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.
Codex is just as good if not better. And theres 3-5 other options out there just as good too (harness + model).
I've never heard anyone in real life discussing what model is better in some benchmark. Money talks.
UPDATE: seems like it is under "open-source" and "open-weight". Woops. Will keep this up simply because I do think the OS (and infra-managed OS services) provided by Chinese labs is a considerable risk to the underlying business, at least with enterprise R&D.
Opensource also means do it yourself and most businesses don't have time or expertise to do that, but this very issue creates a market for 3rd party providers that use open models to compete against Anthropic. So hardware and compute availability becomes somewhat of a moat.
The business feels like like web hosting before cloud computing. Web hosting in itself does not really have a moat, but than again AWS appeared with their abstractions created lock-in and network effects and disrupted the hosting industry.
I feel like it's different from all other cases because it's the first product which can literally obsolete itself, lol. It can show you the door and walk you through it if you ask it to.
The idea that hardware and compute is their moat is interesting, but open/local models become more capable each week. As I write this, I have 3 instances of some no-name model working on 3 separate worktrees on my M1 Mac Studio. It was viable for me ages ago, and I'm not an AI enthusiast (I just happened to have bought a Mac several years ago that can run these models). I haven't paid Anthropic or OpenAI a cent since the early part of 2026.
It's my belief that we will (or probably have) hit a point where the majority of us receive diminishing returns from the sota models for the work we do. I don't need Astra or Mythos just to write some crud apps or refactor react to svelte, for example.
Audited, revenue in 2025 is $4.6 with a computing cost of $7.3 (i.e. heavily subsidizing tokens). Unaudited, revenue in 2026 (first six months) is $16.3, computing cost $8.9 (1.83:1). But after adding personnel, sales and administrative costs, they are still spending $17.0 to get that $16.3 revenue (still subsidizing tokens, but less).
There's just one detail: those 2 high-volume customers are buying my lemonade and re-selling them at a loss for $1 at another neighbourhood. Supposedly some high-profile Japanese bank is financing their lemonade purchasing expenses for eye-wateringly high interest rates. I've heard its well into the double digits. But that's not important, because the future is right around the corner - I can feel it - and in the future everyone wants lemonade. Thousands of litres of it. So even if those two customers go away, things will be fine!
It will all work out in the end. This is a totally sustainable business model. In fact I'm even thinking of going public.
In an alternative world where Walmart is selling it for $10 and I'm buying it from the reseller for $2, that's not the case.
Many people have been saying the second thing is happening.
Second of all, revenue is not profit. So even if they made 2.08x revenue on every 1$ of compute spent in Q2, that's not taking into consideration all the other costs. Hence, the operating income is still negative for 2026 so far.
You can bet that revenue will keep increasing much faster than the more expensive compute commitments come due, but if that doesn't materialize, things go south real fast. Anthropic is going public with a deficit, so more liabilities than assets, so cash is tight to begin with.
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.
1. Anthropic are probably losing money on the SpaceX deal or not making much at all.
2. To be willing to pay a spot rate so high anthropic likely have no better options.
3. Many of the existing cheaper vendors are likely doing "we will give you cheap compute for now if you give us big commitments"... (cf. hyperscaler capex spends)
Which I suppose is to say that if the spot prices are in the same ballpark as future costs then anthro stops looking profitable pretty quickly. If you're especially bearish you can also throw in the huge reduction in token prices recently and that SpaceX is charging google almost 2x as much as they charge anthropic!
Happy to be corrected by someone more knowledgeable.
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.
I think the 500 billion $ of compute commitments are at higher prices than what they've been paying so far. Would be a shame if a price war between the AI labs intensifies at the same time.
Hmmm
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.
$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.
> 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?
| 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.
- 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).
A glut of models doesn't mean there is no moat. There are several dimensions on which to compete, and it might turn out that being able to produce models that optimize on different dimensions is a difficult and valuable thing to do. It also might not, but the "there is obviously no moat" only comes from people who don't use these things systematically.
But the FAANG customers are the opposite of sticky, given that they all 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.
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].
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.
And some of the big spenders have their own models.
If you could go back in time and buy $1000 worth of Amazon when they IPO'd, it would be worth 3.3 million today. Because Amazon's stock value has grown on average 30% year over year for 30 years. Amazon's valuation when they went public was around 400 million.
How much can Anthropic reasonably grow from a 1.5 or 2 trillion dollar valuation? If we want them to grow even half as much as Amazon they'd have to be worth 5.9 quadrillion dollars by 2056. That's 5,900,000,000,000,000, a 16 digit number.
It's pretty sad that Google, Microsoft, Nvidia, Sequoia etc. are the ones who capture all of this growth and not the public, as would have been the case in the previous generation.
So if you know an index buyer who takes satisfaction in staying above fooled-by-randomness active traders, remind them that that they are now the designated unload zone for shares the privates don't want anymore.
Is it more than a rounding error amongst ALL (active/passive) traders?
This means companies stay private and keep getting private capital/investments (the flip side being private equity in the pre-IPO company) and typically an IPO is really existing shareholders realizing their investment.
So Amazon, Microsoft were forced to go public much earlier, then had their growth. Anthropic has already had growth, Claude AI is well known at this point, and after IPO there may not be as much growth after. In fact, the stock might go down because they have to report their full financials.
the public could buy google, m$, nvidia and so on and benefit from that growth, no?
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.
The average investor has been lulled into feeling the index is riskless.
I suggest everyone to find a video online by their choice of podcaster interviewing Mike Green to learn more
Active investors usually fall into the same fallacy where people all rate themselves as above average. Mathematically speaking a large portion of active investors have to do worse than average and simply stating FUD about averages won’t change that
People need to go to jail this time.
We put Capone away on tax evasion. Get creative.
Playing the stock market is a loosing game. It is gambling where all the rules and all the odds are stacked in favor of a handful of people who gamble for a living. (it is also systemic exploitation of the working classes; so if you are into worker solidarity [you should] you should not partake in said exploitation).
If you just buy and hold, and don't panic sell during a recession, you'll win.
Will other more sophisticated players make money exploiting short-term swings? Sure. Will other players beat your returns? Also yes.
But that money isn't coming out of your pocket, so why does it matter? You're still beating leaving your money in a savings account, where inflation is outpacing interest.
Indeed. And yet opting out is an even bigger loss.
But, as they say, bears sound smart, bulls make money.
30% is much higher than 4-5%, but it's still much lower than most public companies (~80%)
Given gov currently spends 1T annually on servicing debt, I expect US is forced to print money and increase inflation for a long time.
Not if open weight models turn inference into a commodity that's sold at cost.
There will be, as is always the case, some amount of new labour skills that emerge and I can't say for sure what percentage or amount that might be.
Looking at tech work being increasingly well the last 20-30y, we can imagine new ways of working might be pretty valued.
The term singularity is worn out, but the physics parallel is quite apt - a point where the known gears of economics stop working, and it's unknowable what's there until you get there.
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.
Now there will be bargaining friction given that any power sharing agreement with Anthropic will likely increase their future capacity and thus the future expected balance of power, but maybe AI has a long enough utility horizon that we should all expect to be dead by the time it realizes the long-term expectation advantage
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.
Altman already has a couple I think.
Thiel has gone to Argentina but has a backup in New Zealand (w/ Citizenship).
Zuckerberg just bought an Irish castle (a Medieval bunker of sorts) but probably has others.
Musk probably has plans for a Moon bunker complete with Pleasure-Dome. Investor funded of course. Not sure how cosmic rays affect sperm however.
Brin couild opt for Blimps - imagine floating above the reeks and the wrecks like a Meth from Altered Carbon.
Bezos - does he have a bunker?
If they aren't patrolled by giant, iris-scanning eyeballs he's missed out on a vertical.
Maybe these sociopaths should try to save the world rather than making fantasy hedges against its collapse (while actively making things worse).
You can pack enough to survive for decades in that bunker, and then see how world will look like. If you are superrich, it is dumb to not take this chance.
> Maybe these sociopaths should try to save the world rather than making fantasy hedges against its collapse (while actively making things worse).
Its very loaded topic. There are other competing sociopaths, and also 8B of population who don't care about saving world much. But both goals(bunker and saving the world) could be tried simultaniously.
These billionaire nerds got lucky, but now think themselves as natural-born leaders — as evidenced by their wealth, but they wouldn't survive the post apocalypse.
If society collapses, and you were an elite ex-special forces armed detail on a billionaire's security team, would you continue to accept their now-worthless dollars, or would you or just take a fully-stocked bunker for you and yours?
Remember there are effectively no cops or courts in this world that would stand in the way of the (former) billionaires from being demoted to farm-hand by those with the guns.
Consequences from the aforementioned functioning society that would have collapsed in the billionaire's dystopian survival fantasy.
Also, soldiers running amok in rhe absence of a strong government happens in our world - ask any civilian who's been caught up in an insurgency, or look at places like the Democratic Republic of Congo where armed militias run fiefs, and you have to pay tribute to operate a cobalt or lithium mine "their" area.
This isn't just an Anthropic issue, but more and more of the upside of companies have been captured in private markets prior to IPO for around the last decade. This is a consequence of so much money floating around, that IPOing is now the last stop on the train instead of one of the early/middle stops where a company actually needs to raise money.
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%.
Biotech IPOs are even worse. There are 5-year segments where only about 1 in 40 biotech & pharmaceutical IPOs trade above their IPO price at expiry.
On the flip side, in biotech, biopharma and SaaS, 2025 IPOs had nearly 10x the valuations of 2015 IPOs. So you may trade below expiry, but the structure of the earlier deals you participated in, you make way more money anyway.
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.
At the time, I didn't know whether or not they would become the biggest, most important company in the world. They did in the end, but if you live your life betting on every company whose valuation depends on them becoming the biggest, most important company in the world, you're gonna have a bad time.
I'm old enough to remember when IPO's existed to generate equity financing for growing companies. Now they exist to facilitate exit liquidity for mature companies, but a two decades of near-zero interest rates and enough inflation and wealth consolidation to make the "qualified investor" requirements trivial will do that. We're living in the days of the pink sheets again, where you really have to invest in small companies with very little reporting on them, but you already have to be wealthy to have access to those 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.
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
> 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...
The number might be too high, but doesn't take more than a little imagination and some basic facts about the world to see how it could be worth 20 trillion in 10 years.
Einstein once said “compound interest is the eighth wonder of the world.” It’s very hard for humans to comprehend compounding returns.
For Anthropic to show similar returns over 29 years, it would be valued at many times the current total market cap of the S&P 500. At Amazon’s current value after 29 years of growth, its market capitalization is about 1/3 the total market cap of the S&P 500 at the of 1997.
It’s quite hard to justify that in terms of future cash flows. At even a quadrillion dollar valuation and a 20x revenue multiplier, they’d need $50 trillion in revenue… or roughly 1.5 quarters of current US GDP.
So while mathematically possible, it’s quite improbable.
"There isn't a mathematical reason Anthropic can't be worth 165x the actual US GDP by 2056".
Amazon would have gotten you rich, but it wasn't there when it IPOed. Anthropic is growing fast, at 4.7B, 11.6B and 16.7B last 3 quarters.
I think people want to believe that AI will be both productive and replace traditional search / ad revenue, which would give it a solid standing for valuation...
The thesis here is that in the past short sellers would short sell overvalued stocks in the index and buy undervalued stocks and drive price discovery and that those mechanisms are broken due to:
- Passive index funds dominate the market and swamp the ability of active traders to drive price discovery
- Massive returns of these funds over the last 15 years have made beating the benchmarks difficult and leading investors away from actively managed portfolios
- The rise of meme stocks, options trading and crypto bro traders driving out hedge funds and institutional short sellers - Stock tickers and crypto being seen as disconnecting from the US Treasury’s as an anchor for risk free returns to a “Snow Crash” model where assets represent a stake in a new world order.
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. It was obvious that all the growth had been captured and it was time to get out. I remember 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 yet, here we are.
If ANT lists at 5% of the US GDP and goes up 35x, it'd be worth 175% of the current US GDP.
Except in some hyperinflation scenario, I don't see how that makes any sense.
in 2016, who would've thought this kind of growth...
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.
Put another way, the risk has to be worth the potential reward - expecting Amazon-like returns might be unrealistic, but what level of returns would be necessary to counteract the amount of risk you're taking on if you buy Anthropic stock? And what kind of valuation would Anthropic have to reach for that to be possible?
If I expect Anthropic to perform as well as the market, I can lower my risk substantially and see a lot of its upside with the right mix of ETFs. It doesn’t make sense to take on all that risk if I have a much less risky path to the upside. On the other hand, if I expect it to outperform the market, it might fit in my high risk bucket. So from the perspective of individual investors, it’s about matching risk levels and returns.
Bahhaa. I love it when a normal guy just exposes the issue. Yes. 10 trillion is getting close to us GDP lol.
Anthropic growth rate is truly unprecedented at it's scale.
They are 10x revenue YoY.
2024: ~$0.4B
2025: ~$4.0B
2026: ~$100.0B
2025: $0.50 revenue per $1.00 of compute
2026: $1.82 revenue per $1.00 of computeValutions are a function of cash flows, growth of those cash flows and risk. Don’t forget to discount properly on your way out.
At $2T Anthropic would need to look roughly like Alphabet today by 2030 for investors to earn a normal market return (20-25X earnings). That or similar baselines should be the basis of discussion, not if AI is overhyped, if it will grow faster than Amazon did, oligarchy(?), etc.
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.
Lol maddest thing I've read all day
"priced in"
I smell your efficient market hypothesis argument, before you even begin just keep in mind that does not apply here, it's an IPO, the price is not set by the secondary market
Even so, I'm not a fan of EMH
> Lol maddest thing I've read all day
didn't someone like the WSJ to a long term experiment picking a basket of stocks by throwing darts at the paper? They beat most/all established funds over 5 years or something like that. I don't think it matter much, i just buy VOO when i get my bonus and go back to living my life. That strategy is on track to put two kids through college.
Regarding the stock picking experiment, yes, there have been many similar experiments. The premise is just pick a random basket of stocks and see how it performs over decades. Indeed those have outperformed cap-weighted the indexes, most of the time.
How? If you pick a random basket of stocks, you'll end up with mostly small-cap stocks. Cap-weighted indexes are heavily driven by a few large stocks. Most years, small-cap outperforms large-cap (Fama-French 5-factor model[1]). So the "monkey picks stocks" experiment is actually just an exercise in harvesting what is called the "size premium".
Since the AI boom, large-cap has been significantly outperforming small-cap, so if you run the same "monkey picks stocks" experiment, it would likely underperform most of the time.
If you want to easily visualize this, just go on TradingView and compare SPY (cap-weighted S&500) with RSP (equal-weighted S&P500).
[1] https://www.quantt.co.uk/resources/fama-french-model-explain...
Almost like a "Veblen good" type investment.
They basically have to price it at an unreasonable valuation so that people curse them while they take it. There's no way around it.
There's a good reason IPOs are shown to underperform the market
Yes, lots of downsides on this one, but people see it as a call option on a future where AI replaces all jobs, what would you pay for that? A rational response from someone that accepts the premise of the question is likely "anything"
Well, priced into the IPO price by Antrophic. It was you who said it would be priced into the IPO at launch, I just used the same terminology you did: "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."
If you don't think one should assume the market's expectations of future results are accurately priced into the IPO price, it's an argument in favour of the comment you tried to argue against, not contrary to it.
> Yes, lots of downsides on this one, but people see it as a call option on a future where AI replaces all jobs, what would you pay for that? A rational response from someone that accepts the premise of the question is likely "anything"
Even if you buy that premise, there are more premises needed. First (1) AI replaces all jobs, then (2) private AI models will be able to convert it into profit without being contested by open models, razor thin margins due to competition, regulation/nationalisation, or general societal upheaval, finally (3) Antrophic specifically will "win the race" and capture the lion's share of that market.
That being said, I would not bet any money on the stock losing value in any reasonable time frame either. It's enough to take a quick look at Tesla to see that fundamentals or actual results does not necessarily matter for a hyped sci-fi stock, even in the long term.
If that's what you think "priced in" means, I've a brand new company with a 1 trillion $ valuation priced in, would you like to buy some shares from me?
> It was you who said it would be priced into the IPO at launch
I actually said in my initial comment that the "priced in" argument is not even worth invoking, but here we are.
> If you don't think one should assume the market's expectations of future results are accurately priced into the IPO price, it's an argument in favour of the comment you tried to argue against, not contrary to it.
The comment I answered to initially said "Unless you have special insight, you should assume all stocks are equally good buys.", written by someone else. To which I replied "I smell your efficient market hypothesis argument, before you even begin just keep in mind that does not apply here, it's an IPO, the price is not set by the secondary market"
> (2) private AI models will be able to convert it into profit without being contested from open models, razor thin margins due to competition, regulation/nationalisation, or general societal upheaval, finally (3) Antrophic specifically will "win the race" and capture the lion's share of that market.
Very good arguments
So, a future where there is no market can only be a future where humans are extinct, in my opinion (some form of communism won't work)
If someone believes markets will still exist (one form or another) and there will still be exchanges of value between people, even in the most maximalist AI future - then I think it becomes rational for said person to seriously consider buying AI labs, even at stupid valuations
Admittedly I've formulated my previous comment wrong, I should've written "a future where AI has the potential to fulfill all jobs known today", instead of "a future where AI replaces all jobs"
As mentioned in other comments, I'm not trying to convince anyone to do anything, I'm here just to argue different points and positions
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.
If it was really "just an exit", people wouldn't buy the IPO and it would flop
Of course people believe there is room for more growth, that's why they are buying it
Even in this thread you can see people (not me) arguing that the IPO is too cheap and it's easily worth 3 trillion $ like numbers mean nothing
Sometimes, there is no logic behind what people do, ultimately hoping to strike gold once while wasting money otherwise.
Also rare for an IPO, I assume.
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.
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.
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.
For context SpaceX's TAM is lower than Anthropic's expected TAM
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?
Anthropic valuation → Dario's estimated stake (1.42%)
$1 trillion → $14.2 billion
$1.5 trillion → $21.3 billion
$2 trillion → $28.4 billion
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?
If you control for cost, not only the gap closed, but it switched already.
DeepSeek 4.1 Flash dominates perf/cost for suitable tasks.
And if you do need SOTA, Kimi 3.1 Pro scores 55 on https://artificialanalysis.ai vs 58 of Opus 5.5. And they were released 1 month appart.
Kimi even outperforms Opus on some tasks because it doesn't downgrade its intelligente on cyber and cryptography workloads or ban you if you use it for LLM research.
So the gap is 1 month, or zero, depending on your needs.
but if they cost the same then who cares if it's SOTA or not? If I can use fable to solve a problem a lesser model is capable of but i have fable at my finger tips at about the same cost then why would i go through the effort to switch?
Idk what 2027 will bring but i've been pretty wrong in my predictions so far and so am excited to see what unfolds. I mean it could unfold as a zombie apocalypse but at least it's different than "more of the same".
Or any hardware, really.
>Under Anthropic’s staggered lock-up schedule, workers and insiders will be able to sell an unspecified number of Class A shares as time passes after the debut. The lock-ups open 27, 48, 62, and 76 days following the IPO, the filing explained.
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.
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.
I’m not sure the same conditions exist in other fields that deal with real world phenomena. Experiments to test hypotheses about biology or physics can take years and cost millions of dollars to run. They rarely scale down to the millipennies and milliseconds scale that makes letting a swarm of agents throw a bunch of shit at the wall and see what sticks a feasible option for finding mathematical proofs.
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.
Amodei's academic background is relevant for protein engineering. Hence the recent press releases Anthropic has released which all concern prototype proof-of-concepts related to binding efficacy.
For a large number of therapeutic relevant indications, the bottleneck is actually clinical trials where you must contend with the sideeffects of any given therapeutic. Almost every drug I've worked on involves very well known mechanisms where knockdowns with targeted compounds will work in a petri dish, but can have catastrophic consequences when dosed on a live human.
As far as I can see there is no way to accelerate clinical trials in humans.
Even the most fantastically large and detailed perturbation datasets will struggle to capture this dynamic in a full human. This is why tech oligarchs are investing in virtual cell models. With a large automated research lab running perturbations 24/7 and capturing massive amounts of data, perhaps we will get as confident with predicting outcomes in cells as we now are confident with many coding projects. However, this is a scientific question, not a technological one. Public companies rarely give the people running them leeway to try and fail on big scientific question marks as opposed to well established or soon-to-be well established technology.
Don't see why it should! Unless there's a harness like in math for other fields.
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.
You're glossing over
> every single niche they've tried to launch and failed to get any traction on.
This isn't true. I personally know a company that has trained over 300 companies this year to use Claude Cowork mostly for "business operations" type tasks.
People love offloading boring, repetitive tasks to it. And the spend is spending - most start on a free plan and after 3 months have multiple people on the Teams plans.
> Chinese models are pretty much on par.
There isn't even an open source harness that is close to Cowork. ChatGPT work is closest, but everything else if coding focused and a mess for people who aren't coders.
Google still has to build and run the chips they rent to Anthropic. I think from their last earnings Google makes ~30% on it, excluding R&D costs. It's a nice business for them, but hardly the thing that is going to make or break Anthropic as a business.
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.
Hmm. Let's give the clanker a try.
They don't want us to have any power left a few years from now, and they're winning.
Your feelings towards those individuals doesn’t matter in the grand scheme of things, what matters is that everyone’s opinions are shaped/influenced by the few with money.
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
We do have them actually. It's called: an engineered virus.
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.
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.)
"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.
This is pure sci-fi...
this conversation is making my day!
We just call them "virus".
I feel like I still don't understand your logical endgame.
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.
You might lose your value, others might gain.
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 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.
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.
People can not be trusted to preserve the agency of others. See history.
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 remember the discussions and predictions when e-books or internet newspapers were first introduced. In 2026 they still sell actual newspapers where they print yesterday's news on large sheets of paper. People still pay for that instead of checking X for free. We all buy and read actual books. TV hasn't killed cinema and YouTube hasn't killed TV. Real world doesn't work in extremes.
Real world also doesn't have 'infinity'. You can't just use undergraduate engineering math to create a feedback loop and explode a variable to infinity. Things don't work like that.
What I'm getting at is that even if it isn't literally omnipotent, it's indistinguishable from the impact it's likely to have on society.
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].
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.
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."
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.
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
So why would you allow that kind of power to be concentrated in the hands of a few companies? If the state can use this technology, which keeps improving on its own, to manage an entire nation's resources better than any human or group of humans, why would we still need private companies to do it? Especially when the ones with the most resources/capital would be able to just win with everyone else and accumulate all the existing resources.
But the bigger issue lies elsewhere. When you replace human labor, you also replace soldiers with robots. Until now, a leader with autocratic tendencies couldn't easily order the military to turn against domestic "terrorists" who are actually their political opponents. But once armies are replaced by robots, that could all change, and we could see democracy go into decline.
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 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.
Yeah I agree with that. However a "valuation in the trillions" ain't very different from their IPO price.
Seems like lots of risk for proportionally very little return.
A $2T valuation may not be that crazy but thinking it'll make returns like Amazon/Google/Meta/Nvidia isn't reasonable.
" It is a well-documented fact that Bill Gates was initially reluctant to take Microsoft public. His primary concern was that the pressures of quarterly earnings reports and the scrutiny of public shareholders would distract the company from its core mission of writing great software. However, a specific regulatory requirement known as the 500-Shareholder Trigger eventually forced the company's hand.
Under Section 12(g) of the Securities Exchange Act of 1934, any private company with more than 500 shareholders and a certain level of assets was required to register with the SEC and begin filing public financial reports. By 1986, Microsoft had issued stock options to so many employees that it was rapidly approaching this limit. Gates realized that if the company had to disclose its financials anyway, it might as well reap the benefits of being public, such as increased liquidity for employees and a stronger currency for acquisitions. "
https://learn.oreateai.com/learn/when-did-microsoft-go-publi...
You have to wonder how many people in AI leadership positions are already making decisions based on this expected outcome.
"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!
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.
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."
If the economy is planned based on datasets, which are inherently backward looking then our best option is our ability to surprise. But that’s for the artists and philosophers to figure out.
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.
not an original thought, ive seen Her
suppose this is just another way to say, "wtf are we doing?"
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.
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 :(
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.
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.
Given that their Q3 sales numbers didn't grow by much, and that if they can't get Congress to both order a halt to the production of new LLM-based tools and either tightly restrict "open weights" models or make them illegal [0], they're going to have the dual squeeze of the ever-increasing R&D costs needed to build the next big LLM-based tool and ever-reducing revenue as more and more businesses notice that they get decent results with something they can host on-prem... and the only cost to the business is hardware that they may or may not already have and the power that they're likely to be already paying for.
[0] ...illegal because "China Bad And Scary", naturally...
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...
> 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.
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?
Exercising your vested options is a taxable event[2] and requires you to upfront some cash to buy the stock depending on what price(and rounds) your options were issued at- this price usually is considerably less than enterprise value of the same share lets say it is $1 and FMV of $100 at the time of issue, however even just $1 for vested 500,000 options is still $500,000 now.
For this simple[4] scenario you need $500,000 immediately to exercise the options into stock before they expire and about ~$13.86M by April to own[5]all stock if ends up say trading at $200 you are worth $100M then.
There are all kinds of funds who would loan you the money or buy the stock off you now on the secondary market, but vested options does not mean owned stock, and selling quickly after exercise is much higher tax under some scenarios.
----
[1]Some companies have generous(relatively) terms ex-employees to exercise up-to 5-10years later; but it not default in the industry.
[2] This close to IPO that should be relatively small risk; i.e. if the company pulls IPO you still have to pay tax end of the year; if you exercise them.
[3] NSO/ISOs work quite differently, and options vest monthly in most corps and there are lot of creative structures out there; so cannot say how it would be for ANT employee specifically.
[4] Simple - because there usually more than singe 409A valuation and more than single set of options plan issued and plenty of other complex calculus only a finance expert would advise on.
[5] You could sell the shares to pay the ~14M-ish in tax but that could be disqualifying sale(2 year after grant, 1 year after exercise) for ISO meaning you will need to pay effectively 40M tax on your 100M holdings versus only ~$27M otherwise, so you would a take loan against the shares rather than sell to pay the tax.
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.
The latest Kimi model, which scores higher than 5.1 Fable on Artificial Analysis, is estimated to require around 6-7 TB of VRAM to run. If we are going with many A100 GPUs for this, then we are looking around a million dollars in GPUs alone
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.
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.
https://enopdf.com/tools/edgar-to-pdf/
Will format the PDF for you properly.
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.
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.
There's two thresholds.
1. Tasks models can do. 2. Tasks models can do with enough reliability that you can YOLO merge without looking at the code.
Most models can do most of 1. That's no longer the interesting part.
2. is quickly expand. I can trust opus 5.5 enough with easy to medium tasks that I can YOLO merge them. For open models, I can only trust them with easy tasks if I want to YOLO merge.
I'd love to have a stronger model that I can trust to YOLO merge hard tasks.
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.
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).
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.
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?
Somewhere in there is a definition of commoditization.
Anthropic is in a business that didn't exist 3 years ago.
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.
And they likely won't be spending them on something without ZDR like Fable 5.
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...
It's like signing a 10-year lease on an apartment in NYC and renting it out by the day on Airbnb. It may or may not work.
On top of that, there's the question of how you treat the remodeling of that apartment (model training). If it benefits you for years to come, it's an investment that you depreciate. If your guests frequently trash the apartment, or tastes change (the model becomes obsolete quickly), that remodeling (training) is just a cost.
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.
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.
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.
Just because something might be not great in aggregate, it doesn't mean any single IPO is a bad idea. Some people have insight into the future of a specific industry/business. If you can pick one, good for you.
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.
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.
https://www.sec.gov/Archives/edgar/data/1326801/000119312512...
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.
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.
Man, what the fuck. Didn't we learn from Facebook?
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.
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...
That's not the case with Anthropic unless you assume it becomes the single AI provider world-wide.
You're betting against local models, against all Chinese labs, against OpenAI, against Meta's recent SoTA model and against xAI. Doesn't make sense.
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."
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.
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?
Claude Fable 5's model card disclosed safeguards that would invisibly degrade output for requests linked to frontier LLM development. The research community called it "sabotage". Dean Ball: "degrading performance on ML research without telling the user is shockingly hostile" — including because it would corrupt third-party safety evaluators of Anthropic's own models.
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?
losses vs assets at hand.
“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.
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.
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.
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.
> 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.
"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.
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?
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.
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.
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?
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)
It looks here in EU most talks recently about souvereign AI and how to quit digital dependence on oversea providers, at least first attempts to decouple. Thus I wonder if is there a place for new serious competitors?
The AI tech itself is likely very liberating - it seems allow to reproduce anything digital with less efforts than ever before, so others may simply replicate your business quickly?
They might be very wrong, but they undoubtedly believe what they wrote and what they put in the S1
How does that "life creation" promise affect anything with the topic of the post, which is the financial valuation of the company?
Does that increase the financial valuation of the company? Expose risks in the S-1 that they haven't properly accounted for?
I don't read many Anthropic blog posts, but usually it's about a model release, interpretability research, or similar, and I haven't seen any of this marketing that you have. That said, they did somehow spend $2B on sales in the last quarter, almost 10x what it was in the prior quarter, and I don't get exposed to advertising anywhere; is this something that's getting played on TV? Billboards? Somewhere else?
The topic of this subthread, which you replied to, was about the sheer absurdity of this statement: "This is in fact very similar to one of Anthropic's guiding principles: underpromise and overdeliver."
That's it. Whatever you're going on about with financial valuations and S-1 risk is completely irrelevant to what you were replying to, because I was not making any kind of claim about those.
I'm really baffled that you think that Anthropic has been promising the creation of life! Even if it's not meant to have anything to do with this subthread or post.
No it isn't, it's just about the absurdity of that statement vs. their usual marketing bullshit and what they actually deliver.
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.
"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.
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.
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.
What do you base that on? (Did you see any reference to that in the linked document or anything published by Anthropic)?
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?
Even if Claude meets all of our wildest goals and earns trillions yearly there is absolutely no “guarantee” that any will flow to shareholders.
1. Shareholders do not have control of the company due to its structure. The Trust controls through class T shares. As a backup the founders control through class F shares.
2. Since the company is a PBC its board is allowed balance dividends with other social benefits as they see fit.
This means that even if Anthropic is wildly successful as shareholders have no general legal claim to compel the company to distribute those profits.
It is absurd that with a 2T IPO upcoming this is not front and center.
Given that this is ~50% of revenue, it would have a huge bearing on how near real profitability Anthropic actually is.
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.
Bloody hell!!!! Who comes up with such crap, seriously?
1793021023 | Anthropic files for listing on US stock market: valuation of more than $1.5T | https://www.theguardian.com/technology/2026/oct/26/anthropic... | https://news.ycombinator.com/item?id=50243225
1793021178 | Anthropic Reveals 14-Fold Increase in Growth as It Prepares for Blockbuster IPO | https://www.nytimes.com/2026/10/26/technology/anthropic-ipo-... | https://news.ycombinator.com/item?id=50243266
1793021950 | Anthropic IPO: S-1 Filing Offers First Look at Claude Maker's Finances | https://www.bloomberg.com/news/articles/2026-10-26/anthropic... | https://news.ycombinator.com/item?id=50243493
1793024104 | Anthropic's prospectus: $16.3B in revenue and an $80.7B net loss in H1 | https://fortune.com/2026/10/26/anthropics-s-1/ | https://news.ycombinator.com/item?id=50244099
1793024600 | Anthropic S-1: Inside the 335-page IPO plan | https://www.ft.com/content/4b2b9c0e-adfb-4362-800f-950f5b905... | https://news.ycombinator.com/item?id=50244232
1793024618 | Anthropic's IPO filing shows explosive growth, risks and staggering costs | https://www.reuters.com/legal/transactional/anthropic-opens-... | https://news.ycombinator.com/item?id=50244236
1793025358 | What's Riding on Anthropic Going Public? Nearly Everything | https://www.nytimes.com/2026/10/26/technology/anthropic-goin... | https://news.ycombinator.com/item?id=50244464
1793025642 | Why Anthropic can't afford to delay its IPO | https://www.axios.com/2026/10/21/anthropic-ipo-ai-costs | https://news.ycombinator.com/item?id=50244547
1793026275 | Anthropic IPO Filing Explosive Revenue Growth, Wall Street Weighs AI Valuations | https://www.ainvest.com/news/anthropic-ipo-filing-reveals-ex... | https://news.ycombinator.com/item?id=50244751
1793027927 | Interesting stuff from Anthropic's S-1 filing with the SEC | https://anthropic-ipo-sec.pagey.site/ | https://news.ycombinator.com/item?id=50245257
1793030340 | Anthropic Files S-1 for IPO | https://mrkt30.com/anthropic-files-s1-ipo-nasdaq-ant/ | https://news.ycombinator.com/item?id=50245989
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.
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.
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.
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
1793020173 | Anthropic S-1 | https://www.sec.gov/Archives/edgar/data/2130357/000162828026... | https://news.ycombinator.com/item?id=50242993 | 1 comment
1793020203 | Anthropic Officially Files S1 Shows $81B Net Loss | https://twitter.com/anthropicai/status/2114705042817110293 | https://news.ycombinator.com/item?id=50243002 | 2 comments
1793021405 | Anthropic rushing IPO before AI bubble bursts | https://nypost.com/2026/10/23/business/wall-street-is-urging... | https://news.ycombinator.com/item?id=50243343 | 1 comment
1793023225 | Anthropic S-1 | https://www.sec.gov/Archives/edgar/data/2130357/000162828026... | https://news.ycombinator.com/item?id=50243857 | 3 comments
1793030719 | Anthropic files for IPO even as CEO warns of risk to humanity from AI | https://apnews.com/article/anthropic-ipo-shares-public-ca2f4... | https://news.ycombinator.com/item?id=50246115 | 1 comment
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.
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.
- 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.
Is that really a viable path? (Honest question)
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.
Between SpaceX, Starlink, Tesla, Neuralink, X, Grok, Grok Bot & Cursor there's not a demand shortage.
Grok Bot's the fastest growing product in the history of the company and the moment you use it, it's clear why. Took me about 1-2 days to realize I'd have a very hard time going back to not having it available.
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.
BRCM and Marvell are both the actual designers of many of the “we designed our own ai chip” chips that so many companies have been announcing.
Broadcom is also a major supplier of the networking chips that the hyperscalers use. Clusters are moving away from infiniband and nobody is particularly impressed by Spectrum.
- 2026: $97.08B
- 2027: $97.08B
- 2028: $97.08B
- 2029: $97.08B
- 2030: $66.96B
- 2031: $66.96B
- 2032: $40.09B
- 2033: $40.09B
- 2034: $14.59B
- 2035: $10.00B
- 2036: $10.00B
Total: $637.0B
Considering everything that is cancellable, ie. hard commitment only, it's:
- 2026: $56.79B
- 2027: $56.79B
- 2028: $56.79B
- 2029: $56.79B
- 2030: $56.79B
- 2031: $56.79B
- 2032: $29.93B
- 2033: $29.93B
- 2034: $10.00B
- 2035: $10.00B
- 2036: $10.00B
Total: $431B
If they go bankrupt, there are some more cancellations available, also from the other side – if some providers don't deliver, it can be lower as well.
I also left out AMD at $20B for 2027, so that would need to jump up.
Finally, the above is only counting the commitments they've already made. It's not very likely they'll only spend $10B in 2035.
AMD is missing, true but commitment schedule isn't known. Also missing estimated additional TPU purchase for 28-31, ~$125B-$150B.
- 2026: $97.08B = Broadcom $26.87B + SpaceX $30.13B + Google $14.31B + Amazon $10B + Microsoft $5.61B + Nscale $5.58B + Lambda $4.59B
- 2027: $97.08B + AMD (TBD) = Broadcom $26.87B + SpaceX $30.13B + Google $14.31B + Amazon $10B + Microsoft $5.61B + Nscale $5.58B + Lambda $4.59B + AMD (TBD)
- 2028: $128.33–134.58B + AMD (TBD) = Broadcom $26.87B + SpaceX $30.13B + Google $14.31B + Amazon $10B + Microsoft $5.61B + Nscale $5.58B + Lambda $4.59B + additional TPUs $31.25–37.50B + AMD (TBD)
- 2029: $128.33–134.58B + AMD (TBD) = Broadcom $26.87B + SpaceX $30.13B + Google $14.31B + Amazon $10B + Microsoft $5.61B + Nscale $5.58B + Lambda $4.59B + additional TPUs $31.25–37.50B + AMD (TBD)
- 2030: $98.21–104.46B + AMD (TBD) = Broadcom $26.87B + Google $14.31B + Amazon $10B + Microsoft $5.61B + Nscale $5.58B + Lambda $4.59B + additional TPUs $31.25–37.50B + AMD (TBD)
- 2031: $98.21–104.46B + AMD (TBD) = Broadcom $26.87B + Google $14.31B + Amazon $10B + Microsoft $5.61B + Nscale $5.58B + Lambda $4.59B + additional TPUs $31.25–37.50B + AMD (TBD)
- 2032: $40.09B = Google $14.31B + Amazon $10B + Microsoft $5.61B + Nscale $5.58B + Lambda $4.59B
- 2033: $40.09B = Google $14.31B + Amazon $10B + Microsoft $5.61B + Nscale $5.58B + Lambda $4.59B
- 2034: $14.59B = Amazon $10B + Lambda $4.59B
- 2035: $10.00B = Amazon $10B
- 2036: $10.00B = Amazon $10B
Combined total: $782–807B+, including estimated additional TPU purchases and conditional AMD spending.
Got the numbers on a spreadsheet. Of course this is a super simplistic version assuming equal yearly commitments.
> Its largest commitment is with Broadcom, which co-develops the TPU AI processors with Google and leases them to Anthropic in deals worth $161bn over five years. From 2028, Anthropic expects to spend up to $150bn more on TPUs.
https://www.ft.com/content/a6c43402-719e-4295-ae5f-541edb0ae...
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.
I'd think it's more sound to just look at what percent of their current spend is on compute? Seems to be 50-60%
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.
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).
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
Comparables are not by peer group or sector.
It’s cash flows, growth and risk bud. If you want to do peer group - go ahead - just don’t forget to control for differences..
Price to sales multiples are internally inconsistent by definition.
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...
Larger point stands. SpaceX is commanding a 62x sales multiple, whether or not you personally believe price:sales should be relevant. SpaceX's AI operation is smaller and growing slower than Anthropic's. It's reasonable to expect investors to benchmark Anthropic against SpaceX, it would be silly not to do so. A normal thing one would expect investors to do is assign a higher multiple to a company that grows faster.
To be clear: I do not have a financial interest in this, and will not be buying the IPO. I very much am just describing the world as it is.
Some people will benchmark Anthropic vs. SpaceX, that doesn't make it a smart approach.
A normal thing is to consider risk, liabilities, cashflow, how diversified revenue streams are etc., and other things which you seem to be missing.
I'm not trying to dissuade you from buying it. I'm just saying that the reasons you give are wrong.
Yeah, I would not pay 62x sales for SpaceX. And I don't buy IPOs. I'm not endorsing these values, I am saying benchmarking against peers is what investors commonly do.
> A normal thing is to consider risk, liabilities, cashflow, how diversified revenue streams are etc., and other things which you seem to be missing.
I'm not missing those things, I am not including them here because being "right" is rarely how markets value companies. (Also because the rest of that stuff is in the S-1.)
It's possible to build a "correct" model of a high-growth high-tech company that looks primarily at risk, liabilities, cashflow, and diversity of revenue streams. That model might put Anthropic at (say) a $100B valuation. That "correct" model is going to be less predictive than a model that starts from what similar firms are trading at in public markets. I personally am more interested in predictive power than correctness when evaluating stocks.
You are benchmarking against an outlier stock with a cult following (Elon Musk) and diversified sources of revenue. Anthropic does not have either.
If it was as easy as comparing the hottest new IPO with Elon's companies and applying the same multiples, people wouldn't have lost so much money on electric car IPOs that pretended to be Tesla (see PSNY -99.5%; NKLA -99.99%; FSRNQ -99.99%; etc.).
> being "right" is rarely how markets value companies.
Conventional metrics are how most stocks are valued most of the time. What you want to say is that market can be exuberant sometimes. That's fair. When the exuberance goes away, valuations come back to earth (see PSNY -99.5%; NKLA -99.99%; FSRNQ -99.99%; etc.).
> That "correct" model is going to be less predictive than a model that starts from what similar firms are trading at in public markets.
Even if we take your statement at face value, you're still not doing it right. A valuation based on comparisons has to have more than 1 peer to compare against. Check out the multiples of other model providers listed on the stock market. You'll probably be shocked that it's not a double digit multiple of revenue.
And then, if you really want to have a proper model, isolate the AI revenues of SpaceX and other hyperscalers, then we can argue that you have a model worth something.
Comparing != benchmarking. The only folks acting like anyone upthread is benchmarking to SpaceX are those who never made that comparison.
So in this case, diversified revenue is a drag on SpaceX because all the non-AI revenue is growing considerably slower.
But your point about Musk is taken. Cerebras went out in May, and despite being a hardware company is trading at 37x sales. Palantir trades at 78x, CrowdStrike at 50x, Cloudflare at 47x, etc. Anthropic is growing significantly faster than any of those companies. I'm not making the case that Anthropic will/should trade at any of those, just that Anthropic trading in the range of the P/S of SpaceX would not be crazy, and it would not require Musk to be involved.
> A valuation based on comparisons has to have more than 1 peer to compare against
Yes, the best peers are "public pure play frontier model providers trading in the US." There are none. SpaceX is closest, despite not really being a frontier provider and definitely not a pure play. But you are correct that investors will use a basket of stocks. It is silly to suggest SpaceX will not be in that basket.
You absolutely can make an AI doomer basket to model Anthropic. Use "real infrastructure companies" as the connective tissue since AI wants to be infra. In your basket put Caterpillar, Kroger, The Southern Company, AT&T, Comcast, and ExxonMobil. You can absolutely make the argument that Anthropic should trade more like them than like CrowdStrike or Cloudflare, that is a coherent position. Then based on that infra peer group, calculate a valuation. I think this model will be much less accurate in the near term than a model that uses other high-growth tech companies.
Price discovery is part of the fun of IPOs! The doomer model could be right, the stock value could collapse toward irrelevance as fast as the exchange's circuit breakers will allow!
99.9999% of the time someone sells something, the goal is to obtain cash. Throughout all of human history.
Obviously it's not like having Claude Code or similar, but those would be very hard to run legally and safely in EU regulated industries like us in energy production. You could run Codex but it would require your IT department to have yet another place to manage security and software integrations. Which is a fairly big issue when you have around 1 IT staff member per 300 employees, and an organisation which will buy five different sharepoint solutions for the same problem.
Microsoft sells something that seamlessly integrates into everything else you buy from them. It's easy to manage credit spending and when I say that I don't mean that it's easy to set it up. It's easy to track and budget so the right departments pay for it. It can read your emails, your onedrive, your loop, your sharepoint, your powerbi/fabric and anything else you have access to. Sure it's annoying to be confronted with a point you've made 7 months ago (like how you think Copilot is utter trash) and since changed opinions on it's frightingly good at finding relevant stuff, even in some obscoure legal document on your intranet.
I assume that Anthropic and OpenAI makes money of this somehow, but for the most parts our users wouldn't care if it was the GPT and Claude models or Mistral or Deepseek. Which is why I asked if they had really gotten it right.
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.
In theory, things will become even more free, because you can copy whatever code you like, it's all in the public domain because it was all written by an AI (or enough of it was that a court will decide that copying the whole code base is fair).
And the ability of AI's to reverse-engineer binaries means that even hiding the code won't be enough.
Companies may write T&Cs that try to cover some of this, but they'll still have lost the biggest protection they have.
So, in theory, we move to what the FOSS movement have always wanted: all the code available, all the time, with anyone able to change whatever they like about the software they run.
Somehow I don't think anyone is going to be happy about this, though.
https://jacquesmattheij.com/beware-gpu-scammers/
Crazy times!
Congrats on getting rid of the debt, that's really a great feeling.
I really want to build something less scuffed, but, yknow. So I'm making do atm.
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.
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.
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.
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.
I don't think the evidence supports this claim. All the important capability gains now come from RL rollouts in real environments. You can't fake that by generating text from a teacher model. Anthropic makes a lot of noise about how China is distilling their models, but all Chinese labs can access is text outputs. They can't even get the logits. Now, compare all of the recent US open-weights models that are far behind the Chinese frontier. Why haven't they simply "distilled" all of those powerful open weight models that are available to them?
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.
Isn't the first open model that likely surpasses original Mythos from February this week's Kimi K3.1 Pro?
Nothing compares to September's Opus 5.5 yet.
Now the question is whether Anthropic is preparing another phenomenal upgrade with Fable 5.5, or if the progress eventually slows down and competitors catch up.
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.
Look at the defense industry: The Big 5 contractors (Boeing, RTX, General Dynamics, Lockheed Martin, Northrop Grumman) capture most of the discretionary military budget, and the largest of them is in the $300B valuation range (Boeing, which has substantial non-government revenue). Fine businesses but nowhere near Anthropic's valuation.
Bottom line, the government doesn't have deep enough pockets.
In fact, I'd assume this direction has been widely discussed and considered at Anthropic. I think Fable's release was an experiment to test this.
The biggest risks though are China and Moore's law. In the short term, if you don't offer a competitive model as the market grows, you fall behind in marketshare. Anthropic's edge is that it's offering is still better than Chinese offerings. If they offer anything less than that, something not better but just comparable for example, they lose on price. In the long term, as computing capacity continues to increase, local models potentially pose the same challenge.
So there's plenty of pressure for Anthropic to keep widely offering the best model they can.
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.
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.
I am under the impression that curated training pipelines are driving the gains, not utilizing random usage data in nefarious ways.
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.
This
So like electricity, where most people will probably just use the network, but a few will opt to invest upfront and generate their own.
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.
Already happening, which is requiring a lot of enterprise DC power retrofits.
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.
>Its economic warfare
You started the "economic warfare". You tried to turn them into enemies because you can't compete under the same conditions.
And don't you say anything about china competing unfairly, e.g. distilling etc. You looted, and continuously looting, the whole internet with 0 care. You are having a net negative impact on the internet as a whole currently. You are aggressively extracting value from things people gave away out of a good will, or just outright stealing and laundering the stolen knowledge.
>Short term benefit for long term harm.
Long term harm to who? Investors who gave money expecting an eventual monopoly?
And since when are we on the same side? Big american labs sure don't behave like allies to the general population.
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.
> whether you want to acknowledge that or not is not my affair.
I felt I acknowledged it pretty explicitly. I said the likes of Deepseek are "cheaper and open and that matters", but it's the rest of that sentence that I think went without acknowledgment.
>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.
Walking is great too! But you're not filling an economic need by selling walking to the masses, and those companies are marginalized and the economic destiny of the world is being set by those who own the infrastructure to build out the world's next generation of electric vehicles (at least in the automotive space).
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.
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.
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?
My macbook is 5 yrs old and Im a big tech guy. Tech matures. It doesn't grow forever. You live in delululand bro.
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.
Neither do Anthropic and OpenAI.
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.
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
Bingo. I recently bought a DGX Spark specifically for Qwen 3.8 Flash Next. I use it for 1-3 concurrent sessions, a few hours a day. I recently pulled the metrics from my gateway and realized that if I were using Opus 4.6 (similar capability profile) through Bedrock with ZDR, I would be spending ~$6k a month.
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.
It seems likely that Anthropic and OpenAI's inference margins on API prices are >95%.
That also casts doubt on the parent's claim that subscriptions are subsidized. It rather seems almost certain that they are overall generating profit.
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?
How many people use an iPhone to its maximum? Isn't it the same with models? I think engineer's like to flex that they need a top of the line frontier model for their shitty corp projects. A Chinese model will write your Jenkinsfile just fine.
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.
Google, the titan mega-corp with more money than they know what to do with and a billion+ android devices to ship gemini on and it's made no dent for ChatGPT's consumer growth and adoption. Yet some plucky open source chinese models will?. It takes more than that.
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.
Comparing two devices at the highest price point is besides the point.
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.
But you can also have many engineers operating it, testing outputs like you would in a real factory, etc.
Will be interesting to see how this pattern evolves. If it even makes sense.
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?
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.
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'?
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.
I understand that US is migrating to a no friends policy, but I don't think its internal market is nearly ready to support it if clients start to go away.
Anecdotally, I talked to people in a recent event and the common topic was "what we are doing to avoid a blackout of US tech." People on big companies have reserved hardware and alternative software and are scaling down Amazon and Microsoft solutions at a fast pace. People on smaller companies are doing similar strategies but relying on a multivendor strategy.
I think this was inconceivable 3 years ago. Every company in Europe and Asian would gladly pay for amazon for cloud services and now they are using AI to migrate out the lock-ins.
We are seeing American LLM companies more and more relying on "secretive" methods to increase scores and this can only mean that they are not evolving fast enough. The gaps between the reported benchmarks and measured ones are increasing. It might be "safety" concerns or whatever, but I don't buy it.
Like Musk, Altman and Amodei have been overpromising every time they need more money and each time they need more money and now they internet is poisoned with their own content and they can't even trust any sources anymore.
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.
I'm sorry and I'm sure you are being honest in knowing non-tech people using it, but this is on the whole false. The vast majority of people not only have no interest in "personal software" or using Claude for programming, but the slice of the population that does actively interact with AI is using free chatbots as a nu-Google. Most tech people don't even want the "personal software" thing, I don't know why this line is being pushed as if your grandma is going to make her own calorie counter app one day.
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.
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.
Free tiers of essentially any AI model would be able to do the same. People will use what MS bundled for free.
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?
Anthropic can take the parts of Google it needs FAR faster than Google can do the reverse.
I’d say it’s more Notion than GDocs for now, but the direction is clear. Gobbling up all the SaaS in order of descending value to agents.
My bet is on promoting their internal Tasks representation to something more like a Jira/Linear.
But then obviously Slack is another one, and Duet is already starting to build a “Channel” abstraction, so making Duet multiplayer is a clear possible next step.
The tool is not a moat when you can tell Opus to build you a better tool.
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"
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.
A supply abundance reveals the inherent cost.
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).
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.
This is a good point. I can code with Claude Code at 10x or maybe 100x, but have very little in the way of design, sales or marketing skills, and thus, I've been unable to make much side-hustle money from my new superpowers.
Meanwhile at my boring day job, my productivity is gated by a frustrating variety of coworkers and embedded processes, none of which seem to operate at 10x, to put it politely.
It's part of the reason so many of the dark enlightenment dorks are pushing more towards automation of control.
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.
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.
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.
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.
“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...
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.
These companies are rent-seeking landlords for the providers themselves. Which model they serve has no fundamental bearing on the business, the cost of the rent they can charge does.
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)
Our claude bills are rivaling our datadog bills and might get to the size of our AWS bills. It's pretty crazy.
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."
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.
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.
They cannot follow the Uber model because of scale. You could keep getting tens/hundreds of millions from investors, back when there was lots of cash floating around. But you can't keep getting hundreds of billions of dollars. There are only so many dollars. The world is tapped out of private capital. That's why they want an IPO - so retirement and pension funds are forced to buy their shit stock, and feed them more money. But again there is only so many dollars.
Anyway it does not matter. Subscriptions are the most effective way to extract wealth from customers. This has been established so clearly that every business in America now has a subscription. Your fridge, TV, car, hell even car washes, now have subscriptions. Not because they didn't make money from you before, but because it's the ideal way to make even more money off you. There is no reason not to use subscriptions. No AI company in their right mind would end them.
The question of how much value you get from the subscription is different. They have already adjusted both price and rate limit a dozen times. They will keep adjusting it... but the subscriptions are here to stay.
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.
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?
The problem with the "double the work" narrative is it ignores the second order effect. You can do twice the work, but so does everyone else. You doubled the supply, was there a massive pent-up demand for lawyers or accountants at the current price point?
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?
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.
n=1 but at $company we are already told to stop tokenmaxing and find cost savings for ai to the point of degrading user facing features (no loading llm generated content by default etc)
from here it looks like prices have to come down or demand will stall...
* 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.