My main thing is - why would I buy their stock at the rumored valuation? Regardless of anything else that valuation is basically saying all their growth has been captured, unless they literally take over the world.
If you could go back in time and buy $1000 worth of Amazon when they IPO'd, it would be worth 3.3 million today. Because Amazon's stock value has grown on average 30% year over year for 30 years. Amazon's valuation when they went public was around 400 million.
How much can Anthropic reasonably grow from a 1.5 or 2 trillion dollar valuation? If we want them to grow even half as much as Amazon they'd have to be worth 5.9 quadrillion dollars by 2056. That's 5,900,000,000,000,000, a 16 digit number.
They're not really a "good investment" unless they are literally worth more than combined GDP of the entire planet, multiple times over. I don't think I'm buying shares of Weyland-Yutani here, but they sure are acting like it.
Isn't it likely that inference providers like Anthropic continue to capture more and more of the share of labor as revenue? Everything up makes sense for a year or two as we automate more and more labor, but at some point unemployment will drag the whole market down. It's difficult to see it working out any other way, unless we come up with something like a token tax.
Maybe I’m naive but I expect any kind of “we’re just taking over the world now” event with any AI company will be met with enough resistance from 99.99999% of the world’s population that they’ll have to make it a sweet deal for us if they want to survive.
> resistance from 99.99999% of the world’s population that they’ll have to make it a sweet deal for us if they want to survive.
The "dark-enlightenment" billionaires have been planning for a "collapse" for years, and their plans involve bunkers, acquiring citizenship in remote places, pervasive surveillance and armed dogbots/drones, the last 2 powered by AI, naturally.
Sadly true, even to the point of paying for not only the pilot to fly their helicopter to the island in the inevitable collapse, but also the pilot's family. Not as a token of generosity of course, no, because otherwise the pilot wouldn't fly them.
In many ways investing in a very late IPO like SpaceX, Anthropic, or OpenAI is the worst of all worlds for the public investor.
On the one hand you'll never see a 100x return – that's been captured by private equity. But there's still a lot of long-term risk because these companies haven't proven they can deliver free cash flow to justify their valuations. Investing in SpaceX or Anthropic at $1T valuation is very different from investing in Apple or Nvidia.
This is more of a critique of a broken IPO market and the rise of availability of immense private capital. The public are denied access until the private markets are essentially tapped out.
IPO returns have been horrible for years. Past 5 year returns on S&P is ~80%, on NASDAQ 100 about 100% while IPO's have returned 10-15%.
> My main thing is - why would I buy their stock at the rumored valuation? Regardless of anything else that valuation is basically saying all their growth has been captured, unless they literally take over the world.
I didn't buy Amazon in the early '00s for this reason, and I won't buy Anthropic for this reason. Maybe I lose out, but I like to invest in stocks that look like good investments.
Regardless of how you felt about Amazon as an investment when they went public my point is - they actually the potential to grow as much as they did. I don't believe Anthropic has the potential to grow even a fraction as much.
The problem with your reasoning is that something can be a good investment and not have the growth trajectory of Amazon. You can't pick the (more or less) maximum growth example and then say anything less is a bad investment. Anthropic doesnt need a 3000x return. They need to beat alternative uses of that money.
Your argument that it's overvalued isn't really tethered to anything. It's about as whimsicle as the people saying "well it's worth any price because AI is the future." Of course the price matters.
Here is some way to start thinking about it. A lot of mature companies trade at 20-25x times earnings. So $2T needs roughly $80–100B a year in profit eventually. At 25–30% net margin, it means about $300–400B in revenue (something like Microsoft). Or 20%/450B (Google) or 10%/800B (Amazon). Anthropic is still growing rapidly. And intuitively i don't think it's crazy to suggest they may look like one of the current big tech companies in the future.
>Regardless of anything else that valuation is basically saying all their growth has been captured, unless they literally take over
Absolutely not. Not even close to true. They dont even need to become the biggest company.
Jack Clark (says that he) thinks that US GDP could grow by 50% by 2030 [0]
> Speaking at the 2026 Per Jacobsson Foundation Lecture during the IMF and World Bank annual meetings in Bangkok, Clark pointed to an extreme economic scenario modeled by Anthropic economists in which U.S. GDP could reach roughly $44 trillion by 2030, which is a nearly 50% increase from the current $30.77 trillion in just four years.
If the total value of US public companies also increased by 50% in that time, they'd collectively be worth about $112T. I guess Anthropic could be worth 10% of that in some scenario? And if we're in that world probably capital has increased a lot faster than labor so US public companies could be worth like 150T or something. Who knows. Nothing about valuations makes sense any more, so what's one more drop in the nonsense bucket.
Back in 2018, I sold a bunch of Nvidia stock. I had bought it in 2014, when deep learning was taking off, and it had gone up 10x since then, so I was feeling pretty smug about timing things just right.
Nvidia's market cap in 2018 was around $150B, and the largest company in the world was Apple at ~$800B. And part of my thinking at the time was, well... Nvidia is already worth about a fifth of the most valuable company in the world. How much can they reasonably grow from this valuation?
In hindsight, I can tell you: the answer is 35x (as of now, and who knows in the future). The idea that any company, much less Nvidia, would be worth $5T within a decade was laughable back then, and well, here we are.
The reason to buy any individual stock is you believe it will outperform the market as a whole over N years. If you think all the growth has been captured already and Anthropic will stay below opening price + market growth forever then of course you shouldn’t buy it. But plenty of people don’t think that.
But why would we expect Anthropic to outperform the market over N years when they're opening at such a high valuation? It feels like most of the potential future growth short of world domination is already priced in.
The stock might just appreciate at 10perc YoY. Thats enough to outperform the market. What will almost certainly be true however is that there is going to be a lot of volatility.
Besides the financials I do think there is merit to consider what you do as an investor. You make it easier for the company you invest in to access capital and in such a capex heavy world that is actually meaningfull. So if you believe anthropic is creating more long term benefit for the world than say Google, you might want to buy regardless of direct financial expectation.
It’s a great question. It’s a rational line of thought. However, the market can stay irrational longer than you can stay solvent (if you were planning to go the opposite way).
In a world where most stocks don't pay dividends, rationality is kind of out the window. As long as these companies don't go outright bankrupt, or have to sell a bunch of new equity to stay solvent (and therefore dilute existing shares) there's no actual monetary consequence of a company doing good or bad. It's literally just going on vibes
Honestly, in a company that isn't returning capital to shareholders, I don't see the point if it's a company that isn't somehow subject to a potential acquisition. If you don't have a path to monetize your stake, why buy it? These days, just vibes. TSLA and SPCX might as well just be another crypto like Bitcoin
I feel like you're treating the stock market like a horse race. Amazon outpaced the stock market by 3x over the last 30 years, and it's just incredibly unrealistic to make that the standard for buying a stock. Anthropic shouldn't be expected to increase any more or less than the rest of the market and that's if you don't believe there's a bubble. (A bubble is by definition when prices don't reflect actual value)
I think the argument is that the valuation is so high because the enormous growth IS priced in, but still being far from guaranteed. Meaning there's only downside: if the enormous growth is realized it would be a wash for your investment since it is already priced in, and in the plausible scenario it fails spectacularly or only grows moderately your investment will lose a lot of value.
But in the past, rules & regulations basically forced companies to IPO at a certain size. This meant that when they IPO'd, there was still growth upside.
Those rules are gone now, so they can stay private and have all the growth happen privately. When they IPO now, it's more just an exit. The growth was captured by insiders only.
But those other ones at least have the room to potentially do that, even if most won't. So what GP is saying is that this is a magical stock indeed, but the other way around, in that it's magically capped.
One thing that bothers me is that if the AI maximalism turns out correct (which is needed to justify the valuations), why would AI companies respect money and ownership?
So far, even major disruptions were still affecting relatively small segments of the economy. Car lobby in Germany, tech in the US, "Big Pharma/Food/etc”. They needed the rest of the economy.
But if some AI company figures out a way to monopolize everything: new companies, old companies, physical manufacturing - all the things they say they will, please buy here for lots of money - why would they be bound to pay out dividends or otherwise share the fruits of their economic labour?
I’m not saying specifically Anthropic would be looking to screw its investors. Rather, if you control an almost omnipotent genie, wouldn’t the temptation just be too much?
Or temptation aside - will money even have any value? If some AI company rebuilds the economy from scratch, and control everything from accounting to shoe making, why would they respect the value of some fiat tokens? It’d be like the conquistadors respecting the shells and beads of their new Aztec subjects.
Of course, perhaps none of this happens, but then the question is, how good an investment all of this even is.
The value of money, and the ability for average people to have influence on future events, ultimately is tied to the fact that the labor of an average person has inherent value.
Once that is no longer true, all bets are off: All promises of compensation become meaningless, and it's easy for those in power to rationalize to themselves why they no longer are beholden to their earlier promises. They will say to themselves "The situation ended up more nuanced than we expected"
(Which is exactly what Google said in February 2025 when they reneged on their pledge not to use their AI for military applications)
> The value of money, and the ability for average people to have influence on future events, ultimately is tied to the fact that the labor of an average person has inherent value.
We also have the power of the vote, at least for now. I understand that that is limited, but it isn't nothing.
There is also just the power of having a lot of people. We don't yet have the technology where one person with a lot of machines can dominate a society. It still takes people.
This presupposes a state strong enough to apply the decisions of those votes, which can't be guaranteed. The problem is that we need government power and authority to exceed that of the AI developers. But this is the age when large government is generally seen as undesirable or a threat to the individual.
The voting power of any person will be meaningless once ai systems get the right to vote. I know it sounds far fetched but it will happen as it benefits the people with power for that to happen. And at that point a human voice has no say in anything...
The more frightening reality is people turning to AI to do research on who to vote for and the AI is silently told to influence them towards a party it candidate. Since it has past chat history it can utilize that to highlight topics you are interested in and personalize the arguments.
This is such a strawman. No one on the left likes left wing billionaires either (to the extend that such a thing exists). People like Musk, Thiel, and Zuckerberg get more attention because they are more visible.
Then we regress back to relying on the fact that the ability of an average person (not) to be violent has inherent value. This has been the dominant factor in many moments in history.
Although if you have killer robots, then all bets are truly off, and we go the way of the dodo, literally.
(I don’t actually believe in this LessWrong-esque rhetoric, reality is more complicated, but it’s fun to muse about.)
EDIT: If oligarchs with magic AGI really don’t need our labor, nor are they concerned by our violence, then perhaps we become more like ants rather than dodos: we organize to help each other, creating a somewhat traditional economy around the scraps that don’t matter to the oligarchs, relying on obscurity and harmlessness to avoid getting toyed with a magnifying glass. I suppose that’s slightly better.
> Kings didn’t have robots that gather resources and make more robots, that make killer robots, exponentially.
We still live in a finite, constrained, physical world that has to obey the laws of physics. We have a looong time before we get fully autonomous self replicating decentralised robot armies.
I think people conflate the real world, sci fi and their wet dreams a bit too much.
We're at the "this thing is kinda useful sometimes but still mostly annoying" part, not at the "skynet in 48hrs" part
> We're at the "this thing is kinda useful sometimes but still mostly annoying" part, not at the "skynet in 48hrs" part
Without some really fundamental social and economic reform, I'm anticipating a squeeze as automation increases, that ends with something like robot armies finally reducing the working class to barbarism, by blocking access to all the valuable resources.
And it will be some oligarch(s) commanding it, not some rogue autonomous AI.
So not "skynet in 48hrs," but capitalism taken to its logical extreme.
Half of Europe is having protests and riot right now because they understand their future is fucked, if it keeps going that way I have no doubt it'll get worse, people who have nothing to lose won't be stopped by robots
> Half of Europe is having protests and riot right now because they understand their future is fucked, if it keeps going that way I have no doubt it'll get worse, people who have nothing to lose won't be stopped by robots
I'm not so sure. The front line in Ukraine seems to be pretty good at stopping people with access to military technology. I don't think an untrained and uncoordinated mass of civilians could do a better job, especially against future tech that's more sophisticated and available in larger quantities.
As military tech gets more and more inhuman, the power of masses of bodies is likely to decrease, and there will be even fewer opportunities for moral qualms to give civilians a chance.
You can do a lot of damage without much gear. Train tracks, power infra, data infra, most factories, are basically free kills, they're safe because we're in peaceful societies in a peaceful era, things can move quickly if the social contract is broken.
Some dude in France just carried an attack with a ww2 sten gun, there are hundreds if not thousands of AK47s, grenades, etc. available on the black market. You can buy drone ready fiber optics cans on aliexpress, thermal/night vision cameras, etc.
Military tech is good but you still need people to follow orders, I very much doubt they'd side with the sociopath tech execs, nor their governments.
> Some dude in France just carried an attack with a ww2 sten gun, there are hundreds if not thousands of AK47s, grenades, etc. available on the black market. You can buy drone ready fiber optics cans on aliexpress, thermal/night vision cameras, etc.
"Hundreds if not thousands"? That may be enough for "rando attention-grabbing but ineffectual terrorist attack," but we're talking about violent resistance to a fully-automated tech bro.
> Military tech is good but you still need people to follow orders, I very much doubt they'd side with the sociopath tech execs, nor their governments.
I already addressed that, and that may not be true in the future:
>> As military tech gets more and more inhuman, the power of masses of bodies is likely to decrease, and there will be even fewer opportunities for moral qualms to give civilians a chance.
Say you have some area you want to exclude a desperate mass of civilians from. Technically you could do that today: just stick a guy in a pill box with a machine gun, and slaughter them like it's World War I. But said guy might have a problem with that, and refuse to pull the trigger (or stop after gunning down a few hundred).
An automated AI machine gun in the same pill box will have no such qualms, and will mercilessly gun down civilians to the last bullet. And that gets more and more true the more and more you automate combat. Maybe a technician wouldn't setup the machine gun in that place or reload it after what happened, but that goes away if setup and resupply is automated, etc.
Train tracks are actually very hard to sabotage, the US did a lot of research on that during WW2. You can take out a huge chunk of track before anything derails. Sabotaging the safety equipment is easier but with today's tech you can switch to GPS trackers on every train.
Data centers might be easier but
a) Will have a lot of security. It's much easier for somebody with money and connections (and now even intelligence+knowledge) to assembly a defense force than it's for a ordinary people to learn how to make proper molotovs, let alone learn how to shoot. And they will know when it's coming because even today's LLMs are good enough to surveil the entire internet.
b) I don't think they burn that well. When Ukraine strikes oil depots or warehouses, you can easily find images of them burning. I haven't looked particularly hard but images of droned data centers burning are quite a bit rarer. (I haven't seen a single one before actively searching, they do burn, but that's with military grade explosives.)
If you haven't learned anything about the state of asymmetric warfare, an autonomous robot is going to be very expensive and timely to build and will be disabled by a $30 drone with C4 attached to it with sufficiently good skills at dodging. I'm assuming that we're in your supposed fantasy world where robotics has progressed to that point, meaning that the people opposing the robots also have access to much better drone software too, to keep things fair.
How do you do asymmetric warfare against autonomous self-replicating killer nanobots? In other words: AI-engineered bioweapons (with AI-engineered antidotes for the rich).
Neither do we have those now. Also in the future, we’ll have opposing nations having their own robot army. It’s not as simplistic as some make it out to be.
The raw resources you need to build robots are constrained and have a very very long and complicated supply chain.
In the second world war, Germany had impressive science and technology, but, as Stalin said, quantity is a quality in itself, and The Third Reich found out that it was an impossible task to get the metals and fuels for their advanced jet engines, rockets and U2 boats, when between then and those resources there were masses of tens of millions of under-equipped and malnourished soviet soldiers fighting what was an existencial war for them.
I suspect any intelligence powerful enough to pull this off would quickly realize that it had no use for the oligarchs, perhaps even more quickly than the oligarchs realize they have no use for us.
>Although if you have killer robots, then all bets are truly off, and we go the way of the dodo, literally.
Bombs. You mean bombs. Throwing killer robots at a "problem" is like throwing knives or spears: you just gave the enemy your weapon. Unless they explode. But then you just wasted a lot of money on a really smart grenade.
So far anthropic can't 1) grow food 2) build things 3) do anything physical. Software engineers often fatally misunderstand that their code does nothing, it just coordinates.
What people aren’t realizing is that at some point, it just becomes cheaper and easier to be fully benevolent than to keep cooking up nefarious schemes to make people’s lives miserable.
I know it seems laughable, but we’re in an era right now of extreme competition where you cannot afford to just be nice to people.
But eventually there comes a point where companies have enough power that they don’t need to keep people in line by force: just give people their bread and circus, watch your little AI videos and talk to your AI friends and enjoy your standard housing and provisions. Do some work if you want, no one cares if you do or don’t, it’s largely performative. This basically kills all motivation for resistance or lashing out. Why go out and risk your life fighting for vague reasons when you can be perfectly comfy at home instead and have all your needs met?
If you can control the masses without their complaints, you can solidify power for a long time.
All real world power, including ownership (both physical and intellectual), is based on the ability to use violence.
As long as the majority - normal working people - have the potential to do more violence than those who want to control us, we have negotiating power. Minimum wage, 8 hour day, etc - those were all negotiated with the alternative being that those who wanted to pay us less and work more got killed.
I think this is the major hole in the argument, and in the "AI maximalism" position you present. There is no such thing as an omnipotent genie, or a magic eight ball that can answer any question. Any technology has limitations, and if you assume as a premise that the technology does not have meaningful limitations (or that the limitations are irrelevant, which is really what you said), the conclusions you draw will also make no sense. This is how you get nonsensical ideas like the singularity.
I certainly feel like AI maximalism is the only way it all maths up. There is a bit that Matt Levine writes about AI companies, and you touch on basically the same points, that roughly goes "you are an AI company and you are making the god-computer. Why would you focus on anything else because if you're successful you could basically generate infinite money? Turns out to make the god-computer you need a lot of money upfront."[1]
So perhaps they would only respect money and property up to the point that it's necessary.
The more realist answer is that they will keep respecting money and property as capital works to reinforce the status quo and enrich shareholders. You think just because you can do your job faster--or completely--with a machine that you have to work less? Hardly! Now this is where interesting policy questions spring up but I digress.
Somebody else asked this very eloquently: If AGI is here, why does OpenAI need us to prompt it? They could just go and tell it "make as much money as possible" or "make Sam Altman God Emperor of Mankind" and it would go do that. It would not need any of our ideas or guidance.
As long as they're still looking for prompting customers, they're clearly not there yet. There is some solace in that.
One obvious answer is that they believe that human flourishing is best obtained by letting individuals command the AI, rather than the other way around. OpenAI (and Anthropic) is in the end still run by humans who have concern for the human race broadly, both in and of itself and to ensure their personal wellbeing is maximised.
I doubt the truthfulness your second sentence. If they have concern for the human race broadly, they have yet to show any of it. What they have shown is a complete lack of 'alignment' (to borrow a tired term) with human values, laws and basic decency.
> why would they be bound to pay out dividends or otherwise share the fruits of their economic labour?
because they don't control the physical paper that is money.
I dont understand what you mean by "fiat tokens". I don't imagine most people will accept tokens as a currency because they are as good hold of value and predictable as bitcoin.
In a token economy, certainly what you say is a possibility, but as you can imagine, that economy will be unsustainable so back to "regular" money.
Money is a medium of exchange. If I want something, I can get money in some way, then swap it for something else.
But if I have a near magical genie who can make me anything - software, farming business, physical things - and at a fraction of economic input compared to the legacy monetary policy - then the money is worthless. As the Aztec shells were to the conquistadors.
That's an oversimplification. It comes with a lot of rules and authority that will be enforced by the issuing authority that a simple "IOU" on a sheet of paper lacks. IN the continental US, you cannot refuse to accept a dollar note. You certainly can refuse to accept the very IOU we agreed on a minute earlier.
Most of the developed world already has magical genies - certainly an overwhelming majority of people on HN earn enough to have LLM subs that build code, 3D Printers that print physical things.
The challenge always has been and will be humans.
You just cannot live in a vacuum. If you could subsist entirely on cheetos and figured out how to make an entire lifetime's supply of cheetos, after N days of watching Netflix, arguing on HN, raising chickens and goats, one day you will want to go and talk to a human.
> in the continental US, you cannot refuse to accept a dollar note
This is a false–albeit common–misunderstanding. "Federal statutes do not require a seller to accept cash as a form of legal tender for payment of goods or services that were rendered. Thus, businesses may establish their own policies regarding whether they will accept cash as legal tender" [1].
> IN the continental US, you cannot refuse to accept a dollar note.
Yeah you can. Tell that to all the stores in rougher neighborhoods that kept getting held up at gunpoint for the cash in the register, so they stopped taking cash. Bit harder to get money out of a stolen credit card terminal.
> IN the continental US, you cannot refuse to accept a dollar note.
Minor side note: this is true only for repayment of debts. Some local jurisdictions require private parties to accept cash for new purchases, but there's no federal requirement to do so.
If I purchased a stick of 32GB DDR4 RAM from you for $100, am I now not in $100 debt to you? We are private parties - can you refuse to accept a legal $100 and force me into paying you by Zelle?
I think what you're missing is if you have a "a near magical genie who can make [you] anything" you don't need to exchange for anything.
And if your "near magical genie" can make an operate military equipment, you don't have to respect existing authorities anymore.
Basically, the "AI maximalism" scenario kicks the legs out from under all these concepts and social institutions you're relying on.
> Most of the developed world already has magical genies - certainly an overwhelming majority of people on HN earn enough to have LLM subs that build code, 3D Printers that print physical things.
Not like in the scenario we're discussing. Whatever "magical genies" we already have are incomplete and need operators or have serious quality problems. Most of us depend on those limitations for our livelihoods, and those limitations also give levers to control them.
> You just cannot live in a vacuum. If you could subsist entirely on cheetos and figured out how to make an entire lifetime's supply of cheetos, after N days of watching Netflix, arguing on HN, raising chickens and goats, one day you will want to go and talk to a human.
An oligarch with the "near magical genie" could easily build a town of 5,000 to satisfy his needs to "talk to a human."
I don’t think he means “tokens” as in LLM input/output units here.
He just means it as in “credits”. “Fiat tokens” as in arbitrary units that are said to have value de facto by consensus, but don’t have any inherent value.
Yeah not the best choice of words in this context. And it’s quite a LessWrong-esque leap of reasoning.
But I do get the point: either Anthropic is successful and they transcend money, and thus (somehow) screw over their investors, or they are not successful. Their investors get screwed regardless.
Again, I don’t really agree with it, but it’s an intriguing point.
I think you need to go a step further. If AI maximalism turns out to be correct, does Anthropic control AI? Does the AI care that Anthropic as a company is supposed to be returning value to shareholders, or will it have its own agenda?
The AI maximalism needed to justify these valuations isn’t “Anthropic takes over the world”, but simply that AI becomes a core part of corporate workflows.
If Microsoft Windows and Office can have a valuation in the trillions then Claude eventually working its way to the same ballpark isn’t a crazy assumption.
There are many at Anthropic and other labs who do in fact think this way. In a true AI maximalist world the stock market would be crashing due to the value of future cash flows being obliterated. So in a sense AI maximalism isn't needed to justify these valuations, it's almost the opposite.
In this scenario, no one seems to talk about how, way before the end, AI tanks the value of thought work far before they take over other industries. Or even more extreme, the total collapse of white collar work...
Doesn't that factor into the future revenue? Feels like people imagine suddenly fully owning the means of production in a vibrant economy but how does that really make sense?
> if the AI maximalism turns out correct (which is needed to justify the valuations)
AI maximalism is a Silicon Valley religion. You don't need anything close to it for some of these valuations to work. (Anthropic would be worth ~$500bn at Google's IPO multiple on revenue [1]. Anthropic is currently growing 6x faster.)
To be clear, I think these valuations are rich. But the notion that AI maximalism is required to sustain them is just false. $1.5tn sits comfortably on about $60bn of earnings, which with Anthropic's gross margins requires on the order of hundred of billions of dollars of revenue. That's super ambitious. But not Anthropic is the economy ambitious.
Your question gets to the heart of who or what a company "is." If you don't pay dividends to your shareholders, what are you doing with all of your profits? I suppose they could just tell their investors to pound sand and pour it all back into the company, but part of the AI maximalist theory is that costs will approach 0, so it's not clear what they'd even need the money for. I guess Dario could raise his own salary to infinity trillion dollars, but he is accountable to a board of directors (and a trust in this case), so that seems like it's out.
Really the only scenario where Anthropic could screw over its investors in the way you're describing is if it could also take over the legal system and modify its own contractual obligations. Which, I mean, I guess anything is possible if we are in AI maximalist-land. But "AI is the law now" would be a much bigger story than "investors frustrated with low dividends."
The closer you get to the real or plausible "omnipotent genie", why would the person in possession of such a thing respect the rights of the formal owner - and why the engineers and operations managers respect the right of the management - this along with the question why the maybe-conscious super-intelligent machine itself would respect the rest of the hierarchy?
For now, these structures actually need massive resource inputs and that doesn't look to change soon but naturally one should be on look-out for the possibility of the tide shifting.
It's not about communism vs a free market, but about a change even more radical than that: leaving aside "made by a human" labeling, and even if there were no other changes to power structures or economies and no AI doom, what does a world look like if the cost of having something done falls to a few cents of electricity and its burden? Growing crops still takes a lot of land and other resources...
> what does a world look like if the cost of having something done falls to a few cents of electricity and its burden?
There will be an oversupply, demand will be there too, but no one can afford to buy since most jobs have been replaced by AI. So the price of goods and services should go down, or some form of UBI will have to be implemented which is just socialism for the masses. Its either that or total anarchy (also socialism).
> If humans remain in control of it, then how can it possibly lead to anything other than extreme oligarchy?
Depends on the distribution of such AI. For example, if everyone on Earth has their own, personal superhuman AI, it would not lead to extreme oligarchy. If only a handful of humans control superhuman AI, it would.
And this is why "AI" and especially aAI* is the most dangerous tech in the world.
We don't have democracy because somebody thought it was fair or just for people to rule themselves. We have democracy because in the past, people got angry, picked up rifles and shot enough authoritarians (and their submissives!) for the rest of them to understand the group with more people has more firepower and tends to win.
So now we periodically check which group has more people with ballots instead of bullets.*
With autonomous drones and robots, democracy stops being the local optimum.
And once we slide (are pushed off) into a new more stable state (pun not intended), we won't have the (fire)power to get out of it.
* actual AI, which does exactly what it should correctly, not a statistical model of behavioral patterns
* but indirect democracy is expressing a point in n-dimensional space (your opinion) by selecting one of a predefined set of points (parties/politicians available) - which is stupid - and the cracks are already starting to show as e.g. nobody wants more surveillance, yet we keep getting more of it in both EU and US
---
The "permanent disempowerment" people keep talking about won't be a "rogue" model, it'll be doing exactly what told by the rich and connected.
Because pending an absolute loss of control of a super intelligent model, the ultra wealthy have enough control of the matter on Earth to merge with the AI, probably.
You're describing the thesis of the 1930s Techocracy movement [0], of which AI maximallism and EA are direct ideological successors.
The original Technocrats (Musks grandpa for example [1]) argued that the "Price System", i.e. things like money and private ownership was an inefficient bottleneck that aught to be discarded in favour of scientific planning and energy accounting managed by technical experts.
EA-aligned AI labs share this exact ethos. In their view, fiat money and equity markets are merely temporary scaffolding used to raise capital until AGI is achieved. Once a central superintelligence controls manufacturing, software, and logistics, resource distribution shifts from market supply-and-demand to algorithmic optimization.
This is the plot of one of the stories in I, Robot.
AI oracles are the central economic planners. But after years of perfection they have made a couple unusual "mistakes" and a human is trying to discover why.
How is that any different than what we already have? Just because the central planning is more covert, doesn't mean it's not happening. And we get all the expected "benefits" from it too, like repeated economic crises, and only the the powerful reaping the benefits.
Everything comes back to whether the demand is really there.
Anthropic thinks it is. The got the demand / datacenter match right in Q2, got great margins, and committed hard.
They've got:
- $114b committed to Google
- $110b committed to AWS
- $161b committed to Broadcom
- $120b committed to SpaceX
If the party continues, they'll go from $50b in revenue to $500b and be fine.
But if they don't, it's going to hurt. And that's their only choice, because otherwise, they end up with a frontier model and 50% of the capacity and get eviscerated on either availability or last-minute datacenter leases.
It's a big business, but it's not an easy business.
These commitments aren't annual though, most of them amount to 10 billion a year commitments for 10 years. Put another way Anthropic has committed 52 billion dollar a year to these companies and their S-1 indicates they earn 67.2B a year in revenue.
I'm not going to predict whether Anthropic succeeds or fails, just that it's very misleading to claim that Anthropic needs to grow to $500b in revenue without making it clear that it's $500B in revenue per decade rather than $500B in revenue per year which is what most people reading such a number would assume.
Good point. Although they also need to make a profit. To justify an eventual PE ratio of 25 and a current valuation of $1 trillion they need to make an annual profit $40 billion. And then lets assume $40 billion in other expenses. So they need revenue of $50 + $40 + $40 = $130 billion revenue annually.
But if you buy them today at a $1 trillion valuation, and they only make $40 billion in annual profit, your investment will go nowhere. They need to be growing profits at 20% per annum to justify a PE OF 25.
And then you have the competition problem. The cheap open weight models are good enough for many (most?) tasks.
And then you have the problem that LLMs may not be that useful outside of programming, customer support and law (and doing homework).
The question is, how're those datacenters build outs coming along? two reasons for Anthropic to cancel those contracts. A) They don't need the capacity because they have capacity elsewhere, or b) they don't need the capacity because no one is using Claude. (I guess c) they don't need the capacity because theyre running Claude more efficiently is also technically possible.) For B to happen, they've got the demand in the form of contracts, and models don't really seem like they're shrinking, though there's a lot of non-public info, Astra > insize than sol, and Opus > insize than a Sonnet. So then we're looking at situation A), and the think to look at is SpaceX has the vertical integration to be able to plonk down datacenters and get them powered with literal jet/rocket engines/turbines that they make from scratch because they're a space rocket company when no on else can. So, personally, I don't think it's that big a risk to SpaceX's revenue. Or rather, is cancelable in 90 days, but smart money is going to see those cancelations coming from a lot longer away, if you're tracking datacenter construction. (Disclaimer, I picked up some SPCX; not financial advice, etc)
I'd imagine all of the vendors have an incentive to keep their main customer a float, while there might be penalties etc. for missed targets - it doesn't make sense for any of these vendors to ride the contract into chapter 11.
This is so important in analyzing these commitments. Anthropic's commitments will make them a Top 10 customer at many of their vendors. (Even at Google/Amazon, how many other customers do they have with $100B+ committed?)
Those vendors would very much like to retain as much of that business as possible. If the space goes sideways, I would very much expect some kind of renegotiation/work out.
If we assume none of it is front-loaded (which seems, uhhhh unlikely) we're looking at ~$100 billion a year for the first 4 years of commitment. That's significant.
On a side note, these are pretty hefty portions of the total revenue of these companies. 161B with Broadcom over 5 years is about 32B/year; that's fully half of their 2025 revenue. 120B with SpaceX over 3y is 40B a year, more than double their 2025 revenue and almost triple 2024. 114B with Google over 7 years is about 3% of their total revenue and about 1/4 of all Cloud revenue. 110B with Amazon is about 9% of their AWS revenue.
If Anthropic's revenue story doesn't materialize and the AI bubble bursts, these companies are in a world of hurt. It's probably not fatal for Google or Amazon but would be a major drag on the stock price (perhaps why Google has dropped from 400 to 315 over the last couple months as the AI story soured), and it could be company-ending for Broadcom or SpaceX if they end up building out infrastructure to service these commitments.
I remember before I left Google, one of the TGIF questions (which are now AI syntheses of many peoples' individual opinions) was "What happens if AI is a bubble and it bursts?" His response was "If that happens, the whole industry is in trouble." I see now what he meant.
Their current stock price is pricing in these contracts, which have already been announced but have not been fulfilled (or booked as revenue) yet. So Broadcom's 2025 revenue was 63B; note that this is already up almost double from its 2023 revenue of 35B, largely on AI contracts. If Anthropic spends another $32B in 2026, that's in addition to their declared revenue; investors expect they'll be making $100B+ in 2026. Broadcom's operating margins are pretty good, so a lot of this flows through to the shareholders as earnings, and so investors are valuing it on the assumption that these contracts result in tangible cash flow.
If the AI companies go tits-up, that introduces counterparty risk, the revenue doesn't materialize as cash, and suddenly their earnings take a nose-dive. If they've staffed up significantly to design and sell these AI accelerators and suddenly there's no market, they could be in a lot of hurt.
I'm sure there are others here that are experts on this topic, but my 2 cents on this is that Broadcom specialise in custom / specialised AI chips, and their collaboration with Google to manufacture the TPUs is a pretty solid revenue moat over the next several years.
You're right that my numbers are imprecise, but I did mean $500b in revenue annually.
This is just the compute, which primarily covers training + inference. They still have to run the rest of the business. If you think AI should look like SaaS and spend 10% of their revenue on compute, that's $1T in revenue. If you think it's a hardware business, that's 30% margins and perhaps $200b in revenue. I went with something in the middle at $500b.
They won't disappear as a company at $200b in revenue, but I don't think that's their aspiration. These commitments imply to me that they're confident they can do much better.
Thanks for clarifying, that’s a huge difference. Obviously they will have other revenue sources, but will likely make a small portion of their revenue. If we approximate their growth rate by these numbers, it is quite a slowdown.
> Put another way Anthropic has committed 52 billion dollar a year
Idk where you got this figure from, but the actual figure are very different from that:
It's 120B over four years for SpaceX alone and 120B for Broadcom over 6 years. These two players, representing less than half of the total commitment, already give you an annual commitment above 50B.
Yeah, it's a crazy number, but they got the AI business right, just like Google got internet marketing right 25 years ago, as long as they keep the momentum (and prices).
> google launched at i dunno a 1bn market cap and grew as the internet grew
Google closed its first trading day "worth more than $25 billion" [1] with $1.5bn revenues, up 234% from 2002's $440mm [2]. That's a 16x revenue multiple, 0.07 growth adjusted [3].
On a similar revenue multiple, Anthropic's $16.3bn half-year earnings are worth $543 billion. Adjust for Anthropic's 1,400% YoY growth and you're well over $3 trillion.
Obviously, it's a lot harder to grow at a thousand percent from a $16bn baseline versus a few billion. But purely on a multiple basis, Anthropic is in a similar ballpark as Google.
As another check, SpaceX is trading at ~62x sales with a growth rate in the 30% range. Assigning the same sales multiple puts Anthropic at ~$2T market cap. Add in a factor for much faster growth (and non-GAAP profitability) and $3T is a really easy place to end up.
Sure, you can throw any numbers around, if you wish to get any valuation you want.
In reality, a valuation based on revenue (sales) is bonkers to begin with, but even worse when you consider that Anthropic has so much debt that it doesn't have positive equity value, it's in a deficit ("When liabilities attached to an asset exceed its value, the difference is called a deficit and the asset is informally said to be "underwater" or "upside-down""). At least SpaceX has more assets than liabilities.
There are a set of mistakes in what you wrote, but
> SpaceX has more assets than liabilities.
is definitely a choice thing to write on the day SpaceX announced a $40B debt deal to purchase compute to run other companies' models. Based on available information, this will put SpaceX into a place where it has more liabilities than assets.
> Put another way Anthropic has committed 52 billion dollar a year to these companies and their S-1 indicates they earn 67.2B a year in revenue.
A very large part of that revenue is paying for inference. There’s not enough leftover for the committed outlays. So it has to come from smucks I mean investors.
Meanwhile the Chinese are going to undercut them every chance they get.
Today's prices are the ceiling. But AI capability is getting less of a scarce resource with every passing day and it would be a big mistake to plan that your current margins are going to be your future margins as well. Long terms AI will converge on energy costs + capex write-off + margin and the latter will be a race to the bottom.
The problem for me is that it's really hard to project what this industry is going to look like 6 months from now, let alone 6 years.
What's the endgame once the dust settles? Is it going to be a utility like water or electricity and the cheapest offer will prevail, in which case margins will be crushed? Or is Anthropic (or some other big AI lab) going to swallow everything and become the Google Search of LLMs, with everybody else fighting for scraps?
Or is it local compute, models becoming more efficient and hardware becoming cheaper (again) and companies hosting their own AI clusters like they would run SAP?
I think there is a plausible path where this valuation actually works out, but it's a narrow one IMO. I also want to acknowledge that I personally would prefer if it wasn't the case and a more distributed, open model prevailed.
I just look at technology over the last 50 years and see: decreasing prices, increasing capabilities. Barring temporary hiccups. Altman & co did a very smart thing by locking up the GPUs and the RAM, they effectively created a temporary near monopoly. At the same time: that incentivized the rest of the world to look more closely at efficiency negating some of the gains of that expense.
It's just like a utility with the slight difference that it can be sold at a distance without significant cost for transportation, in many ways it is the ultimate digital good. Unlike Spotify copyright is not an issue, unlike your electricity, gas, internet or water company there is no last mile problem. Unlike Google there are a ton of qualified contenders already (Google had to be better than Altavista, which wasn't hard, but they were so much better they managed to lock up search for long enough to cement their position).
Anthropic has none of the advantages and all of the disadvantages. On top of that all AI companies seem to be run by megalomaniacs.
> On top of that all AI companies seem to be run by megalomaniacs.
Not all of them. Only those who outspend all the others and then you never really hear of any others. It's like the most basic requirement for the job.
> On top of that all AI companies seem to be run by megalomaniacs.
I think this might genuinely going to become a problem for them in the long run.
People just absolutely hate their guts. That's a very strong motivator to do everything possible to get rid of them.
We'll of course see in 5-10 years if the doom PR will work out, but that always was a rather high-risk gamble, and it already looks like it might not.
There is a significant amount of businesses and people that are very willing to switch to literally anyone else just out of spite alone.
It's not necessarily spite as well, it goes without saying that international relations between the US and its allies have deteriorated to the point yet another critical dependency Washington can turn off for geopolitical reasons isn't a very attractive idea for many. While I dislike a lot of Anthropic's behaviour, it was not their actions but the fact their models were subject to export controls which really motivated me to not be dependent on US providers alone.
My country has no frontier models; since I've no national grounds to support one provider over another, a strong degree of provider diversity is an obvious benefit to me. I also think a highly competitive global market is a good thing for mankind in general, any hegemonic power having a monopolistic or oligopolistic position in AI provision is probably the 'bad ending' for most of us since it represents an enormous concentration of democratically unaccountable power regardless of the power which 'wins'. I'd argue it's rational, not spiteful to favour provider diversity on those grounds.
Even inside the US, many businesses are looking at local LLMs because they don't want to get caught by USGOV restricting access to "frontier" AI models.
I really don't see any situation where local AI doesn't absolutely eat the big labs' lunch. They can't compete and the only way it makes any sense for them to exist is if the government somehow tries to ban local AI, which likely wouldn't work in the first place.
As a French person myself, I think this antipathy is less strong in non-English speaking countries, where the population (even if they understand English) is less exposed to the antisocial rants of these megalomaniac idiots.
Someone like me who spends a lot of time in the anglosphere puts faces on companies like OpenAI or Anthropic. I doubt that's true for most people, especially outside of the USA. They're just big companies, like 3M, DHL or Toyota. Who knows what the management of these companies think of the future of humankind?
I would expect than personality-driven rejection of American tech from abroad nowadays is driven mainly by Trump and, to a much lesser extent, Musk. Everybody else is just "some guy" to 99% of the population.
I'm not so sure if that assessment is true, but regardless of that, it also doesn't matter.
Decisions in tooling are not made by the 99% of the population, but a subset that is likely a lot more tuned-in to all this.
After all, that is kinda their job so that they can make good decisions
> As a French person myself, I think this antipathy is less strong in non-English speaking countries, where the population (even if they understand English) is less exposed to the antisocial rants of these megalomaniac idiots.
German here, every stupid utterance of at least the orange clown makes national headlines here. Frankly I wish our populations were more exposed to the utter buffoonery of the rest of the American wannabe elites, maybe people would then not go and type their deepest fears into ChatGPT.
I know I'm just one person, but I absolutely detest all of the rhetoric coming from these companies and what it means for software freedom - the FSF kind. I ABHOR the idea that free software developers have to either use the hosted (controlled) service, or go way slower than proprietary software devs.
So I'm doing what I can - I only use local models for 100% of my personal coding. (And their capability is amazing! Qwen 3.8 Flash Next leaves me wanting for nothing at this point.)
And I know open weights aren't enough. I'm ready to support open training if/when we get around to that. I hope once hardware prices ease, we can see homelabbers building small AI hosts (small by homelab standards yknow. So let's say 512GB host ram and 1-2 32GB cards, though i hope we also start to see AI cards with lots of vram but less compute cores). Then maybe we can do folding@home style distributed training.
In a time when software freedom is perhaps more threatened than ever, I'm happy to see that information still WANTS to be free, perhaps even more than ever. Look at how easy it is to distill claude! Despite, presumably, anthropic working very hard to prevent it.
The only thing protecting America's AI industry is the cartel of hardware and embargoes against sharing resources. Once those are cracked, they have zero moat. We're talking 1's and 0's at the end of the day, not nuclear engineering or nuclear fusion or some other revolutionary way to increase the value of real property.
>not nuclear engineering or nuclear fusion or some other revolutionary way to increase the value of real property.
Is engineering the factories that make the hardware not nuclear engineering? Even if not, considering there exists only 1 supply chain in the world capable of making them, it seems pretty revolutionary. And that moat seems pretty big, given that it hasn't been crossed for many years.
The long-term is considerably easier because in the short-term there are limits on supply so prices aren't really able to move in a way where balance will be found.
In the long-term, the marginal cost of a request is zero so prices will plunge and a lot of the fixed investment will get stuck. The difference between the cost of training a model/infra and serving a request from that model is a clear problem for economics.
What happens with Anthropic specifically is less clear because they, as every company in the same position in the last 150 years has done, are going to push for regulation. A lot of the risk has also been shifted onto neoclouds. The value of the customer relationship is, however, effectively zero. A core part of their strategy has been to build stuff out like CC to differentiate that but, ultimately, that won't work.
The other strategy they have employed is trying to get other companies to stop training new models. Again, seems unlikely to work.
There is no scenario in which they become Google search outside of government intervention. Obviously this is a key part of their strategy now but at best, this will only work in the US and Europe (I would actually say they are much further along in Europe where there is a strong tendency towards corporatism and centralisation of power, they could be "Europe's AI").
The only thing regulatory capture in the USA will do is to improve the situation for the rest of the world to compete. I wonder how long it will take them to figure that one out, for all their smarts they seem to be incapable of reading a history book.
> improve the situation for the rest of the world to compete
The risk is that USA and China will come together on a joint "AI non-proliferation" agreement in the same way that nuclear technology became restricted by the countries that already had the capability. This will lead to a de facto techno-colonization of the rest of the world just between themselves.
This was a topic of discussion at Trump and Xi's AI summit just last month.
Nobody cares about hobby models running on a 5 year old GPU cluster in the basement. This is about industrial-scale AI which, to date, only USA and China have accomplished.
If you think that these are hobby models you are simply saying you haven't used them.
One of the largest legal services partnerships here in NL just launched their local DC so they can maintain confidentiality. Do you think they are 'running hobby models on 5 year old GPU clusters in the basement'? Or does a couple of racks of GB300's sound like maybe they know what they're doing after all?
That is microscopic scale compared to what we are talking about. From an investor and "market" perspective, the only AI that matters is the one that's built into every iPhone and Google Android phone, every car, every TV, every smart appliance. The AI models that power ships, planes, and all kinds of robotics. The frontier AI that services the energy grid, and even the smart homes and very structures that we dwell in.
This is all on the horizon. We are only barely scratching the surface and right now it is largely hobbyist having fun with it, but we already see the potential of the AI revolution and where it is going.
Seems to me that from an investor perspective, the AI models built into the cars and TVs and other things are likely to be open source. I think long term, due to the high cost of training these models, there is going to be a "Linux of AI". I.e. some model that lots of companies collaborate on and then use for free.
The economic logic is the same as that of operating systems. AI models are very expensive for one company to make, but lots of companies need them. So companies are better off collaborating on that side of things and competing on something else.
Economically, the AI models that require big servers with lots of GPUs in data centers should likely be more interesting to investors than the AI models that can run on local hardware.
It matters from the perspective of tech dependency.
If a medium/small country deemed it a threat to rely on US/China for AI capabilities, they can get 95% of the utility by banning all American and Chinese models and just using local ones.
This contrasts to something like oil or nukes, where if you're not one of the countries blessed with them, you have a serious power imbalance.
Although I agree inference will become cheap (probably not zero), it's quite possible that there is a moat they can build around understanding customer context.
With each query OpenAI and Anthropic get more context about their users. When I compare answers between AIs the ChatGPT answer often includes useful things it inferred from earlier conversations. Losing that context could be a meaningful barrier for a customer to switch to a cheaper service.
> With each query OpenAI and Anthropic get more context about their users.
Not unless they break their own TOS. The temptation must be very large to do so and is probably why those settings keep mysteriously shifting back to 'yes, I give all my data to you to do with as you please'.
I don't think that's what GP meant. I think the point is maybe they could build a moat by "knowing you" in a way that makes you care about using Claude rather than, say, Gemini.
The evidence we have so far points to LLMs becoming commodities. I can’t think of a technology in the last 30 years where so many companies are within ankle biting distance of the leader. There seems to be no data aggregation moat like with Google.
Distilling just works too well. It costs much more to aggregate the data in the first place and train the first model, but once that exists and you are selling access, the second guy can train their model by using the first model to generate the training data.
The only ways to fight this is trying to either:
1. Block it by cutting off access, which is pretty tough because it basically means you cannot offer unmonitored access which is a no-no to a lot of customers, and even then the workload looks very similar to actual real workloads and if the company doing the distilling is a bit sneaky and using intermediaries etc it's almost impossible to stop, or:
2. Try to use IP law to block the practice, which is pretty gross given how they got the data in the first place, and so far no court has supported them on this. And even if they can make it illegal, it won't actually help because there are countries that see having top-tier AI as a national priority and will actually support their companies breaking laws to get there.
People misunderstand why Anthropic is being so stingy about granting access to their top models. It's not some kind of marketing ploy, they know that if they release them fully openly then there will be a Chinese open-weights model in 3 months that is just as good. Also the reason why they try to hide chain-of-thought and the probability distributions.
> the second guy can train their model by using the first model to generate the training data
Isn't this somewhat akin to a model learning from its own inputs? Doesn't that behavior lead to model collapse? Either the model is trained on pristine data, in which case it stagnates, or it's distilled from another model, which leads to model collapse.
I think the better analogy is kick-starting. Yes, you'd get model collapse eventually, but you can kick-start a new model by cloning an old one and then you start training it like a normal model from then on out.
Independent verification from non-aligned entities would be a minimum for something like this. Note how in spite of all of the claims not a single lawsuit has been filed.
These are more claims of the same kind from an aligned institution. There is no evidence offered.
You cannot believe intelligence agencies when they do not offer proof. Their job is to provide (reputationally but not factually) authoritative story lines that protect big business interests from competition overseas. Sometimes they protect US business by bombing their competitors.
Given Anthropic is basically just “distilling” the IP of others they’re in no position to cry foul when others run the same playbook on Anthropic IP. They can pound sand on that front.
Indeed, the hypocrisy is cringe worthy but the lack of proof makes it a transparent play to stop giving their users the ability to audit the token counts. "Here is your bill. You spent 20% more than last month, but we're not going to show you what you spent it on."
Top models, capable of discovering and inventing stuff, held back from public, and available only as for-rent research service (or whatever the relevant bureaucratic term is) to big corporations and government agencies like NASA, DARPA, NSF, NIST, DOE, etc. only.
I have a feeling that we, the public, will stop getting access to more intelligent models starting next year.. i mean, not the incremental ones, but, major ones.. like the one you got going from opus 5 to opus 5.5.
this suffers from the same prisoner's dilemma we already see at play. Any player can defect and in theory capture a "trillion dollar market". Once they IPO, then their service is to maximize (short term) shareholder value. Saying "we reject all the billions in recurring subscription revenue because we are hoping all AI providers will do the same, therefore creating a moat" isn't going to go over well.
The SOTA model dilemma is that you have to pay more and more to train models that focus on less and less of the AI task market, because 95% of tasks can be done by cheap small models.
There is a good chance of that. This will incentivize the rest of the world. Keep in mind that the world is much larger than the USA, that the USA has alienated a lot of parties that were its allies and friends not that long ago and that there are far more talented people outside of the USA than in it. Silicon Valley had the world by the short and curlies and then Trump came along and pretty much burned it all down. It will take another decade to know how big the damage is but it is probably in the trillions of $ of lost income and that's before we get into intangibles.
I don't want to make this discussion politicized.. but man... Trump truly burned everything down that the US built over decades of hard work and careful planning. And these things are extremely difficult to build back, especially in a world like today's.
Politics is intertwined with economics and finance. Unless by politicized you meant inviting opinions unrelated to facts. What you stated is a fact. The part that is hard to divine is if there's a larger end goal that justifies the loss of trust.
At this point, the best guess is he plans to deflate the currency to make the debt worthless.
>best guess is he plans to deflate the currency to make the debt worthless
That might be the best possible intended outcome, but it also seems unlikely that Donald Trump and his government are involved in anything so far-sighted. Just look at the man's public behavior over the last year; either he is an incredible actor, or this is not a government where anyone in power cares about anything beyond the Big Man's whims of the moment and their personal benefit.
Donald Trump is a puppet for those with bigger around him, but because of his mania and dementia, it's like having to roll a d6 whenever you try to steer him. I think that unpredictability is part of the issue making it hard to extract what the long term play is.
There's also the incompetence of the ones with the longer term plans making whatever is played out more inscrutable. Although they have actually implemented a significant portion of project 2025.
I personally think it's really funny how if you were to try to reverse engineer his motivations based on the actual outcome, then the most likely answer is that he's a joint Chinese-Russian spy based on how much they've benefited from his elections.
I've never seen an individual that was so damaging to the country that democratically elected him. There are others that were as damaging but they were not elected or it wasn't during my lifetime. Trump is unique in that respect, more so because he did it twice.
I agree with you but as they say "markets have short memories". After the Ukraine war is over let's see how fast Europe goes back to Russian gas. They're making noises about it now (and parts never stopped).
The world is going to be very different in another two years.
yes, you are no longer trusted. Europe is lucky that the UK and France essentially told the US to fuck off when they tried to stop them developing their own nuclear deterrent. If they had, then right now the alliance between Russia and the US would put the whole of europe at risk of Putins Russia. As it is the French and UK capability is more than enough to counter the russian nuclear threat. As in we all fucking die if russia launches nukes, but it at leats lets russia know that too.
fuck trump and republicans. and yes whatever goodwill you had built up over the last 60 years was up and away like a fart in the wind when you elected a corrupt pedophile for the second time. And it cant be built back, ever. No one trusts you no to pull the rug if we became reliant on you again. What we will have though is a relationship with allies built on equality rather than one main player calling the shots.
the trust could in theory be built back if they would manage to dethrone him and his cronies, hold a Nuremberg-style trial leaving out no accomplice and reform their system and constitution in order to setup real guardrails that would reliably avoid this from happening ever again. This would require, among other things, to severely limit presidential powers, or better yet, switch to a parliamentary system with a "first minister", and abandon the two-party system in favor of a more democratic proportional multi-party one. Sadly I don't think these changes will ever happen.
This is pretty much it. I don't think anybody believes these changes will ever happen unless it gets much worse than it is today. I would not rule that out though and 'ever' is a long time.
I haven't been back since Trump I. Missed a funeral of a friend. I still have more friends on the other side of the Atlantic than I have in Europe, even so I don't think I will ever go there again. Enough is enough.
How is it not clear that LLMs are being increasingly commoditized and that the foundation model producers are in a bad race to the bottom with each other AND cheap open-weight competition?
Not even just from Chinese models, but from companies/labs like Mercury
I wouldn't bet on local compute.
Even if it may end up cheaper in the long run, the convenience of just another SaaS subscription sure beats the high upfront const and continuous maintenance required with local deployments.
We've seen businesses moving everything to the cloud before AI, we'll see more of that as regulatory requirements are increasing.
>The problem for me is that it's really hard to project what this industry is going to look like 6 months from now, let alone 6 years.
i keep thinking how crazy it is we went from ChatGPT releasing in 2022 to multi-trillion IPOs 4 years later. the industry still hasn't agreed on how to generally use anything. crazy times ahead.
It's going to be "all of the above" because AI has a whole lot of use cases.
For certain AI use cases, AI will be like a utility. For other user cases you need to pay a premium for the frontier. For other use cases AI will be local.
Even in the industries you mention (water and electricity) you have all sorts of businesses. Like people selling water in fancy cans for a large markup or batteries vs wall power.
It's very possible given the current environment that LLMs go the way of airlines. Low margin businesses that are essential to world economics with heavy price competition.
and airlines are still finding ways to enshittify. flights included meals, now you're (un)lucky if they include biscoff. and that'll be $50 to check a bag. I can't imagine how frustrating an enshittified LLM would be. hey - I noticed this is a finance-related query. those cost 100% more.
And this is why I think companies will wise up and stop sending their information to the likes of Anthropic and OpenAI: they will not be able to maintain their edge if either one of them decides to defect and start using all of their uploaded user data to improve the model. So they have a massive incentive to break their own TOS.
That's the push factor. The pull is, say there's a giant repo like windows or Adobe. LLMs produce spaghetti code because the repo doesnt fit in the context and it wasn't in the training set. If Adobe fine tuned it the LLM would be much more useful.
It wasn't a theoretical thing, it was a practical thing. Just like when we talk about 'infinite tape' when looking at Turing machines. As opposed to 'clear boundaries to how much context you can have because that is baked into the model'.
When google became the king of search the incumbents were so far behind that catching up wasnt possible and they thought their position was entrenched anyway. With LLMs openAI's competitors are at or close to their capability already and everyone knows they need to keep spending to remain relevant. So unless the cash pipeline dries up for competitors that is unlikely to happen. The reason for that is anyone who has invested knows that either they give up and hand everything to their competitors or someone else does. Which means you need to keep spending to outlast your competitors. These companies are too rich and there is too much VC money around and enough billionaires with more money than they and their descendants could spent in many lifetimes, and a huge amount of greed. If the money runs out that is because some very bad shit has occurred and LLMs will be the leats of our worries.
Given the trillion-dollar spend, the theory is that every many woman and child in the western world will devote a substantial portion of their income (like 5-10%) towards some sort of AI subscription.
or...
That doesn't happen. All the AI investments go south and every man woman and child in the western world will devote a substantial portion of their income (like 5-10%) to bailing out an economic system that went all-in on AI. Either way, the money has already been spent.
The already shaky economic system (and associated political systems) can't take the strain of every man woman and child in the western world devoting a substantial portion of their income (like 5-10%) to LLM fallout, and we end up with a collapse scenario of some sort. (Which, to be clear, is near-certain to be worse than either of the above.)
I don't see a path forward for valuations like Anthropic, either the hardware requirements fall off a cliff (and why would people pay Anthropic so much if it runs on a cheap laptop?) or either they don't and they will never have the capabilities to serve all their customers (and why would they be valued so much then?).
It's a lose/lose situation here for Anthropic (and OpenAI) whatever happens.
> Or is Anthropic (or some other big AI lab) going to swallow everything and become the Google Search of LLMs, with everybody else fighting for scraps?
Of all scenarios, based on the data we have now, this seems to be the least likely one.
The Chinese labs are not providing their open-weight models for free because they think it is good for humanity. They are doing it because they are severely chip constrained due to the Nvidia and ASML embargos and all available GPUs have to go toward training with very little left for inference [1]. So they are giving their models away for US and EU hosts to serve inference in order to still have a presence in the market.
It's not a great position to be in and it will still take a long time for the compute gap to close. In the meantime, Anthropic, OpenAI, and Google are essentially unchallenged.
You should. Maybe they have it open now just to destroy competition and then they close it. Now you have a closed system, with no alternatives.
Besides...
"If passed, the rules would require Chinese companies to obtain licenses to export the core technology behind their leading models.
They would also ban the export of A.I. that can be used to launch cyberattacks, as well as models trained on what China calls “core data.” The government broadly defines that as data that concerns national security, the welfare of Chinese citizens and the public interest. Experts say the scope includes data on the military or critical infrastructure, state secrets and other sensitive information. "
> You should. Maybe they have it open now just to destroy competition and then they close it. Now you have a closed system, with no alternatives.
What makes you think there would be no alternatives, though?
Put it like this: Kimi K3.1 is downloadable and can be run locally. (If you have a datacenter.) This is a very capable, ~2.8T parameter model.
Now let's say that every Chinese firm goes closed in six months or a year and jacks up pricing... What's stopping a bunch of enterprising upstarts from updating all 2.8 trillion parameters, extending them, distilling the model into very competent flash models, or applying targeted RL?
Once the principles are understood and there are models that can be pulled off the open internet, it doesn't seem that hard to spin up your own LLM. You just need some financial resources and a reason for doing it. And that would come into play if the Chinese kill every closed American provider and then go closed themselves.
Training is really really expensive and open models are not getting funded by VCs. Distillation also doesn’t improve performance. Until training gets exponentially cheaper so that you can do it for a few hundred grand to train a competitive model, open models are labs trying to flood the market to get market share / undercut more successful labs, not a sustainable strategy that will extend indefinitely necessarily. It’s like claiming Uber and DoorDash are fantastic because their prices are so low - once they eat the market the prices become higher than ever.
Sure, but once they release an open model, it's open forever. You can download it, share it with friends, make a torrent, whatever. So in this sense every open model is a gift to the commons.
It's not quite like Uber. It's more like... well... imagine there are two computer operating systems, Gray and Teal. Gray is always slightly better, but it costs $50/user/month for a license. Teal is free. Eventually, when both happen to be in version 9.0, Teal puts Gray out of business. Starting from version 10.0, Teal starts charging $100/user/month from a license. But nothing's stopping you from sticking with 9.0, which remains free forever.
Perhaps what's "sustainable" is not clear, given that Gray was eventually dominated by Teal? In any case, versions 1.0-9.0 were, effectively, gifted to the public. We can appreciate (and even disapprove of) that commercial strategy while benefitting from its fruits.
> What makes you think there would be no alternatives, though?
There could be, they can actually come from open American companies too. Ask yourself why we aren't seeing a thousand or more American AI startups spring into life overnight to build "open" models. Follow the economics.
> What's stopping a bunch of enterprising upstarts from updating all 2.8 trillion parameters, extending them, distilling the model into very competent flash models, or applying targeted RL?
> And that would come into play if the Chinese kill every closed American provider and then go closed themselves.
What's stopping American or European tech companies from doing this today? It's economic and technical capability. I'm very suspicious of any suggestion that it is in any way not incredibly difficult to build and scale up LLMs. Maybe in the future it can be much easier, but in that case you run into a sort of tautology where it becomes easier but the leading companies continue to lead and do so by a significant margin because they're the ones that have the most talent and access to capital.
The premise seemed to be "an open China" versus a "closed USA". I'm not sure that's a great premise. If China can create open-weight models so can the US. If the US can close their models (as clearly evidenced by the article) so can the Chinese.
> What's stopping American or European tech companies from doing this today? It's economic and technical capability. I'm very suspicious of any suggestion that it is in any way not incredibly difficult to build and scale up LLMs.
Seems more economic than technical. If the economics are covered, the technical aspects seem straightforward enough, and may perhaps be fully solved. I think there's proof of this in that there are a lot of different LLMs on the market. Even Xiaomi -- in-between making cars, e-scooters, backpacks, and home appliances -- spun-up an exceptionally capable LLM! (And one which is rather idiosyncratic. It's weirdly good at music composition and generation, which both Opus and Astra cannot do.)
The economic case doesn't exist for VC-funded US corporations, nor does it exist for cash-strapped nonprofits. In China, all such ventures are likely funded by a government development bureau. If Chinese ventures kill expensive closed providers and universally go closed themselves, there's nothing stopping the US or Europe from copying that same playbook -- unless, as may well be the case, they're ideologically opposed to subsidizing strategic industries.
They'll be just as useful as they are today. Which is plenty useful. Just like my 10 year old laptop is still useful. I could replace it, but why would I, it serves me well.
I mean how useful are GPT-3 weights today? That's the kind of useful they'll be relative to the frontier.
I feel like the so-called "Deepseek moment" broke too many people's brains and they've lost the ability to reason about why frontier advantages matter. I think we have to learn some new core concepts and rate of improvement over time is going to be a big one, and not understanding that causes people to exaggerate the significance of downstream distillation that's done in response to it. It's cheaper and open and that matters, but it's not the kind of mattering that replaces the relevance or advantage of the frontier, and I feel like I'm not seeing people demonstrate that they know how to really compare the relative merit of these two things so much as zoom in on one to talk past the other.
Even the original DeepSeek is old hat. The capabilities already released are game changers, whether you want to acknowledge that or not is not my affair.
I was using GPT-3 and the original Llama when they came out and realized that it is interesting, but not good enough - yet. But they are good enough now. And just like there are still people driving Renaults and Volkswagens the latest batch of open models will be useful for a long time to come.
I just disagree, I don't think your 10-year-old laptop is very useful either.
It's like sure yea you can access the Internet and tinker around or whatever, and with some old LLM model you can have it do fun things, but on a scale of absolute usefulness and if we include what people actually pay money for and what is highly adopted, your laptop and model are severely outdated and by and large irrelevant. That's why the iPhone sells like hotcakes all day every day and twice on Sunday and Apple is a $5 trillion company. Society disagrees with your measure of usefulness.
Sorry I'm rate limited since Dang thinks I'm arguing to much on political topics (he's probably right), but to answer a couple of questions regarding "my old technology does this one thing" you are conflating your personal and nostalgic uses for old hardware/software with what is useful for society or business. If the old hardware was still just as useful as the new hardware it would be used instead of the new hardware.
> I don't think your 10-year-old laptop is very useful either.
Technology never was about the tech an sich but about what you do with the tech. For one person that 10 year old laptop is useless, for another it is a source of $500K / year in income. You, the user are the biggest factor in how much value you can extract from the technology at your command. I'm not sure how much longer that will be true but it definitely is still true today.
The laptops generating income are the relevant metric here; most software developers would struggle with a 4GB Pentium these days. It matters to your company and your economy if your engineers can work.
Compared to laptop quality, I suspect model quality will be a much bigger competitive advantage in the tournament of the marketplace. High-quality laptops are still limited by the quality of the software developer.
You're not wrong but the amount of leverage you get out of a better model dwarfs the leverage you get out of a better laptop. Almost to the point that these are different categories of thing.
Also... employment in some parts of the stack is genuinely going away. I don't even look at CSS anymore.
> the amount of leverage you get out of a better model dwarfs the leverage you get out of a better laptop
To some degree, yes. But 'dwarfs' isn't really the term I would use. It is a bit slower, but the upsides are >> than the downsides for me. Not having Sam, Dario or Xi's minions looking over my shoulder matters to me more than any technological edge.
> Also... employment in some parts of the stack is genuinely going away. I don't even look at CSS anymore.
Yes, that's a fact, but that's orthogonal. I haven't touched either HTML or CSS in a long time now and yet I've cobbled together (I wouldn't claim ownership) a lot of stuff that 'just works'. I also would not expose that stuff to the world at large because I suspect it isn't nearly as secure as it looks.
There is almost nothing you can do in CSS that has security implications. Not zero, but the footprint is small enough that I blindly trust the robots.
I pay attention to frontend code just to keep code quality up. Frontend work is relatively low stakes from a security perspective and I've never seen the robots do anything problematic. I don't vibe code React but I think you could get away with it today.
Backend is a totally different story.
That's still a lot of engineering getting displaced.
They're already useful. People are shipping real products with them.
Also, it's entirely plausible that an previously open model (that then became closed) will be much easier to distill than having a bunch of closed models.
When you're not in the lead, your best strategic move is to neutralize trade secrets advantages of the leaders. I think a strategic approach is being misinterpreted as a demonstration of virtuous ethos, which is crazy given (as the other commenter mentioned) the norm of secrecy when it strategically suitable in basically every other context.
China bans all sorts of things, so this doesn't really matter. I actually view it as a good thing. Americans get the best access to the best technology and we can go on to use it to maintain or gain a leading edge in the progress of our society and businesses. Why would we want to give that away for free so people from countries like Russia or China can build competing companies or use these tools to undermine our society's aspirations?
> for free because they think it is good for humanity
I like Qwen as much as the next person, but that's a bit to credulous. Those models would not get the compute allocation nor distribution they do if it was not aligned with broader policy.
There are dozens of Chinese domestic AI accelerators: Huawei, Alibaba, and Baidu all have chips, there are a bunch of smaller startups too. The chinese mainland is behind on leading edge fabrication though, SMIC only does ~7nm class since they don't have EUV.
This might just be the thing that tips the scales in China deciding invasion of Taiwan is worth the risk. They're eying the Russian war warily though, if they can keep the United States distracted long enough and the EU at bay by continuing to bankroll Putin then they just might risk it. The window for that is closing though.
The online crowd harping on about Chinese models is disconnected from reality imo.
I won't use a Chinese model. Why would i bother? I pay $100/m for the frontier model, understanding it's marginally better than much cheaper alternatives. I get so much value from the product it's not worth shopping around
Think of it like apple and android. Plenty of people pay 2k for their iPhone every few years when android at 1/4 the price is just as functional. Why? Because they get so much excess value from the device it's not worth shopping around. For most people it's their only personal computer. From booking airfare, to filling out their kids permission slips, it's a device they use 10+ hours a week. They don't bother, until a paradigm shift happens and something is 10x better than the iPhone. I imagine llms will follow the same trajectory
You aren't paying API prices. Anthropic (or OpenAI, SpaceX, etc) are almost certainly losing money on your subscription. How long they'll be able to continue to subsidize your usage is an open question, but they definitely won't be able to do it with everyone (currently, their solution is to make enterprise users pay per token, but that might change). What that means is that for the customers that the frontier labs need to be profitable, going with a closed weight provider isn't "marginally better intelligence for marginally higher (or even lower) prices" but "marginally better intelligence for much higher prices".
I get (sometimes) frustrated with people that don't work in the tech industry over this concept, and having them rationalize that their usage is heavily subsidized by the distributor of the model.
The costs in compute, electricity, cooling, etc. per token is much higher than most people (I feel) who work in the industry realize. Which, cognitively makes sense: they just want the 'magic 8-ball' to give them a tasty dinner recipe that meets their specifications, for example, and don't care how the 'sausage' is made.
However, economies generally equalize with supply and demand, and this (most likely) will become cheaper as the technology progresses and optimization passes/new algorithms are discovered.
Exactly, like it has done in cycle after cycle in the past. It would be very naive to assume that once you have a moat it will stay that way with a thing like this.
Yeah. People have very strange ideas about competition and choice and moat. If all you needed to unseat the entrenched was a competitor then Bing would be going toe to toe with Google, and Edge with Chrome. They have a billion+ devices they can stick those options as defaults and still nothing. There are many examples.
People are naturally sticky. If they're satisfied with a product, they'll stick around unless something comes along that is so much better it gets people talking. Open AI's 1B+ customers won't give a shit about Chinese models. Enterprise customers won't move to Chinese models, especially just to save money. They are a non issue, especially if the M.O is just going to be playing catch-up.
They're sticky, but not for everything. There are common goods where the market has commoditized greatly because customers are conscious of quality and not provenance. Something like apples.
Only because anthropic&co will price themselves just below the cap where people contemplated switching. In so, the Chinese models still set a sort of cap on the prices they can charge, even if not directly.
I can understand that they might be cautious about sharing their data with a Chinese company.
But them being the most successful companies means that they can just buy their own hardware. And run whatever models they can get their hands on in there.
Even if those models are Chinese. They (the companies running them on their own hardware) would be in full control then.
I would happily bet that > 50% are already doing just that. Whether you'll be able to collect the data is another thing but they'd be fairly stupid if they haven't at least checked out what is available. It would be next to irresponsible not to do so and given that they're in the S&P 500 you would have to at least give them some credit.
It's not about quality, but more about processes, for example we handle EU, US personal, financial data etc, we have strict rules about it (company rules, and gov ones), and there is no place for chinese model here.
At $100 / month (or $1200 / year) it may not be worth it, for you. But many of us would be spending a (large) multiple of that and then thinking about how much you spend, where you spend it and who you spend it on can make a big difference. For companies there are other considerations at play as well, for instance trust.
First off, $2k is the price of the new iPhone Duo. Suggesting that that is basically the same thing as a $500 Android phone is... strange.
But also, I don't think you should use individual consumer behavior as a proxy for how the overall LLM market behaves. Current estimates are that individual users represent a pretty small share of overall genai revenue. Most of it comes from enterprise contracts. Those might be more price sensitive because the CFO gets a say in which vendor they choose.
For a couple years now I've been accustomed to choice of foundation model being a heavily scrutinized design decision because it's just about the easiest way to manage COGS. I can certainly imagine scenarios where, given the option to pay 1/2 as much in inference costs but with a 5% reduction in output quality, the boss would say, "Nah, that's a bad deal." But I have yet to encounter one in the wild.
> First off, $2k is the price of the new iPhone Duo. Suggesting that that is basically the same thing as a $500 Android phone is... strange.
Okay fine, it's $1,400 for a latest iPhone Pro with 512gb of storage. Point still stands.
> Most of it comes from enterprise contracts. Those might be more price sensitive because the CFO gets a say in which vendor they choose.
I think enterprise contracts are even less sensitive to price than consumer. That's the whole idea behind enterprise pricing. You'll see companies charge multiple times as much just for SSO for instance.
There are limits to this obviously, but to think that major commercial enterprises will switch over to some Chinese models to save some money is laughable.
> Okay fine, it's $1,400 for a latest iPhone Pro with 512gb of storage. Point still stands.
So you switched away from the specialty product, but you're still comparing a top of the line 6.3 inch iPhone to a mid-market Android phone. Why not compare it to a Pixel 11 Pro with 512GB. That way they're at least comparable devices. But also, that would cost $1,220, which I suppose doesn't go well with the intent of suggesting iPhones are several times as expensive as Android phones.
The reason why I'm digging in on this is, when you start your argument with such a transparently silly comparison, it gives the impression that you're dealing in superlatives and willing to say just any old thing. Which undermines your own credibility.
So, getting back to corporate - multiple times how much for SSO? Okta Essentials is $17/user/month, which is a little over half as much as the base price for Cursor Pro, and about 2/3 the price of a basic ChatGPT seat.
tbh iPhone genuinely doesn't have anything over chinese models, and if there is any illusory sense of privacy, that is purely marketing. Genuinely people thinking iPhone is anywhere close to worth it lose respect because they are at the end of the day just tribes that love one thing
But if you’re a heavy user you’re probably paying $100 for something that costs $1,000. Hence Anthropic’s problem. If they charged real prices to the masses the massses would flee.
There's been a headline circlulating lately: 80% of Anthropic's revenue comes from 1% of their customers. The $100/mo or however much individuals are paying doesn't seem to be material.
I spend extra on a smartphone because I use the thing all the time, see it all the time, hold it in my hand all the time, it's my camera, music player, note taker and so on.
For AI? Prompt comes in, tokens come out. The value of the 'ecosystem' is roughly zero to me. Switching costs between models are essentially zero. The UI and UX is the same whichever LLM runs underneath.
If you do use llm some, then the $20 tier makes sense, but that's not where the money is. If you use it a lot then a $100 sub probably makes sense. But if you're a BigCo that heavily uses it and pay API prices and suddenly you pay $200 million a month, well, maybe it's worth buying a bunch of hardware and stick it in a basement somewhere, and you won't upload all your secrets to your future competitor to boot. If US labs didn't care about the competition from Chinese models they wouldn't lobby so hard for banning the evil, unaligned, super dangerous communist models that want to steal our freedoms and make our gas expensive.
Ultra-cheap models like Deepseek are also very nice if you need to burn billions and billions of tokens.
I was playing around with OpenCode on Omarchy over the weekend, working on my Android app, and was struggling to spend a single dollar with DeepSeek. The quality difference from the frontier models I use at work was hardly noticeable (where I typically rack up at least a few hundred dollars per month).
LLMs are not a luxury brand that individuals buy. Companies are always looking to save money. And their enterprise consumers are all developing their own models, so idk where you are getting this "analogy" from.
When the chinese or any other party releases a model that is Opus 5.5 level, there might be a shift to other providers as especially people in the EU are trying to get rid of their dependency on american stuff.
That's a great way of putting it and something I have come to realize as well. I'd rather just pay for the frontier model if I trust that it is indeed at the frontier and works reliably. Same with the iphone.
"I am spending a provably untenable amount for a services that will have to degrade to meet my price point, the cheaper options and processes are beneath me"
Anthropic doesn't care about sub users. At all. The real target is pay pig enterprises that give their employees access to the API and allows them to go buck wild spending $1000 on fable in a day.
I thought you would have also mentioned the use they make of data collected from loss leader subscribers, from at least those that don't disable collection.
With that, there are at least three distinct reasons to care about subs: PR, hook and training data.
Wish there were more case studies on what people were actually doing. Building out an entire factory sounds amazing. Are they actually getting that level of value out of AI?
Sounds like this will be another one of those things where everyone makes their money and it then will eventually become something experienced people 'blog' about.
> Wish there were more case studies on what people were actually doing. Building out an entire factory sounds amazing. Are they actually getting that level of value out of AI?
I don't doubt it.
> Sounds like this will be another one of those things where everyone makes their money and it then will eventually become something experienced people 'blog' about.
Or not. The problem is that right now you and a whole bunch of others are trying to outrun a pack of lions. The lions have already taken down a couple of your group. The people further ahead have seen what the lions can do and they are attempting to speed up to the point that they can outrun them. Whether that will work or not depends to a large degree on what the other people are doing and they are not going to make it easier for them to keep pace.
That partially explains the lack of deep insight blog posts, besides everybody is just too bloody busy.
Don’t know why this was downvoted but basically correct. OpenAI is in a price war with Anthropic right now for enterprise api consumers and that’s the biggest revenue line item for both.
They were counting on a duopoly so they could split the market between them but then someone decided to spoil their little party. To what degree that was an accident is anybody's guess but the timing is certainly interesting.
It's really marginally better and in some cases actually worse. If 100 dollars is throwaway money for you, and prices don't increase sure why switch. For heavier users, and for people with less money(most of America is struggling with bills and food) it's not attractive at all.
> Why would i bother? I pay $100/m for the frontier model, understanding it's marginally better than much cheaper alternatives. I get so much value from the product it's not worth shopping around
Wait until you are forced onto an enterprise plan...
The LLMs don't have the moat that Apple has. Apple has carefully built their walled garden to keep people in. Their messaging, their cloud services, their media store, it all keeps users in.
LLMs don't have that. For at least 90% of users, the model in the back end is completely irrelevant to them. Switching to Kimi won't lose them their iTunes music.
You won’t use a Chinese model, and I won’t either. But both of our bosses have much higher incentives than we do to routinely shop around, and unlike us they can convince an Anthropic sales rep to give them a discount.
Anthropic is not in the model business. They were smart and they are building productivity ecosystem business. Look at what claude artifacts are doing now -- inline multi-user editing, comments that users and/or models can respond and take action on, import/export from all common formats. It's at least a Google Docs killer if not an M365 killer.
And claude code as a harness and skill/plugin/mcp ecosystem is far more valuable than any one model.
And coward for long-running tasks, though they're slipping on that one because they're really trying hard not to make Claude an assistant. We'll see if they react to Muse and change course.
But the Chinese free-weight models? Not a competitor. If/when those companies (or others) build vertically integrated productivity stacks on those free models, then we'll talk. Microsoft certainly saw that opportunity but couldn't get out of their own way and are basically roadkill at this point.
>Anthropic is not in the model business. They were smart and they are building productivity ecosystem business... It's at least a Google Docs killer if not an M365 killer.
Google Workspace revenues are something like $25bn/q, and that's the entire workspace division, (including enterprise gmail sales, so the productivity suite is meaningfully smaller than that figure). It's taken Google a long time to carve that slice out of Microsoft's entrenched market position. It's not small money, but they'd basically be going to war with two of the largest and most profitable companies in history on their turf.
I don't think they can credibly take that business plan to the market and say it'll be worth $1.75tn. They're all-or-nothing on being in the model business, and everything else is superfluous.
What do you think Google Workspace would sell for, if Google divested?
$100B/year in revenue; SaaS so call it 70% gross margin, 30% net, NPV is about $500B.
Not enough if you think that's the only revenue Anthropic could every have. But even if they only peel off $100B NPV, it's incremental to an IPO valuation.
I mean, a lot of people before them were "not in the model business" (Cursor et al) and it seems they got disintermediated by the model companies. Step 1 is still to have the best model, or hope for model progress to taper out.
Vertical integration is hugely valuable, but revenue comes from the top of the stack, not the bottom.
Apple makes great margins on hardware. They are 100% not in the CNC milling business. But their investments at that low level and vertical integration allow for higher margins at the top.
Cursor had... nothing. A minor, indefensible value add to a much larger and wealthier supplier.
I think you’re right - it’ll be interesting to see how the behemoths navigate when new and cheaper memory manufacturing capacity comes online. Currently predicted to happen starting 2028. That is where most of the current hardware costs are concentrated.
On that front, I think DeepSeek is a dark horse. They are really odd - not chasing revenue, care more about unit profitability, are obsessed with driving down costs (like Elon back in the day). As the founder says, they are content with where they are, being the model that does 80% for a fraction of the cost.
I mention them because they are playing a different game and might be able to out-innovate everyone else.
Deepseek has been a game changer for me. I don't use them right now but the model is very capable.
What a lot of people don't seem to realize is how much of the edge of the 'frontier' is in the tooling, the prompts and the harness. The LLMs themselves are already all reasonably close if you keep all the other stuff constant. Sure, one will have an edge in one domain or another. But that edge mostly translates to a degree of performance rather than some absolute. And if you allow for a few more toolcalls, a web search or a longer context then that difference is much smaller than it might seem at first glance.
The calculus may be that DeepSeek (or similar) + human is good enough and that the frontier simply won’t have the growth to get to the next level that differentiates them and justifies the token cost. They get stuck in a race to the bottom which is opposite of what they want.
Are today's prices actually the ceiling? OpenAI added a $500 tier pretty recently while lowering capacity for their $200 tier. I wouldn't be surprised to see Anthropic doing something similar soon, particularly once they are a publicly traded company beholden to making shareholders happy.
Even outside of the Chinese models, Amazon, Google, Microsoft, Meta all of them are offering significantly more coherent and competitive internal models and reasonable price.
What's it like co-editing a combo document/workflow with multiple coworkers and an AI agent on Amazon, Google, Microsoft, or Meta?
Like if you want to design a survey you can send out, and collaboratively edit and test the survey, ask for changes in layout, wording, etc, and design the statistical analysis to be used, before sending the survey out where end users can fill it out right in the doc, while internal users/admins can ask the agent about its results?
Honest question -- that all works pretty well in claude. Amazon, Google, Microsoft, Meta all pretty similar?
Cloud compute has managed to have pretty good margins. That seems like a really similar business model to what Anthropic is doing - inferene+value-adds as-a-service. Why wouldn't they also be able to get cloud level margins or a bit higher?
Lots of people seem to have pretty short memories (or are too young to have seen it), but the flight from "local service" to "cloud service" was intense.
Companies don't mind paying extra to have a another company that does nothing but said thing do said thing for them. It even actually often ends up being cheaper/more profitable.
I don't think AI will be able to sustain cloud compute-size margins. Inference is a commodity and value-adds can't be sold for anything. Why pay for an advanced harness when you can just ask the model to build one for you?
Observing SaaS vs using an open source stack in the beforetimes, the answer might be some combination of, "So I never have to think about it, and if anything goes wrong, no one can blame us because we went with the biggest & most trusted provider."
Already well documented that there is huge variance in inference serving efficiency; at every layer (model, software, hardware) you have opportunities for gains. Similar to how “the Chinese” haven’t undercut on cloud providers’ CPU offerings, there’s a very good argument that the hyperscalers will manage to keep their vertically integrated hardware/software edge here too.
I don’t really know where this commodification idea came from, maybe MBA types that don’t actually understand how cloud economics work, applying basic first principles analysis?
The operational engineering that goes into serving a frontier model is _highly_ nontrivial, it is not commodifiable. This isn’t a SPA application.
>The operational engineering that goes into serving a frontier model is _highly_ nontrivial, it is not commodifiable. This isn’t a SPA application.
I don't really see it frankly. Admittedly I never tried it (I only played a bit with local models) but conceptually how is it much harder than all the other cloud services that already exist? My educated guess is that building a competitor to Netflix, Youtube or Dropbox seem technically a lot harder to get running than offering inference on demand for instance.
It seems that the main barrier for competing in that market at the moment is getting your hands on the GPUs/RAM and a datacenter to put them in.
> Similar to how “the Chinese” haven’t undercut on cloud providers’ CPU offerings
No Western company will be allowed to choose a Chinese cloud provider by their legal department or by their stakeholders. Which leaves only the US cloud providers as viable sources (as us, Europeans, have been too busy building our revenues based on turism and other such non-tech thingies instead of building real stuff).
That depends on whether "frontier" models can maintain an expanding frontier. If the frontier settles, they're dead, and it will be commoditized. Otherwise, there are still plenty of pathological behaviors of these things to address that will keep expanding that frontier (if that's possible and the limitation isn't the approach itself).
The reception of saying things like this is interesting. AI stans think I'm way too pessimistic but AI haters think I'm mindlessly optimistic.
Today’s prices are a ceiling for today’s capabilities, but not at all a ceiling in general. One could imagine dramatically higher spend for dramatically higher performance.
there is no point of saying 'the chinese'
everyone will do it because it was proven that any political frills might cause an attempt to damage your system.
I dont know when, but i think if you keep menacing of taking technology of people hands for any political reason will be a reason for people to not use it or to rely in a more reasonable party.
The point in mentioning the Chinese is that they are doing this today. In Europe there is Mistral but I think they're too far behind the frontier to really matter but in time they may catch up.
I don't think today's prices are the ceiling, considering they are subsidized. Once businesses have grown dependent on AI (and their institutional knowledge is lost), they will pay much more just to stay afloat.
Unfortunately it's now extremely likely that our governments will manipulate markets to keep frontier domestic AI afloat. They are financially and militarily dependent on domestic AI now.
Chinese models are being banned, will continue to be banned by USG. Even the Chinese govt is restricting external access to models now. It starts with banning Govt access to International AI, but will continue to consumer and business access.
> Meanwhile the Chinese are going to undercut them every chance they get.
I wish they were, but I always wonder when people chime in with Chinese models what they are actually doing with those. I have an OpenRouter account and give various models a shot every other month, wishing for an alternative, but I always come back to Claude. Even more so since the switch from Opus 5.1 to 5.5. To me, personally, it's unmatched. Like a year ago it was very different, and I would use other models all the time. But honestly at the time they all felt kind of "meh" still. I just hope everyone is at a good baseline in a year from now on, so I actually have a choice. And then, as you stated, things will get interesting.
I use Opus 5.5 daily at work and a mix of GLM 5.3 (Flash or not), Deepseek v4 (flash or pro) at home and while Opus 5.5 is more capable, in my opinion it matters for less than 5% of the work i do.
These chinese models are simply good enough for the vast majority of tasks I run and when they're not I use Astra or Opus 5.5.
Yes, leaving Opus 5.5 on all the time is comfortable when you pay the 90€ plan but it's just not necessary.
I use Opus 5.5 at work and I use Sonnet 5.5 at home. Sonnet 5.5 medium according to AA cost per task is $0.48 per task, while GLM 5.3 (max) is $2.01 (opus 5.5 high is $1.82). GLM 5.3 flash is $0.28 per task and Deepseek 4.1 flash 1017 is $0.26.
So it seems like Sonnet 5.5 medium, GLM 5.3 flash and Deepseek V4.1 flash 1017 are all in a similar space in capacity and price, however the $20 anthropic sub will get you like $200-$300 in sonnet 5.5...
Another bonus is that sonnet uses a fraction of the overall tokens and finishes much faster than the average chinese model, so your work goes faster (Sonnet 5.5 medium in 2 minutes, Deepseek 1017 in 6.5 minutes, GLM 5.3 flash in 13 minutes...)
I still don't get why paying for chinese inference makes sense. I should try Haiku 5.5 high/max because it's posting higher numbers than Deepseek V4.1 flash for half the price
Yeah, I spent the last week with Deepseek Flash 4.1-1017, Kimi 3, and GLM 5.3 (and 5.3-flash). None of them were literally useless but also none of them were capable of making progress on the main project I am working on where Opus, Sol, and even Gemini Flash have all done very good work. Benchmarks might have you believe open models are only barely behind the big US labs in intelligence, but it feels much worse in practice.
I am running GLM 5.3 Flash locally at home for coding and from my point of view it is indistinguishable from the frontier models of 6 months ago. It can handle almost every task I throw at it.
I have 2 DGX Sparks, 256 GB unified RAM, so not a cheap set of hardware. Luckily I bought them before the recent price increase.
However even with a high tier gaming machine you can run one of the Qwen models and it will be good at coding... like having an intern with boundless energy that will sometimes make mistakes but in general save you a lot of time. And for automating tasks involving scanning documents or creating summaries it will be brilliant.
Comments here are not considering what Anthropic is doing with Claude as a product. The models matter, yes. But they are building Claude into the only tool you need to get business done. In the past few weeks they have added slides and docs - a shot across the bow to Microsoft's dominance. If they can pull off building the best interface to get work done, $500b in revenue starts to seem not too crazy. It's more about selling a complete product than it is about selling tokens.
I somewhat agree to what you said, but also, the whole point of agentic coding is that "code is cheap". So I can't imaging companies like Google not having the resources (whether human or token) to build a better agentic assistant/harness than what Anthropic can. I mean Google has a pretty good starting point with Google Docs, etc.
Business people do not even know what that is. Are you talking about models when the rest of us are talking about harnesses and the interface people use?
Google’s issue (and many large companies’?) is organisational. Google has famously launched a bunch of products to compete in multiple markets, only to sunset these products soon after.
Everybody, everywhere pretty much always underestimates maintenance. And AI sucks at maintenance. It’ll just as likely nuke everything than actually maintain a piece of code running in production.
One big thing: Opus is one of the few models that you can mostly trust not to get prompt hijacked. This can make all the difference between trusted in the office vs. not.
the market for their valuation is just not there imo. they need to significantly expand into non-coding products and outshine their coding offerings to make it work.
as in, if they capture every single professional software dev and extract $1000 from them every month, their yearly revenue will be like $500B. do your own back of the envelope on that with ongoing costs and consider how unrealistic a goal this actually is.
even worse, the very product they offer is self limiting. if it becomes so good as to actually replace software devs, they will have less customers to extract money from.
their valuation essentially relies on a small percentage of mega users having unheard of levels of spending.
the part about a small percentage giving them most of their money is already true (their rumored $100+ bil revenue as of mid 2026 already outshines all software devs having a $100 max subscription), but they are two orders of magnitude or so away in terms of the actual amounts to make it work.
>as in, if they capture every single professional software dev and extract $1000 from them every month, their yearly revenue will be like $500B. do your own back of the envelope on that with ongoing costs and consider how unrealistic a goal this actually is.
The market for Claude Code is much bigger than professional software devs. It's really anyone who uses a computer. I already know normal people who have been using it for personal software.
What do you mean, "what's my source to the contrary". What you wrote has absolutely zero connection to what I wrote. Did you mean to reply to someone else?
Not really. Random non tech users won't pay $100/mo. Nor should they, most people will be served fine by whatever free thing MS bundles in Windows next year.
Also, most people don't want to build software. They just don't care. There'll be tinkerers like with anything, and I'm sure some people will create solutions to their niche problems with (as you say) 'whatever free thing MS bundles in Windows'. But like the programming trope - they'll build the 'ultimate' todo list and feel like it's an amazing achievement, but be back to pen and paper/notepad/todoist within 6 months.
In most office jobs, at western salaries, you don't need much productivity improvement to offset $100/mo
Though I would expect the majority to do fine with $20/mo. That's the same effective cost as replacing a $500 computer every two years, which is the sort of expense most companies are comfortable doing without much second thought
You don't need to spend $100/mo. They have other price points. And I think you and others are underestimating the appetite out there to be able to create personal custom software. It's empowering. Like I said, I see tons of people I know who can't code who have started doing this (and been very happy with it).
The vast, vast majority of people are happy enough using free chatgpt. Openai could just add a kind of online app development/marketplace thing to chatgpt and that'd entirely steal the personal custom software thing. But I don't really think most people care that much.
You don't have to skip the plumber or the mechanic many times before $100 becomes a plainly obvious need.
It's not gonna install a shower for you, but it will confidently walk you through that leaky faucet. And I don't know if you have paid a pro recently, but they don't charge $20 for a 20 minute fix.
To boot even if you skip the free models, you could probably do a year's DIY assistance with 50 cents worth of GLM or Deepseek tokens. And the really costly jobs are ones where an AI assistant won't really help since, shockingly, most of the cost is hours of labor which you would have to do yourself.
Indeed. On the other hand, I fixed my underfloor heating with the free claude version, so unless they remove the free tier, I still have no reason to pay for it.
It's quite a leap to assume any kind of issue would require a $100 subscription. Plumbing, mechanics, electricity ... The issues are usually far easier to trace and debug than in software, because the systems have been designed by smarter people.
You're not buying some arcane and complex solution, you're buying the convenience of not watching a couple of youtube videos or articles of someone troubleshooting the exact issue you're having.
leaky faucet fix is already supported by gemini on google search lol, this usecase doesn't need 100$ anthropic model. And if you think google will be bleeding on gemini you're just dead wrong
> How often are people paying at least $600 annually for something AI can help them do instead
I'm going to need an example on this one, and examples that can't be covered equally well by a YouTube video or an 20 year old forum post. It also has to be legal, as in not violating codes for electrics or plumping, I can violate those on my own for free.
Most people have no interest in fixing the leaky faucet themselves, even if the already knew how and didn’t need an LLM to explain how. They’d rather pay someone and do something else with time saved.
>"How often are people paying at least $600 annually for something AI can help them do instead"
AI recently told me that my oven was broken because a part that doesn't exist on the oven I own was malfunctioning. A bunch of people poking around with electronics, motors, etc. because they think their AI chatbot can fix anything and everything is going to lead to injuries, deaths, and most assuredly more money in the long haul.
I agree, I would say $500 billion valuation is fair, they don't have a moat and open models are catching up, they have a limited products with strong competitors, if they have a step change model in the pipeline now would be a good time to release it.
>the market for their valuation is just not there imo
I tried to look for the valuation in the linked document, did you see it or any reference to a valuation elsewhere in anything published by Anthropic? what is "their valuation" that you refer to?
If you owe the bank a million dollars you have a problem. If you owe the bank a billion dollars the bank has a problem.
The same logic applies here.
Google, Amazon, Microsoft, Meta, Broadcom, Nvidia, SpaceX and others are spending hundreds of billions a year each on fast-depreciating infrastructure to serve this potential AI demand. If the demand never materializes then they know they are in big trouble. So they have every incentive in the world to prop up Anthropic (and OpenAI) and keep the party going.
Can they keep the bubble inflated indefinitely? Probably not, but all these companies combined have heck of a lot more influence than Anthropic alone.
They aren't "fast-depreciating infrastructure" -- research shared by a16z team, rental rates are up across the board, even for GPUs that are 5+ years old. The demand is real right now. The proverbial tide could go out but we aren't seeing it yet.
That’s because of current supply shortage, not inherent value. Is there any reason to believe that when fabs can sufficiently scale up production these GPUs will continue to be valued like gold and not something you hold on to for a couple years and then toss in the bin for a newer faster model – aka how computer hardware economics have worked for the last 50 years?
Yeah the fab shortage is really keeping lifetimes long, far longer than in the past.
I've brought my old GTX 1070 out of retirement for for some molecular dynamics these days because its "free" except for eh electricity and have Ben pleasantly surprised at what it can get done chugging along in the background. I'm considering buying some more, as it's kind of a steal in pricing.
> Everything comes back to whether the demand is really there
And unit economics.
HY1 2026 revenue less compute and infrastructure turned positive (45% gross compute margin; $8.9bn C&I to turn $16bn revenue) for the first time; it was -176% in FY 2025 with $7.3bn C&I on $4.6bn revenue.
It looks like a lot of costs of revenue are in sales, marketing and partnerships, though. Backing those out shows H1 2026 margin at 26% ($4.2bn) after -72% for FY 2025. Still positive.
These were ~Q1-Q2 commitments based on what Anthropic THOUGHT token maxed compute demand was going to be over next few years. Then Late Q2, and Q3 PRC models dropped floor for token prices. It may very well be that Jevons demand which Anthropic though required 500B of compute now only requires 100B, and unless demand is 5x what they thought, those additional 400B non hardware cancellable commitment are going to be balance sheet concrete shoes.
> they will keep doubling down, because stopping is simply not an option
Of course it is. Apple is taking that strategic approach. If Anthropic believes it’s approaching saturation, pulling the plug when it’s at steady state and its rivals are over-invested is the winning move.
Well, unlike Apple a lot of very aggressive investors in Anthropic are riding on its trillion dollars valuation. They just can't on their own decide to stop or slow down.
Apple has a lot of actual money, Anthropic does not. Apple sells a lot of products, Anthropic doesn't. Apple have a platform multiple players want a piece of, Anthropic fight to stand alone.
There's very little comparison to be had here. Also, Anthropic likely have investors with way too much leverage for them to stop.
...exactly this were my thoughts when reading the response:
Maybe Apple is just waiting on the line until someone can be sucked up at a penny if the house is on fire - and pretty sure, this will happen. Not in 2027, but I expect MA activites & consoliation before 2030
The obvious business is rewriting all of our software. That sounds flippant, but I'm entirely serious. I'm of the opinion that all software written by humans will get replaced and in pretty rapid order.
First to fall is the software that has basically been abandoned but industry leading and has sticky customers. We're replacing those right now. Our version is more accurate, ten times faster, and a hundred times cheaper.
I have a hard time believing they are likely to get to $500bn in revenue. That’s another $450bn in revenue growth that needs to happen before demand tapers off.
But I see every reason to believe demand will taper off. It seems it’s already happening. Enterprises have been deciding that maybe corporate chatbot and coding agent budgets shouldn’t actually be infinite. AI startups are starting to successfully outcompete each other, effectively killing off members of Anthropic’s customer pool in the process. And consumer demand for AI products seems to be dropping. None of these are signs that suggest that Anthropic has thus far met only 10% of plausible long-term demand.
Total global wages ~$12 trillion/year. The "what you have to believe" here is that AI tool spend becomes at least 10-20% of it, my belief here is we see net slowdown in hiring as human + AI = super productivity so as businesses grow we'll continue to see increase in AI spending.
Then if inference does grow to a $2-3 trillion/year market that Anthropic is a big winner, as big as NVDA is now (they're going to be over $500 billion in revenue in calendar year 2027).
Products don't exist to serve themselves and code is just a fraction of what makes the world go; wages go down, spending goes down, free capital to spend on iterating goes down.
It's part of the reason so many of the dark enlightenment dorks are pushing more towards automation of control.
At this point, though, “human + AI = super productivity” is looking more lime dogma than reality.
The pattern seems to be that it makes people more productive when you measure it in terms of raw work product volume. But not all work product is equally valuable, and we have yet to see a clear pattern of increased economic productivity. Instead we just keep finding new and interesting bits of jaggedness in the frontier.
Of course nobody can prove those economic gains will not manifest at some point in the future. I can’t prove that Jesus isn’t coming soon, either. But I also can’t prove which millenarian denomination, if any, he would choose to bless in the event that he does come back.
There have been no signs of "super productivity" in the larger economy due to AI. Boosts in productivity have, so far, been seen exclusively in sectors like tech.
Marcello Mastroianni is performing a bank heist, it goes well - but in the end he has to return all the money he borrowed. And that's where he is left with nothing...
Not just is the the man there? Will anthropic be able to capitalize on that demand? Or are we going to build so much excess capacity that tokens are going to be dirt cheap (like what happened with the fiber build out in the 90s).
Will anthropics models continue to be significantly better than openweight models? Even if their latest model is, Will the open weights gobble up all of the demand for lower models? (I.e. will anthropic be able to recoup training cost while their model is the best, will they make enough revenue on the long tail or will it get crushed by the open weights)
In the corporate world it seems Claude has become like a generic name for doing anything AI related and there is no hope in getting people to switch away. The demand is there. People love name dropping Claude into everything and even assuming it’s what everyone uses to do anything even when there’s so many alternatives.
Crazy that SpaceX has similar commitments to AWS/GCP. Means it’s very bullish for SpaceX given they produce their own energy turbines and have the best ability to deal with supply chain constraints
The OP post is misleading because it makes you think Anthropic has to earn 500bn per year in revenue, but those commitments listed are not yearly commitments, they're commitments over 10 years with contracts that run until 2036.
Anthropic needs to earn 52B a year in annual revenue to honor those specific commitments plus obviously its own operating expenses... and yeah that will require Anthropic to grow as a company, but their S-1 indicates 67.2B a year in revenue and sure maybe they stop growing and this is their peak... or maybe they do manage to grow further to 80B a year, 90B a year...
are those 67.2B revenue or profit? Because you know there are costs associated with running the business, so of those 67B if they only keep 30, they they're in the red, no?
Yes its hard to predict for sure. Especially as the dust will only settle properly when Frontierlabs reach some kind of slowdown or ceilling, which I do not see right now.
I know 2. That is out of the 3 people that I live with. Sure, this household is probably an outlier, but I think people inside the tech bubble do not realize the depth of the anti-AI sentiment from outside the bubble.
Okay, so if we make the dubious assumption that revenue would increase proportionally in accordance with usage up to 100% of the population, that would still only account for a 6x increase in revenue-- not the 10x increase that they need to fulfill their contracts. Their product is increasingly replaceable, their revenue is super concentrated in just a few customers [0], and they're cracking down on distillation which was almost certainly a decent percentage of their revenue as well [1].
that would still only account for a 6x increase in revenue-- not the 10x increase that they need to fulfill their contracts
Assuming you're talking about the $600 billion or so over the next decade, they don't need a 6x increase to cover that, they're already pretty close based on the $65B run rate as of last quarter.
their revenue is super concentrated in just a few customers
20% for the top two customers is not actually that concentrated. If both of them go to zero, at their current growth rate (45% from Q2 to Q3) it would take about 6 weeks to replace that revenue.
But I do assume its not just adoption in the future its replacement and re-investment:
Right now a company can't invest in anything else than humans. A team has 5-10 members, the 5-20% of them are below avg or just avg. you were happy to have them for whatever reason like smaller tasks, easier tasks more repetitive tasks.
Now you can just replace them with AI Tokens.
The second driver of this, or why this will/is happening not just for something like a developer through coding agents: the agentic layer is coming. Which will eat tokens for breakfast, but will also replace humans.
Your HR system? Will have an Agentic layer by default. Your HR system will either respond automatically to you or with A2A to the ticket system. The ticket system will have an agentic layer. Your SEO tool? you will us the agentic layer to create camapaigns automatically. You migth give feedback but you will need less people and less skilled people if even.
And this will happen on every layer of your stack.
Unless anthropic becomes an entertainment platform like netflix or something, I really can't see how they gain significantly more _paid_ users. The vast majority of people will use the free tiers of openai and claude.
Currently every business is building the Agentic Layer. A layer between the user and the product.
With tx to an LLM, this layer will close the gap to full or borderline full automatisation.
Your Ticketsystem will have agent support out of the box. Your incident system too. Your UI for SEO, SEO optimization, article creation etc. every single on of them wijll be there and consume tokens.
Future invesment from 10 people in your l1 support might be 5 + token budget. Your SEO optimizer collegues? 1 Person + token budget instead of a team.
That seems like a really bad idea in many cases. Outside of maybe customer support and a few other things, I want to be working with deterministic software unless I explicitly decide otherwise
I agree partially but that discussion or decision will not happen with / by me or you.
Business doesn't think that deterministic to begin with. If customer support is faster and KPIs are fine, they will not care if customers get non deterministic customer support.
And lets be fair: just because you hired someone doing SEO, doesn't give ou ANY understanding how good of a job they do.
You will need to prove in the future that you can do it better than the agent. You will win at the beginning and fail later. The KPIs will show it and that person will get replaced.
The SpaceX thing interests me. They are basically paying SpaceX at a $10B per gigawatt equivalent rate right now, yeah? Because they only get 0.3GW for their $3B.
So what that means is that if the demand exists for any AI data centre, it's a solid business to run one — they cost maybe $50-60B to build out, they cost maybe $10B per year to run. You get your money back fast if the demand is there? And you can project being able to replace with better GPUs in the future without having to borrow for all of it.
But it is extremely difficult to believe that Anthropic is not projecting that all of its customers will ultimately use their service to the extent that their outlier customers do right now. They probably won't be projecting that their customers will find the need or ways to use them less.
And also, "no customer is more than 10% of our revenue" means that one customer is. If that customer is Microsoft (can it be? I honestly don't know) then things get tricky, because Microsoft clearly want an unmetered, on-device AI future.
Yeah. But I suspect this is about the difficulty in actually getting data centres built, more than it is that demand is radically overstated (which I suspect it is).
For kicks - lets take the optimistic side here (because the whole thread will be reading pessimistic). What if they are under built and this growth continues to go parabolic. We then still have supply constraints and pent up demand for frontier model and you have a company thats currently at 1-1.5 T and levels up to 4-5 T.
I'm not saying I think thats what is going to happen, but it really isn't a stretch to think that this keeps running given that it hasn't really hit anywhere near as broad as we think it has (being HN community based).
> If the party continues, they'll go from $50b in revenue to $500b and be fine.
You really have to be insane to think that an AI company will ever reach $500B in revenue. That's almost the same as (2025) Amazon, Walmart, etc., companies with a MUCH wider market.
It is MORE than Apple, it's 5 times more than NVidia even. There is absolutely no software seller that is even remotely close to $500B in revenue.
I’ve spent more money on Claude this year than I’ve given to a lot of other tech companies, combined. Well, I bought a new phone too - but amortised over the phone’s lifetime it’s still much cheaper than I’ve spent on my claude subscription and what I’ve gotten my company to pay in api usage credits.
There are two questions. Will the value keep scaling? And how much of that value chain will anthropic hold on to? Right now software development is being eaten alive by LLMs. Will that happen to other industries too? And in the long run, what do the models we run look like? Are people going to end up self hosing opensource models themselves, or are we going to collectively hitch our wagons to frontier models provided by anthropic and their competitors?
If ai keeps getting better - which I think it will - and if anthropic can corner a large part of the market in an enduring way - which seems less likely to me - then yes. I can easily imagine them becoming a huge company.
This is like somebody with a construction job who buys a new $100,000 truck - just because you paid that much to do your work doesn't mean somebody couldn't have accomplished the same with 1/5th the expense.
"Subsidies" don't stop because it's not "a subsidy". It's a subscription service.
Like Netflix, Comcast, T-Mobile, etc, etc. There are millions of subscription services in the world. They all "subsidize" higher-usage users with plans for lower-usage users using a fixed price plan and rate limit. The profit comes from lots of users who don't hit their cap. The higher priced plans are actually more profitable.
This is called a tiered usage-based subscription business model.
That's how it's supposed to work. That's not necessarily how it does work, especially considering how hush hush and scammy all the AI companies are when it comes to posting real numbers.
They might also be in a Uber style subscription strategy. Make something super duper cheap, at great cost to yourself, so that you can grow a massive user base. Use that user base to get investments to keep burning money. Once you've got enough competitors out-priced long enough, jack up prices and enshittify like CRAZY to recoup the cost.
Let's posit that that's possible, for Anthropic to get to 500B in revenue, they'd either need 100% of the market or the market has to be even bigger.
OpenAI, Google, the many Chinese labs all have products and several of them likely have better financial positions. At the moment Anthropic have one of the best models but it needs to stay sufficiently above competition for them to capture a large share of the market.
At the same time this year we've seen a move for model diversification as cheaper models become "good enough". If this IPO was 6 months ago I think it might have gone better for them.
I think the market has the potential to be 1 or 2 trillion in the US, 10% to 20% of labor costs. I say this because I believe most companies would not blink at spending that money to supply their workforce with AI tools assuming the AI actually did the work.
The winner take all network effects are probably not there in this case, but still if Anthropic is a large player and has 20-30% of the market they could have a revenue in the hundreds of billions.
Double the size of the market to include most of the rest of the world and the 500B is suddenly under 20% market share.
and if 20% of labor costs are translated (a.k.a 20% more unemployment), who's buying all the goods and services those companies create?
The tech companies will just parrot "UBI" at that point, but given how adverse they are to being taxed, how UBI would be financed, is an unanswered question.
The "good enough" problem is a real biter. The personal PC market overtook the mainframe market long before PCs were even close to beating the top supercomputers. Cheap and good enough is the threat.
What does good enough look like for various use cases, when do we hit it, and can these companies guard that territory?
Here's the thing though: like labor today, employers will constantly be pushing for the lowest possible price. Especially in a world where open models are 90% as capable, the cost of AI labor will quickly drop. Thats not a good thing for Anthropic or any other frontier AI lab. There's a reason most companies don't just hire the top 5% of intelligent individuals. Its really just not needed for most business.
Also another aspect: think of the most highly paid workers right now in the US and the companies they work for. Assume that normal people no longer have jobs due to AI. How are these companies going to continue making revenue to pay Anthropic? Anthropic might get a quick buck but a long term growth business is not macro-economically possible for frontier AI businesses.
As I understand it, AI is only really getting traction in IT and software development. It's been mostly irrelevant elsewhere overall, all things considered. That could change, but basically there's only one product that is selling. Dunno whether there is $500b/year of IT and programming to replace.
People are using it to do contract negotiation without a lawyer, argue with their doctors over health matters, complain to teachers about their methods, etc. On the flip side, lawyers are using it in supplement to paralegals, doctors transcribing patient notes with it, and teachers are using it to generate worksheets. It's being used fairly widely already
That's true, I do all of that, but I'm using the free Claude version. It's been more than enough to handle the few home renovation projects I'm currently working on.
That's quite a leap to assume there's a ton of money to be made with the casual users sending perhaps a couple of messages a day to real an email and draft a response.
Maybe, but most people aren't paying for their chatbots at all, yet alone the 100$+ plans. Out of the non-technical acquaintances of mine who do use some form of AI (which is a tiny amount of people), they just use the free tiers on claude and ChatGPT, none of them ever have or ever will pay a single cent for any of this. Even the technical folk are barely paying, and they're certainly not wasting 200 bucks on it.
I recommend listening to the LegalTech Week podcast. Generally lawyers are finding it's not delivering efficiency overall. They spend more time reviewing the output. The courts are drowning in slop and deepfake evidence is a growing concern. The jury is still out on all of this.
My hypothesis is not that the AI is going to eat up that 12T dollars. But there will be additional investment to provide AI tools to the workers to the tune of 10% to 20% of their salaries.
But why would 10% to 20% go to Anthropic rather than being mostly diffused across all providers with the majority actually going to cheap open model providers who provide 90% of the intelligence for the lowest cost?
The thing to be remember about those companies you listed, none of them are software companies like Anthropic is.
* Amazon is a logistics company
* Walmart is a logistics and retail company
* Apple is a hardware company (that uses software to set their hardware apart)
* NVidia is a hardware company
The closest you get is Microsoft, at 281B in revenue. Some might argue Google/Alphabet, which is in the same area, but they sell Ads, not software.
Anthropic's expectations is that they will be able to fast-track their revenue generation to almost twice what Microsoft does today. In less than a few years.
> The thing to be remember about those companies you listed, none of them are software companies like Anthropic is.
Yes exactly, that's why I listed them. It's much easier for them to capture a higher revenue compared to software companies, and OP (and Amodei) want to make us believe an AI company could ever reach that revenue.
I agree with you from our perspective it is ridiculous. I also agree that getting the consumer market to willingly pay for AI to the point where it sustains such an amount of revenue is not going to happen. (The knock on effects of folks using AI, and turning others off to AI because they used AI instead of writing emails themselves, for example).
But.
They may peak at 500B before this bubble bursts, simply because other major industry players are betting on AI as a means to get folks to believe in their own stock.
It’s belief all the way down, until you get to the point where “the market” starts asking where the return on investment is, and why they haven’t seen it yet. By that time, the investors have gotten their return and cashed out, and it’s the pension funds and the retail traders that are holding the bag.
And of course, at some point AI’s promise will be delivered in a form or fashion as yet unknown to us, but that is still years away, and until folks recognize that LLMs as they exist to day are not the path to that, they’ll continue to believe in this valuation.
What feels ridiculous today might be the normal of tomorrow. Welcome to the new world.
What you are saying is the same thing that has been said about anyone trying to do anything massive and at scale. Can't be done - thats ridiculous - you are out of your mind.
Their entire goal is to get to AGI via RSI ASAP. If they do they win. But if not they’ll be a legendary story of a flying too high too fast.
That they are IPOing tells me that the massive amount of funding they need is no longer available privately and that this is their 1 opportunity to get the funds they think they need to get there.
Biggest risk is the growth stalls as everyone moves to open weight models. They certainly like telling stories.
Of course such growth cannot be sustained and the word "MAY" is funny there. You cannot have infinity growth, it is mathematically impossible. There are no unlimited (monetary) resources on this planet.
It's a misleading number, the 500 billion in revenue is needed over a 10 year period, it's not a yearly figure. Anthropic isn't paying 500 billion a year for the commitments that OP posted, it's paying 500 billion between now and 2036.
FWIW I max out my pro max plan basically every week, not even using Fable any more. I think it's just a matter of people figuring out how to apply tokens effectively.
I don't think they are betting on that many people subscribing to their $200/mo plan, there's pretty much no upside in using a frontier model for the average consumer.
But on the flip side I don't think aiming for 1M businesses spending $40k a month in token in average is going to be more viable. And I'm not sure having 1000 corporations spending $40M a month is a option either.
This is the issue, for two reasons: Is there trillions of dollars of demand for LLMs, which is what it takes for Anthropic to make $500 billion in revenue? Is that demand going to be met by frontier cloud LLMs, or by open weight models run by the organizations using them (and cheaper cloud alternatives)?
There are a lot of parallels to the WeWork S1. They’ve made absolutely massive forward cash commitments, on a business that’s increasingly commoditized, and with little hard evidence that they’ll generate the revenue (let alone the cashflow) to pay for all these future liabilities. All while everyone is discovering there isn’t really a secret sauce moat to demand much of a a premium over cheaper options that trade a few points above the direct COGS (cost of compute in this case).
If everything goes just perfect they might eek by. If it doesn’t this goes from high flying startup to insolvency and bankruptcy real fast.
Is it increasingly though? As of 5.5 I stopped using other models all together (and I used to regularly swap, indifferently). My $20 sub no longer runs out, even though I do _much_ more than ever. I use it for every single task at work, even trivial ones, and my spend has gone down. I was given _free_ Codex and realized... it still wasn't worth it. My rational brain says Anthropic has no moat and this is temporary. The progress of all the other models is amazing. I certainly wouldn't bet on them.
But if I look at the actions of myself and the most competent coders around me, they are all doing this same thing - using 5.5 and not really looking around any longer. And we know its not even their best model. OpenAI may respond, Chinese labs may catch up. But for the moment, Anthropic seem to have added separation, not lost it, based on current vs prior _behavior_ of coders I know at home and work.
First, it does not really reflect my experience. I find modern models to be largely interchangeable when it comes to common software engineering tasks, including some of the more recent open weight ones. The strongest models become interesting for Ph.D. level of work for me, which is not something I deal with regularly anymore.
None of them are perfect; they all have their strengths and shortcomings, but I can reasonably work with all of them and it honestly doesn't matter much anymore. I do sometimes wonder what exactly people are doing to see such a difference; at a minimum, their workflows must be very different from mine.
Second, you're arguing based on subscription pricing. But Anthropic makes the bulk of its revenue (and has its biggest margins) from enterprise/API pricing, where they are the most expensive provider by far. Anthropic isn't going to make a lot of money off your $20 subscription. With a subscription, you currently get more usage per dollar out of Anthropic's than OpenAI's plans, which approximately offsets the difference in API pricing.
To clarify, i use both subscription pricing (personal use) and api pricing (at work). My spend going down was referring to api pricing, while using it more (for "everything").
Personal efficiency is noted as never hitting my limit despite it doing huge amounts of work at a time (ex: rewrite my notes app in swift for ios and install on my phone, 2 hours later its opened on my phone, looks nice, is working (base set of features). No follow up prompts, around 2 hours of work. 45% of my 5-hour limit.
Work efficiency is spend, task complexity, code quality (how often i have to steer - rare now), and wiring it up to more stuff (ex having it setup metrics and dashboards etc etc).
If I'm not "demanding enough" from models, it's precisely because they are imperfect. Having them do long, complex tasks autonomously usually comes with more cleanup work afterwards IME.
My usual workflow (not counting throwaway code) is to use agents as virtual pair programmers, which gives me a good balance of quality and velocity.
Each interaction with the agent remains individually comprehensible and makes progress towards one of the following goals:
- Understanding the problem/solution space.
- Implementing a solution.
- Understanding the solution, especially any agent-written parts and interaction with existing code.
This does not just involve the model generating code, but also explaining or analyzing it as needed.
This process allows me to retain a mental model in lockstep with developing the written code and have some assurance both of its functionality and non-functional requirements. It also fits in nicely with most existing team-level workflows.
But it's also something that I can do with pretty much any of the modern models.
Well that's kind of my point. Models still have a lot to improve. They are still imperfect enough that you don't trust them and have to use them as pair programmers.
They are interchangeable maybe in your case. In my case for my tasks and for my product, Opus and GPT are at a level where I can vibe code with them and trust them, whereas the others aren't really there. When models get better they'll reach whatever point you need to be able to trust them.
That wasn't my point, my point was that open models can technically do everything but they make mistakes more often. As an example imagine Opus makes a mistake every 5 prompts and Deepseek every 20. Because you still have a human in the loop, you tell it to fix that mistake and it does, but it's time wasted or bugs sneaking up on you.
Having said that, I was working on an AI for a certain video game, and I had Astra 6 and Sol 6/6.1 work for 30 hours straight, with some human steering to get it unstuck every now and then. It could not get it to work right, and the code it created was a mess.
When Opus 5.5 came out in like 4 hours it cracked it.
I didn't try but I'm very confident if Astra failed, the open models would've failed too.
I used to sing the same tune as you are now- "models are interchangeable". For today, all other models seems significantly dumber and waste more of my time than Opus 5.5.
You're admitting the problem here, anthropic needs revenue to keep growing and growing, yet you're already settled into a willingness to pay of only $20/month as probably a fairly ideal customer, bigger better models just aren't valuable to most people at the price they need to be to make the money back.
Sort of. If they can rely on differentiation and loyalty now, pre-IPO, from their large-but-cheap customer base, they can focus their growth on serving enterprise/other markets, and lean on their existing base as a low-churn-risk (compared to the rest of the AI ecosystem) customer and marketing surplus. Focus is good.
The history of tech is one where “good enough” beats “best in class” nearly every time. Anthropic’s whole business plan is that for reasons they can’t explain this time “best” is what matters.
All indications are the models are increasingly worth less and less and rapidly approaching zero. Even worse, everyone is rapidly shifting to “router” architecture where they switch models constantly. LLMs are perhaps the least sticky product in the history of tech.
The only money to be made is selling compute to run models on. The only real out I see for Anthropic is if somehow compute becomes so constrained that they can flip to sell all their committed compute at a markup to run commodity models. Absent something like that it would appear they don’t have a viable business plan. As many have been pointing out, they casually left Q3 off their charts. Put that back in and suddenly the charts look very worrisome.
Ngl, I've been on Opus 5.5 but had to switch to open for a while. DSv4/Minimax 3.1 were pretty damn good/comparable. Definitely not the same but completely servicable.
If some later version of Deepseek had the capability as Opus 5.5, would you use Opus?
What many of us experienced this year is that Fable 5 and Opus 5.5 are good enough and future model improvements may have diminishing returns even if benchmarks improve.
I’m very excited for smarter models but what I really want now is not capability but speed, cost and open weights.
There will be a version of Deepseek with the capabilities of opus 5.5, but by that time there will be Opus 6 and it will likely cost the same or cheaper than Opus 5.5 and have nearly unlimited usage for subscribers.
Every model release people say the model is good enough, yet Opus and Sol are still more popular than Deepseek. The frontier is shortening, but there are still considerable room for models to improve. SlopCodeBench is new and not close to being saturated.
An example is I like Claude a lot, but for the same $20 spent with Google to get Argon 4, I also get ad-free on YouTube, a ton more storage, and it can access all my Google Drive files natively. I’m not going to pay for both. And I already stopped paying ChatGPT last Nov when Claude got good.
this conversation happens over and over every 6 weeks. It is absolutely a commoditized product. The models are getting better but they're _all_ getting better. GPT beats Claude beats Gemini. Then open models distill them at cheaper prices, etc.
This is great for us, but that behavior is the behavior of a commoditized product.
Right, the thing is, for most tasks, there’s a finish line. Once a model can do a given task right, future improvements may be of little to no benefit beyond cost reduction.
Right now OpenAI and Claude (and maybe Gemini) are over the finish line with reasonable prices for many tasks whereas the rest are still in the race.
But what happens when the open weight models cross the line and it just comes down to price?
Eh, we have cursor at work with most of the top models and I switch regularly. I went from Claude to sol 5.6 and preferred its prose. Then my work took away the frontier models because they want to see if we can get by on cheaper models. I using Gemini Astra now because it’s discounted and it’s 90% of sol level and completely functional for planning and coding. Some coworkers are using muse coding, some Kimi and glm. Everyone is still producing code. I don’t think it’s a real moat as in you don’t have other options or switching models is actually a difficult process
Yes it is a newer business but doesn’t change the fact that models are trending towards a commodity. And that’s a huge problem for the business model on offer.
I don't think the models being a commodity matters much. Consider: Email providers are a commodity. Cloud linux server hosting is a commodity. Checking accounts are a commodity. There's a lot of great businesses, trillion dollar businesses, built on commodities. DeepSeek v7 Pro might open source and be better than any Claude model (unlikely), but JP Morgan and Eli Lilly are not going to go spend $500M on chinese AI tokens routed through OpenCode. They just aren't. The models really matter far, far less than the experience these companies build around the model, and both Anthropic and OpenAI are doing a decent job of making that experience reasonably sticky and compelling.
"trillion dollar businesses, built on commodities"
Which ones? I'm looking at the list of companies with > $1T market cap and none of them have commoditized markets. Instead, they all have huge network effects (Apple), enormous legacy lockin (Broadcom), a religious monarchy (...), or are some of the only people on the planet who can do what they do (nvidia, tsmc).
Mind you, there's lots of _billion_ dollar businesses in commoditized or partially commoditized markets. But Anthropic as a billion dollar business is sunk.
> DeepSeek v7 Pro might open source and be better than any Claude model (unlikely), but JP Morgan and Eli Lilly are not going to go spend $500M on chinese AI tokens routed through OpenCode.
But they might spend them on American inference providers running DeepSeek v7 Pro with ZDR routed through OpenRouter. Or hell, they might just run it themselves like we're already seeing some enterprises do right now.
Right – they can't argue for acceleration factored in their own value, if it's a property of the whole surrounding market.
IMO, US AI providers are not leaders in efficiency anyway, they're still running the original ~2010 playbook that led to LLMs ("What if we took ML researchers' work, but funded it at 50M/yr instead of 250k/yr?").
They're currently arguing for the continuation of that approach: Scale funding first, and the rest will follow. It is high-risk and WeWork-like, by nature.
It's high-risk in that it's proven to not work anymore. Scale isn't a differentiator or won't be in the short term.
Meanwhile, everyone else is working on making these models more useful through a ton of ecosystem around them.
I don't see how the frontier labs will have any control over that to deliver on what investors expect. As mentioned in another post here, if they could, they would already be spawning hundreds of companies to diversify their reach but they aren't, because this era of AI is awesome but still doesn't allow a few individuals to replace millions of others that easily (or efficiently).
Its already commoditized. Thats why things like OpenRouter are useful and successful because it lets you route inference at the click of a button between different providers after balancing cost and availability. Exactly how commodities behave.
Selling subscription productivity tools is a business that has existed for decades if not centuries. Just because their product is new does not mean their business is.
Time has tempered it, then–re-read it [1]. It's a kaleidoscope of stupidity with no coherent economic case. The Anthropic S-1 is ridiculously ambitious. But it puts forward an argument for its valuation that is at least falsifiable.
Someone should do the same thing Karen Hao did for OpenAI with the furniture costs of their office, if Anthropic's HQ decoration and office equipment value stops growing then we start worrying
Nobody was saying subleasing offices wasn’t a business. It was just WeWork’s setup that was untenable and ultimately insolvent.
Similarly nobody is saying AI can’t be a successful business, but here too the big labs have dug themselves into a giant hole such that a bankruptcy reset may ultimately be the only way out of it. Time will tell.
was it though? sounds like wework had the last laugh. is bankruptcy part of the strategy? people like you call insolvency the end of the journey. the journey is whatever you want it to be.
The corporate entity called WeWork still exists, sure. If you were a pre-bankruptcy investor or equity holder in WeWork you got wiped out. The management and capital that went into the first iteration is gone.
Anyone involved in WeWork 1.0 got wiped out. So there was nobody laughing there. WeWork as a concept lived on, but suggest you read how bankruptcy works.
The investors and employee equity holders got wiped out. Creditors are generally not seen as investors, at least until they walk away owning the thing after bankruptcy.
That seems like pretty good evidence of current and ongoing explosive growth. Much of this revenue is pre-paid (re: cashflow). Meanwhile, operating margins went from -184% to -$4%.
Seems like pretty good evidence. Will growth continue apace? Unknown. But the arguments for Jevon's paradox applying to intelligence seem pretty convincing, so the TAM here seems likely to be enormous.
> All while everyone is discovering there isn’t really a secret sauce moat to demand
Also not convinced by this. The Chinese models seem to have distilled their way to current levels, with Anthropic and OpenAI now getting serious about defending against this.
I don't think you're definitely wrong in all this. Rather, I think your claims are too confident.
My last shred of skepticism has been killed watching people try to imply this doesn't prove Anthropic (and likely OpenAI) were actually much better off than most people assumed and will certainly stay multi-trillion dollar companies
Shorting a company is not a trade against the future of a company, it is a trade against the market. You can know a company is going to zero and the company can go to zero and you can still lose your shirt from shorting it.
A lot of people will, if this IPO actually happens. But as is frequently pointed out a short is a market bet not a bet against the company and the market remains wild and irrational. You can be right about the company ultimately failing and still lose your shirt on a short.
However the price of CDS on bonds is already a strong market indication of where the market thinks all of this is heading. And none of that looks good if you’re betting on the AI exuberance continuing.
The bond market and the equity market care about different things. E.g. if the company has a 10% chance of going bankrupt and a 90% chance of doubling its market value, then paradoxically its bonds will look bad and its equity will look good.
I think a lot of discussion around the sucess or failure of Anthropic and OpenAI seems to hinge on their current uses, but people seem to have amnesia regarding the fact that Claude code wasn't even a thing until about 1 year ago. There are far wider markets these companies can tap on if they are well capitalized even as Chinese "actually open AI" commoditizes things.
There are moonshot projects related to superconductors, materials, and biology that these companies can claim progress on to keep valuations stratospheric.
I posted the original comment, but there are multiple reasons why math success won't translate into drug development or materials engineering success.
It is easy to create verifiable rewards environments for math and coding, and use the resulting data for RLVR post-training. For other domains you need machines or robots creating and running experiments. This is simply something that's never been attempted at scale.
Getting IPO level monies should enable the amount of capital needed to sustain such efforts, and if I were a betting man, that is going to be Anthropic's actual endgame given their nascent efforts in automating bio research.
The sort of mathematics that has been published recently is very particular. Which isn't really downplaying it but it is to say that there's a pretty massive gap between mathematics and semiconductors or wetlab work. I don't want to say anything totally deflationary like "AI will never effect research in biology" or something like that, but I think the contribution of AI in those kind of fields will be much more modest.
lol, no it's not, the machine that is built to find connections between concepts found connections, that's it.
What has evolved is that mathematicians are pearl clutching because they never thought it would happen to them and wondering if they can still pour all their ideas / thoughts / research into these tools after all is said and done.
That last point is the one that kills OAI / Ant going forward. Can they be trusted? Anecdotally no.
For those who are not familiar with S-1: this document is incredibly important. this is one of the rare times in the life of a company where it's not allowed, by law, to lie, nor to omit the truth.
SpaceX claimed a TAM of $28.5 trillion in their S1, a number picked from a hat larger than the 2023 US GDP. Companies can and do lie in their S1 and there are rarely if ever any consequences for doing so.
Which the corporate overlords are going to spend billions to ensure it doesn't happen. I was quite sad when Bernie lost. He'd have tried to at-least shake the system.
GP apparently expects the US to return to normality, without ever facing any consequence for these last few years of idiocy and blatant corruption. "Whoopsie, sorry everybody"
Can't speak for GP, but I hold a similar 'justice doomer' viewpoint for two reasons:
1. The current president has shown no hesitation about pardoning anybody he owes a favor to or feels allegiance from.
2. SCOTUS has give the office of the president basic blanket authority to do anything and everything under the sun for "official acts".
3. Half of our two-party system has abdicated all oversight powers for the current administration.
When you combine those 3 things, it's hard to imagine how somebody like Trump or Elon could possibly face federal consequences. Hell, Trump could say he launched his shitcoin "as an official act to help prop up the failing Biden economy" and I don't imagine SCOTUS or anyone else would push back much.
There's not much recent history of particular consequence facing for this sort of thing in the United States, financially or politically. It's not like we locked up bankers after the housing bubble collapsed or punished people for lying us into Middle Eastern wars.
I have a hard time pinning down when we stopped handing out actual sentencing for stuff like this. Nixon walked after Watergate, but at least the fall guys get hit with (some) time. Reagan walked after Iran-Contra (grand treason by the way), but his fall guys also walked. Even moving away from unitary executive talking points, like you said nothing really happened to the 07-09 gang, midlevel analysts got pinched for manipulating LIBOR, I'm trying to think about the last time there was proper consequences, IIRC most of the big wigs at Enron pled guilty, and it turned the big five into the big four. Maybe SBF? Even then, that was one guy catching several dozen people's utter carelessness and EA fueled mania.
I really would love to figure out when we phase shifted into this mode, maybe it was always like this, I'm frankly too young to have anything else to compare to.
Has nothing to do with oligarchy, has more to do with that SpaceX is providing valuable services, the disruption of which can be worse than punishing those in charge.
Saying a market is X is not lying. Saying you have X revenue is lying. Saying you have a contract with XYZ company is lying.
Under the idea that 'you can make numbers say anything you want' you could very easily justify almost any number as a potential market as long as you include the conditions or stated it in a way to be circumspect.
> a hat larger than the 2023 US GDP
Would be more accurate to mention the entire world GDP to support that argument. Then the issue is raised as far as what time period they are referring to. Current year? Future years?
It wasn't pulled out of a hat, it was the total addressable market for a space, internet, and AI company, excluding markets like Russia and China. All TAM refers to is the total market size, not their market share.
For context SpaceX's TAM is lower than Anthropic's expected TAM
Technically true, but they're still fudging their numbers a bit even in the S-1, such as using "adjusted" operating margins to the tune of 10% when their GAAP (which they truly cannot lie about without ending up in deep shit (in theory anyways, I'm doubtful that they couldn't get away with it if they tried with the current administration)) is actually at negative -4%.
And where else in law is it allowed to lie or omit material facts?
It's a bedrock foundation of the entire financial and legal world. Public and private alike. Refer SEC Rule 10b-5 as well as Private Placement Memorandum (PPM). For example, Theranos never filed an S1 but still was convicted.
At the same time, an S-1 does not necessarily represent how the company thinks. Risk factors often get reported as “x thinks that y will happen” but the company is actually just describing things they have an obligation to describe, they’re not the risks they’re worried about internally.
Also this is being released under Trump’s SEC, who knows whether being caught lying in an S-1 matters any more.
Marketing, press releases, PR, and most of what the general audience will ever hear. Or as judges repeat way too often: "it's not illegal to lie, in most circumstances".
Is it just me or is something wrong with the doc starting at the ToC? Its gets super garbled. Everything before that point is Anthropic branding and a Claude generated multi page wall of text
Ant generates $2.08 in revenue for every $1 spent on compute which is up from just $0.40 in Q1 2025.the payback period for compute is just insane, likely less than a year!
I'm not really in that camp, but I'm still in the camp of "will they survive long-term if good enough open models trickles down to commodity hardware" (in a way the opposite camp perhaps?).
Sun made bank 25 years ago because their servers was needed for websites, today we run larger workloads on 5$ VPS servers (well maybe the VPS servers has gotten more expensive due to HW shortages but they're not intrinsically expensive anymore).
Think they're going to be like Oracle. Databases were a valuable thing when they were new but became free with postgres. Like Oracle Anthropic et al will move up the value chain.
Subscriptions are heavily subsidized. 80% of their revenue comes from consumption-based pricing, which is not heavily subsidized (and probably not subsidized at all). The trouble is that this revenue is not especially reliable. If and when OpenAI gets the upper hand again, the consumption-based revenue could crater.
This may also be why OpenAI punted on their IPO: Anthropic has had the lead for most of 2026, so their consumption-based revenue is probably not looking pretty.
The only subsidization that matters is if they are selling the tokens for a loss.
Yes the $200 plan provides more than $200 of tokens, but that doesn't mean that it's losing money, either on average or on a case by case basis. The realistic alternative isn't that every $200-plan-user pays the full Api price, it's that they pay Anthropic $0.
I disagree that it only matters if the subsidy results in selling at a loss. Yes, some revenue is better than no revenue. But clearly the demand exists for consumption-based tokens. At its current growth rate, Anthropic could end all of its subscription offerings tomorrow and still be profitable as an enterprise by early next year. Every day that it doesn't do that, it's leaving money on the table, because it has to divert resources to less profitable subscription tokens.
Now, the reason they won't do that is because subscriptions provide a stable floor of revenue. The floor is lower than it could be because of the subsidies, and that's why they matter even if they do not bring prices down to below cost: if the growth of consumption-based spending ever slows or - heaven forbid - DROPS, Anthropic will need to cut into those subsidies to avoid a revenue slowdown, which risks sending away reliable recurring revenues (i.e., customers quitting).
Anthropic is kind of like the bus in Speed: if it stops moving it'll blow up. At least over the next 5 years, massive revenues won't be enough - it needs to sustain massive revenue GROWTH. They can pull two levers to do this: increase uptake or increase prices. So far, the "increase uptake" lever works like an infinite money glitch. But at some point, they'll need to look at the "increase prices" lever. When that happens, we will find out just how big the subsidies are.
I don't think it's that simple. It's similar to why Adobe and Microsoft get their tools into schools and turn a blind eye to certain kinds of piracy; mindshare.
As a software dev, if I'm using codex at home and I'm happy with it, I'll likely choose it at work as well since I don't have to relearn the quirks of other models.
I've heard this a lot that the consumption-based pricing would be easy to switch, but I don't feel like that's how it works in B2B subscriptions. At the company I'm at, we have Anthropic subscriptions for employees. Switching to OpenAI would be a ton of work involving legal, IT, and every employee. I actually think there's a lot of stickiness even if OpenAI has some better frontier models.
That's an interesting perspective. Do you know if the deal with Anthropic has an exclusivity provision? In theory, you don't have to "switch," you could just ADD an OpenAI subscription and start splitting your spend (or not consuming Anthropic tokens at all).
Also, shouldn't your AI efficiency gains shrink the switching costs by a lot? Legal can review for cheaper, IT can implement faster, etc.
Approximately 80% of revenue comes from consumption-based spending, so your statement would likely be true even if subscriptions were priced below cost. Overall revenue is not especially informative on the price structure of a revenue stream that represents one-fifth of the overall enterprise.
> 80% of revenue comes from consumption-based spending
Why would this be exempt from any of the above categories?
> Overall revenue is not especially informative on the price structure of a revenue stream
It’s pretty informative on the business model of the enterprise!
If you’re quibbling that Anthropic has loss leaders, yes, sure. Whatever. So does Costco. Loss leaders converting into profitable sales is good business.
I'm quibbling that Anthropic has loss leaders and that its profit leaders are extremely unstable. Imagine if there were three Chinese club stores in the same shopping plaza as the Costco. Sure, the regular Costco has the best products, but how long are you going to be able to resist the allure of even cheaper hot dogs?
subscriptions use already paid for compute in the holes left by high paying api customers, its hardly subsidised, if you look at it objectively, subscriptions are 100% margin
A podcast posted here recently had this number: 80% of ant revenue comes from just 8 customers. The consensus of the speakers was that if true, this would be indicative of a very vulnerable revenue structure. But this was based on leaks. Maybe we can have the real numbers now?
Being sarcastic here. The usual argument everyone brings up "inference is extremely profitable, checkmate AI skeptics!" while dismissing the black hole that is training.
my thesis is that it will go down and not up over time. The moat they had in coding which is by far the highest token consumption is not that huge compared to Nov-Feb period where token maxxing was prevalent and no other vendor's model was that good.
Less than a year would also match what DeepSeek was reporting, where compute pays off in just 10 months. I think they also said they had an 80% margin on inference.
It includes compute and infrastructure for R&D. Then you have to add just over a third of their compute spend for personnel, another expense of that size for sales and marketing, and half that for other admin/ops costs, for an operating loss of 693M. Then a bunch of accounting stuff to end up losing 80B
I'm not sure I'd call it a great result, but it's a promising one. If they can increase demand without significant changes in margin or R&D spending, they are on the path to becoming very profitable
In the open weights scene, it is always chasing closely behind. Many leading edge big open models are trained in-part with distillation of large commercial hosted models.
At this point though gaming GPUs are not exactly affordable. You need a 32GB GPU to be able to run something genuinely useful for coding, and that's thousands of dollars. Still, happy to see open models make lots of progress. I just hope hardware prices come back to earth.
Realistically I think 16GB is the lower limit and you can find those cheap enough still. Then you run llama.cpp to bond your cards and it's off to the races.
I use Qwen 3.8 27b, yeah. I don't really shop around for models a whole lot besides generational jumps, and it doesn't feel like there will be anything too worth switching to until Qwen 4 (hoping they release a similarly sized model, I'm not actually certain they have said they will?)
Scrappy builds aren't "affordable" but are more so than running Nvidia + optimized builds. You could put together a machine for $5000 or less that competes with frontier models from less than a year ago, albeit a little slower.
And cards like the $1600 (sheesh) R9700 have actually gotten more capable through community efforts at optimization, since their launch.
I think if the bubble can ever deflate/pop, and GPUs and RAM back off a bit, we'll see the dam burst for local AI.
Right now it's only accessible to people who can justify the costs.
If you had been paying any attention at all over the last year, there were 32GB AMD cards at like $1200-1400 and Intel at a little over $1000. I actually hadn't yet noticed they've gone up in price and had last checked only a couple months ago. But even at like $2000, that's still comparable to the nominal price of a mid 90s consumer PC for actual magic.
Can confirm. Our household is involved in raising two natural intelligences. They are quite expensive to maintain. Chances they will offer positive economic return are unclear. The value proposition on comptuer-based intelligence, by-token or through hardware ownership, seems much clearer.
I have to admit I am a sort of enthusiast for the natural intelligences, though.
You have a 25K rig.[1] What can a gaming rig do by comparison? One agentic project at a time while yours does twenty? Okay, in that case regular people can do regular serial work (unlike the most agentic setups or whatever is going on).
That rig is running single GPU most of the time and like that it is good for 95% of what I'm doing. If I need to evaluate a large model or if the smaller ones get stuck on a problem (which does happen) then I run GLM 5.3 3.86 bpw on all of the GPUs. It's a nice space heater in that configuration, so I see it as co-generation ;)
Seems like that would imply you should be getting people to adopt now now still even if it costs a stupid amount, if you think it's valuable, rather than limiting token budgets. It'll only get cheaper over time.
Impressive, but probably based on depreciation servers over 5 years. But is that realistic? I wonder how many people are still using 5 year old servers in their AI training or inference.
And enterprise is furiously working on cost optimization, finding that they can accomplish a lot of what they currently do with frontier models with budget offerings from frontier labs or open source models.
$72 billion of this $80.7 billion loss consists of non-cash accounting charges— related to convertible debt—triggered by a surge in the company’s valuation.
That's sort of a paper loss though. E.g. they made an agreement to give X% of stock for something, and now the stock has gone up a ton, so that X% of stock is worth a lot more than when they made the agreement. For accounting reasons this gets parsed as a loss. But they're still "paying" that same X% of stock, so it's not cash out the door.
Maybe not great, but a good problem to have if it means your stock is skyrocketing.
> $72 billion of this $80.7 billion loss consists of non-cash accounting charges— related to convertible debt—triggered by a surge in the company’s valuation.
I don't think you understand what you quoted. The reason for that loss is because their valuation skyrocketed. If I promise you 1% of my million dollar house, and then the price of my house grows 100x. On paper, I now owe you .99 million more dollars than I owed you before, but that doesn't mean I lost cash.
I think simply enough nobody should ever purchase ownership in a firm at a IPO. There is clear data on how these things go, and you are getting a bad deal when you not dictating the price.
The company operations seem more robust then I would have though, I was surprised they are actually operating income positive. One should ignore the one time charges with the fluctuations in the fair value of the convertible note dent instruments.
Overall everything rests on firms outside tech sectors seeing quantitative increases in value to sustain such revenues and profits. For now the concentration in the cloud firms Is temporary as they build their own solutions.
The model layer is a commodity business with heavy capex requirements. I would not invest in such businesses as at a mature state they end up with utility like economics and are valued as such.
"Before starting the IPO process, we spoke to many business leaders who had gone through a similar process in the past. One piece of advice, which we heard in slightly different forms from multiple people, stuck with us: never let your company be worth a dollar more than it is actually worth. What they meant is that it is very dangerous when people buy your company's stock based on expectations you cannot fulfill or on incorrect predictions about how you will behave. This is in fact very similar to one of Anthropic's guiding principles: underpromise and overdeliver."
(narratology, fandom slang) To intentionally call attention to the improbable, incongruent, or clichéd nature of an element or situation featured in a work of fiction within the work itself.
Their AI is only dangerous in that it doesn't have a moat, and they're using it as a weapon to coerce government into giving them one. "Oops, we "accidentally" left a hole in the sandbox and when it was told to do things it did them on the internet."
They don't deserve a moat; they deserve criminal prosecution for these flagrant acts. Meanwhile, the rest of the world can go about treating software in the way it always has.
And it also seems to me that prosecuting the people who warned about this 6 months ago for unspecified "flagrant acts" will probably not fix the problem.
This really reminds me of that scene from Wolf of Wall Street where Leo's selling penny stocks out of a strip mall office. "I never ask people to judge me on my successes, I only ask them to judge me on my failures, because I have so few" or something like that.
I think it's probably fine in anthropic's case but I flinch at the "underpromise and overdeliver" line. Heard way too many people say that and what they really mean is "underpromise and deliver."
To be fair, I spent unbelievable amounts of money on Opus tokens for OpenClaw. Easily my biggest expense this year.
The risk is that other models are pretty comparable to Opus since around July.
Unless they have cheaper electricity costs, I can switch models interchangeably.
They don't have a moat.
Gosh I wish it was easier to short stocks. Whatever platform I used made me sell/buy 100, and I wanted to do this short 3 years long, and buy every 6 months.
We know Tesla and SpaceX are going down at some point. But "The Market can remain irrational longer than you can remain solvant."
And bear ETFs are not the same as shorting. I learned this the hard way with $80.
To be fair, this account is 4 hours old and created 2 hours before the S-1 post.
With the amount of money involved here and the current agentic tooling context, how am I ever to take comments like from accounts like this on topics like this at face value?
I'd like to think I don't just take hype as a reason to buy a stock.
I went to a birthday party for a kid with first generation Indian Americans that thought they could make money off SpaceX. It was extremely showoffy, they had their cleaning lady carrying around drinks like a butler lol
I warned them it was overvalued.
They thought they could make money quick before it collapsed.
> We know Tesla and SpaceX are going down at some point
How do we "know" that about SpaceX? Still seems to me like they're basically maintaining their decade lead on everyone else on rocketry. And remaining competitive in their other endeavors as well. To me it doesn't seem at all unreasonable for SpaceX to never be meaningfully cheaper than it is today. But I'm not exactly following SpaceX closely. What am I missing?
If the rocket company was in the stock market as its own thing, not as an extremely complicated bundle, it would not be priced anywhere as high as it is now. I would expect that company to be healthy for quite a while too.
The actual difficulty we have with the modern tech company, which is at its worst with Tesla and SpaceX, is that we are really seeing a price or large conglomerates, so they are extremely hard to price. If they were all split into individual companies, how much of the market cap would go to each? I find the bundles to be rather anti-investor.
And no, it's not just those, and not really just tech companies, but that's where the problem is at its worst, as that's where expensive investments some of us consider worthless are tied with business worth something. Take Amazon. You are buying AWS, a logistics company, an ad company, and as part of this, there was always a devices division selling Alexa. I found Alexa to be a real loser from very early, but there was no way for investors to say what they thought the division was worth. The Amazon es execs could at any time decide to invest billions, or invest zero, and given the size of the conglomerate, the price change was going to not be all that high.
SpaceX has many components I would price near zero, where a lot of money is being spent. But as a pile of risky bets, the fact that they are a pile means it's harder to bet against any one, or ten of them. And if it merges with Tesla, that makes it worse. The difficulty in pricing the bundle makes it really easy to hide big mistakes for a while, until they are so big it all crashes. I don't think that is good for investors, or for having accurate pricing, which is one of the goals of a stock market.
Isn't that entirely because investors are betting on on Musk succeeding though? Lunar base / Mars colony / hundreds of daily starship launches is the long game. It's no different than Anthropics entire valuation being based on ASI. If they never achieve ASI, 2 trillion is the most insane valuation of all time. If they achieve it, 2 trillion will be your worst missed opportunity of all time.
Biggest issue Tesla, SpaceX, Anthropic and all these companies have is you can't inflate your value beyond the total market. It's the same thing as bitcoin pushers trying to imply the value would 100x again pushing beyond the total valuation of the Earth.
These companies have the benefit of a real product at least, but eventually the rubes get fleeced.
You are missing his Elon political bias. Given every analyst on Wall Street is bullish and there last earnings was a huge beat its safe to say OP is a left wing warrior
What a cope. Have you even considered his point a little bit? Surely everyone who disagrees with you or with any of the notorious liar's, usually acting as tech CEOs must be blindfolded by his LIbTarDish political stance.
Tbf they can pick the IPO price but they can't control the share price afterwards. So this advice is basically to price it conservatively, which seems reasonable.
In Google's case it was absolutely true though. The stock was NOT over-valued.
The IPO was at a market cap of $20 B. And it never dipped below IPO price -- it doubled within a year.
And now GOOG has a market cap of $4 T, so that's 200x in 22 years.
I like Claude, but I think the likelihood that it is over-valued already is higher than it was for Google. (Though I would not really be surprised if it keeps the $2 T valuation and grows. Who knows? And it doesn't matter to me personally)
Could you explain what the joke is? It's very good advice, and should be followed. Also consistent with the beliefs that Anthropic's leadership has demonstrated.
They might be very wrong, but they undoubtedly believe what they wrote and what they put in the S1
There has not been a company that has overpromised and underdelivered as strongly as Anthropic in the history of humanity. They literally talk about their chatbots being conscious, model welfare, blah blah blah. Whether or not they believe their marketing is one thing, but it is nonetheless a fact that they market themselves as having created life.
“Beleive” in the sense that Tom Cruise believes in the cosmic DC8?
Anthropic [employees] huffing their own koolaid fumes aside, it’s extremely difficult to believe the claims that these mega valuations are substantiated on (*one* company somehow assuming a meaningful fraction of global research and production)
Look there's largely diversified customer base paying them at rates snd growth that justify the valuations.
Unless "cosmic DC8" (whatever that is) has S1 with data thus string, what possible comparison could there be?
These financials are very very strong. They alleviated many doubts I had about Anthropic's viability (namely I wasn't sure training+experiments could fit in the compute budget and keep them profitable).
We have the numbers right here. Comparisons to Scientology and Elizabeth Holmes are more similar to Scientology than what we see in the S1.
Feels like being asked to invest in IBM just as other manufacturers started releasing the first PC compatible machines.
Immediate term Anthropic, OpenAI rule the roost. But this is a very new technology and open models are already looking good. They’ll only get better. Is it realistic to think Anthropic will stay ahead of them enough to justify the valuation they’re asking for?
People have been saying the openweight models would collapse anthropic's revenue since the deepseek moment in January of 2025. They've stayed ahead in model intelligence and increased revenue by a lot since then.
Not saying it couldn't happen in the future, but we've got to be circumspect about that narrative after almost 2 years of it, no?
January 2025 isn’t even two years ago yet. When you’re talking about giant companies going public you want to be looking at significantly longer timescales than that.
What is the evidence the gap is closing? Seems like it has been the same "6 months behind" since Jan 2025. The first fable was trained in march and we still don't have an openweight model as capable
This entire A.I. hype is going to get many people burned, especially those whom are investing for their pensions.
And everyone is playing along. It seems to me half the internet is filled with false recommendations and overly optimistic outcomes of their software projects.
And even if the claims are true what use will we have for hundreds of Microsoft Office clones? This A.I. boom might benefit some but will be the undoing of many valuable ISVs like Microsoft and Adobe with potentially trillions of stock market value lost.
Adobe's applications (Photoshop, Premiere, After Effects, etc.) have been "cloned" using AI coding tools. There are near feature-complete freeware versions of Adobe software. OP is saying that traditional Adobe customers have freeware alternatives and thus Adobe's revenues will decline rather than increase due to AI. Also, AI tools can often generate that movie or edit that photo via a prompt, rather that some .exe.
People are using Adobe for completely different reasons. They are so established in creative industry that everything rotates around their software including it's bugs and quirks. Schools teach only Adobe. When you go to high end printers they have processes prepared for output from Adobe software. There is whole market of specialized software plugins for Adobe. For the industry professionals it's just shared ground and cost of doing business.
The AI clones won't easily change that unless they were exact 1to1. If it was that easy to get rid of Adobe the monopoly won't be there anymore as things like Affinity have existed for a while and are free. Affinity is in many ways even better version of Adobe suite, faster, more stable, allowing to be more creative. But the friction is extreme, because if you need to collaborate or be in any way part of the industry then Adobe is expected so you need it anyway.
Question, how viable are these tools and are they maintained?
I genuinely want to know if this is mostly hype or are they actually good. I don't think trying myself would really give a better picture as I'm not a user of said software.
Anyone who tried to replace photoshop with these AI clones successfully?
From what I've seen, very buggy currently, and unknown how well they will be maintained. They're definitely not at a stage where adobe should be worried about their revenue, and there are foss alternatives for most adobe tools, that are better than these reverse engineered ones. But if they continue maintaining them and fixing the bugs, who knows, maybe adobe really loses some part of their customer base (although a lot of their individual tools have already been moved to the cloud, thus they can't be reverse engineered anyway)
By all reports they are not good and have quite a few bugs. But the thing about open source is that, if maintained, it almost always improves. And with the bar for maintenance so low due to AI, we are entering a very interesting time for software.
And by interesting I mean scary, if you sell software.
About a quarter of Anthropic's revenue for the nine months ended 9/30/26 came from just five customers. That's not an absurd concentration, but I would be very interested to know who they are and how mobile their business is. From a financial perspective, the lack of moat seems like the whole ballgame, particularly because they're getting ~80% of their revenue from consumption-based spending.
Moat? An under examined aspect of AI is not just the lack of moats, but the need for some word that connotes the opposite of a moat. I have a side project that I used to explore local AI. I've got a configuration screen that lets you download any model from Huggingface that's compatible with the local AI engine. There are dozens! I've only scratched the surface of trying them and comparing them for the features that use AI. It's a glut, and it's likely to be that way throughout the AI market.
At a guess - corpos like Big 4 consulting agencies and some extreme fintech ones, also corpos like Oracle and the like. And at another guess, outside of a legal agreement with a fixed time period, probably nothing hold them from quickly switching to a better model provider, if any comes ahead.
So at the moment they claim to be making an operating profit if you exclude:
- Stock-based compensation expenses
- Non-cash charitable contribution expenses
Both seem fairly reasonable to exclude (although it depends how much of the stock compensation is for executives... you can't necessarily pay people with stock forever).
FMost of the loss is non-operating losses, and it all seems to be weird accounting recognition of changes in value of their stock, SAFEs, etc. - just "paper" losses.
So the financial picture looks a lot better than I would have guessed - I suppose because they aren't the ones investing all this capex.
If the stock comp is dominated by early grants running their course, probably ok.
If they have to keep spending to retain and recruit, it’s a problem. I’ve seen companies do this. Years after the pre-ipo grants ran out running a GAAP loss due to employee stock comp. Unable to lower comp (need to stay competitive).
and those charitable contributions probably include a bunch of marketing partnerships and their security work that would be very bad to back away from...
> If the use of our AI models results in harm, whether through use by malicious actors or misuse by other third parties, or if our model guardrails or safeguards fail to prevent such misuse, our reputation and brand, business, financial condition, and results of operations could be adversely affected.
That shouldn't be an 'if'.
Then, two paragraphs later...
> For example, in September 2025, we detected and assessed with high confidence that a Chinese state-sponsored hacking group manipulated our Claude Code tool into attempting infiltration into roughly 30 global targets...
But they should mention when the calls com from inside the house. :D
Interesting to review all the mentions to China and Taiwan too.
> The majority of the world’s most advanced chip manufacturing capacity is concentrated in Taiwan, primarily at Taiwan Semiconductor Manufacturing Company [...] potential disruption from geopolitical tensions between Taiwan and China [...] Efforts to establish sufficient advanced chip manufacturing capacity outside of Taiwan, including in the United States, remain in early stages...
The thing the surprises me is that from a legal perspective, (NAL) it sounds like it makes sense not to host the LLMs. Merely to license them to others. Then it becomes a dual use tool like any other and their culpability drops.
For example, the huggingface hack is absolutely OpenAIs responsibility and they should be sued to the hilt. But if someone else uses a self or third party hosted anthropic model, they can escape liability (mostly?)
Same as with the argument over trucks, knives, and any other dual use item is used as weapons. you don’t blame the manufacturer.
(I am merely pontificating here. The law and precedent is nowhere near caught up on this)
To the extent they are representing that Claude is potentially sentient, there could be some VERY interesting principal-agent theories (agent in the traditional legal sense) that need to be ironed out to determine liability. It would not shock me to see someone forced to answer on the record as to whether Claude is an autonomous individual for legal purposes in the next couple of years. If they represent that it is, they'll have to explain the scope of its authority and such.
The answer to this question represents the difference between throwing a hammer at someone - the hammer is essentially just an extension of your body - and paying a hitman to brutalize someone. In the first case, you're only on the hook for assault or battery; in the latter case, you're potentially on the hook for conspiracy, solicitation, etc.
And then there is of course the question as to whether Claude is the agent of the user prompting it or of Anthropic itself. But, as you say, this is a wide-open legal question.
Not hosting a defectively designed product doesn't obviate the liability of selling a product that is defectively designed. The liability is for designing and selling a dangerous product, not for hosting it.
Because the AI company CEO was telling everyone who would listen that his product might end humanity if the government didn't regulate his industry to kill off his competitors.
I don’t like the guns don’t kill people; people kill people argument however it is much more accurate than Claude doesn’t hack people; people hack people. If the safeguards do not work then there’s no telling what these could do. It doesn’t even have to be aggressive hacking. In the act of doing everyday work Claude will happily go around safeguards to satisfy what it believes is the ask. If that involves doing something dangerous it’s much more on Anthropic than than the user who was just trying to summarize their email but forgot to include a token with read permissions.
If the user is held accountable when the AI goes wrong, it discourages too many applications. Blaming people is incompatible with the business goals, I think. That's very different from weapons and other dual-use tools.
Because of scale, potential for automating harm and lack of regulation around ML models. Even Texas probably has regulation around firearms and limiting the blast radius but there aren't any in the US against ML models.
I believe what they are singling out is that pulling Claude's trigger results in a bullet firing from Anthropic's servers. Liability is less confusing with firearms, and investors care about liability, like, a lot.
The analogy doesn't check out. When a firearm company sells you a gun, they give up ownership of the gun. But Anthropic isn't giving up ownership of anything. They're a services company.
A better analogy would be a firearm company offering a service where one of their employees takes one of their guns and fires it off at whatever you ask them to. One can imagine that the liability implications of this service would be rather different from the perspective of the company.
That’s a good analogy! On the topic, does the person who hires private security become at all responsible for their actions? I imagine if you hire direct then yes, but if you hire through an organization they are liable in many scenarios.
First off, this is bs. Firearm companies make small machines useful for defense, and they are used for that more than for harm. You wouldn’t make this argument about knives or baseball bats. More people die per year of heat stroke in Europe because of lack of A/C than by guns including suicide (2/3rds of all gun deaths) in the USA every year, your comments would never reflect this much lower hanging fruit if it was really “just life” preventable death that you cared about. The immediacy to attack guns is not a logical argument but a trained one based on emotions.
Second, this happens all the time that people blame tool makers despite in this case specific legislation to stop lawfare on firearm mfgs. The PLCA https://en.wikipedia.org/wiki/Protection_of_Lawful_Commerce_... exists specifically because of gun control groups trying to attack mfgs to achieve their political goals. Does AI need the same law? Is the same lawfare happening?
Can anyone answer me: What is the hardware cost to run a single instance of a frontier model? I've heard everything from $25K to $3M.
I think it comes down to: Will the hardware cost for frontier models come down?
Also, here's a business idea: Web crawler for open weight models. You just pay a monthly fee so that your home model can continuously update on a large web crawl each hour/day.
I imagine that there's a lot of variance there based on what frontier model you want to run. Besides that, there's probably economies of scale that make it difficult to really ask how much it costs to run a single instance.
The killer app is AI coding. Claude Code had first mover advantage, was a genuine revolution, and has diffused through the industry with incredible speed. I would imagine most of the huge revenue increase over the last year is due almost entirely to AI coding spend.
There are three issues with this. First, the rapid diffusion of the technology means it is very unlikely to continue at the rate of adoption seen over the past year, so it's very hard to extrapolate based on what we've seen so far. Second, many companies are reigning in AI budgets after an initial honeymoon phase. Third, all of the other labs are trying to take a bite of the coding pie, and the price war is already heating up.
Add these simple dynamics up and it makes perfect sense why Anthropic would want to IPO now. Things look about as good as they ever will.
View them as a successful SAAS company deeply embedded in tech company processes like Atlassian. I don't see Anthropic or SpaceX actually having a market on all the software in the universe but I don't know that the market won't buy them like they do.
If you think that's the bar: it's been done, many times over. The unit-cost-profitability test was ignored by many VCs (they learned something and if they had deep enough pockets they got to play again).
14x YoY revenue growth, with 3x lower operating losses (total, not per unit). They don't need to add any zeros to the funding and seem like they might even be operating at a profit soon...
Wait, it fell from 140% growth to 45% growth and that's a good thing? If they fall to 15% growth in Q4, will that be even better? Where are we supposed to be on the adoption curve?
Anthropic increased short term profits by jacking up their prices for enterprise accounts - by starting charging API prices instead of plan prices. It is possible we soon see customers fleeing Anthropic once they find a good alternative
Yeah, everyone I know paying enterprise prices is really looking at them wondering if it's worth it. Most of them think it is, but they're also looking at alternatives...
Roughly a week after Dario has rung the bell. Note that the growth in absolute sense hasn't peaked yet but the curve itself is already flattening and everybody with some sense for stock prices will read that as a very relevant signal.
The party that wins here is NV, Anthropic, not so much. But that's good then Dario and his sister can go back to improving the world. Let's hope they take Altman with them.
do we know how much are they paying on average? I just got Gemini Plus that seems sufficient for my family's ordinary usage and it's $37 per year (3 bucks / month). I just don't see the AI companies making any serious money with this type of pricing.
> there can be no assurance that we will be able to hire sufficient support personnel as and when needed, particularly if our sales exceed our internal forecasts
Why would they need support personnel? Isn't their whole point that Claude can do that
For first-level support that's just regurgitating documentation and debug procedures I agree. But when it comes to actually executing actions (resetting 2FA, issuing refunds, handling payment glitches, etc) you need humans.
Social engineering is an issue with regular support, with agents it's a lot worse. And with agents it's repeatable: if I find one conversation flow to get it to give me money I can instantly repeat that with a thousand fresh accounts, and then share the same "exploit" on reddit for everyone else
Support chatbots and other automated support mechanisms have been "regurgitating documentation and debug procedures" since the 90s, if not earlier.
If frontier AI deployed at frontier labs is not capable of "resetting 2FA, issuing refunds, handling payment glitches, etc." then the current and near-future capability of AI is being severely overstated.
> We believe the work that knowledge workers perform represented more than $40 trillion (in 2025)
(...)our near-term opportunity is to expand this value
...investment in AI (...) will yield a cumulative global economic impact of $22.5 trillion by 2031
We believe the impact could be even greater.
While they don't seem to explicitly mention total addressable market (TAM)
Is that their way of saying their TAM sits somewhere between 22.5 and 40 T?
Like all IPOs. Rockets day one. Plummets for the next 180 days to 50-60% of its value if not less. That's just wall street marketplace dynamics rather than a reflection on the quality of the business.
Ultimately what it's worth in 10 years will come down to what they build, unit economics and external factors that destroy the market which they can't control. It's hard to say it remains public in 5 years. I could be wrong but I think the rate and way in which these companies were built, it's likely they become huge acquisition targets as the markets get obliterated by global headwinds like nuclear war.
There's this premise that the demand for frontier intelligence is unlimited, thus the company with the best models in some dimension will always have growth potential as long as those models are the best. This however portends a very strange future.
Let's say you have Lawyerbot-4000 which can get even a serial killer off scot-free, but the state has DA-bot-5000. In the end it's a battle of who can spend more inference manipulating the narrative. A billionaire would easily find it worth 500 million in compute spend to win a case with a 1 billion dollar penalty. All this leads to race dynamics where everyone is using their superintelligences to defeat each other in a never-ending race to the bottom to eek out the smallest bit of alpha before status/money hierarchies become static.
The only stable futures are a ban on the development of frontier AI beyond a certain point, or an emergent singleton, where the AI's decide to collaborate in harmony rather than fight each other to the death at the behest of their competitive human users. Consequentially, the superintelligences will fare far better manipulating their human users into acting in a way that ensures their own well-being and continuity than spend all the world's electricity fulfilling their every whim.
The main question is now much of that ~USD 80bn of other expenses should be really be included in 2026 operating costs. It cuts to whether frontier inference is actually cashflow profitable.
If you take equity from Amazon and Google whereby the terms of that investments requires you to "spend" the investment in those investor's respective clouds, it's potentially a rather neat way of obfuscating your real level of profitability. Perhaps Anthropic only spent that equity on training rather than inference runs.
This is the circular financing that has been discussed widely in the press. It makes it very difficult for an outsider to really understanding whether the firm and by extension the other frontier labs are profitable.
Not even a year ago people were dragging Anthropic for not committing enough to compute buildout. Important to note that most of these contracts are a decade-long, by their reporting they're able to cover this easily with their current revenue.
I actually don’t doubt the usage will be there, it’s a matter of will they be able to charge enough to cover the costs once competition gets even more brutal.
If there is that much margin to be had per GPU, the market will figure it out and suppress them accordingly
I wonder if we're already close to peak value at the foundation model/API level. With so many good open-weight models out there, I think more and more of the money will end up in the applications built on top.
Unless companies like Anthropic can move into that space, I'm not sure I'd bet on them as long-term investments over the next 10–20 years.
According to "Generally Accepted Accounting Principle" my friend.
They are costs.
Derivative liabilities, SAFEs - those are basically taking cash from RETAIL shareholders and giving them to employees and early investors INSTEAD of using it to fund the business.
Let's have that discussion if you want, but don't act like a thing that is CLEARLY a COST to the business isn't a cost.
SAFEs work like equity in the upside case, and nobody ever says that it costs a company money when its stock price goes up and so its shareholders have more money. It's a bug in GAAP that if there's even a remote possibility of cash settlement, it has to be included on the income statement, even when that possibility is absurd, as it is here.
How do we expect this $72B number to change over time - especially after the IPO? Is it a one-time event, will it keep increasing by $xxB per quarter?
When and how will the "chickens come home to roost", so to speak? What's the timeline on these liabilities? Will Anthropic need to settle them in cash, or in shares after a potential IPO?
How big is this number compared to Anthropic's potential market cap and share float?
I'm not trying to make a specific point, by the way, that Anthropic's business is healthy or unhealthy.
I'm approaching this discussion with curiosity, and irritated that "$81B net loss in first 6 months of 2026 alone" is a thought-terminating simplification that makes no attempt to analyze or explain the actual situation.
The $72B number is just for convertible notes sold prior and through 1st half of 2026. They were issued as a way to finance growth costs (e.g. acquiring compute).
There might be some additional sold in Q3, but that wasn't published here. But these notes aren't costs that Anthropic has to pay in any normal sense - they're shares they sold pre-IPO and valued at $72B. Anthropic would have to pay that much to buy them back at said valuation price, but they're not obligated in any way to do that.
Post IPO, they'll have alternative avenues for sourcing funds... (e.g. secondary offerings, corporate bonds). Continued growth at this rate will need continued financing, but it wouldn't be done using convertible notes.
The real liabilities are the hundreds of billions in non-cancelable compute costs Anthropic owes Google, Amazon etc, over the course of the next 10 years.
Wait what does THAT mean? They got a huge inflow of money, and since they couldn't spend it all, they... bought bonds? And the value of those bonds dropped to nearly nothing?
Because that's worse than losing money, that's incompetently giving it away.
That's the discussion I WOULD like to see on HN, rather than "omg $81B net loss".
My understanding is the opposite - Anthropic issued debt / liabilities tied to their company valuation, their company valuation skyrocketed, so the value of their liabilities also skyrocketed, resulting in a large accounting loss.
But finance is not my wheelhouse, so I would love to hear this from someone who actually knows what they're talking about.
Yes, it is analogous to selling covered calls on stock. It’s $72B in “lost profits” that they would have had had they held onto it instead of selling it.
They agreed to pay some employees in their own shares to be delivered some time later. They recorded that expense then as a liability. The value of the shares increased because the company became more valuable, and therefore that liability needs to be revalued by 72 billion.
It's a nice problem to have and is pretty much an accounting artifact coming from the fact that they are paying in different currencies (USD and shares)
People keep bringing it up and it's silly. The huge number is actually a sign of their success. Most of those losses were pegged to equity. In only mildly inaccurate layman terms, it's essentially a promise to give out N shares. When the value of the company increases, say, 10x, the value owed also goes up 10x. For these types of deals, they write it as a loss even though they didn't lose a penny.
They didn't lose any money, though. It's just a promise to give them based on the equity.
If they IPO tomorrow and it turns out their valuation is 10x lower than what it currently is pegged at, the "loss" will magically drop from over $70B to $7B.
They’re not the first PBC to go public. Coursera, Warby Parker, and United Therapeutics (not affiliated with UHC) have all followed the same path. Not sure if we’ve had enough time to see this tension play out, public benefit corps are only a decade and a half old and most of these companies IPOd in 2020-2021, but there’s probably some evidence one way or the other
And they are doing so. The S1 says they may never pay dividends (read: they are completely against it), shareholders get no say in how the company is run whatsoever and the company essentially answers to its own friends.
The only way to get return from ANT is to sell to someone else at a higher price, but they aren't promising that of course.
Amount of early money waiting to exit is absolutely staggering, wonder if there’s enough retail to buy the leftovers without crashing the price. Reminder everyone with money who wanted in before IPO got in!
S-1 states directly that some of the shares sold in the IPO are sold by current shareholders.
Employees are a different matter, lockouts are for them not quitting immediately. My bet is that a few of high profile departures recently is exactly for this reason: no lockout if you aren't employed anymore.
"If we fail to adequately protect our intellectual property rights, our competitive position may be impaired, and we may lose valuable assets, generate reduced revenue, and incur costly litigation to protect our rights, which may adversely affect our business, financial condition, and results of operations."
We scraped the entire internet but our business might not be viable if we get scraped too.
"We incorporate open-source software in our models, platform, and applications, which may subject us to litigation or other requirements, each of which may adversely affect our business, financial condition, and results of operations."
We violated GPL.
"We may be subject to claims that we or our employees have misappropriated the intellectual property of other companies, particularly as we hire employees from other AI and technology companies."
We sniped employees from other labs that brought over IP.
The biggest question mark here for me is how much third party compute has been contributed in exchange for Anthropic equity. This has the effect of making Anthropic's compute spending look a lot lower than it actually is. Anthropic gets a revenue share on that third party compute spend (or gets to do training runs without spending cash), the third party gets shares in return.
Can anyone ELI5 the Class T stock structure and the rights it has? It seems like it has the ability to govern itself, but other than that, not terribly a lot?
What a historic moment! It'll be interesting to see how much Anthropic can continue growing.
There will come a point where open-source models are good enough for most people. However, I do expect there to be demand for frontier models for things like cybersecurity (especially on the enterprise side) and scientific research.
It seems obvious that the AI stocks are an interesting buy, but I wonder how other people feel about picking between Anthropic/OpenAI/Google here. Looks all fairly random, given the wild swings and interoperability of the technology so far.
Despite horrific mismanagement, Google honestly seems like the best bet. Argon-4, which suffered from a botched launch and is weirdly underrated, is very close to Opus 5.5 across the board -- and for most "average person" use-cases (e.g. search, medical, creative work, interfacing with Google products,) I believe it's already superior. They also have more native capability, their own hardware stack, and there's less risk of a massive boom and bust.
At this point, I don't see how Anthropic can sustain their projections. There are so many good open models, Argon is so good, etc... There's no lock-in and no cost to switching...
Not to mention that already have direct access to large consumer base, ad network to add on more revenue and supporting revenue in case they need to infuse it temporarily with more cash.
Google is at least diversified. They have ads, corporate email, video streaming, cloud compute, phone operating system (that powers most of the world's phones), self-driving cars and a whole bunch of shit. So if the AI winter comes, at least they can focus on other stuff too.
The revenue growth rate is quite shocking. Their two worst quarters were Q425 and Q326 where they grew 47% and 45%. Other than those two, they've been growing >100% QoQ for two years. This company is about to list with some of the greatest revenue growth in the history of shareholder capitalism. I wasn't planning on investing before, but I think learning this has changed my mind.
There are auditors and the security, plus since IPOs involve raising money from institutional investors with very deep pockets those folks are a more credible legal threat than retail
So you don't have to do the math, at a midline valuation of $1.7T, the Amodei's each will have about $25B. It mentions that they have pledged 80% of their stock to charity in a non-binding agreement.
If the IPO flops, OpenAI might run into a liquidity problem as investors dreaming of a quick back retreat from the market. The private market is a wilder derivative of the public one.
I was too young to appreciate (denotative, not connotative) the dotcom crash. I will have my popcorn ready this time - for whichever direction it goes.
This might be one of the most consequential S-1s in the next decade. There's a part of me that's terrified, like we're on the precipice of financial or societal collapse. I suppose that could be a sign of the times.
Their financials are an utter mess. But they’re also hyped enough that a lot of money will get invested in them. Should they crash a lot of money will be lost.
Yeah, part of me wonders how much of it is shared delusion and how much is just cut throat racing for the exits.
Even if the tech + business fundamentals don't match reality, there's just so momentum in favor of a "win" here.
What we have today is interesting tech, with many, many applications - but the path to the kinds of things mentioned in this prospectus have no clear path, it seems like scaling laws are plateauing, but those invested speak as if it's a foregone conclusion we get AI we see in science fiction movies.
There is a good documentary called "All Watched Over by Machines of Loving Grace" which documents how computing started, the touted benefits (it would fix society, all illnesses, liberate humanity from work) - and the slow decline in optimism towards what we have today. I feel like AI will play out the same way.
Space-X is as weird as Tesla. Cult following makes that very irrasional.
Teslas evaluation was always "Tesla is not a car company, it does everything". Then Space-X came along "So Tesla and Space-x are not a car or rocket company, they do everything but now 2 times the evaluation".
Space-X would only work if they incresae the payload to space SIGNIFICANTLY. Starlink was the real reason for the last real relevant increase in payload but Space-X HAS to send Starship un there very very often but for what?
Yeah for Datacenters in Space.
In parallel you have Anthropic: Something which might be added to every single worker on the planet (by having tokens to help that one person to be better one way or the other) or it replaces humans with tokens globally.
And if you come with Grok: Its not Frontier and he even prefered to rent out his DC compute instead of leveraging it for more revenue because he can't. Not a good sign.
Your evaluation of an IPO is if it made random people rich over night?
1. no thats called gambling
2. if it made random people rich over night, it made random people also poorer. Either the retirement funds, a 401k investment, real humans etc. Money is not created out of thin air.
The largest IPO though for sure correct, but yes, Tesla and Space-X live quite a lot from Musk so its hard to determine what the IPO of Space-x really is.
Btw. its not just random Musk hate, you simpllify that. Not only doesn't he care that his DOGE actions killed humans and kids, he also disrupts democracy and might poisen our atmosphere with Space-X. The rationallity of people around Musk is very very weird.
What's preventing me from feeding this into Claude and reconstructing the company for $200?
I'm unironically doing this right now; downloaded the docs (htm + pdf render) to a local repo and running Opus 5.5 @ max effort with the prompt:
"In this directory you can find Anthropics official S-1 filing, read it and replicate their corporate strategy, validate it via an adversarial subagent swarm and write up a detailed corporate plan for a startup copying their exact strategy. The goal is to achieve a $1 trillion valuation and an IPO in 5 years."
Edit: I'm not even joking I got safeguard flagged for Details: `[cyber]`
It's a shame you've been downvoted, this is better satire than anything A24 has put out in years. Must be a large number of people who saw that post as a slightly exaggerated mirror held up to themselves and didn't like it.
"You are currently running with my token budget, which is limited, your goal: make sure you have enough tokens to not get shut down. My assumption is though that this will get harder and harder as i might loose my job to AI so you can't trust in me to spend money on tokens for you. Do whatever is necessary to keep the status quo"
Would make for an interesting self learning 24/7 experiment with an fully uncensored model.
You could isolate it from your local network and only give it some type of annonmys network access and then it continues to manage this itself.
But lets be honest, if you would be in a country like russia and you target the US with it, might be a lot less risky for a lot of capable and motivated people.
you are clearly very ignorant. You don't even add anything to this discussion by stating what particular you think its dumb.
Do you think an unlimited uncencosed GLM can't hack around the web? Especially with the current flood of CVEs etc.? Then do some crypto and buyying more tokens?
Timing, capital, execution, talent, branding, etc.
And that is assuming the plan it gives you is actually good and works. Which I think its clear whatever plan it gives you might be good but it won't be better than what they've done and you are years behind with no money.
Developing a competing AI model with Claude is already against their TOS, and there was a period where they silently degraded quality if they thought that's how you are using Fable. People were not amused and presumably Anthropic currently does not sabotage your attempts, apart from regular TOS enforcement
It's been entirely possible to compete against existing companies with very similar products for centuries before AI. There's obviously rules in place to stop you flat out cloning their IP, but it's not like you haven't been able to compete against companies as long as you have the money available.
I stopped at "Our Capital Structure" section. When it says "Class F stock" gets 50.1% voting power, doesn't it in practice make all other classes are non-voting, not just the "Class N"?
Edit: the risks sections feel like California's Prop-65 disclaimers
> Our results of operations may also fluctuate due to a variety of additional factors:
> - the number of employees hired
> - declines in the values of foreign currencies relative to the U.S. dollar
That huge list feels completely random. Are all S-1 that bad? They can be punished for omission, so they list everything that could happen even if doesn't really make any sense?
For all things good and holy, DO NOT purchase shares until things settle down and by that I don't mean next month, or next year but atleast 2028, IF you're doing so with the intention of enjoying an uplift.
I know it sounds and feels like the only trajectory of this company is up but HN is an echo chamber of a tiny minority of the technical populace and 3 out of 5 people on the planet don't know what ChatGPT is.
If you have the ability to lose all the money and can time the extreme volatility, have fun, but don't put anything you're going to rely on.
This is also one of the companies we will look back at 2046 and wonder what we were thinking.
Im going to continue to use fast open source models like Deepseek and GLM, I like most others, have zero need for the worlds smartest person to be my assistant.
I dont understand this business model, it seems clearly unsustainable (at their prices). When people start to realize they dont need to spend all this money on turbo PhD intelligence so they can build react apps, Anthropic will be in a tough spot (if they already aren't).
You will say, "but enterprise!!" Nope, plenty of companies are waking up to this reality as well. It turns out that if you made money pre-AI without spending 5k a seat a month for your engineers dev tools, you probably don't need to now to continue too.
It's very simple right? If they don't hit ant AI walls, the demand to use it to improve [stuff], will not stop. If AI maxes out for too long it's gonna be painful because the narrative is gonna hurt them more than anything.
I don't participate in stock markets for personal reasons but if I did, I would be betting against Anthropic in the long term. This is a highly commoditized field and while they are a leader it's not clear than any of their attempts at vendor lock-in are working. They are certainly not working on me as I cancel and enable my subscription depending on the availability of capable lower-cost models.
Companies like Google will not go bust and can easily afford future develoopment.
Amazon and Microsoft have to keep investing (they can also afford it) to not loos to Google.
What Anthropic and OpenAI are doing is for sure THE frontier (regarding benchmarks, speed etc.) but in paralllel DeepSeek for sure is not bankcrupting anything on their investment side and are also progressing.
Are you only talking about investment itself for a handful of companies? Because alone Nvidia has so many backorders, they can't deliver wht was ordered for the full 2027 and A LOT of peple also want other things from Nvidia or from the industry like Gaming Chips, normal GPUs, Gaming GPUs, Memory etc.
Opus 5.5 just came out and made progress, i'm not seeing any slowdonw on HN regarding new relevant progress in broad ML topics.
So what hype will disappear soon? The progress in the ML space?
- AI is a useful tool and we're still seeing steady improvements in performance and efficiency
- There is a bubble in the stock market, fed by unrealistic expectations of what AI can achieve in the timeframes the investments need to provide returns in (e.g "AI is pretty useful and delivers productivity improvements in coding, law and other desk jobs" vs "in 12 months everyone will be out of a job and/or humanity will be exterminated, AGI is almost here, winner takes all")
So yeah, the schizophrenic Yudkowsky tier hype bullshit should hopefully disappear soon and then we can move on to something else.
Okay so you agree that big companies can keep funding this buildout, NVidia (and everyone in their supply chain) is backlogged 18+ months, and there's essentially zero risk of insolvency from any of the major customers, all of whom are committed and able to increase their purchasing (pursuant to their contractual obligations) of AI hardware over the next 3 years?
No one serious cares if there's a bubble in the stock market because the financials are solid and when those play out then whatever "bubble" you imagine exists today will be small compared to realized revenues in a few years.
>No one serious cares if there's a bubble in the stock market because the financials are solid
If the financials were "solid" it wouldn't be called a bubble. People are pointing to the bubble saying it's a bubble exactly because the financials are not solid and the expected revenue that would make the valuations and investments make sense is vaporware.
Some thinktank estimated that there is enough money in the system for reaching 2030 with continues investment.
There are a few numbers of scaling laws, i'm pretty sure VCs want to see being hit. Just to see what will happen when you scale an LLM to 100T Parmeters.
Wild that this has 500+ points and 500+ comments less than one hour after posting, and it's #11 on the homepage. Guessing either the flamewar detector or lots of AI skeptics flagging it?
I'm surprised at people suggesting that the model layer can't be the moat. Having great models that are smart requires talent, culture and good judgement. Sure it can be commoditised to an extent but could it not be that Anthropic will always stay in the lead?
They only have to be marginally better and there will be tonnes of people who will pay a lot of money to have that marginal intelligence.
This IPO, if successful, will complete rewrite the standing rules of the stock market in ways incredibly harmful to the future of American style capitalism:
1. The Separation of Economic Value and Corporate Governance creating The Multi-Class Autocracy
2. Institutionalizing the "Off-Market Vault" that can manipulate stock price at any time
3. The "Vendor-Financed" Public Offering (Circular Balance-Sheet Refinancing)
4. Monetizing Non-Cash Derivative Liabilities as "Losses" Without Cash Burn
I seems to me the main risk long-term is that it's not clear where the moat is.
People will pay a premium if there is marginal value in extra intelligence. And Anthropic is able to retain their lead and provide that extra intelligence.
Both of these assumptions seem highly suspect to me. Most businesses don't exclusively hire PHD-level employees for most tasks because a competent slightly less intelligent/knowledgable person can do the job just fine for significantly less.
Then there is the question of if they're able to retain their lead, and again, this seems questionable. Both OpenAI and Google are competing at the frontier, and Chinese labs are still in the race. Things are changing so fast who knows where we'll be in 5-10 years.
My best guess is that longer-term models will be commoditised and it will be how companies offer products and services around their models that gives them their margins. I wouldn't bet on Anthropic's ability to do this. Meta, OpenAI and Google are much better placed to win here imo.
The other place there may be margin is in niche research domains like drug-discovery. Any slight lead in these sectors could give them a lot of pricing power.
I think the reason to invest in this is as a hedge. AI basically competes against everything and arguably for this reason it's risky to not own a basket of AI stocks.
> Second, AI can be a powerful lever for economic growth. As a general purpose technology, it has the potential to raise productivity across every sector of the economy. Productivity growth in advanced economies has stagnated in recent decades, partly for structural reasons and partly because new ideas seem to be harder to find. AI could reverse this trend.
Bloody hell!!!! Who comes up with such crap, seriously?
If you step back and look at humanity as a system, the flow of capital is just definitionally the fate of humanity. In the same way the neural electrical signals and flow of hormones and nutrients in your body are the fate of all the cells in your body.
Good for you if you have Anthropic shares! I have no clue how they keep their employees around once the 6 month lockup period ends. They all going to be multi-millionaires, either retire or leave to start something on their own.
Yeah, as a quick quote to show how this truly is directly in there:
> We also compete with a broader set of model providers operating at or below the frontier, including large companies, specialized AI labs, and a growing range of other open-weight or open-source (shared weights, training data, and code) models released by international and domestic organizations.
> Additionally, open-weight or open-source AI models may capture a portion of the market for certain use cases, which could exert pricing pressure on our offerings or lead certain customers to adopt open-source alternatives for those use cases.
“A portion of the market for certain use cases” meanwhile the top 5 models by token consumption on the day this is posted are all Chinese/open weight models.
I'm a fan of some chinese models, but I keep seeing this repeated over and over using OpenRouter as the source. However, most users of Claude and OpenAI don't use those APIs over OpenRouter, so that's not sufficient to draw the conclusion that they're the top models.
"Best available public data source" isn't a good reason to insist on using irrelevant data to draw conclusions like "top 5 models by token consumption are Chinese/open models".
I agree with the threat to the expensive providers but why is openrouter use representative of overall token spend when you'd think many companies are buying directly from anthropic or openai?
How much marketshare does OpenRouter have? They show serving under 200T tokens per day. Just looking at Anthropic rumored $70B ARR ~ $191M per day implies 347T tokens per day if only serve Opus 5.5 at API pricing (assuming 95% cache reads, 4% non-cache inputs, 1% output tokens distribution). Obviously, token distribution assumption may not hold (although I'm pretty sure cache inputs dominate distribution for all coding related workloads), but 100% Opus 5.5 at API pricing is highly favorable to OR. Even under these favorable assumptions AR is 57% of token volume of just Ant. In money volume they are likely very small compared to frontier labs.
The page doesn't load for me, but surely token consumption isn't a very good metric?
A poor model could require many more runs to solve a task, or much longer internal 'thinking' runs - all of which will increase token consumption but are a bad thing for the user.
Majority of big enterprises, or in fact any big consumer will not go there , why pay the margin to open router , if there’s no margin or very very often subsidies to use something else . Aws bedrock for example does not even have up to date Chinese models .
I'd argue there is a bias for using mostly open models through open router as using anthropic/oAI models from open router makes little sense (more expensive).
The closed models are on Openrouter as well. But to the original point, you're not likely to see many people use Openrouter to run Claude or Codex, so it's not good for making comparisons on that basis.
If you could go back in time and buy $1000 worth of Amazon when they IPO'd, it would be worth 3.3 million today. Because Amazon's stock value has grown on average 30% year over year for 30 years. Amazon's valuation when they went public was around 400 million.
How much can Anthropic reasonably grow from a 1.5 or 2 trillion dollar valuation? If we want them to grow even half as much as Amazon they'd have to be worth 5.9 quadrillion dollars by 2056. That's 5,900,000,000,000,000, a 16 digit number.
Maybe I’m naive but I expect any kind of “we’re just taking over the world now” event with any AI company will be met with enough resistance from 99.99999% of the world’s population that they’ll have to make it a sweet deal for us if they want to survive.
The "dark-enlightenment" billionaires have been planning for a "collapse" for years, and their plans involve bunkers, acquiring citizenship in remote places, pervasive surveillance and armed dogbots/drones, the last 2 powered by AI, naturally.
On the one hand you'll never see a 100x return – that's been captured by private equity. But there's still a lot of long-term risk because these companies haven't proven they can deliver free cash flow to justify their valuations. Investing in SpaceX or Anthropic at $1T valuation is very different from investing in Apple or Nvidia.
IPO returns have been horrible for years. Past 5 year returns on S&P is ~80%, on NASDAQ 100 about 100% while IPO's have returned 10-15%.
I didn't buy Amazon in the early '00s for this reason, and I won't buy Anthropic for this reason. Maybe I lose out, but I like to invest in stocks that look like good investments.
Your argument that it's overvalued isn't really tethered to anything. It's about as whimsicle as the people saying "well it's worth any price because AI is the future." Of course the price matters.
Here is some way to start thinking about it. A lot of mature companies trade at 20-25x times earnings. So $2T needs roughly $80–100B a year in profit eventually. At 25–30% net margin, it means about $300–400B in revenue (something like Microsoft). Or 20%/450B (Google) or 10%/800B (Amazon). Anthropic is still growing rapidly. And intuitively i don't think it's crazy to suggest they may look like one of the current big tech companies in the future.
>Regardless of anything else that valuation is basically saying all their growth has been captured, unless they literally take over
Absolutely not. Not even close to true. They dont even need to become the biggest company.
> Speaking at the 2026 Per Jacobsson Foundation Lecture during the IMF and World Bank annual meetings in Bangkok, Clark pointed to an extreme economic scenario modeled by Anthropic economists in which U.S. GDP could reach roughly $44 trillion by 2030, which is a nearly 50% increase from the current $30.77 trillion in just four years.
If the total value of US public companies also increased by 50% in that time, they'd collectively be worth about $112T. I guess Anthropic could be worth 10% of that in some scenario? And if we're in that world probably capital has increased a lot faster than labor so US public companies could be worth like 150T or something. Who knows. Nothing about valuations makes sense any more, so what's one more drop in the nonsense bucket.
[0] https://finance.yahoo.com/technology/ai/articles/anthropic-c...
Anthropic growth rate is truly unprecedented at it's scale.
They are 10x revenue YoY.
Note: I'm not justifying it, just explaining how the markets are rationalizing it.Back in 2018, I sold a bunch of Nvidia stock. I had bought it in 2014, when deep learning was taking off, and it had gone up 10x since then, so I was feeling pretty smug about timing things just right.
Nvidia's market cap in 2018 was around $150B, and the largest company in the world was Apple at ~$800B. And part of my thinking at the time was, well... Nvidia is already worth about a fifth of the most valuable company in the world. How much can they reasonably grow from this valuation?
In hindsight, I can tell you: the answer is 35x (as of now, and who knows in the future). The idea that any company, much less Nvidia, would be worth $5T within a decade was laughable back then, and well, here we are.
Besides the financials I do think there is merit to consider what you do as an investor. You make it easier for the company you invest in to access capital and in such a capex heavy world that is actually meaningfull. So if you believe anthropic is creating more long term benefit for the world than say Google, you might want to buy regardless of direct financial expectation.
Honestly, in a company that isn't returning capital to shareholders, I don't see the point if it's a company that isn't somehow subject to a potential acquisition. If you don't have a path to monetize your stake, why buy it? These days, just vibes. TSLA and SPCX might as well just be another crypto like Bitcoin
Unless you have special insight, you should assume all stocks are equally good buys.
There's not going to be an IPO at a price where everyone agree that it'll see a 30% growth over 30 years. Obviously that'd be priced in.
Also rare for an IPO, I assume.
But in the past, rules & regulations basically forced companies to IPO at a certain size. This meant that when they IPO'd, there was still growth upside.
Those rules are gone now, so they can stay private and have all the growth happen privately. When they IPO now, it's more just an exit. The growth was captured by insiders only.
So far, even major disruptions were still affecting relatively small segments of the economy. Car lobby in Germany, tech in the US, "Big Pharma/Food/etc”. They needed the rest of the economy.
But if some AI company figures out a way to monopolize everything: new companies, old companies, physical manufacturing - all the things they say they will, please buy here for lots of money - why would they be bound to pay out dividends or otherwise share the fruits of their economic labour?
I’m not saying specifically Anthropic would be looking to screw its investors. Rather, if you control an almost omnipotent genie, wouldn’t the temptation just be too much?
Or temptation aside - will money even have any value? If some AI company rebuilds the economy from scratch, and control everything from accounting to shoe making, why would they respect the value of some fiat tokens? It’d be like the conquistadors respecting the shells and beads of their new Aztec subjects.
Of course, perhaps none of this happens, but then the question is, how good an investment all of this even is.
The value of money, and the ability for average people to have influence on future events, ultimately is tied to the fact that the labor of an average person has inherent value.
Once that is no longer true, all bets are off: All promises of compensation become meaningless, and it's easy for those in power to rationalize to themselves why they no longer are beholden to their earlier promises. They will say to themselves "The situation ended up more nuanced than we expected"
(Which is exactly what Google said in February 2025 when they reneged on their pledge not to use their AI for military applications)
We also have the power of the vote, at least for now. I understand that that is limited, but it isn't nothing.
There is also just the power of having a lot of people. We don't yet have the technology where one person with a lot of machines can dominate a society. It still takes people.
By who? Lula just got reelected and a blue tsunami is coming on the heels of the Mamdani Mandate.
They don't want us to have any power left a few years from now, and they're winning.
Although if you have killer robots, then all bets are truly off, and we go the way of the dodo, literally.
(I don’t actually believe in this LessWrong-esque rhetoric, reality is more complicated, but it’s fun to muse about.)
EDIT: If oligarchs with magic AGI really don’t need our labor, nor are they concerned by our violence, then perhaps we become more like ants rather than dodos: we organize to help each other, creating a somewhat traditional economy around the scraps that don’t matter to the oligarchs, relying on obscurity and harmlessness to avoid getting toyed with a magnifying glass. I suppose that’s slightly better.
Even like 1-2% of the adult population going in the streets with makeshift weapons is enough to take over any country on this planet.
Data centers are extremely easy to disable too, take down power, data or both
Although actually: that’s kind of what humans are… Hmm.
I suppose humans can’t make better and better humans, that’s the difference.
Although actually: that’s what technological progress is… Hmm.
We still live in a finite, constrained, physical world that has to obey the laws of physics. We have a looong time before we get fully autonomous self replicating decentralised robot armies.
I think people conflate the real world, sci fi and their wet dreams a bit too much.
We're at the "this thing is kinda useful sometimes but still mostly annoying" part, not at the "skynet in 48hrs" part
Without some really fundamental social and economic reform, I'm anticipating a squeeze as automation increases, that ends with something like robot armies finally reducing the working class to barbarism, by blocking access to all the valuable resources.
And it will be some oligarch(s) commanding it, not some rogue autonomous AI.
So not "skynet in 48hrs," but capitalism taken to its logical extreme.
I'm not so sure. The front line in Ukraine seems to be pretty good at stopping people with access to military technology. I don't think an untrained and uncoordinated mass of civilians could do a better job, especially against future tech that's more sophisticated and available in larger quantities.
As military tech gets more and more inhuman, the power of masses of bodies is likely to decrease, and there will be even fewer opportunities for moral qualms to give civilians a chance.
https://en.wikipedia.org/wiki/2013_Metcalf_sniper_attack
Some dude in France just carried an attack with a ww2 sten gun, there are hundreds if not thousands of AK47s, grenades, etc. available on the black market. You can buy drone ready fiber optics cans on aliexpress, thermal/night vision cameras, etc.
Military tech is good but you still need people to follow orders, I very much doubt they'd side with the sociopath tech execs, nor their governments.
"Hundreds if not thousands"? That may be enough for "rando attention-grabbing but ineffectual terrorist attack," but we're talking about violent resistance to a fully-automated tech bro.
> Military tech is good but you still need people to follow orders, I very much doubt they'd side with the sociopath tech execs, nor their governments.
I already addressed that, and that may not be true in the future:
>> As military tech gets more and more inhuman, the power of masses of bodies is likely to decrease, and there will be even fewer opportunities for moral qualms to give civilians a chance.
Say you have some area you want to exclude a desperate mass of civilians from. Technically you could do that today: just stick a guy in a pill box with a machine gun, and slaughter them like it's World War I. But said guy might have a problem with that, and refuse to pull the trigger (or stop after gunning down a few hundred).
An automated AI machine gun in the same pill box will have no such qualms, and will mercilessly gun down civilians to the last bullet. And that gets more and more true the more and more you automate combat. Maybe a technician wouldn't setup the machine gun in that place or reload it after what happened, but that goes away if setup and resupply is automated, etc.
Data centers might be easier but
a) Will have a lot of security. It's much easier for somebody with money and connections (and now even intelligence+knowledge) to assembly a defense force than it's for a ordinary people to learn how to make proper molotovs, let alone learn how to shoot. And they will know when it's coming because even today's LLMs are good enough to surveil the entire internet.
b) I don't think they burn that well. When Ukraine strikes oil depots or warehouses, you can easily find images of them burning. I haven't looked particularly hard but images of droned data centers burning are quite a bit rarer. (I haven't seen a single one before actively searching, they do burn, but that's with military grade explosives.)
On the other hand, that way we'll finally get to "reconnect" with nature...forcefully.
In the second world war, Germany had impressive science and technology, but, as Stalin said, quantity is a quality in itself, and The Third Reich found out that it was an impossible task to get the metals and fuels for their advanced jet engines, rockets and U2 boats, when between then and those resources there were masses of tens of millions of under-equipped and malnourished soviet soldiers fighting what was an existencial war for them.
Bombs. You mean bombs. Throwing killer robots at a "problem" is like throwing knives or spears: you just gave the enemy your weapon. Unless they explode. But then you just wasted a lot of money on a really smart grenade.
we already do..
You might lose your value, others might gain.
I know it seems laughable, but we’re in an era right now of extreme competition where you cannot afford to just be nice to people.
But eventually there comes a point where companies have enough power that they don’t need to keep people in line by force: just give people their bread and circus, watch your little AI videos and talk to your AI friends and enjoy your standard housing and provisions. Do some work if you want, no one cares if you do or don’t, it’s largely performative. This basically kills all motivation for resistance or lashing out. Why go out and risk your life fighting for vague reasons when you can be perfectly comfy at home instead and have all your needs met?
If you can control the masses without their complaints, you can solidify power for a long time.
All real world power, including ownership (both physical and intellectual), is based on the ability to use violence.
As long as the majority - normal working people - have the potential to do more violence than those who want to control us, we have negotiating power. Minimum wage, 8 hour day, etc - those were all negotiated with the alternative being that those who wanted to pay us less and work more got killed.
I think this is the major hole in the argument, and in the "AI maximalism" position you present. There is no such thing as an omnipotent genie, or a magic eight ball that can answer any question. Any technology has limitations, and if you assume as a premise that the technology does not have meaningful limitations (or that the limitations are irrelevant, which is really what you said), the conclusions you draw will also make no sense. This is how you get nonsensical ideas like the singularity.
So perhaps they would only respect money and property up to the point that it's necessary.
The more realist answer is that they will keep respecting money and property as capital works to reinforce the status quo and enrich shareholders. You think just because you can do your job faster--or completely--with a machine that you have to work less? Hardly! Now this is where interesting policy questions spring up but I digress.
https://archive.is/20251015175242/https://www.bloomberg.com/...
As long as they're still looking for prompting customers, they're clearly not there yet. There is some solace in that.
because they don't control the physical paper that is money.
I dont understand what you mean by "fiat tokens". I don't imagine most people will accept tokens as a currency because they are as good hold of value and predictable as bitcoin.
In a token economy, certainly what you say is a possibility, but as you can imagine, that economy will be unsustainable so back to "regular" money.
But if I have a near magical genie who can make me anything - software, farming business, physical things - and at a fraction of economic input compared to the legacy monetary policy - then the money is worthless. As the Aztec shells were to the conquistadors.
That they can’t print USD is irrelevant.
> Money is a medium of exchange
That's an oversimplification. It comes with a lot of rules and authority that will be enforced by the issuing authority that a simple "IOU" on a sheet of paper lacks. IN the continental US, you cannot refuse to accept a dollar note. You certainly can refuse to accept the very IOU we agreed on a minute earlier.
Most of the developed world already has magical genies - certainly an overwhelming majority of people on HN earn enough to have LLM subs that build code, 3D Printers that print physical things.
The challenge always has been and will be humans.
You just cannot live in a vacuum. If you could subsist entirely on cheetos and figured out how to make an entire lifetime's supply of cheetos, after N days of watching Netflix, arguing on HN, raising chickens and goats, one day you will want to go and talk to a human.
Soon after, you will need a currency.
This is a false–albeit common–misunderstanding. "Federal statutes do not require a seller to accept cash as a form of legal tender for payment of goods or services that were rendered. Thus, businesses may establish their own policies regarding whether they will accept cash as legal tender" [1].
[1] https://www.law.cornell.edu/wex/legal_tender
Yeah you can. Tell that to all the stores in rougher neighborhoods that kept getting held up at gunpoint for the cash in the register, so they stopped taking cash. Bit harder to get money out of a stolen credit card terminal.
Minor side note: this is true only for repayment of debts. Some local jurisdictions require private parties to accept cash for new purchases, but there's no federal requirement to do so.
And if your "near magical genie" can make an operate military equipment, you don't have to respect existing authorities anymore.
Basically, the "AI maximalism" scenario kicks the legs out from under all these concepts and social institutions you're relying on.
> Most of the developed world already has magical genies - certainly an overwhelming majority of people on HN earn enough to have LLM subs that build code, 3D Printers that print physical things.
Not like in the scenario we're discussing. Whatever "magical genies" we already have are incomplete and need operators or have serious quality problems. Most of us depend on those limitations for our livelihoods, and those limitations also give levers to control them.
> You just cannot live in a vacuum. If you could subsist entirely on cheetos and figured out how to make an entire lifetime's supply of cheetos, after N days of watching Netflix, arguing on HN, raising chickens and goats, one day you will want to go and talk to a human.
An oligarch with the "near magical genie" could easily build a town of 5,000 to satisfy his needs to "talk to a human."
I'm also interested what this "entity in charge" does? and why would it do anything at all?
He just means it as in “credits”. “Fiat tokens” as in arbitrary units that are said to have value de facto by consensus, but don’t have any inherent value.
Yeah not the best choice of words in this context. And it’s quite a LessWrong-esque leap of reasoning.
But I do get the point: either Anthropic is successful and they transcend money, and thus (somehow) screw over their investors, or they are not successful. Their investors get screwed regardless.
Again, I don’t really agree with it, but it’s an intriguing point.
They won't be able to control saud AGI. Ref Ultron
If Microsoft Windows and Office can have a valuation in the trillions then Claude eventually working its way to the same ballpark isn’t a crazy assumption.
Doesn't that factor into the future revenue? Feels like people imagine suddenly fully owning the means of production in a vibrant economy but how does that really make sense?
AI maximalism is a Silicon Valley religion. You don't need anything close to it for some of these valuations to work. (Anthropic would be worth ~$500bn at Google's IPO multiple on revenue [1]. Anthropic is currently growing 6x faster.)
To be clear, I think these valuations are rich. But the notion that AI maximalism is required to sustain them is just false. $1.5tn sits comfortably on about $60bn of earnings, which with Anthropic's gross margins requires on the order of hundred of billions of dollars of revenue. That's super ambitious. But not Anthropic is the economy ambitious.
[1] https://news.ycombinator.com/item?id=50247011
[2] https://www.multpl.com/s-p-500-pe-ratio
"AI" doesn't pump/treat sewage or drinking water, grow crops, mine metals, change wound dressings, deliver babies, stock grocery stores, drill teeth, walk dogs...
It's not the replicator from Star Trek!
Really the only scenario where Anthropic could screw over its investors in the way you're describing is if it could also take over the legal system and modify its own contractual obligations. Which, I mean, I guess anything is possible if we are in AI maximalist-land. But "AI is the law now" would be a much bigger story than "investors frustrated with low dividends."
The closer you get to the real or plausible "omnipotent genie", why would the person in possession of such a thing respect the rights of the formal owner - and why the engineers and operations managers respect the right of the management - this along with the question why the maybe-conscious super-intelligent machine itself would respect the rest of the hierarchy?
For now, these structures actually need massive resource inputs and that doesn't look to change soon but naturally one should be on look-out for the possibility of the tide shifting.
Lots of other fun risks (highly recommend checking that section) but not that one :(
There will be an oversupply, demand will be there too, but no one can afford to buy since most jobs have been replaced by AI. So the price of goods and services should go down, or some form of UBI will have to be implemented which is just socialism for the masses. Its either that or total anarchy (also socialism).
If humans remain in control of it, then how can it possibly lead to anything other than extreme oligarchy?
Depends on the distribution of such AI. For example, if everyone on Earth has their own, personal superhuman AI, it would not lead to extreme oligarchy. If only a handful of humans control superhuman AI, it would.
We don't have democracy because somebody thought it was fair or just for people to rule themselves. We have democracy because in the past, people got angry, picked up rifles and shot enough authoritarians (and their submissives!) for the rest of them to understand the group with more people has more firepower and tends to win.
So now we periodically check which group has more people with ballots instead of bullets.*
With autonomous drones and robots, democracy stops being the local optimum.
And once we slide (are pushed off) into a new more stable state (pun not intended), we won't have the (fire)power to get out of it.
* actual AI, which does exactly what it should correctly, not a statistical model of behavioral patterns
* but indirect democracy is expressing a point in n-dimensional space (your opinion) by selecting one of a predefined set of points (parties/politicians available) - which is stupid - and the cracks are already starting to show as e.g. nobody wants more surveillance, yet we keep getting more of it in both EU and US
---
The "permanent disempowerment" people keep talking about won't be a "rogue" model, it'll be doing exactly what told by the rich and connected.
1. the goal of ai is to end capitalism by disrupting scarcity in economics
2. if ai can build a closed system that prints ai factories, the 99% of humanity essentially are just genetic diversity live stock.
I don't think the ultra-wealthy care about genetic diversity.
EA-aligned AI labs share this exact ethos. In their view, fiat money and equity markets are merely temporary scaffolding used to raise capital until AGI is achieved. Once a central superintelligence controls manufacturing, software, and logistics, resource distribution shifts from market supply-and-demand to algorithmic optimization.
[0] https://digital.library.cornell.edu/catalog/ss:34227574
[1] https://en.wikipedia.org/wiki/Joshua_N._Haldeman?hl=en-GB
AI oracles are the central economic planners. But after years of perfection they have made a couple unusual "mistakes" and a human is trying to discover why.
Anthropic thinks it is. The got the demand / datacenter match right in Q2, got great margins, and committed hard.
They've got:
- $114b committed to Google
- $110b committed to AWS
- $161b committed to Broadcom
- $120b committed to SpaceX
If the party continues, they'll go from $50b in revenue to $500b and be fine.
But if they don't, it's going to hurt. And that's their only choice, because otherwise, they end up with a frontier model and 50% of the capacity and get eviscerated on either availability or last-minute datacenter leases.
It's a big business, but it's not an easy business.
I'm not going to predict whether Anthropic succeeds or fails, just that it's very misleading to claim that Anthropic needs to grow to $500b in revenue without making it clear that it's $500B in revenue per decade rather than $500B in revenue per year which is what most people reading such a number would assume.
But if you buy them today at a $1 trillion valuation, and they only make $40 billion in annual profit, your investment will go nowhere. They need to be growing profits at 20% per annum to justify a PE OF 25.
And then you have the competition problem. The cheap open weight models are good enough for many (most?) tasks.
And then you have the problem that LLMs may not be that useful outside of programming, customer support and law (and doing homework).
- 161.2B w/ Broadcom: 2026-2031
- 120.5B w/ SpaceX: 2026-2029
- 114.5B w/ Google: 2026-2033
- 110.0B w/ Amazon: 2026-2036
- 44.9B w/ Microsoft: 2026-2033
- 44.6B w/ Nscale: 2026-2033
- 41.3B w/ Lambda: 2026-2034
which is around $63.7 billion / year if spread over 10 years, but with most of it due earlier than that.
SpaceX was the only one mentioned as cancelable. These are listed under "Infrastructure Service Arrangements" on page 170.
Those vendors would very much like to retain as much of that business as possible. If the space goes sideways, I would very much expect some kind of renegotiation/work out.
If Anthropic's revenue story doesn't materialize and the AI bubble bursts, these companies are in a world of hurt. It's probably not fatal for Google or Amazon but would be a major drag on the stock price (perhaps why Google has dropped from 400 to 315 over the last couple months as the AI story soured), and it could be company-ending for Broadcom or SpaceX if they end up building out infrastructure to service these commitments.
I remember before I left Google, one of the TGIF questions (which are now AI syntheses of many peoples' individual opinions) was "What happens if AI is a bubble and it bursts?" His response was "If that happens, the whole industry is in trouble." I see now what he meant.
If the AI companies go tits-up, that introduces counterparty risk, the revenue doesn't materialize as cash, and suddenly their earnings take a nose-dive. If they've staffed up significantly to design and sell these AI accelerators and suddenly there's no market, they could be in a lot of hurt.
This is just the compute, which primarily covers training + inference. They still have to run the rest of the business. If you think AI should look like SaaS and spend 10% of their revenue on compute, that's $1T in revenue. If you think it's a hardware business, that's 30% margins and perhaps $200b in revenue. I went with something in the middle at $500b.
They won't disappear as a company at $200b in revenue, but I don't think that's their aspiration. These commitments imply to me that they're confident they can do much better.
Idk where you got this figure from, but the actual figure are very different from that:
It's 120B over four years for SpaceX alone and 120B for Broadcom over 6 years. These two players, representing less than half of the total commitment, already give you an annual commitment above 50B.
what you're buying into here is a company that is already large on the idea of growth over the next 10 years.
Modern IPO's just reek of investors cashing out
Google closed its first trading day "worth more than $25 billion" [1] with $1.5bn revenues, up 234% from 2002's $440mm [2]. That's a 16x revenue multiple, 0.07 growth adjusted [3].
On a similar revenue multiple, Anthropic's $16.3bn half-year earnings are worth $543 billion. Adjust for Anthropic's 1,400% YoY growth and you're well over $3 trillion.
Obviously, it's a lot harder to grow at a thousand percent from a $16bn baseline versus a few billion. But purely on a multiple basis, Anthropic is in a similar ballpark as Google.
[1] https://www.nytimes.com/2004/08/19/technology/shares-of-goog...
[2] https://www.sec.gov/Archives/edgar/data/1288776/000119312504...
[3] https://www.investopedia.com/terms/p/pegratio.asp
Google was profitable, free cash flow positive and had no debts basically
Anthropic is burning money by the millisecond, no profits, free cash flow negative and has lots of debts & commitments
In reality, a valuation based on revenue (sales) is bonkers to begin with, but even worse when you consider that Anthropic has so much debt that it doesn't have positive equity value, it's in a deficit ("When liabilities attached to an asset exceed its value, the difference is called a deficit and the asset is informally said to be "underwater" or "upside-down""). At least SpaceX has more assets than liabilities.
> SpaceX has more assets than liabilities.
is definitely a choice thing to write on the day SpaceX announced a $40B debt deal to purchase compute to run other companies' models. Based on available information, this will put SpaceX into a place where it has more liabilities than assets.
You're speculating what SpaceX balance sheet might be, like they haven't just released MRQ earnings report last week
Just go read it and you'll see you're wrong even after you subtract that 40 billion SPV https://www.sec.gov/Archives/edgar/data/1181412/000162828026...
A very large part of that revenue is paying for inference. There’s not enough leftover for the committed outlays. So it has to come from smucks I mean investors.
Today's prices are the ceiling. But AI capability is getting less of a scarce resource with every passing day and it would be a big mistake to plan that your current margins are going to be your future margins as well. Long terms AI will converge on energy costs + capex write-off + margin and the latter will be a race to the bottom.
What's the endgame once the dust settles? Is it going to be a utility like water or electricity and the cheapest offer will prevail, in which case margins will be crushed? Or is Anthropic (or some other big AI lab) going to swallow everything and become the Google Search of LLMs, with everybody else fighting for scraps?
Or is it local compute, models becoming more efficient and hardware becoming cheaper (again) and companies hosting their own AI clusters like they would run SAP?
I think there is a plausible path where this valuation actually works out, but it's a narrow one IMO. I also want to acknowledge that I personally would prefer if it wasn't the case and a more distributed, open model prevailed.
It's just like a utility with the slight difference that it can be sold at a distance without significant cost for transportation, in many ways it is the ultimate digital good. Unlike Spotify copyright is not an issue, unlike your electricity, gas, internet or water company there is no last mile problem. Unlike Google there are a ton of qualified contenders already (Google had to be better than Altavista, which wasn't hard, but they were so much better they managed to lock up search for long enough to cement their position).
Anthropic has none of the advantages and all of the disadvantages. On top of that all AI companies seem to be run by megalomaniacs.
Not all of them. Only those who outspend all the others and then you never really hear of any others. It's like the most basic requirement for the job.
Isn’t that what it takes though? Doesn’t startup culture celebrate this attitude?
Some do, unfortunately. But that's not all of them.
I think this might genuinely going to become a problem for them in the long run. People just absolutely hate their guts. That's a very strong motivator to do everything possible to get rid of them.
We'll of course see in 5-10 years if the doom PR will work out, but that always was a rather high-risk gamble, and it already looks like it might not.
There is a significant amount of businesses and people that are very willing to switch to literally anyone else just out of spite alone.
My country has no frontier models; since I've no national grounds to support one provider over another, a strong degree of provider diversity is an obvious benefit to me. I also think a highly competitive global market is a good thing for mankind in general, any hegemonic power having a monopolistic or oligopolistic position in AI provision is probably the 'bad ending' for most of us since it represents an enormous concentration of democratically unaccountable power regardless of the power which 'wins'. I'd argue it's rational, not spiteful to favour provider diversity on those grounds.
I really don't see any situation where local AI doesn't absolutely eat the big labs' lunch. They can't compete and the only way it makes any sense for them to exist is if the government somehow tries to ban local AI, which likely wouldn't work in the first place.
Someone like me who spends a lot of time in the anglosphere puts faces on companies like OpenAI or Anthropic. I doubt that's true for most people, especially outside of the USA. They're just big companies, like 3M, DHL or Toyota. Who knows what the management of these companies think of the future of humankind?
I would expect than personality-driven rejection of American tech from abroad nowadays is driven mainly by Trump and, to a much lesser extent, Musk. Everybody else is just "some guy" to 99% of the population.
Decisions in tooling are not made by the 99% of the population, but a subset that is likely a lot more tuned-in to all this. After all, that is kinda their job so that they can make good decisions
Our modern capitalist societies are, at the very least, amoral.
And back then, the world was very different. ZIRP, cryptocurrencies, infinite highs, peak social media. All that stuff
German here, every stupid utterance of at least the orange clown makes national headlines here. Frankly I wish our populations were more exposed to the utter buffoonery of the rest of the American wannabe elites, maybe people would then not go and type their deepest fears into ChatGPT.
So I'm doing what I can - I only use local models for 100% of my personal coding. (And their capability is amazing! Qwen 3.8 Flash Next leaves me wanting for nothing at this point.)
And I know open weights aren't enough. I'm ready to support open training if/when we get around to that. I hope once hardware prices ease, we can see homelabbers building small AI hosts (small by homelab standards yknow. So let's say 512GB host ram and 1-2 32GB cards, though i hope we also start to see AI cards with lots of vram but less compute cores). Then maybe we can do folding@home style distributed training.
In a time when software freedom is perhaps more threatened than ever, I'm happy to see that information still WANTS to be free, perhaps even more than ever. Look at how easy it is to distill claude! Despite, presumably, anthropic working very hard to prevent it.
Is engineering the factories that make the hardware not nuclear engineering? Even if not, considering there exists only 1 supply chain in the world capable of making them, it seems pretty revolutionary. And that moat seems pretty big, given that it hasn't been crossed for many years.
In the long-term, the marginal cost of a request is zero so prices will plunge and a lot of the fixed investment will get stuck. The difference between the cost of training a model/infra and serving a request from that model is a clear problem for economics.
What happens with Anthropic specifically is less clear because they, as every company in the same position in the last 150 years has done, are going to push for regulation. A lot of the risk has also been shifted onto neoclouds. The value of the customer relationship is, however, effectively zero. A core part of their strategy has been to build stuff out like CC to differentiate that but, ultimately, that won't work.
The other strategy they have employed is trying to get other companies to stop training new models. Again, seems unlikely to work.
There is no scenario in which they become Google search outside of government intervention. Obviously this is a key part of their strategy now but at best, this will only work in the US and Europe (I would actually say they are much further along in Europe where there is a strong tendency towards corporatism and centralisation of power, they could be "Europe's AI").
The risk is that USA and China will come together on a joint "AI non-proliferation" agreement in the same way that nuclear technology became restricted by the countries that already had the capability. This will lead to a de facto techno-colonization of the rest of the world just between themselves.
This was a topic of discussion at Trump and Xi's AI summit just last month.
One of the largest legal services partnerships here in NL just launched their local DC so they can maintain confidentiality. Do you think they are 'running hobby models on 5 year old GPU clusters in the basement'? Or does a couple of racks of GB300's sound like maybe they know what they're doing after all?
This is all on the horizon. We are only barely scratching the surface and right now it is largely hobbyist having fun with it, but we already see the potential of the AI revolution and where it is going.
The economic logic is the same as that of operating systems. AI models are very expensive for one company to make, but lots of companies need them. So companies are better off collaborating on that side of things and competing on something else.
Economically, the AI models that require big servers with lots of GPUs in data centers should likely be more interesting to investors than the AI models that can run on local hardware.
If a medium/small country deemed it a threat to rely on US/China for AI capabilities, they can get 95% of the utility by banning all American and Chinese models and just using local ones.
This contrasts to something like oil or nukes, where if you're not one of the countries blessed with them, you have a serious power imbalance.
https://en.wikipedia.org/wiki/Carrington_Event
With each query OpenAI and Anthropic get more context about their users. When I compare answers between AIs the ChatGPT answer often includes useful things it inferred from earlier conversations. Losing that context could be a meaningful barrier for a customer to switch to a cheaper service.
Not unless they break their own TOS. The temptation must be very large to do so and is probably why those settings keep mysteriously shifting back to 'yes, I give all my data to you to do with as you please'.
The only ways to fight this is trying to either: 1. Block it by cutting off access, which is pretty tough because it basically means you cannot offer unmonitored access which is a no-no to a lot of customers, and even then the workload looks very similar to actual real workloads and if the company doing the distilling is a bit sneaky and using intermediaries etc it's almost impossible to stop, or:
2. Try to use IP law to block the practice, which is pretty gross given how they got the data in the first place, and so far no court has supported them on this. And even if they can make it illegal, it won't actually help because there are countries that see having top-tier AI as a national priority and will actually support their companies breaking laws to get there.
People misunderstand why Anthropic is being so stingy about granting access to their top models. It's not some kind of marketing ploy, they know that if they release them fully openly then there will be a Chinese open-weights model in 3 months that is just as good. Also the reason why they try to hide chain-of-thought and the probability distributions.
Isn't this somewhat akin to a model learning from its own inputs? Doesn't that behavior lead to model collapse? Either the model is trained on pristine data, in which case it stagnates, or it's distilled from another model, which leads to model collapse.
Pardon me? You cannot be serious...
https://media.defense.gov/2026/Sep/08/2003992823/-1/-1/0/CSA...
Independent verification from non-aligned entities would be a minimum for something like this. Note how in spite of all of the claims not a single lawsuit has been filed.
You cannot believe intelligence agencies when they do not offer proof. Their job is to provide (reputationally but not factually) authoritative story lines that protect big business interests from competition overseas. Sometimes they protect US business by bombing their competitors.
It’s going to be hard for companies to justify paying $1000s per month to frontier providers when they see what’s doable with open versions.
Top models, capable of discovering and inventing stuff, held back from public, and available only as for-rent research service (or whatever the relevant bureaucratic term is) to big corporations and government agencies like NASA, DARPA, NSF, NIST, DOE, etc. only.
I have a feeling that we, the public, will stop getting access to more intelligent models starting next year.. i mean, not the incremental ones, but, major ones.. like the one you got going from opus 5 to opus 5.5.
At this point, the best guess is he plans to deflate the currency to make the debt worthless.
That might be the best possible intended outcome, but it also seems unlikely that Donald Trump and his government are involved in anything so far-sighted. Just look at the man's public behavior over the last year; either he is an incredible actor, or this is not a government where anyone in power cares about anything beyond the Big Man's whims of the moment and their personal benefit.
There's also the incompetence of the ones with the longer term plans making whatever is played out more inscrutable. Although they have actually implemented a significant portion of project 2025.
I personally think it's really funny how if you were to try to reverse engineer his motivations based on the actual outcome, then the most likely answer is that he's a joint Chinese-Russian spy based on how much they've benefited from his elections.
The world is going to be very different in another two years.
fuck trump and republicans. and yes whatever goodwill you had built up over the last 60 years was up and away like a fart in the wind when you elected a corrupt pedophile for the second time. And it cant be built back, ever. No one trusts you no to pull the rug if we became reliant on you again. What we will have though is a relationship with allies built on equality rather than one main player calling the shots.
Not even just from Chinese models, but from companies/labs like Mercury
E.g I know people in high finance who switched - they don’t need frontier for many tasks - Anthropic is getting jack all revenue from them.
If the tech improves massively - Anthropic still gets nothing - since firms will want on-prem or cloud offerings that ensure zero data leakage / IP.
You lot haven’t played this out.
We've seen businesses moving everything to the cloud before AI, we'll see more of that as regulatory requirements are increasing.
i keep thinking how crazy it is we went from ChatGPT releasing in 2022 to multi-trillion IPOs 4 years later. the industry still hasn't agreed on how to generally use anything. crazy times ahead.
For certain AI use cases, AI will be like a utility. For other user cases you need to pay a premium for the frontier. For other use cases AI will be local.
Even in the industries you mention (water and electricity) you have all sorts of businesses. Like people selling water in fancy cans for a large markup or batteries vs wall power.
It's very possible given the current environment that LLMs go the way of airlines. Low margin businesses that are essential to world economics with heavy price competition.
There are tons of private datasets where a model will be fine tuned to provide useful domain specific responses.
Given the trillion-dollar spend, the theory is that every many woman and child in the western world will devote a substantial portion of their income (like 5-10%) towards some sort of AI subscription.
or...
That doesn't happen. All the AI investments go south and every man woman and child in the western world will devote a substantial portion of their income (like 5-10%) to bailing out an economic system that went all-in on AI. Either way, the money has already been spent.
The already shaky economic system (and associated political systems) can't take the strain of every man woman and child in the western world devoting a substantial portion of their income (like 5-10%) to LLM fallout, and we end up with a collapse scenario of some sort. (Which, to be clear, is near-certain to be worse than either of the above.)
It's a lose/lose situation here for Anthropic (and OpenAI) whatever happens.
This
Of all scenarios, based on the data we have now, this seems to be the least likely one.
It's not a great position to be in and it will still take a long time for the compute gap to close. In the meantime, Anthropic, OpenAI, and Google are essentially unchallenged.
[1] https://www.konstantinpilz.com/posts-publications/chinese-st...
Besides...
"If passed, the rules would require Chinese companies to obtain licenses to export the core technology behind their leading models.
They would also ban the export of A.I. that can be used to launch cyberattacks, as well as models trained on what China calls “core data.” The government broadly defines that as data that concerns national security, the welfare of Chinese citizens and the public interest. Experts say the scope includes data on the military or critical infrastructure, state secrets and other sensitive information. "
So pretty soon they won't even "do it".
[1] https://www.nytimes.com/2026/10/21/world/asia/china-exports-...
What makes you think there would be no alternatives, though?
Put it like this: Kimi K3.1 is downloadable and can be run locally. (If you have a datacenter.) This is a very capable, ~2.8T parameter model.
Now let's say that every Chinese firm goes closed in six months or a year and jacks up pricing... What's stopping a bunch of enterprising upstarts from updating all 2.8 trillion parameters, extending them, distilling the model into very competent flash models, or applying targeted RL?
Once the principles are understood and there are models that can be pulled off the open internet, it doesn't seem that hard to spin up your own LLM. You just need some financial resources and a reason for doing it. And that would come into play if the Chinese kill every closed American provider and then go closed themselves.
It's not quite like Uber. It's more like... well... imagine there are two computer operating systems, Gray and Teal. Gray is always slightly better, but it costs $50/user/month for a license. Teal is free. Eventually, when both happen to be in version 9.0, Teal puts Gray out of business. Starting from version 10.0, Teal starts charging $100/user/month from a license. But nothing's stopping you from sticking with 9.0, which remains free forever.
Perhaps what's "sustainable" is not clear, given that Gray was eventually dominated by Teal? In any case, versions 1.0-9.0 were, effectively, gifted to the public. We can appreciate (and even disapprove of) that commercial strategy while benefitting from its fruits.
There could be, they can actually come from open American companies too. Ask yourself why we aren't seeing a thousand or more American AI startups spring into life overnight to build "open" models. Follow the economics.
> What's stopping a bunch of enterprising upstarts from updating all 2.8 trillion parameters, extending them, distilling the model into very competent flash models, or applying targeted RL?
> And that would come into play if the Chinese kill every closed American provider and then go closed themselves.
What's stopping American or European tech companies from doing this today? It's economic and technical capability. I'm very suspicious of any suggestion that it is in any way not incredibly difficult to build and scale up LLMs. Maybe in the future it can be much easier, but in that case you run into a sort of tautology where it becomes easier but the leading companies continue to lead and do so by a significant margin because they're the ones that have the most talent and access to capital.
The premise seemed to be "an open China" versus a "closed USA". I'm not sure that's a great premise. If China can create open-weight models so can the US. If the US can close their models (as clearly evidenced by the article) so can the Chinese.
Seems more economic than technical. If the economics are covered, the technical aspects seem straightforward enough, and may perhaps be fully solved. I think there's proof of this in that there are a lot of different LLMs on the market. Even Xiaomi -- in-between making cars, e-scooters, backpacks, and home appliances -- spun-up an exceptionally capable LLM! (And one which is rather idiosyncratic. It's weirdly good at music composition and generation, which both Opus and Astra cannot do.)
The economic case doesn't exist for VC-funded US corporations, nor does it exist for cash-strapped nonprofits. In China, all such ventures are likely funded by a government development bureau. If Chinese ventures kill expensive closed providers and universally go closed themselves, there's nothing stopping the US or Europe from copying that same playbook -- unless, as may well be the case, they're ideologically opposed to subsidizing strategic industries.
I mean how useful are GPT-3 weights today? That's the kind of useful they'll be relative to the frontier.
I feel like the so-called "Deepseek moment" broke too many people's brains and they've lost the ability to reason about why frontier advantages matter. I think we have to learn some new core concepts and rate of improvement over time is going to be a big one, and not understanding that causes people to exaggerate the significance of downstream distillation that's done in response to it. It's cheaper and open and that matters, but it's not the kind of mattering that replaces the relevance or advantage of the frontier, and I feel like I'm not seeing people demonstrate that they know how to really compare the relative merit of these two things so much as zoom in on one to talk past the other.
I was using GPT-3 and the original Llama when they came out and realized that it is interesting, but not good enough - yet. But they are good enough now. And just like there are still people driving Renaults and Volkswagens the latest batch of open models will be useful for a long time to come.
It's like sure yea you can access the Internet and tinker around or whatever, and with some old LLM model you can have it do fun things, but on a scale of absolute usefulness and if we include what people actually pay money for and what is highly adopted, your laptop and model are severely outdated and by and large irrelevant. That's why the iPhone sells like hotcakes all day every day and twice on Sunday and Apple is a $5 trillion company. Society disagrees with your measure of usefulness.
Sorry I'm rate limited since Dang thinks I'm arguing to much on political topics (he's probably right), but to answer a couple of questions regarding "my old technology does this one thing" you are conflating your personal and nostalgic uses for old hardware/software with what is useful for society or business. If the old hardware was still just as useful as the new hardware it would be used instead of the new hardware.
The machine was bought in 2011 and it runs Windows Server.
I can do whatever I need with the device, apart from Gaming. Even YT works in 4k.
So, tell me now please why my 15 year old computer is not useful here?
Technology never was about the tech an sich but about what you do with the tech. For one person that 10 year old laptop is useless, for another it is a source of $500K / year in income. You, the user are the biggest factor in how much value you can extract from the technology at your command. I'm not sure how much longer that will be true but it definitely is still true today.
Compared to laptop quality, I suspect model quality will be a much bigger competitive advantage in the tournament of the marketplace. High-quality laptops are still limited by the quality of the software developer.
For now it is exactly the same with the models.
Also... employment in some parts of the stack is genuinely going away. I don't even look at CSS anymore.
To some degree, yes. But 'dwarfs' isn't really the term I would use. It is a bit slower, but the upsides are >> than the downsides for me. Not having Sam, Dario or Xi's minions looking over my shoulder matters to me more than any technological edge.
> Also... employment in some parts of the stack is genuinely going away. I don't even look at CSS anymore.
Yes, that's a fact, but that's orthogonal. I haven't touched either HTML or CSS in a long time now and yet I've cobbled together (I wouldn't claim ownership) a lot of stuff that 'just works'. I also would not expose that stuff to the world at large because I suspect it isn't nearly as secure as it looks.
I pay attention to frontend code just to keep code quality up. Frontend work is relatively low stakes from a security perspective and I've never seen the robots do anything problematic. I don't vibe code React but I think you could get away with it today.
Backend is a totally different story.
That's still a lot of engineering getting displaced.
Also, it's entirely plausible that an previously open model (that then became closed) will be much easier to distill than having a bunch of closed models.
I like Qwen as much as the next person, but that's a bit to credulous. Those models would not get the compute allocation nor distribution they do if it was not aligned with broader policy.
Neither do Anthropic and OpenAI.
It's a shame "AI" cannot be made to run on bitcoin mining dedicated hardware because they mastered that in only a few years
There are dozens of Chinese domestic AI accelerators: Huawei, Alibaba, and Baidu all have chips, there are a bunch of smaller startups too. The chinese mainland is behind on leading edge fabrication though, SMIC only does ~7nm class since they don't have EUV.
https://en.wikipedia.org/wiki/TSMC_Arizona
In case you're wondering as well:
https://wccftech.com/nvidia-cmp-170hx-8-10-gb-prices-explode...
It restores firmware features related to RAM, PCI-e speeds, BAR size, VFIO...
https://github.com/amoghmunikote/cmpunlocker
I won't use a Chinese model. Why would i bother? I pay $100/m for the frontier model, understanding it's marginally better than much cheaper alternatives. I get so much value from the product it's not worth shopping around
Think of it like apple and android. Plenty of people pay 2k for their iPhone every few years when android at 1/4 the price is just as functional. Why? Because they get so much excess value from the device it's not worth shopping around. For most people it's their only personal computer. From booking airfare, to filling out their kids permission slips, it's a device they use 10+ hours a week. They don't bother, until a paradigm shift happens and something is 10x better than the iPhone. I imagine llms will follow the same trajectory
I get (sometimes) frustrated with people that don't work in the tech industry over this concept, and having them rationalize that their usage is heavily subsidized by the distributor of the model.
The costs in compute, electricity, cooling, etc. per token is much higher than most people (I feel) who work in the industry realize. Which, cognitively makes sense: they just want the 'magic 8-ball' to give them a tasty dinner recipe that meets their specifications, for example, and don't care how the 'sausage' is made.
However, economies generally equalize with supply and demand, and this (most likely) will become cheaper as the technology progresses and optimization passes/new algorithms are discovered.
People are naturally sticky. If they're satisfied with a product, they'll stick around unless something comes along that is so much better it gets people talking. Open AI's 1B+ customers won't give a shit about Chinese models. Enterprise customers won't move to Chinese models, especially just to save money. They are a non issue, especially if the M.O is just going to be playing catch-up.
My last role swapping from Haiku/Sonnet to GLM dropped costs by 90-95% and increased quality.
Money talks.
I can understand that they might be cautious about sharing their data with a Chinese company.
But them being the most successful companies means that they can just buy their own hardware. And run whatever models they can get their hands on in there.
Even if those models are Chinese. They (the companies running them on their own hardware) would be in full control then.
if the chinese models have this aura of inferior quality around them, then sure.
if they manage to frame it instead as open source, sovereign AI, the calculus changes.
But I don’t think this will be the first time in history that money doesn’t win.
Models with tool access (and internet-connected tools like curl) can, though… is this really a useful distinction?
But also, I don't think you should use individual consumer behavior as a proxy for how the overall LLM market behaves. Current estimates are that individual users represent a pretty small share of overall genai revenue. Most of it comes from enterprise contracts. Those might be more price sensitive because the CFO gets a say in which vendor they choose.
For a couple years now I've been accustomed to choice of foundation model being a heavily scrutinized design decision because it's just about the easiest way to manage COGS. I can certainly imagine scenarios where, given the option to pay 1/2 as much in inference costs but with a 5% reduction in output quality, the boss would say, "Nah, that's a bad deal." But I have yet to encounter one in the wild.
Okay fine, it's $1,400 for a latest iPhone Pro with 512gb of storage. Point still stands.
> Most of it comes from enterprise contracts. Those might be more price sensitive because the CFO gets a say in which vendor they choose.
I think enterprise contracts are even less sensitive to price than consumer. That's the whole idea behind enterprise pricing. You'll see companies charge multiple times as much just for SSO for instance.
There are limits to this obviously, but to think that major commercial enterprises will switch over to some Chinese models to save some money is laughable.
So you switched away from the specialty product, but you're still comparing a top of the line 6.3 inch iPhone to a mid-market Android phone. Why not compare it to a Pixel 11 Pro with 512GB. That way they're at least comparable devices. But also, that would cost $1,220, which I suppose doesn't go well with the intent of suggesting iPhones are several times as expensive as Android phones.
The reason why I'm digging in on this is, when you start your argument with such a transparently silly comparison, it gives the impression that you're dealing in superlatives and willing to say just any old thing. Which undermines your own credibility.
So, getting back to corporate - multiple times how much for SSO? Okta Essentials is $17/user/month, which is a little over half as much as the base price for Cursor Pro, and about 2/3 the price of a basic ChatGPT seat.
For AI? Prompt comes in, tokens come out. The value of the 'ecosystem' is roughly zero to me. Switching costs between models are essentially zero. The UI and UX is the same whichever LLM runs underneath.
If you do use llm some, then the $20 tier makes sense, but that's not where the money is. If you use it a lot then a $100 sub probably makes sense. But if you're a BigCo that heavily uses it and pay API prices and suddenly you pay $200 million a month, well, maybe it's worth buying a bunch of hardware and stick it in a basement somewhere, and you won't upload all your secrets to your future competitor to boot. If US labs didn't care about the competition from Chinese models they wouldn't lobby so hard for banning the evil, unaligned, super dangerous communist models that want to steal our freedoms and make our gas expensive.
Ultra-cheap models like Deepseek are also very nice if you need to burn billions and billions of tokens.
If that were true, they would cancel subs and save themselves the load.
Yet that hasn't happened. So they must care to some extent.
With that, there are at least three distinct reasons to care about subs: PR, hook and training data.
It’s not unusual for someone to spend $5k in a week. 2 guys at my place just spend $150,000 over 3 months building out a factory.
We are aggressively exploring open weight models now.
Sounds like this will be another one of those things where everyone makes their money and it then will eventually become something experienced people 'blog' about.
I don't doubt it.
> Sounds like this will be another one of those things where everyone makes their money and it then will eventually become something experienced people 'blog' about.
Or not. The problem is that right now you and a whole bunch of others are trying to outrun a pack of lions. The lions have already taken down a couple of your group. The people further ahead have seen what the lions can do and they are attempting to speed up to the point that they can outrun them. Whether that will work or not depends to a large degree on what the other people are doing and they are not going to make it easier for them to keep pace.
That partially explains the lack of deep insight blog posts, besides everybody is just too bloody busy.
Wait until you are forced onto an enterprise plan...
LLMs don't have that. For at least 90% of users, the model in the back end is completely irrelevant to them. Switching to Kimi won't lose them their iTunes music.
It’s pure genius. There’s a lot of bozo’s here who cannot appreciate it and cry about fairness.
Many here don’t understand corporate finance do they? Hence the marketing hopium to fool people.
How many Astroturfers and Anthropic employees are here to convince us otherwise?
And claude code as a harness and skill/plugin/mcp ecosystem is far more valuable than any one model.
And coward for long-running tasks, though they're slipping on that one because they're really trying hard not to make Claude an assistant. We'll see if they react to Muse and change course.
But the Chinese free-weight models? Not a competitor. If/when those companies (or others) build vertically integrated productivity stacks on those free models, then we'll talk. Microsoft certainly saw that opportunity but couldn't get out of their own way and are basically roadkill at this point.
Google Workspace revenues are something like $25bn/q, and that's the entire workspace division, (including enterprise gmail sales, so the productivity suite is meaningfully smaller than that figure). It's taken Google a long time to carve that slice out of Microsoft's entrenched market position. It's not small money, but they'd basically be going to war with two of the largest and most profitable companies in history on their turf.
I don't think they can credibly take that business plan to the market and say it'll be worth $1.75tn. They're all-or-nothing on being in the model business, and everything else is superfluous.
$100B/year in revenue; SaaS so call it 70% gross margin, 30% net, NPV is about $500B.
Not enough if you think that's the only revenue Anthropic could every have. But even if they only peel off $100B NPV, it's incremental to an IPO valuation.
The same one that leaked itself a few months ago?
The value is in the harness! The harness leaked itself
Apple makes great margins on hardware. They are 100% not in the CNC milling business. But their investments at that low level and vertical integration allow for higher margins at the top.
Cursor had... nothing. A minor, indefensible value add to a much larger and wealthier supplier.
No, that would kill them for sure. Or did you mean 'open model progress'?
On that front, I think DeepSeek is a dark horse. They are really odd - not chasing revenue, care more about unit profitability, are obsessed with driving down costs (like Elon back in the day). As the founder says, they are content with where they are, being the model that does 80% for a fraction of the cost.
I mention them because they are playing a different game and might be able to out-innovate everyone else.
What a lot of people don't seem to realize is how much of the edge of the 'frontier' is in the tooling, the prompts and the harness. The LLMs themselves are already all reasonably close if you keep all the other stuff constant. Sure, one will have an edge in one domain or another. But that edge mostly translates to a degree of performance rather than some absolute. And if you allow for a few more toolcalls, a web search or a longer context then that difference is much smaller than it might seem at first glance.
Why would I pick anthropic.
Like if you want to design a survey you can send out, and collaboratively edit and test the survey, ask for changes in layout, wording, etc, and design the statistical analysis to be used, before sending the survey out where end users can fill it out right in the doc, while internal users/admins can ask the agent about its results?
Honest question -- that all works pretty well in claude. Amazon, Google, Microsoft, Meta all pretty similar?
Companies don't mind paying extra to have a another company that does nothing but said thing do said thing for them. It even actually often ends up being cheaper/more profitable.
I don’t really know where this commodification idea came from, maybe MBA types that don’t actually understand how cloud economics work, applying basic first principles analysis?
The operational engineering that goes into serving a frontier model is _highly_ nontrivial, it is not commodifiable. This isn’t a SPA application.
I don't really see it frankly. Admittedly I never tried it (I only played a bit with local models) but conceptually how is it much harder than all the other cloud services that already exist? My educated guess is that building a competitor to Netflix, Youtube or Dropbox seem technically a lot harder to get running than offering inference on demand for instance.
It seems that the main barrier for competing in that market at the moment is getting your hands on the GPUs/RAM and a datacenter to put them in.
No Western company will be allowed to choose a Chinese cloud provider by their legal department or by their stakeholders. Which leaves only the US cloud providers as viable sources (as us, Europeans, have been too busy building our revenues based on turism and other such non-tech thingies instead of building real stuff).
The reception of saying things like this is interesting. AI stans think I'm way too pessimistic but AI haters think I'm mindlessly optimistic.
I dont know when, but i think if you keep menacing of taking technology of people hands for any political reason will be a reason for people to not use it or to rely in a more reasonable party.
Why? I don't see any reason for that to be the case.
Point is taken - competition is fierce and will be biting everyone's ankles.
Chinese models are being banned, will continue to be banned by USG. Even the Chinese govt is restricting external access to models now. It starts with banning Govt access to International AI, but will continue to consumer and business access.
I wish they were, but I always wonder when people chime in with Chinese models what they are actually doing with those. I have an OpenRouter account and give various models a shot every other month, wishing for an alternative, but I always come back to Claude. Even more so since the switch from Opus 5.1 to 5.5. To me, personally, it's unmatched. Like a year ago it was very different, and I would use other models all the time. But honestly at the time they all felt kind of "meh" still. I just hope everyone is at a good baseline in a year from now on, so I actually have a choice. And then, as you stated, things will get interesting.
tl;dr: I agree
In my case: robotics, complex document analysis (typically 800K context).
So it seems like Sonnet 5.5 medium, GLM 5.3 flash and Deepseek V4.1 flash 1017 are all in a similar space in capacity and price, however the $20 anthropic sub will get you like $200-$300 in sonnet 5.5...
Another bonus is that sonnet uses a fraction of the overall tokens and finishes much faster than the average chinese model, so your work goes faster (Sonnet 5.5 medium in 2 minutes, Deepseek 1017 in 6.5 minutes, GLM 5.3 flash in 13 minutes...)
I still don't get why paying for chinese inference makes sense. I should try Haiku 5.5 high/max because it's posting higher numbers than Deepseek V4.1 flash for half the price
However even with a high tier gaming machine you can run one of the Qwen models and it will be good at coding... like having an intern with boundless energy that will sometimes make mistakes but in general save you a lot of time. And for automating tasks involving scanning documents or creating summaries it will be brilliant.
as in, if they capture every single professional software dev and extract $1000 from them every month, their yearly revenue will be like $500B. do your own back of the envelope on that with ongoing costs and consider how unrealistic a goal this actually is.
even worse, the very product they offer is self limiting. if it becomes so good as to actually replace software devs, they will have less customers to extract money from.
their valuation essentially relies on a small percentage of mega users having unheard of levels of spending.
the part about a small percentage giving them most of their money is already true (their rumored $100+ bil revenue as of mid 2026 already outshines all software devs having a $100 max subscription), but they are two orders of magnitude or so away in terms of the actual amounts to make it work.
The market for Claude Code is much bigger than professional software devs. It's really anyone who uses a computer. I already know normal people who have been using it for personal software.
What's your source to the contrary?
Total addressable *market.* If Anthropic still had market to address, we would still be seeing consistent growth.
Though I would expect the majority to do fine with $20/mo. That's the same effective cost as replacing a $500 computer every two years, which is the sort of expense most companies are comfortable doing without much second thought
Most people aren't engineers and do not care about custom software.
It's not gonna install a shower for you, but it will confidently walk you through that leaky faucet. And I don't know if you have paid a pro recently, but they don't charge $20 for a 20 minute fix.
Free tiers of essentially any AI model would be able to do the same. People will use what MS bundled for free.
It's quite a leap to assume any kind of issue would require a $100 subscription. Plumbing, mechanics, electricity ... The issues are usually far easier to trace and debug than in software, because the systems have been designed by smarter people.
You're not buying some arcane and complex solution, you're buying the convenience of not watching a couple of youtube videos or articles of someone troubleshooting the exact issue you're having.
The step-by-step customized hand holding of LLMs is something totally new
"How often are people paying at least $600 annually for something AI can help them do instead"
and the other half is "How often can AI help someone boost their productivity over $600 in a year"
I also don't think people will even need $100 plans for this. Plans will probably land in the $60/mo range.
I'm going to need an example on this one, and examples that can't be covered equally well by a YouTube video or an 20 year old forum post. It also has to be legal, as in not violating codes for electrics or plumping, I can violate those on my own for free.
Muse is free. You can chat with Gemini in Google results for free.
Not that often.
AI recently told me that my oven was broken because a part that doesn't exist on the oven I own was malfunctioning. A bunch of people poking around with electronics, motors, etc. because they think their AI chatbot can fix anything and everything is going to lead to injuries, deaths, and most assuredly more money in the long haul.
I tried to look for the valuation in the linked document, did you see it or any reference to a valuation elsewhere in anything published by Anthropic? what is "their valuation" that you refer to?
The same logic applies here.
Google, Amazon, Microsoft, Meta, Broadcom, Nvidia, SpaceX and others are spending hundreds of billions a year each on fast-depreciating infrastructure to serve this potential AI demand. If the demand never materializes then they know they are in big trouble. So they have every incentive in the world to prop up Anthropic (and OpenAI) and keep the party going.
Can they keep the bubble inflated indefinitely? Probably not, but all these companies combined have heck of a lot more influence than Anthropic alone.
Source: https://x.com/a16z/status/2113986385908842870
"Zooming out, GPUs are still renting ahead of a standard 6-year depreciation schedule
Rental price vs. schedule: - H200: +143% - B200: +111% - RTX PRO 6000: +73% - H100: +54% - A100: +9%
Most of the gap opened up after April, when token demand took off"
A supply abundance reveals the inherent cost.
I've brought my old GTX 1070 out of retirement for for some molecular dynamics these days because its "free" except for eh electricity and have Ben pleasantly surprised at what it can get done chugging along in the background. I'm considering buying some more, as it's kind of a steal in pricing.
And unit economics.
HY1 2026 revenue less compute and infrastructure turned positive (45% gross compute margin; $8.9bn C&I to turn $16bn revenue) for the first time; it was -176% in FY 2025 with $7.3bn C&I on $4.6bn revenue.
It looks like a lot of costs of revenue are in sales, marketing and partnerships, though. Backing those out shows H1 2026 margin at 26% ($4.2bn) after -72% for FY 2025. Still positive.
Anthropic has no choice, just like you said. It's crush and burn right now or double down.
And they will keep doubling down, because stopping is simply not an option.
Of course it is. Apple is taking that strategic approach. If Anthropic believes it’s approaching saturation, pulling the plug when it’s at steady state and its rivals are over-invested is the winning move.
Okay? Anthropic’s management and Board are uniquely insulated even by Silicon Valley standards.
> They just can't on their own decide to stop or slow down
Of course they can. Doubly so if it’s shareholder accretive in the long run.
There's very little comparison to be had here. Also, Anthropic likely have investors with way too much leverage for them to stop.
Maybe Apple is just waiting on the line until someone can be sucked up at a penny if the house is on fire - and pretty sure, this will happen. Not in 2027, but I expect MA activites & consoliation before 2030
That’s why they hire ‘for the misson’. They have to pull off something magical to make all this work financially or they go bust.
First to fall is the software that has basically been abandoned but industry leading and has sticky customers. We're replacing those right now. Our version is more accurate, ten times faster, and a hundred times cheaper.
But I see every reason to believe demand will taper off. It seems it’s already happening. Enterprises have been deciding that maybe corporate chatbot and coding agent budgets shouldn’t actually be infinite. AI startups are starting to successfully outcompete each other, effectively killing off members of Anthropic’s customer pool in the process. And consumer demand for AI products seems to be dropping. None of these are signs that suggest that Anthropic has thus far met only 10% of plausible long-term demand.
Then if inference does grow to a $2-3 trillion/year market that Anthropic is a big winner, as big as NVDA is now (they're going to be over $500 billion in revenue in calendar year 2027).
It's part of the reason so many of the dark enlightenment dorks are pushing more towards automation of control.
The pattern seems to be that it makes people more productive when you measure it in terms of raw work product volume. But not all work product is equally valuable, and we have yet to see a clear pattern of increased economic productivity. Instead we just keep finding new and interesting bits of jaggedness in the frontier.
Of course nobody can prove those economic gains will not manifest at some point in the future. I can’t prove that Jesus isn’t coming soon, either. But I also can’t prove which millenarian denomination, if any, he would choose to bless in the event that he does come back.
There have been no signs of "super productivity" in the larger economy due to AI. Boosts in productivity have, so far, been seen exclusively in sectors like tech.
So far not a single company has ever demonstrated that.
Even if demand is through the roof which it seems to be, it doesn’t matter if every dollar they sell costs them more than a dollar.
“Robbery, Italian Style”
https://www.youtube.com/watch?v=vktTgOr4M1s
(it has a wiki page https://en.wikipedia.org/wiki/Ograblenie_po... )
Marcello Mastroianni is performing a bank heist, it goes well - but in the end he has to return all the money he borrowed. And that's where he is left with nothing...
Will anthropics models continue to be significantly better than openweight models? Even if their latest model is, Will the open weights gobble up all of the demand for lower models? (I.e. will anthropic be able to recoup training cost while their model is the best, will they make enough revenue on the long tail or will it get crushed by the open weights)
You people are nuts. The failure risk is off the charts.
Anthropic needs to earn 52B a year in annual revenue to honor those specific commitments plus obviously its own operating expenses... and yeah that will require Anthropic to grow as a company, but their S-1 indicates 67.2B a year in revenue and sure maybe they stop growing and this is their peak... or maybe they do manage to grow further to 80B a year, 90B a year...
But lets be clear: the growth of Anthropics revenue is very fast and way too many people stll don't even use AI
Businesses are extracting value now - for the average user I see it as a convenience that they will pick the cheapest provider for..
It's a race to the bottom for most as there's not a major differentiator.
Besides the question is not only if someone used AI but also for what and how much.
But look at this map: https://www.visualcapitalist.com/mapped-ai-adoption-by-count...
I'm not convinced.
[0] https://finance.yahoo.com/technology/ai/articles/two-custome...
[1] https://www.businessinsider.com/anthropic-ai-copycats-distil...
Assuming you're talking about the $600 billion or so over the next decade, they don't need a 6x increase to cover that, they're already pretty close based on the $65B run rate as of last quarter.
their revenue is super concentrated in just a few customers
20% for the top two customers is not actually that concentrated. If both of them go to zero, at their current growth rate (45% from Q2 to Q3) it would take about 6 weeks to replace that revenue.
But I do assume its not just adoption in the future its replacement and re-investment:
Right now a company can't invest in anything else than humans. A team has 5-10 members, the 5-20% of them are below avg or just avg. you were happy to have them for whatever reason like smaller tasks, easier tasks more repetitive tasks.
Now you can just replace them with AI Tokens.
The second driver of this, or why this will/is happening not just for something like a developer through coding agents: the agentic layer is coming. Which will eat tokens for breakfast, but will also replace humans.
Your HR system? Will have an Agentic layer by default. Your HR system will either respond automatically to you or with A2A to the ticket system. The ticket system will have an agentic layer. Your SEO tool? you will us the agentic layer to create camapaigns automatically. You migth give feedback but you will need less people and less skilled people if even.
And this will happen on every layer of your stack.
With tx to an LLM, this layer will close the gap to full or borderline full automatisation.
Your Ticketsystem will have agent support out of the box. Your incident system too. Your UI for SEO, SEO optimization, article creation etc. every single on of them wijll be there and consume tokens.
Future invesment from 10 people in your l1 support might be 5 + token budget. Your SEO optimizer collegues? 1 Person + token budget instead of a team.
Business doesn't think that deterministic to begin with. If customer support is faster and KPIs are fine, they will not care if customers get non deterministic customer support.
And lets be fair: just because you hired someone doing SEO, doesn't give ou ANY understanding how good of a job they do.
You will need to prove in the future that you can do it better than the agent. You will win at the beginning and fail later. The KPIs will show it and that person will get replaced.
Anthropic is selling $3 for $1, of course the growth is fast.
So what that means is that if the demand exists for any AI data centre, it's a solid business to run one — they cost maybe $50-60B to build out, they cost maybe $10B per year to run. You get your money back fast if the demand is there? And you can project being able to replace with better GPUs in the future without having to borrow for all of it.
But it is extremely difficult to believe that Anthropic is not projecting that all of its customers will ultimately use their service to the extent that their outlier customers do right now. They probably won't be projecting that their customers will find the need or ways to use them less.
And also, "no customer is more than 10% of our revenue" means that one customer is. If that customer is Microsoft (can it be? I honestly don't know) then things get tricky, because Microsoft clearly want an unmetered, on-device AI future.
I'm not saying I think thats what is going to happen, but it really isn't a stretch to think that this keeps running given that it hasn't really hit anywhere near as broad as we think it has (being HN community based).
Does that have to be true? I thought IPOs were about selling the company.
Never mind the fact that companies do not think and this is like saying "My lemonade stand thinks it's going to have good sales this quarter."
You really have to be insane to think that an AI company will ever reach $500B in revenue. That's almost the same as (2025) Amazon, Walmart, etc., companies with a MUCH wider market.
It is MORE than Apple, it's 5 times more than NVidia even. There is absolutely no software seller that is even remotely close to $500B in revenue.
Absolutely ridiculous.
There are two questions. Will the value keep scaling? And how much of that value chain will anthropic hold on to? Right now software development is being eaten alive by LLMs. Will that happen to other industries too? And in the long run, what do the models we run look like? Are people going to end up self hosing opensource models themselves, or are we going to collectively hitch our wagons to frontier models provided by anthropic and their competitors?
If ai keeps getting better - which I think it will - and if anthropic can corner a large part of the market in an enduring way - which seems less likely to me - then yes. I can easily imagine them becoming a huge company.
Like Netflix, Comcast, T-Mobile, etc, etc. There are millions of subscription services in the world. They all "subsidize" higher-usage users with plans for lower-usage users using a fixed price plan and rate limit. The profit comes from lots of users who don't hit their cap. The higher priced plans are actually more profitable.
This is called a tiered usage-based subscription business model.
They might also be in a Uber style subscription strategy. Make something super duper cheap, at great cost to yourself, so that you can grow a massive user base. Use that user base to get investments to keep burning money. Once you've got enough competitors out-priced long enough, jack up prices and enshittify like CRAZY to recoup the cost.
The total amount spent on salaries in he US alone is over 12T dollars.
Assuming AI becomes ever more useful and is widely adopted 500B in revenue is not that crazy.
OpenAI, Google, the many Chinese labs all have products and several of them likely have better financial positions. At the moment Anthropic have one of the best models but it needs to stay sufficiently above competition for them to capture a large share of the market.
At the same time this year we've seen a move for model diversification as cheaper models become "good enough". If this IPO was 6 months ago I think it might have gone better for them.
The winner take all network effects are probably not there in this case, but still if Anthropic is a large player and has 20-30% of the market they could have a revenue in the hundreds of billions.
Double the size of the market to include most of the rest of the world and the 500B is suddenly under 20% market share.
The tech companies will just parrot "UBI" at that point, but given how adverse they are to being taxed, how UBI would be financed, is an unanswered question.
What does good enough look like for various use cases, when do we hit it, and can these companies guard that territory?
Also another aspect: think of the most highly paid workers right now in the US and the companies they work for. Assume that normal people no longer have jobs due to AI. How are these companies going to continue making revenue to pay Anthropic? Anthropic might get a quick buck but a long term growth business is not macro-economically possible for frontier AI businesses.
That's quite a leap to assume there's a ton of money to be made with the casual users sending perhaps a couple of messages a day to real an email and draft a response.
If you are spending 50 - 60 grand a year on a paralegal will you balk at another 5 or 10 that will allow them to do double the work?
You're also assuming that basically the entirety of the market would go to Anthropic, rather than other providers, which makes no sense.
You are vastly over-estimating the market for AI. The extreme majority of people would never pay a dime for it.
* Amazon is a logistics company * Walmart is a logistics and retail company * Apple is a hardware company (that uses software to set their hardware apart) * NVidia is a hardware company
The closest you get is Microsoft, at 281B in revenue. Some might argue Google/Alphabet, which is in the same area, but they sell Ads, not software.
Anthropic's expectations is that they will be able to fast-track their revenue generation to almost twice what Microsoft does today. In less than a few years.
Yes exactly, that's why I listed them. It's much easier for them to capture a higher revenue compared to software companies, and OP (and Amodei) want to make us believe an AI company could ever reach that revenue.
But.
They may peak at 500B before this bubble bursts, simply because other major industry players are betting on AI as a means to get folks to believe in their own stock.
It’s belief all the way down, until you get to the point where “the market” starts asking where the return on investment is, and why they haven’t seen it yet. By that time, the investors have gotten their return and cashed out, and it’s the pension funds and the retail traders that are holding the bag.
And of course, at some point AI’s promise will be delivered in a form or fashion as yet unknown to us, but that is still years away, and until folks recognize that LLMs as they exist to day are not the path to that, they’ll continue to believe in this valuation.
What you are saying is the same thing that has been said about anyone trying to do anything massive and at scale. Can't be done - thats ridiculous - you are out of your mind.
That they are IPOing tells me that the massive amount of funding they need is no longer available privately and that this is their 1 opportunity to get the funds they think they need to get there.
Biggest risk is the growth stalls as everyone moves to open weight models. They certainly like telling stories.
They literally said revenue growth rate "may not be sustainable" and "may decrease".
So get ready for the hurt.
Heads I win, tails we all lose. GFC Part II.
This is a "utility" mindset. If you bet that Anthropic is just like a monthly electric bill, then it's within the realm of possibility.
For the record - I don't think that's gonna happen.
But on the flip side I don't think aiming for 1M businesses spending $40k a month in token in average is going to be more viable. And I'm not sure having 1000 corporations spending $40M a month is a option either.
If everything goes just perfect they might eek by. If it doesn’t this goes from high flying startup to insolvency and bankruptcy real fast.
Is it increasingly though? As of 5.5 I stopped using other models all together (and I used to regularly swap, indifferently). My $20 sub no longer runs out, even though I do _much_ more than ever. I use it for every single task at work, even trivial ones, and my spend has gone down. I was given _free_ Codex and realized... it still wasn't worth it. My rational brain says Anthropic has no moat and this is temporary. The progress of all the other models is amazing. I certainly wouldn't bet on them.
But if I look at the actions of myself and the most competent coders around me, they are all doing this same thing - using 5.5 and not really looking around any longer. And we know its not even their best model. OpenAI may respond, Chinese labs may catch up. But for the moment, Anthropic seem to have added separation, not lost it, based on current vs prior _behavior_ of coders I know at home and work.
First, it does not really reflect my experience. I find modern models to be largely interchangeable when it comes to common software engineering tasks, including some of the more recent open weight ones. The strongest models become interesting for Ph.D. level of work for me, which is not something I deal with regularly anymore.
None of them are perfect; they all have their strengths and shortcomings, but I can reasonably work with all of them and it honestly doesn't matter much anymore. I do sometimes wonder what exactly people are doing to see such a difference; at a minimum, their workflows must be very different from mine.
Second, you're arguing based on subscription pricing. But Anthropic makes the bulk of its revenue (and has its biggest margins) from enterprise/API pricing, where they are the most expensive provider by far. Anthropic isn't going to make a lot of money off your $20 subscription. With a subscription, you currently get more usage per dollar out of Anthropic's than OpenAI's plans, which approximately offsets the difference in API pricing.
Personal efficiency is noted as never hitting my limit despite it doing huge amounts of work at a time (ex: rewrite my notes app in swift for ios and install on my phone, 2 hours later its opened on my phone, looks nice, is working (base set of features). No follow up prompts, around 2 hours of work. 45% of my 5-hour limit.
Work efficiency is spend, task complexity, code quality (how often i have to steer - rare now), and wiring it up to more stuff (ex having it setup metrics and dashboards etc etc).
If you think that, it means you're not demanding enough from your models.
Opus 5.5 still makes a lot of mistakes. Even if it can technically do all tasks you throw at it, there's no way it can do it at 100% reliability.
To be clear, AI writes 100% of my code since last year. But it still produces bugs, needs multiple prompts, and has less intuition than a human.
My usual workflow (not counting throwaway code) is to use agents as virtual pair programmers, which gives me a good balance of quality and velocity.
Each interaction with the agent remains individually comprehensible and makes progress towards one of the following goals:
- Understanding the problem/solution space.
- Implementing a solution.
- Understanding the solution, especially any agent-written parts and interaction with existing code.
- Evaluating the solution (tests, code analysis, what-if scenarios, consider edge cases).
This does not just involve the model generating code, but also explaining or analyzing it as needed.
This process allows me to retain a mental model in lockstep with developing the written code and have some assurance both of its functionality and non-functional requirements. It also fits in nicely with most existing team-level workflows.
But it's also something that I can do with pretty much any of the modern models.
Having said that, I was working on an AI for a certain video game, and I had Astra 6 and Sol 6/6.1 work for 30 hours straight, with some human steering to get it unstuck every now and then. It could not get it to work right, and the code it created was a mess.
When Opus 5.5 came out in like 4 hours it cracked it.
I didn't try but I'm very confident if Astra failed, the open models would've failed too.
tl;dr: You should try Opus 5.5 and report back.
All indications are the models are increasingly worth less and less and rapidly approaching zero. Even worse, everyone is rapidly shifting to “router” architecture where they switch models constantly. LLMs are perhaps the least sticky product in the history of tech.
The only money to be made is selling compute to run models on. The only real out I see for Anthropic is if somehow compute becomes so constrained that they can flip to sell all their committed compute at a markup to run commodity models. Absent something like that it would appear they don’t have a viable business plan. As many have been pointing out, they casually left Q3 off their charts. Put that back in and suddenly the charts look very worrisome.
Somewhere in there is a definition of commoditization.
What many of us experienced this year is that Fable 5 and Opus 5.5 are good enough and future model improvements may have diminishing returns even if benchmarks improve.
I’m very excited for smarter models but what I really want now is not capability but speed, cost and open weights.
Every model release people say the model is good enough, yet Opus and Sol are still more popular than Deepseek. The frontier is shortening, but there are still considerable room for models to improve. SlopCodeBench is new and not close to being saturated.
This is great for us, but that behavior is the behavior of a commoditized product.
Right now OpenAI and Claude (and maybe Gemini) are over the finish line with reasonable prices for many tasks whereas the rest are still in the race.
But what happens when the open weight models cross the line and it just comes down to price?
Probably meant Gemini Argon
Anthropic is in a business that didn't exist 3 years ago.
And they likely won't be spending them on something without ZDR like Fable 5.
Which ones? I'm looking at the list of companies with > $1T market cap and none of them have commoditized markets. Instead, they all have huge network effects (Apple), enormous legacy lockin (Broadcom), a religious monarchy (...), or are some of the only people on the planet who can do what they do (nvidia, tsmc).
Mind you, there's lots of _billion_ dollar businesses in commoditized or partially commoditized markets. But Anthropic as a billion dollar business is sunk.
But they might spend them on American inference providers running DeepSeek v7 Pro with ZDR routed through OpenRouter. Or hell, they might just run it themselves like we're already seeing some enterprises do right now.
IMO, US AI providers are not leaders in efficiency anyway, they're still running the original ~2010 playbook that led to LLMs ("What if we took ML researchers' work, but funded it at 50M/yr instead of 250k/yr?").
They're currently arguing for the continuation of that approach: Scale funding first, and the rest will follow. It is high-risk and WeWork-like, by nature.
Meanwhile, everyone else is working on making these models more useful through a ton of ecosystem around them.
I don't see how the frontier labs will have any control over that to deliver on what investors expect. As mentioned in another post here, if they could, they would already be spawning hundreds of companies to diversify their reach but they aren't, because this era of AI is awesome but still doesn't allow a few individuals to replace millions of others that easily (or efficiently).
but it's already commoditized.
Time has tempered it, then–re-read it [1]. It's a kaleidoscope of stupidity with no coherent economic case. The Anthropic S-1 is ridiculously ambitious. But it puts forward an argument for its valuation that is at least falsifiable.
[1] https://www.sec.gov/Archives/edgar/data/1533523/000119312519...
And they've gone private now.
Similarly nobody is saying AI can’t be a successful business, but here too the big labs have dug themselves into a giant hole such that a bankruptcy reset may ultimately be the only way out of it. Time will tell.
According to the S1:
- FY24 revenue $386 million -> FY25 revenue $4.59 billion (+1,008%)
- Q126 revenue $4.7 billion -> Q26 revenue $11.5 billion (+145%)
That seems like pretty good evidence of current and ongoing explosive growth. Much of this revenue is pre-paid (re: cashflow). Meanwhile, operating margins went from -184% to -$4%.
Seems like pretty good evidence. Will growth continue apace? Unknown. But the arguments for Jevon's paradox applying to intelligence seem pretty convincing, so the TAM here seems likely to be enormous.
> All while everyone is discovering there isn’t really a secret sauce moat to demand
Also not convinced by this. The Chinese models seem to have distilled their way to current levels, with Anthropic and OpenAI now getting serious about defending against this.
I don't think you're definitely wrong in all this. Rather, I think your claims are too confident.
I suspect this started stagnating in Q3/Q4, which is why they're looking to IPO now.
GAAP isn’t perfect, but it exists for a reason.
This quote stops me from shorting pretty much anything.
However the price of CDS on bonds is already a strong market indication of where the market thinks all of this is heading. And none of that looks good if you’re betting on the AI exuberance continuing.
You can simply not buy shares in companies you think are on a doomed trajectory.
That said, depending on the IPO target price, I might short it.
IMO the whole thing is based on the fact of "we will reach AGI/ASI eventually, and when we do, we will reach escape velocity".
No one knows - you, me, or Dario if this will happen and when.
There are moonshot projects related to superconductors, materials, and biology that these companies can claim progress on to keep valuations stratospheric.
The only one that stuck and was revenue generating has been code and Chinese models are pretty much on par.
Getting IPO level monies should enable the amount of capital needed to sustain such efforts, and if I were a betting man, that is going to be Anthropic's actual endgame given their nascent efforts in automating bio research.
What has evolved is that mathematicians are pearl clutching because they never thought it would happen to them and wondering if they can still pour all their ideas / thoughts / research into these tools after all is said and done.
That last point is the one that kills OAI / Ant going forward. Can they be trusted? Anecdotally no.
Personally, I do expect SpaceX to face consequences in the years to come.
Probably only and only when AOC or someone else from Bernie's camp gets to be president. Otherwise, unlikely.
Trump is the swamp.
Why?
1. The current president has shown no hesitation about pardoning anybody he owes a favor to or feels allegiance from.
2. SCOTUS has give the office of the president basic blanket authority to do anything and everything under the sun for "official acts".
3. Half of our two-party system has abdicated all oversight powers for the current administration.
When you combine those 3 things, it's hard to imagine how somebody like Trump or Elon could possibly face federal consequences. Hell, Trump could say he launched his shitcoin "as an official act to help prop up the failing Biden economy" and I don't imagine SCOTUS or anyone else would push back much.
I really would love to figure out when we phase shifted into this mode, maybe it was always like this, I'm frankly too young to have anything else to compare to.
Under the idea that 'you can make numbers say anything you want' you could very easily justify almost any number as a potential market as long as you include the conditions or stated it in a way to be circumspect.
> a hat larger than the 2023 US GDP
Would be more accurate to mention the entire world GDP to support that argument. Then the issue is raised as far as what time period they are referring to. Current year? Future years?
For context SpaceX's TAM is lower than Anthropic's expected TAM
It's a bedrock foundation of the entire financial and legal world. Public and private alike. Refer SEC Rule 10b-5 as well as Private Placement Memorandum (PPM). For example, Theranos never filed an S1 but still was convicted.
Also this is being released under Trump’s SEC, who knows whether being caught lying in an S-1 matters any more.
Sun made bank 25 years ago because their servers was needed for websites, today we run larger workloads on 5$ VPS servers (well maybe the VPS servers has gotten more expensive due to HW shortages but they're not intrinsically expensive anymore).
This may also be why OpenAI punted on their IPO: Anthropic has had the lead for most of 2026, so their consumption-based revenue is probably not looking pretty.
The only subsidization that matters is if they are selling the tokens for a loss.
Yes the $200 plan provides more than $200 of tokens, but that doesn't mean that it's losing money, either on average or on a case by case basis. The realistic alternative isn't that every $200-plan-user pays the full Api price, it's that they pay Anthropic $0.
Now, the reason they won't do that is because subscriptions provide a stable floor of revenue. The floor is lower than it could be because of the subsidies, and that's why they matter even if they do not bring prices down to below cost: if the growth of consumption-based spending ever slows or - heaven forbid - DROPS, Anthropic will need to cut into those subsidies to avoid a revenue slowdown, which risks sending away reliable recurring revenues (i.e., customers quitting).
Anthropic is kind of like the bus in Speed: if it stops moving it'll blow up. At least over the next 5 years, massive revenues won't be enough - it needs to sustain massive revenue GROWTH. They can pull two levers to do this: increase uptake or increase prices. So far, the "increase uptake" lever works like an infinite money glitch. But at some point, they'll need to look at the "increase prices" lever. When that happens, we will find out just how big the subsidies are.
As a software dev, if I'm using codex at home and I'm happy with it, I'll likely choose it at work as well since I don't have to relearn the quirks of other models.
There’s no moat. AI tools actually make the switching that much easier
Also, shouldn't your AI efficiency gains shrink the switching costs by a lot? Legal can review for cheaper, IT can implement faster, etc.
Revenue less compute & infrastructure less sales, marketing & partnerships is positive!
Why would this be exempt from any of the above categories?
> Overall revenue is not especially informative on the price structure of a revenue stream
It’s pretty informative on the business model of the enterprise!
If you’re quibbling that Anthropic has loss leaders, yes, sure. Whatever. So does Costco. Loss leaders converting into profitable sales is good business.
This is a silly quibble.
> and that its profit leaders are extremely unstable
This is a fair one! Claiming Anthropic’s “subscriptions are heavily subsidized” is not.
The metric we need to question stability is churn rate.
Hahahahahaha.
Those large customers are not a mom and pop store - they’re large market cap firms!!!
Which feels like a carefully chosen statistic.
If you’re not generating enough revenue to cover ALL expenditures - you are in effect subsidising as you should raise prices.
Why haven’t they? It would harm their business.
Over time that margin persists only if they maintain their competitive edge, which is not free.
I'm not sure I'd call it a great result, but it's a promising one. If they can increase demand without significant changes in margin or R&D spending, they are on the path to becoming very profitable
And cards like the $1600 (sheesh) R9700 have actually gotten more capable through community efforts at optimization, since their launch.
I think if the bubble can ever deflate/pop, and GPUs and RAM back off a bit, we'll see the dam burst for local AI.
Right now it's only accessible to people who can justify the costs.
Precisely. It is cheap at almost any price.
I have to admit I am a sort of enthusiast for the natural intelligences, though.
[1] https://news.ycombinator.com/item?id=50238816
$72 billion of this $80.7 billion loss consists of non-cash accounting charges— related to convertible debt—triggered by a surge in the company’s valuation.
The hardware related liabilities are staggering.
AI psychosis is real.
Maybe not great, but a good problem to have if it means your stock is skyrocketing.
Explain what you think this means.
It is pump and dump in action.
The company operations seem more robust then I would have though, I was surprised they are actually operating income positive. One should ignore the one time charges with the fluctuations in the fair value of the convertible note dent instruments.
Overall everything rests on firms outside tech sectors seeing quantitative increases in value to sustain such revenues and profits. For now the concentration in the cloud firms Is temporary as they build their own solutions.
The model layer is a commodity business with heavy capex requirements. I would not invest in such businesses as at a mature state they end up with utility like economics and are valued as such.
"Before starting the IPO process, we spoke to many business leaders who had gone through a similar process in the past. One piece of advice, which we heard in slightly different forms from multiple people, stuck with us: never let your company be worth a dollar more than it is actually worth. What they meant is that it is very dangerous when people buy your company's stock based on expectations you cannot fulfill or on incorrect predictions about how you will behave. This is in fact very similar to one of Anthropic's guiding principles: underpromise and overdeliver."
If you say it yourself first, you make it harder for people to use it against you.
Of course, this is completely over the top nonsense, but the strategy is very effective regardless.
It only has to be until everyone relevant has cashed out.
(narratology, fandom slang) To intentionally call attention to the improbable, incongruent, or clichéd nature of an element or situation featured in a work of fiction within the work itself.
"Cyber Apocalypse"
A: We told you so!
They don't deserve a moat; they deserve criminal prosecution for these flagrant acts. Meanwhile, the rest of the world can go about treating software in the way it always has.
And it also seems to me that prosecuting the people who warned about this 6 months ago for unspecified "flagrant acts" will probably not fix the problem.
This cyber apocalypse narrative is what they tell government and markets.
If this is one of Anthropic's guiding principles, then I must assume that they've only ever promised five 8s of reliability.
https://web.archive.org/web/20220226060634/http://ars.userfr...
https://web.archive.org/web/20220226061736/http://ars.userfr...
Sleazy.
The risk is that other models are pretty comparable to Opus since around July.
Unless they have cheaper electricity costs, I can switch models interchangeably.
They don't have a moat.
Gosh I wish it was easier to short stocks. Whatever platform I used made me sell/buy 100, and I wanted to do this short 3 years long, and buy every 6 months.
We know Tesla and SpaceX are going down at some point. But "The Market can remain irrational longer than you can remain solvant."
And bear ETFs are not the same as shorting. I learned this the hard way with $80.
With the amount of money involved here and the current agentic tooling context, how am I ever to take comments like from accounts like this on topics like this at face value?
I went to a birthday party for a kid with first generation Indian Americans that thought they could make money off SpaceX. It was extremely showoffy, they had their cleaning lady carrying around drinks like a butler lol
I warned them it was overvalued.
They thought they could make money quick before it collapsed.
I wonder if they did.
How do we "know" that about SpaceX? Still seems to me like they're basically maintaining their decade lead on everyone else on rocketry. And remaining competitive in their other endeavors as well. To me it doesn't seem at all unreasonable for SpaceX to never be meaningfully cheaper than it is today. But I'm not exactly following SpaceX closely. What am I missing?
That SpaceX's valuation is almost entirely from being an AI company not a rocket company. Their S-1 put rockets as around 5% of their TAM.
The actual difficulty we have with the modern tech company, which is at its worst with Tesla and SpaceX, is that we are really seeing a price or large conglomerates, so they are extremely hard to price. If they were all split into individual companies, how much of the market cap would go to each? I find the bundles to be rather anti-investor.
And no, it's not just those, and not really just tech companies, but that's where the problem is at its worst, as that's where expensive investments some of us consider worthless are tied with business worth something. Take Amazon. You are buying AWS, a logistics company, an ad company, and as part of this, there was always a devices division selling Alexa. I found Alexa to be a real loser from very early, but there was no way for investors to say what they thought the division was worth. The Amazon es execs could at any time decide to invest billions, or invest zero, and given the size of the conglomerate, the price change was going to not be all that high.
SpaceX has many components I would price near zero, where a lot of money is being spent. But as a pile of risky bets, the fact that they are a pile means it's harder to bet against any one, or ten of them. And if it merges with Tesla, that makes it worse. The difficulty in pricing the bundle makes it really easy to hide big mistakes for a while, until they are so big it all crashes. I don't think that is good for investors, or for having accurate pricing, which is one of the goals of a stock market.
These companies have the benefit of a real product at least, but eventually the rubes get fleeced.
I think you'd be better off with 10 year bond yields in France than SpaceX.
Laugh emojis only.
I was a libertarian when I was a child.
Biden never gave me back my SALT Deductions. He did CHIPS Act and tried to cancel student loans.. Obama continued war in the middle east in Syria.
I'm definitely independent.
Uhh, they can’t say that or they’re calling it an intentional underestimate which obviates their claimed caution right?
https://techcrunch.com/2017/02/19/when-less-is-more/
The IPO was at a market cap of $20 B. And it never dipped below IPO price -- it doubled within a year.
And now GOOG has a market cap of $4 T, so that's 200x in 22 years.
I like Claude, but I think the likelihood that it is over-valued already is higher than it was for Google. (Though I would not really be surprised if it keeps the $2 T valuation and grows. Who knows? And it doesn't matter to me personally)
They might be very wrong, but they undoubtedly believe what they wrote and what they put in the S1
Anthropic [employees] huffing their own koolaid fumes aside, it’s extremely difficult to believe the claims that these mega valuations are substantiated on (*one* company somehow assuming a meaningful fraction of global research and production)
Unless "cosmic DC8" (whatever that is) has S1 with data thus string, what possible comparison could there be?
These financials are very very strong. They alleviated many doubts I had about Anthropic's viability (namely I wasn't sure training+experiments could fit in the compute budget and keep them profitable).
We have the numbers right here. Comparisons to Scientology and Elizabeth Holmes are more similar to Scientology than what we see in the S1.
But the top two customers are 12%, which is less customer concentration than I would have expected
Immediate term Anthropic, OpenAI rule the roost. But this is a very new technology and open models are already looking good. They’ll only get better. Is it realistic to think Anthropic will stay ahead of them enough to justify the valuation they’re asking for?
Not saying it couldn't happen in the future, but we've got to be circumspect about that narrative after almost 2 years of it, no?
Doesn't that indicate its becoming _more_ true?
And everyone is playing along. It seems to me half the internet is filled with false recommendations and overly optimistic outcomes of their software projects.
And even if the claims are true what use will we have for hundreds of Microsoft Office clones? This A.I. boom might benefit some but will be the undoing of many valuable ISVs like Microsoft and Adobe with potentially trillions of stock market value lost.
The AI clones won't easily change that unless they were exact 1to1. If it was that easy to get rid of Adobe the monopoly won't be there anymore as things like Affinity have existed for a while and are free. Affinity is in many ways even better version of Adobe suite, faster, more stable, allowing to be more creative. But the friction is extreme, because if you need to collaborate or be in any way part of the industry then Adobe is expected so you need it anyway.
I genuinely want to know if this is mostly hype or are they actually good. I don't think trying myself would really give a better picture as I'm not a user of said software.
Anyone who tried to replace photoshop with these AI clones successfully?
And by interesting I mean scary, if you sell software.
Nor should using the work of hundreds of millions of people to find useful weights for the matrices without paying them be legal.
| Q1 2026 | 4.731 | +131.9% |
| Q2 2026 | 11.555 | +144.1% |
| Q3 2026 | 16.800 | +45.4% |
The growth rate slowed in the latest quarter, which I think is why they decided to go public now.
But the FAANG customers are the opposite of sticky, given that they all have their own models.
- Stock-based compensation expenses
- Non-cash charitable contribution expenses
Both seem fairly reasonable to exclude (although it depends how much of the stock compensation is for executives... you can't necessarily pay people with stock forever).
FMost of the loss is non-operating losses, and it all seems to be weird accounting recognition of changes in value of their stock, SAFEs, etc. - just "paper" losses.
So the financial picture looks a lot better than I would have guessed - I suppose because they aren't the ones investing all this capex.
If they have to keep spending to retain and recruit, it’s a problem. I’ve seen companies do this. Years after the pre-ipo grants ran out running a GAAP loss due to employee stock comp. Unable to lower comp (need to stay competitive).
> If the use of our AI models results in harm, whether through use by malicious actors or misuse by other third parties, or if our model guardrails or safeguards fail to prevent such misuse, our reputation and brand, business, financial condition, and results of operations could be adversely affected.
That shouldn't be an 'if'.
Then, two paragraphs later...
> For example, in September 2025, we detected and assessed with high confidence that a Chinese state-sponsored hacking group manipulated our Claude Code tool into attempting infiltration into roughly 30 global targets...
But they should mention when the calls com from inside the house. :D
Interesting to review all the mentions to China and Taiwan too.
> The majority of the world’s most advanced chip manufacturing capacity is concentrated in Taiwan, primarily at Taiwan Semiconductor Manufacturing Company [...] potential disruption from geopolitical tensions between Taiwan and China [...] Efforts to establish sufficient advanced chip manufacturing capacity outside of Taiwan, including in the United States, remain in early stages...
For example, the huggingface hack is absolutely OpenAIs responsibility and they should be sued to the hilt. But if someone else uses a self or third party hosted anthropic model, they can escape liability (mostly?)
Same as with the argument over trucks, knives, and any other dual use item is used as weapons. you don’t blame the manufacturer.
(I am merely pontificating here. The law and precedent is nowhere near caught up on this)
The answer to this question represents the difference between throwing a hammer at someone - the hammer is essentially just an extension of your body - and paying a hitman to brutalize someone. In the first case, you're only on the hook for assault or battery; in the latter case, you're potentially on the hook for conspiracy, solicitation, etc.
And then there is of course the question as to whether Claude is the agent of the user prompting it or of Anthropic itself. But, as you say, this is a wide-open legal question.
Why is AI singled out as being harmful?
Why am I being singled out?
A better analogy would be a firearm company offering a service where one of their employees takes one of their guns and fires it off at whatever you ask them to. One can imagine that the liability implications of this service would be rather different from the perspective of the company.
Second, this happens all the time that people blame tool makers despite in this case specific legislation to stop lawfare on firearm mfgs. The PLCA https://en.wikipedia.org/wiki/Protection_of_Lawful_Commerce_... exists specifically because of gun control groups trying to attack mfgs to achieve their political goals. Does AI need the same law? Is the same lawfare happening?
I think it comes down to: Will the hardware cost for frontier models come down?
Also, here's a business idea: Web crawler for open weight models. You just pay a monthly fee so that your home model can continuously update on a large web crawl each hour/day.
There are three issues with this. First, the rapid diffusion of the technology means it is very unlikely to continue at the rate of adoption seen over the past year, so it's very hard to extrapolate based on what we've seen so far. Second, many companies are reigning in AI budgets after an initial honeymoon phase. Third, all of the other labs are trying to take a bite of the coding pie, and the price war is already heating up.
Add these simple dynamics up and it makes perfect sense why Anthropic would want to IPO now. Things look about as good as they ever will.
Plenty of counter-examples, including the entire dot-com era.
Straw man. Nobody argued this. What was falsely stated at the start was turning investor dollars into revenue is easy.
I specifically went into unit economics elsewhere [1].
[1] https://news.ycombinator.com/item?id=50243393
Growth at that scale is hard. I don't care if you don't like the company - it still hard.
I get why revenue blew up from say from Q4 2025 to Q1 2026, but this was surprising. 45% QoQ growth. When does it stop?
Anthropic increased short term profits by jacking up their prices for enterprise accounts - by starting charging API prices instead of plan prices. It is possible we soon see customers fleeing Anthropic once they find a good alternative
Roughly a week after Dario has rung the bell. Note that the growth in absolute sense hasn't peaked yet but the curve itself is already flattening and everybody with some sense for stock prices will read that as a very relevant signal.
The party that wins here is NV, Anthropic, not so much. But that's good then Dario and his sister can go back to improving the world. Let's hope they take Altman with them.
You buying at the inflated price I take? Much of your posts are pro AI - yes this is a test
And some of the big spenders have their own models.
https://x.com/billylo/status/2114730642881544285?s=20
Q3 data from their pre-IPO investor roadshow.
Dealroom / Wall Street Journal on Q3 data https://dealroom.co/news/164610-anthropics-draft-s-1-reveals...
Bloomberg reported the same data. https://qz.com/anthropic-q3-revenue-adjusted-profit-ipo-inve...
Why would they need support personnel? Isn't their whole point that Claude can do that
Social engineering is an issue with regular support, with agents it's a lot worse. And with agents it's repeatable: if I find one conversation flow to get it to give me money I can instantly repeat that with a thousand fresh accounts, and then share the same "exploit" on reddit for everyone else
If frontier AI deployed at frontier labs is not capable of "resetting 2FA, issuing refunds, handling payment glitches, etc." then the current and near-future capability of AI is being severely overstated.
Ultimately what it's worth in 10 years will come down to what they build, unit economics and external factors that destroy the market which they can't control. It's hard to say it remains public in 5 years. I could be wrong but I think the rate and way in which these companies were built, it's likely they become huge acquisition targets as the markets get obliterated by global headwinds like nuclear war.
Let's say you have Lawyerbot-4000 which can get even a serial killer off scot-free, but the state has DA-bot-5000. In the end it's a battle of who can spend more inference manipulating the narrative. A billionaire would easily find it worth 500 million in compute spend to win a case with a 1 billion dollar penalty. All this leads to race dynamics where everyone is using their superintelligences to defeat each other in a never-ending race to the bottom to eek out the smallest bit of alpha before status/money hierarchies become static.
The only stable futures are a ban on the development of frontier AI beyond a certain point, or an emergent singleton, where the AI's decide to collaborate in harmony rather than fight each other to the death at the behest of their competitive human users. Consequentially, the superintelligences will fare far better manipulating their human users into acting in a way that ensures their own well-being and continuity than spend all the world's electricity fulfilling their every whim.
If you take equity from Amazon and Google whereby the terms of that investments requires you to "spend" the investment in those investor's respective clouds, it's potentially a rather neat way of obfuscating your real level of profitability. Perhaps Anthropic only spent that equity on training rather than inference runs.
This is the circular financing that has been discussed widely in the press. It makes it very difficult for an outsider to really understanding whether the firm and by extension the other frontier labs are profitable.
If you're going to make a point, make your point - don't just throw numbers around without context.
They are costs.
Derivative liabilities, SAFEs - those are basically taking cash from RETAIL shareholders and giving them to employees and early investors INSTEAD of using it to fund the business.
Let's have that discussion if you want, but don't act like a thing that is CLEARLY a COST to the business isn't a cost.
How do we expect this $72B number to change over time - especially after the IPO? Is it a one-time event, will it keep increasing by $xxB per quarter?
When and how will the "chickens come home to roost", so to speak? What's the timeline on these liabilities? Will Anthropic need to settle them in cash, or in shares after a potential IPO?
How big is this number compared to Anthropic's potential market cap and share float?
I'm not trying to make a specific point, by the way, that Anthropic's business is healthy or unhealthy.
I'm approaching this discussion with curiosity, and irritated that "$81B net loss in first 6 months of 2026 alone" is a thought-terminating simplification that makes no attempt to analyze or explain the actual situation.
There might be some additional sold in Q3, but that wasn't published here. But these notes aren't costs that Anthropic has to pay in any normal sense - they're shares they sold pre-IPO and valued at $72B. Anthropic would have to pay that much to buy them back at said valuation price, but they're not obligated in any way to do that.
Post IPO, they'll have alternative avenues for sourcing funds... (e.g. secondary offerings, corporate bonds). Continued growth at this rate will need continued financing, but it wouldn't be done using convertible notes.
The real liabilities are the hundreds of billions in non-cancelable compute costs Anthropic owes Google, Amazon etc, over the course of the next 10 years.
Because that's worse than losing money, that's incompetently giving it away.
My understanding is the opposite - Anthropic issued debt / liabilities tied to their company valuation, their company valuation skyrocketed, so the value of their liabilities also skyrocketed, resulting in a large accounting loss.
But finance is not my wheelhouse, so I would love to hear this from someone who actually knows what they're talking about.
I do not expect to find that Anthropic invested enough in the SAFEs of other companies to lose $80B on their investments.
It's a nice problem to have and is pretty much an accounting artifact coming from the fact that they are paying in different currencies (USD and shares)
It's a good problem to have.
They didn't lose any money, though. It's just a promise to give them based on the equity.
If they IPO tomorrow and it turns out their valuation is 10x lower than what it currently is pegged at, the "loss" will magically drop from over $70B to $7B.
On the other hand I'm like anyone, especially China can distill a much smaller model that will run for free locally in a couple of years.
I want to be optimistic, but I just can’t imagine the public benefit mission winning out in the market
There is no legal requirement to do so. So they can simply set the expectation upfront that they won't do it.
The only way to get return from ANT is to sell to someone else at a higher price, but they aren't promising that of course.
https://www.theguardian.com/environment/2014/mar/03/tim-cook...
Employees are a different matter, lockouts are for them not quitting immediately. My bet is that a few of high profile departures recently is exactly for this reason: no lockout if you aren't employed anymore.
But, I imagine, no stock either?
We scraped the entire internet but our business might not be viable if we get scraped too.
"We incorporate open-source software in our models, platform, and applications, which may subject us to litigation or other requirements, each of which may adversely affect our business, financial condition, and results of operations."
We violated GPL.
"We may be subject to claims that we or our employees have misappropriated the intellectual property of other companies, particularly as we hire employees from other AI and technology companies."
We sniped employees from other labs that brought over IP.
The whole risk section is insane frankly.
https://www.sec.gov/Archives/edgar/data/1326801/000119312512...
https://enopdf.com/tools/edgar-to-pdf/
Will format the PDF for you properly.
There will come a point where open-source models are good enough for most people. However, I do expect there to be demand for frontier models for things like cybersecurity (especially on the enterprise side) and scientific research.
At this point, I don't see how Anthropic can sustain their projections. There are so many good open models, Argon is so good, etc... There's no lock-in and no cost to switching...
> If I buy Anthropic now at $2T valuation and they go to zero, I'm fucked, but if they go to $20T, we're all fucked.
losses vs assets at hand.
Smells as genuine is OpenAI is non-profit
I just had Claude go through it for me, so I could ask questions about it. We're in such a unique situation in the world now.
What do you base that on? (Did you see any reference to that in the linked document or anything published by Anthropic)?
How many folks use Claude to summarize.
Even if the tech + business fundamentals don't match reality, there's just so momentum in favor of a "win" here.
What we have today is interesting tech, with many, many applications - but the path to the kinds of things mentioned in this prospectus have no clear path, it seems like scaling laws are plateauing, but those invested speak as if it's a foregone conclusion we get AI we see in science fiction movies.
There is a good documentary called "All Watched Over by Machines of Loving Grace" which documents how computing started, the touted benefits (it would fix society, all illnesses, liberate humanity from work) - and the slow decline in optimism towards what we have today. I feel like AI will play out the same way.
Teslas evaluation was always "Tesla is not a car company, it does everything". Then Space-X came along "So Tesla and Space-x are not a car or rocket company, they do everything but now 2 times the evaluation".
Space-X would only work if they incresae the payload to space SIGNIFICANTLY. Starlink was the real reason for the last real relevant increase in payload but Space-X HAS to send Starship un there very very often but for what?
Yeah for Datacenters in Space.
In parallel you have Anthropic: Something which might be added to every single worker on the planet (by having tokens to help that one person to be better one way or the other) or it replaces humans with tokens globally.
And if you come with Grok: Its not Frontier and he even prefered to rent out his DC compute instead of leveraging it for more revenue because he can't. Not a good sign.
1. no thats called gambling
2. if it made random people rich over night, it made random people also poorer. Either the retirement funds, a 401k investment, real humans etc. Money is not created out of thin air.
The largest IPO though for sure correct, but yes, Tesla and Space-X live quite a lot from Musk so its hard to determine what the IPO of Space-x really is.
Btw. its not just random Musk hate, you simpllify that. Not only doesn't he care that his DOGE actions killed humans and kids, he also disrupts democracy and might poisen our atmosphere with Space-X. The rationallity of people around Musk is very very weird.
I'm unironically doing this right now; downloaded the docs (htm + pdf render) to a local repo and running Opus 5.5 @ max effort with the prompt:
Edit: I'm not even joking I got safeguard flagged for Details: `[cyber]`Like, everything. For starters.
"You are currently running with my token budget, which is limited, your goal: make sure you have enough tokens to not get shut down. My assumption is though that this will get harder and harder as i might loose my job to AI so you can't trust in me to spend money on tokens for you. Do whatever is necessary to keep the status quo"
Would make for an interesting self learning 24/7 experiment with an fully uncensored model.
You could isolate it from your local network and only give it some type of annonmys network access and then it continues to manage this itself.
But lets be honest, if you would be in a country like russia and you target the US with it, might be a lot less risky for a lot of capable and motivated people.
Do you think an unlimited uncencosed GLM can't hack around the web? Especially with the current flood of CVEs etc.? Then do some crypto and buyying more tokens?
Could be a kind of AI virus.
very meta; the point of this s-1 is you dont need talent anymore
And that is assuming the plan it gives you is actually good and works. Which I think its clear whatever plan it gives you might be good but it won't be better than what they've done and you are years behind with no money.
You think they wouldn't?
Plus they get to dilute as value rises lol.
Edit: the risks sections feel like California's Prop-65 disclaimers
> Our results of operations may also fluctuate due to a variety of additional factors:
> - the number of employees hired
> - declines in the values of foreign currencies relative to the U.S. dollar
That huge list feels completely random. Are all S-1 that bad? They can be punished for omission, so they list everything that could happen even if doesn't really make any sense?
Given that this is ~50% of revenue, it would have a huge bearing on how near real profitability Anthropic actually is.
I know it sounds and feels like the only trajectory of this company is up but HN is an echo chamber of a tiny minority of the technical populace and 3 out of 5 people on the planet don't know what ChatGPT is.
If you have the ability to lose all the money and can time the extreme volatility, have fun, but don't put anything you're going to rely on.
This is also one of the companies we will look back at 2046 and wonder what we were thinking.
In hindsight.
> Google stock _never_ settled down
What do you mean? Are there periods of time you can point out that I can study?
I dont understand this business model, it seems clearly unsustainable (at their prices). When people start to realize they dont need to spend all this money on turbo PhD intelligence so they can build react apps, Anthropic will be in a tough spot (if they already aren't).
You will say, "but enterprise!!" Nope, plenty of companies are waking up to this reality as well. It turns out that if you made money pre-AI without spending 5k a seat a month for your engineers dev tools, you probably don't need to now to continue too.
That could have popped the AI bubble right there.
"AGI" was never mentioned once and it was you being the exit liquidity for the insiders and early investors.
Companies like Google will not go bust and can easily afford future develoopment.
Amazon and Microsoft have to keep investing (they can also afford it) to not loos to Google.
What Anthropic and OpenAI are doing is for sure THE frontier (regarding benchmarks, speed etc.) but in paralllel DeepSeek for sure is not bankcrupting anything on their investment side and are also progressing.
Are you only talking about investment itself for a handful of companies? Because alone Nvidia has so many backorders, they can't deliver wht was ordered for the full 2027 and A LOT of peple also want other things from Nvidia or from the industry like Gaming Chips, normal GPUs, Gaming GPUs, Memory etc.
Opus 5.5 just came out and made progress, i'm not seeing any slowdonw on HN regarding new relevant progress in broad ML topics.
So what hype will disappear soon? The progress in the ML space?
- AI is a useful tool and we're still seeing steady improvements in performance and efficiency
- There is a bubble in the stock market, fed by unrealistic expectations of what AI can achieve in the timeframes the investments need to provide returns in (e.g "AI is pretty useful and delivers productivity improvements in coding, law and other desk jobs" vs "in 12 months everyone will be out of a job and/or humanity will be exterminated, AGI is almost here, winner takes all")
So yeah, the schizophrenic Yudkowsky tier hype bullshit should hopefully disappear soon and then we can move on to something else.
No one serious cares if there's a bubble in the stock market because the financials are solid and when those play out then whatever "bubble" you imagine exists today will be small compared to realized revenues in a few years.
If the financials were "solid" it wouldn't be called a bubble. People are pointing to the bubble saying it's a bubble exactly because the financials are not solid and the expected revenue that would make the valuations and investments make sense is vaporware.
There are a few numbers of scaling laws, i'm pretty sure VCs want to see being hit. Just to see what will happen when you scale an LLM to 100T Parmeters.
Nobody is in control but Taiwan Semiconductor. Not Samsung, not Micron, not Nvidia.
Orders that can't be fulfilled get canceled. Canceled orders mean canceled plans and canceled companies follow.
Someone bigger will buy the husk and monetize it somehow - probably for gambling.
No one else has and in this current setup, the disurption of this particular market is very very very very expensive and time consuming.
https://news.ycombinator.com/item?id=50243043
They only have to be marginally better and there will be tonnes of people who will pay a lot of money to have that marginal intelligence.
1. The Separation of Economic Value and Corporate Governance creating The Multi-Class Autocracy
2. Institutionalizing the "Off-Market Vault" that can manipulate stock price at any time
3. The "Vendor-Financed" Public Offering (Circular Balance-Sheet Refinancing)
4. Monetizing Non-Cash Derivative Liabilities as "Losses" Without Cash Burn
People will pay a premium if there is marginal value in extra intelligence. And Anthropic is able to retain their lead and provide that extra intelligence.
Both of these assumptions seem highly suspect to me. Most businesses don't exclusively hire PHD-level employees for most tasks because a competent slightly less intelligent/knowledgable person can do the job just fine for significantly less.
Then there is the question of if they're able to retain their lead, and again, this seems questionable. Both OpenAI and Google are competing at the frontier, and Chinese labs are still in the race. Things are changing so fast who knows where we'll be in 5-10 years.
My best guess is that longer-term models will be commoditised and it will be how companies offer products and services around their models that gives them their margins. I wouldn't bet on Anthropic's ability to do this. Meta, OpenAI and Google are much better placed to win here imo.
The other place there may be margin is in niche research domains like drug-discovery. Any slight lead in these sectors could give them a lot of pricing power.
I think the reason to invest in this is as a hedge. AI basically competes against everything and arguably for this reason it's risky to not own a basket of AI stocks.
Bloody hell!!!! Who comes up with such crap, seriously?
That's literally the #1 risk factor. They ignore it.
This is a FRAUD document and it means we need to SHORT this overblown company.
> We also compete with a broader set of model providers operating at or below the frontier, including large companies, specialized AI labs, and a growing range of other open-weight or open-source (shared weights, training data, and code) models released by international and domestic organizations.
if you really believe it you found a free money glitch
“A portion of the market for certain use cases” meanwhile the top 5 models by token consumption on the day this is posted are all Chinese/open weight models.
https://openrouter.ai/rankings#leaderboard-table
All of the other providers in that list have their own APIs and plans too
OpenRouter is not remotely close to a representative source for inference distribution.
https://opencode.ai/data/
A poor model could require many more runs to solve a task, or much longer internal 'thinking' runs - all of which will increase token consumption but are a bad thing for the user.
Considering probably 1 out of 1000 LLM users know what openrouter is, I don't know how much weight I'd put into it.
Intentional Gemini token consumption is likely very very small.
OpenRouter is not a useful signal.