limiting usage on heavily subsidized subscription plans is not the same as cutting access to their models. Switch to API billing and you can have as many tokens as you want. In fact their salespeople will aggressively try to sell you more.
> 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!
The vc’s have to be allowed to cash out - so that money remains a strategic weapon for US venture funds over any other nation re. Funding startups in future - esp capital intensive.
The valuation is a joke but they will be allowed to go on and cash out - just like the investors of spacex.
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?
> 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.
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?
> 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.
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.
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).
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.
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.
> 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.
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.
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
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 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.
“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.
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.
“Now trades well above the IPO valuation” does not mean something would have been a good investment at the IPO price given opportunity cost and the time value of money. Additionally, the current price could equally not represent good value.
I suspect SpaceX is going to be the opposite of what will happen with Anthropic. With SpaceX I think the overwhelming majority of people didn't initially understand what Starship is, how far along it is, or what it even means in terms of its impact on the pathway of getting humans to be a multiplanetary species. So it was greatly undervalued and zoomed upward.
With Anthropic I think a lot of people haven't really realized the trend line of cost of "AI" (both in literal $ terms, and compute costs for local operation) or what open weight systems will do to the market in the "long run", where long run in this case means the next year or two. I don't think any LLM company is going to come out a winner in the longrun, because the price for LLM output is going to approach $0 with no chance for a moat whatsoever.
> the overwhelming majority of people didn't initially understand what Starship is, how far along it is, or what it even means ... So it was greatly undervalued
I don't think anyone was undervaluing the "space" segment of SpaceX. It's the clear leader in launch frequency and cost-to-orbit among the new wave of space firms, and shows no sign of losing that position.
Where the IPO raised a bunch of red flags was SpaceX suddenly acquiring Elon's AI firm, which had a significantly more nebulous basis for its valuation...
> the pathway of getting humans to be a multiplanetary species
I am afraid that you're suffering from Flavor-Aid poisoning here. We need a reality check about "multiplanetary colonization".
I've been following human spaceflight since I was born. I've actually participated in robotic spaceflight. And I'm here to say that it is robots who are destined to be a multiplanetary species. The robots have already successfully escaped our solar system and extensively explored the Moon, Mars, and elsewhere.
Many unscientific people believe that it's harder to colonize the Moon or Mars because they are farther than Africa or Rio de Janeiro is from Rome. But mere distance is not really your biggest obstacle.
I've also been following the ISS since its inception, and they have empirically disproven the feasibility of colonizing planets. If we succeed in establishing a crewed Moon base, it will be an ultra-Herculean effort, and it's on the edge of feasibility.
But Mars? Venus? Asteroids? Europa? You really think humans are going to live there?
The reasons that ISS has disproven this are manifold, but I'll point out two key points:
Their supply-chain is only about 8-48 hours, and they can stash large amounts of provisions up there. Their escape route is also only 8 hours and they're back on Earth in a jiffy. None of this is true for any body outside of Earth orbit. The Apollo missions arrived on the Moon and returned safely, by burning, jettisoning, consuming, and abandoning nearly everything they started with!!
A 15th-century expedition to Africa or Brazil means that you can fish in the ocean, breathe the air, drink rainwater along the way. An expedition to the Moon puts you in an airtight bubble with no stops, no rescue, no resupply, and most importantly, no breathing on the way, nor once you get there.
The ISS has also demonstrated the severe toll on the human physique in microgravity conditions. Watch astronauts who land or splash down. They are carted off in gurneys. They are literally unable to walk unassisted. NASA restricts returnees from driving or even jogging. The astronauts describe having to "relearn gravity" activities like brushing your teeth and showering. Any astronaut arriving on Mars would be as helpless as a toddler! Do you want to colonize Mars with toddlers? Because all the treadmills and workouts along the way won't make them fit for purpose on arrival.
So between here and Mars it's minimum six months, no escape, no rescues, no takey-backsies. We could send humans to Mars if we didn't want them to survive or return. I mean, no problem. There's no air to breathe on Mars; no water to drink; no fuel to burn; no fish to fish nor deer to hunt; no steel to build a shelter. You pack it all into the spacecraft, newbie?
But NASA and the rest of the world has amply demonstrated just how capable robots are where humans fail. Robots are going to inherit the solar system. Robots are in 2026, the de facto interplanetary species, sine qua non. My heart is warmed by these human achievements. I, for one, am happy to live and die on Earth. I think that every American should be grateful for Earth, and not permit our oligarchs to cheat and lie to us with fairytales of escaping our Earth.
We're not escaping Earth nor seeking to replace it. The entire idea of becoming a multiplanetary species is exactly that. Ostensibly we all started in Africa, and plenty of us are still in Africa. The same will be true on a planetary level, and eventually on a star system level. You said a lot and I don't want this to turn into a wall of zig-zagging tit for tat nonsense, so I just want to speak briefly and holistically. The first missions to Mars will be fully dependent upon supplies we're bringing. The goal of self sustainability is aspirational and long-term. At best it will take decades. In reality, it may never happen much in the same way that no country in the world today is fully self sustainable in practice, even if many could be in theory.
The whole point of the extended stays in LEO are precisely to simulate worse case scenarios for travel to Mars. So for instance the record for the longest time in space is held by Valeri Polyakov. [1] He spent 437 days on Mir in LEO, and then opted to immediately walk upon landing back on Earth. It was all to prove that humans would be physically capable of working on Mars (which has 1/3rd the gravity of Earth) even after absurdly long periods of time in space. In fact his first words upon return from his first (240 day) stay in space were "We can fly to Mars."
Robotics don't really work well for space exploration, because moving parts break. For instance the Curiosity/Perseverance drills are cutting edge yet have a max depth of ~2.7 inches. And traveling is even harder. On average Curiosity ended up traveling about 1 mile per year. It's all because if anything breaks, that's game over. So everything has to be done with the utmost of caution, and even then stuff constantly breaks. Curiosity's drill broke after about a dozen activations and required a team of scientists and months of full-time work to create a passable work-around when it could have viably been fixed on the ground by a human in a few moments.
This is part of the reason that we only learned in 2013 that the soil/regolith on Mars is actually extremely moist, 2-5% water by volume. A cubic foot of soil heated up gets you about 2 pints, a liter, of water. The whole plot-line in "The Martian" about having to jump through hoops to get water was correct based on the latest knowledge when the book was written in 2011. We'll probably learn more in a couple of weeks with people on Mars than we have with 60 years of probes and rovers.
I'm certain every human of sound mind is grateful for Earth. That's not a reason to not seek to expand out as far and as wide as we can.
The whole caring oh so much about humanity simply doesn't pass the smell test for me. I don't want to go into details and individuals, but I just don't buy it; what I do buy is wanting to get a foot into space to get even more leverage over the humans on Earth, and not for our benefit. That actually fits their actions and their aura, so to speak. But "preserving the light of human consciousness" and such? Now I know it's a scam and an agenda. And the more flowery the language, the more sinister I expect the actual designs to be.
There is one core reason that Machiavellianism is naive. It's because the grand long-term ends people seek to create with all of their sinister deeds in the short-run rarely ever comes to pass. Yet all those sinister deeds absolutely do come to pass and are what we all get to live through.
So the most well intentioned person doing awful things? In my mind he's an awful person. But this also goes the other way as well. Imagine you're right, and the idea of getting humans into space is some elaborate scheme to somehow get more leverage over humanity. Awesome! Because it's highly unlikely such schemes will come to pass in any sort of remotely realistic way, but we'll be left with the means of humans actually meaningfully expanding into space.
I'd love to see as sharp increase in the number of evil people plotting to do good things to further their evil ends. All the 'good' people doing evil deeds in the name of some grand end that never happens is quite tiresome.
I fully agree with your points: the hard, unyielding reality which most Trekkie fanatics refuse to acknowledge, except for one: "severe toll on the human physique in microgravity conditions."
That's easily fixed!
Spinning a space station for gravity is straightforward, it's just that the ISS wasn't designed for it, and NASA didn't have the budget to build a second, bigger space station with "extra engineering challenges" on top.
It's definitely practical though, it's just a matter of launching enough mass to orbit.
Like you said, Starship is going to change a lot of things, starting with space station design.
Yeah, I mean, I get that the spinning has long been a viable proposition. Perhaps if we send a spinning expedition to Mars, the astronauts won't be toddlers when they arrive on a barren, hostile, resource-free world. Yet, that is a lot of extra mass; that is non-zero extra fuel; that is a lot of extra "stuff goes wrong" risk inherent in that design.
But it's unprecedented, untried, and not currently in any pipeline, AFAIK. I believe there were a few experimental spinning crewed flights, during the original Space Race. But does Starship spin and simulate gravity? Is there any crewed spinning spacecraft extant, in production, or even being designed?
They don't need to spin their way to the Moon, so it would be unlikely that any Artemis or future crewed Moon mission spins at all. But if spinning our way to Mars will solve an otherwise intractable set of problems, I suppose we'd better get started on proving it.
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.
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.
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.
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
Yes, they have the same problem WeWork had on the multiple front. Coworking was a thing long before WeWork was a thing. It’s an important but boring business that trades at low multiples. WeWork tried to IPO on the basis that somehow it was worth vastly more, but the market woke up and realized it’s just subleasing office space.
The same is unfolding with Anthropic. It’s doing important work but everyone is realizing it’s not got a serious edge over anyone else. It’s important but ultimately a boring business. It’s still likely worth a few hundred billion, which is massively impressive for any startup, but trillions is pipe dream.
The thing that makes the frontier labs frontier is mostly access to huge amounts of training data and compute. In the earlier days of AI access to top AI talent was a moat, but that moat is rapidly eroding as more and more people familiarize themselves with the "black magic" of LLMs and training. The success of the Chinese models is evidence of this diffusion of knowledge.
Give me a team of, say, 20 good engineers with a deep knowledge of AI/LLMs and training and give me a billion dollars worth of GPU compute and a huge amount of training data and I'll give you a frontier model.
New Constructs is bearish on every tech IPO. Easy to reinforce your bias by selectively looking at instances where they were right, like WeWork, 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.
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.
Criticize the argument, not the speaker.
Track record is extremely relevant when the "argument" is mostly about judgement and subjective opinions.
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.
Part of their argument is, "Look how reliable the speaker is."
TFA does not contain an argument beyond reporting on the statement
Their track record is directly relevant.
Right, if you are in the business of predicting the future your track record of past predictions is extremely relevant.
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
So is Anthropic's. You'd have to be ludicrously gullible to buy 1/4 of the shit Dario says as true
Sure, but is that a negative for the stock price?
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.
Exactly. If everyone else is gullible, it’s a good buy!
No, but is it much of a stretch to say that the valuation and profit/loss are out of proportion?
…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.
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.
> 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 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.
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 define good or bad research, based on my time horizon and the time-value-of-money. For example its irrelevant for me how much money Tesla makes, since I judge there only two possible outcomes for the company: bankruptcy or assimilation.
So would you consider putting money into the Tesla IPO a bad investment?
Would you consider putting money into Tulips in Amsterdam on Feb 1636 ?
No, because people who did so lost money. Now answer my question.
the peak of tulip mania was in 1637, people who invested in 1636 and got out in early 1637 would probably have made good money.
I believe the analogy here is that investing in the Tesla IPO would have made a lot of money, yes, but at some point in a future implied to be not so far off, staying in Tesla should lead to losing all that money.
I sort of feel like that will probably prove to be true. Was it a bad idea to invest in the IPO, no, but it wasn't a bad idea to invest in tulips either, until it became a very bad idea.
Tesla is up 29,644% since IPO 16 years ago. Where is the argument exactly?
Every company in existence is likely going to 0 at some point in its life. So then what is a good investment?
One which produces an income. Otherwise it's speculating, not investing.
I just did
"The company’s growing operating losses" - yeah, if you are 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.)
UPDATE: 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...
"The company grew revenue twelvefold in 2025 to ~$4.6 billion. According to the New York Times, Anthropic is on pace to generate $100 billion in annualized revenue by the end of 2026."
It does lean into those 2025 figures when talking about Anthropic's losses though, which is weird when Anthropic have supposedly claimed two profitable quarters in 2026.
> 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
$2 trillion is a lot of money and certainly doesn’t seem a safe bet at that price. But also, their revenue went from <$0 in 2024 to $4b in 2025 to what will likely be >15x that in 2026. Has anything ever grown that fast before?
If you carry that forward even one year, and I’m not saying you certainly can, they’re outselling NVIDIA.
I get it, there are risks, scalability issues, low cost competitors, etc. $2 trillion is a big number, but it’s tiny compared to all human payroll.
I’m not buying it either but I dont think anyone who does failed an IQ test.
> Has anything ever grown that fast before?
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.
With the NASDAQ rule change, even more so.
https://ir.nasdaq.com/news-releases/news-release-details/nas...
> it’s tiny compared to all human payroll
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.
> Has anything ever grown that fast before?
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.
If you don't need ROI then with this kind of money I can make revenue grow even faster.
I’m buying, this is the greatest invention of all time and Anthropic has garnered a pretty solid lead right now.
> this is the greatest invention of all time
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’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).
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.
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.
> it's the fact that they have to train the next iteration right away due to competition
That it would be profitable if only there were no competition is not a really strong starting point for an IPO, though, is it?
(It is, however, the winner-takes-all world view Anthropic still seems to operate with)
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)
> 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.
It's a sort of weird chicken game in that there's a meta-chicken game going on too — they are both, sort of separately, betting that the outcome of their chicken game will be too devastating for the US economy for it to be allowed to happen.
(I say "sort of separately". But the one guy used to work for the other guy. You know how people who split up from partners spend the next few years trying to shake their ex-partner's framing of the world? They know each other's thinking; they are aligned where this meta-chicken game is concerned)
They don't need it to actually be devastating. They just need sufficient fear of it.
Especially if it is finely calibrated enough that they get to continue at a slower pace, but end up with enough expensive red tape to slow down upstart competition more because of high compliance costs.
If they can't beat OpenAI etc., the second best is to near-freeze market shares in place at a lower rate of investment - hence my comparison to cloud providers where none of the big providers makes too large reductions in prices etc. because they all know they'll all lose on a price war.
> 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
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 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.
> 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.
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.
I could be wrong, of course.
This is insanely delusional.
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
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.
So delusional you had to hide behind a throwaway
What’s your goal here
Oh so people who recently sign up = throwaway
Interesting. Are you an Anthropic investor?
The forklift analogy proves the opposite point.
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.
Except that’s simply not how it works. Companies just have one forklift. Yes it’s too much for most use cases but you don’t have a garage full of different sized forklifts. There’s a big cost to keeping all these extra forklifts on standby.
Models, however, are completely interchangeable on demand. That’s why companies are building these realtime internal marketplaces to route tokens to different models. Anthropic may win the occasional “bleeding edge” use case but the money is in the day to day use cases that get routed to the cheap-but-works options. There’s zero cost to having all the forklift sizes at your disposal and only using the size needed when it’s truly needed.
Anthropic is trying to sell the biggest baddest forklift in a world where companies can swap out cheaper ones easily and on demand. Hence why Anthropic doesn’t appear to have a viable business model in its current form.
The biggest, baddest forklift in the world is a crane.
And crane, despite being bigger, more powerful and more awesome (they lift skyscrapers and do things nothing else can do), the Forklift is actually more useful to more people.
I think the argument carries solid weight. Making bigger and better things doesn't necessarily lead to bigger and better businesses.
No doubt that if they wanted to they could be profitable.
But profitable enough to justify the ludicrous valuation?
>> Their inference margins are already high
So they make a profit on each burger they sell you, but however they keep limiting how many they are willing to sell you?
Only in this analogy it also takes years and lots of money to train the people flipping them, and they would like their investors not to notice that.
How are they limiting it?
https://www.bleepingcomputer.com/news/artificial-intelligenc...
https://explainx.ai/blog/anthropic-claude-code-limits-17-per...
Limiting usage on heavily subsidized subscription plans is not the same as cutting access to their models. Switch to API billing and you can have as many tokens as you want. In fact their salespeople will aggressively try to sell you more.
Sounds like the trick of restaurants with cheap food, and expensive wine ;-) I dont drink alcohol and dont date anymore...
> 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!
They don’t care if they get to sell more equity.
This. The product is the stock, the tech is the fomo theater to sell the product.
It’s even more sinister.
The vc’s have to be allowed to cash out - so that money remains a strategic weapon for US venture funds over any other nation re. Funding startups in future - esp capital intensive.
The valuation is a joke but they will be allowed to go on and cash out - just like the investors of spacex.
Open source is what has given them all their coding ability.
If the models get good enough, the demand for them will soar.
These companies believe they're a year from AGI, and that's how they'll be profitable.
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?
> 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.
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?
Agree with you overall, but:
> 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.
Interesting take. How high is that probability within the next five years, do you think?
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.
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).
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.
Most here need a finance lesson.
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.
> inference - which is profitable in isolation
They have not actually demonstrated this, really.
Question is really how many companies will stay due to inertia while competition catches up
You're of course speaking of a world that doesn't manipulate the cost of memory.
Hard to run local modals when sam altman continues to drive up the cost of compute.
Open source doesn't have the compute to meaningfully hurt them.
BullSHIT.
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.
Yep, system working as intended.
> In an interview with CNBC in 2021, Trainer acknowledged that “crazy stuff happens” and New Constructs doesn’t always get it right.
> “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.
> 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.
I posted other (different) research into the IPO yesterday: https://news.ycombinator.com/item?id=50033644
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.
I will be waiting 1-2 weeks prior to opening a short position.
At least one person in this thread is putting their money where their mouth is
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.
None of this sounds credible.
It's pretty clear actually.
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.
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 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.
Shouldn’t we wait until the S-1 is officially released before jumping to conclusions? Currently the financial data we have is based on leaks.
..."a mere $150 billion"
I mean, compared to the desired IPO valuation in the trillions, it certainly deserves the "mere" description, but still...
Not easy for humans to understand the power of AI transformation
“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.
"In the history of… <pregnant pause> capitalism"
That whole scene is absolutely full of perfect observations; I refer to it often in different contexts.
It's the first film JC Chandor ever directed, from 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."
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.
“Now trades well above the IPO valuation” does not mean something would have been a good investment at the IPO price given opportunity cost and the time value of money. Additionally, the current price could equally not represent good value.
Yeah. Look at SpaceX. Dropped to $108 from an Ipo price of $135, but it's currently at $162 which is... fine?
While I think SpaceX is still horribly over-valued they at least have a diverse line of businesses that are very hard to copy.
Anthropic is a one trick pony and the world is discovering lots of other cheap ponies that do the same trick.
I suspect SpaceX is going to be the opposite of what will happen with Anthropic. With SpaceX I think the overwhelming majority of people didn't initially understand what Starship is, how far along it is, or what it even means in terms of its impact on the pathway of getting humans to be a multiplanetary species. So it was greatly undervalued and zoomed upward.
With Anthropic I think a lot of people haven't really realized the trend line of cost of "AI" (both in literal $ terms, and compute costs for local operation) or what open weight systems will do to the market in the "long run", where long run in this case means the next year or two. I don't think any LLM company is going to come out a winner in the longrun, because the price for LLM output is going to approach $0 with no chance for a moat whatsoever.
> the overwhelming majority of people didn't initially understand what Starship is, how far along it is, or what it even means ... So it was greatly undervalued
I don't think anyone was undervaluing the "space" segment of SpaceX. It's the clear leader in launch frequency and cost-to-orbit among the new wave of space firms, and shows no sign of losing that position.
Where the IPO raised a bunch of red flags was SpaceX suddenly acquiring Elon's AI firm, which had a significantly more nebulous basis for its valuation...
> pathway of getting humans to be a multiplanetary species.
We must send our best people to represent Earth. Lets send a trillionaire and the next 300 richest billionaires.
> the pathway of getting humans to be a multiplanetary species
I am afraid that you're suffering from Flavor-Aid poisoning here. We need a reality check about "multiplanetary colonization".
I've been following human spaceflight since I was born. I've actually participated in robotic spaceflight. And I'm here to say that it is robots who are destined to be a multiplanetary species. The robots have already successfully escaped our solar system and extensively explored the Moon, Mars, and elsewhere.
Many unscientific people believe that it's harder to colonize the Moon or Mars because they are farther than Africa or Rio de Janeiro is from Rome. But mere distance is not really your biggest obstacle.
I've also been following the ISS since its inception, and they have empirically disproven the feasibility of colonizing planets. If we succeed in establishing a crewed Moon base, it will be an ultra-Herculean effort, and it's on the edge of feasibility.
But Mars? Venus? Asteroids? Europa? You really think humans are going to live there?
The reasons that ISS has disproven this are manifold, but I'll point out two key points:
Their supply-chain is only about 8-48 hours, and they can stash large amounts of provisions up there. Their escape route is also only 8 hours and they're back on Earth in a jiffy. None of this is true for any body outside of Earth orbit. The Apollo missions arrived on the Moon and returned safely, by burning, jettisoning, consuming, and abandoning nearly everything they started with!!
A 15th-century expedition to Africa or Brazil means that you can fish in the ocean, breathe the air, drink rainwater along the way. An expedition to the Moon puts you in an airtight bubble with no stops, no rescue, no resupply, and most importantly, no breathing on the way, nor once you get there.
The ISS has also demonstrated the severe toll on the human physique in microgravity conditions. Watch astronauts who land or splash down. They are carted off in gurneys. They are literally unable to walk unassisted. NASA restricts returnees from driving or even jogging. The astronauts describe having to "relearn gravity" activities like brushing your teeth and showering. Any astronaut arriving on Mars would be as helpless as a toddler! Do you want to colonize Mars with toddlers? Because all the treadmills and workouts along the way won't make them fit for purpose on arrival.
So between here and Mars it's minimum six months, no escape, no rescues, no takey-backsies. We could send humans to Mars if we didn't want them to survive or return. I mean, no problem. There's no air to breathe on Mars; no water to drink; no fuel to burn; no fish to fish nor deer to hunt; no steel to build a shelter. You pack it all into the spacecraft, newbie?
But NASA and the rest of the world has amply demonstrated just how capable robots are where humans fail. Robots are going to inherit the solar system. Robots are in 2026, the de facto interplanetary species, sine qua non. My heart is warmed by these human achievements. I, for one, am happy to live and die on Earth. I think that every American should be grateful for Earth, and not permit our oligarchs to cheat and lie to us with fairytales of escaping our Earth.
We're not escaping Earth nor seeking to replace it. The entire idea of becoming a multiplanetary species is exactly that. Ostensibly we all started in Africa, and plenty of us are still in Africa. The same will be true on a planetary level, and eventually on a star system level. You said a lot and I don't want this to turn into a wall of zig-zagging tit for tat nonsense, so I just want to speak briefly and holistically. The first missions to Mars will be fully dependent upon supplies we're bringing. The goal of self sustainability is aspirational and long-term. At best it will take decades. In reality, it may never happen much in the same way that no country in the world today is fully self sustainable in practice, even if many could be in theory.
The whole point of the extended stays in LEO are precisely to simulate worse case scenarios for travel to Mars. So for instance the record for the longest time in space is held by Valeri Polyakov. [1] He spent 437 days on Mir in LEO, and then opted to immediately walk upon landing back on Earth. It was all to prove that humans would be physically capable of working on Mars (which has 1/3rd the gravity of Earth) even after absurdly long periods of time in space. In fact his first words upon return from his first (240 day) stay in space were "We can fly to Mars."
Robotics don't really work well for space exploration, because moving parts break. For instance the Curiosity/Perseverance drills are cutting edge yet have a max depth of ~2.7 inches. And traveling is even harder. On average Curiosity ended up traveling about 1 mile per year. It's all because if anything breaks, that's game over. So everything has to be done with the utmost of caution, and even then stuff constantly breaks. Curiosity's drill broke after about a dozen activations and required a team of scientists and months of full-time work to create a passable work-around when it could have viably been fixed on the ground by a human in a few moments.
This is part of the reason that we only learned in 2013 that the soil/regolith on Mars is actually extremely moist, 2-5% water by volume. A cubic foot of soil heated up gets you about 2 pints, a liter, of water. The whole plot-line in "The Martian" about having to jump through hoops to get water was correct based on the latest knowledge when the book was written in 2011. We'll probably learn more in a couple of weeks with people on Mars than we have with 60 years of probes and rovers.
I'm certain every human of sound mind is grateful for Earth. That's not a reason to not seek to expand out as far and as wide as we can.
[1] - https://en.wikipedia.org/wiki/Valeri_Polyakov
The whole caring oh so much about humanity simply doesn't pass the smell test for me. I don't want to go into details and individuals, but I just don't buy it; what I do buy is wanting to get a foot into space to get even more leverage over the humans on Earth, and not for our benefit. That actually fits their actions and their aura, so to speak. But "preserving the light of human consciousness" and such? Now I know it's a scam and an agenda. And the more flowery the language, the more sinister I expect the actual designs to be.
There is one core reason that Machiavellianism is naive. It's because the grand long-term ends people seek to create with all of their sinister deeds in the short-run rarely ever comes to pass. Yet all those sinister deeds absolutely do come to pass and are what we all get to live through.
So the most well intentioned person doing awful things? In my mind he's an awful person. But this also goes the other way as well. Imagine you're right, and the idea of getting humans into space is some elaborate scheme to somehow get more leverage over humanity. Awesome! Because it's highly unlikely such schemes will come to pass in any sort of remotely realistic way, but we'll be left with the means of humans actually meaningfully expanding into space.
I'd love to see as sharp increase in the number of evil people plotting to do good things to further their evil ends. All the 'good' people doing evil deeds in the name of some grand end that never happens is quite tiresome.
I fully agree with your points: the hard, unyielding reality which most Trekkie fanatics refuse to acknowledge, except for one: "severe toll on the human physique in microgravity conditions."
That's easily fixed!
Spinning a space station for gravity is straightforward, it's just that the ISS wasn't designed for it, and NASA didn't have the budget to build a second, bigger space station with "extra engineering challenges" on top.
It's definitely practical though, it's just a matter of launching enough mass to orbit.
Like you said, Starship is going to change a lot of things, starting with space station design.
> spinning ... for gravity
Yeah, I mean, I get that the spinning has long been a viable proposition. Perhaps if we send a spinning expedition to Mars, the astronauts won't be toddlers when they arrive on a barren, hostile, resource-free world. Yet, that is a lot of extra mass; that is non-zero extra fuel; that is a lot of extra "stuff goes wrong" risk inherent in that design.
But it's unprecedented, untried, and not currently in any pipeline, AFAIK. I believe there were a few experimental spinning crewed flights, during the original Space Race. But does Starship spin and simulate gravity? Is there any crewed spinning spacecraft extant, in production, or even being designed?
They don't need to spin their way to the Moon, so it would be unlikely that any Artemis or future crewed Moon mission spins at all. But if spinning our way to Mars will solve an otherwise intractable set of problems, I suppose we'd better get started on proving it.
Everything you’re saying is true but it’s nevertheless going to happen anyway.
The REAL reason Anthropic must IPO now: https://www.youtube.com/shorts/E80oYhrGa8c
New findings reveal AI bubble worries are justified: https://www.youtube.com/shorts/xCzCyPoI-eA
Related:
Anthropic IPO prospectus shows AI vision, surging costs
https://news.ycombinator.com/item?id=49886005
You don't buy their stock to obtain money, you do it to placate the future overlords.
Maybe the portion of Anthropic that produces Opus/Sonnet can be spun out for us devs at a reasonable valuation?
Keep all the Mythos/Projects/etc. hype/feature-creep crap in some other entity and value that at $5 tn or something if you wish.
Just spin the golden-egg production part out of the goose, then we can cook and eat the rest.
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.
This reminds me of all the people asking for AWS to be spun out of Amazon.
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 think they have a fair chance at this.
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.
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
The question isn’t whether Anthropic makes a good product. The question is whether it can rationally sustain multiples like this.
Yes, they have the same problem WeWork had on the multiple front. Coworking was a thing long before WeWork was a thing. It’s an important but boring business that trades at low multiples. WeWork tried to IPO on the basis that somehow it was worth vastly more, but the market woke up and realized it’s just subleasing office space.
The same is unfolding with Anthropic. It’s doing important work but everyone is realizing it’s not got a serious edge over anyone else. It’s important but ultimately a boring business. It’s still likely worth a few hundred billion, which is massively impressive for any startup, but trillions is pipe dream.
Great comparison.
The thing that makes the frontier labs frontier is mostly access to huge amounts of training data and compute. In the earlier days of AI access to top AI talent was a moat, but that moat is rapidly eroding as more and more people familiarize themselves with the "black magic" of LLMs and training. The success of the Chinese models is evidence of this diffusion of knowledge.
Give me a team of, say, 20 good engineers with a deep knowledge of AI/LLMs and training and give me a billion dollars worth of GPU compute and a huge amount of training data and I'll give you a frontier model.
No moat.