Pascal's wager was not at all anchored to any specific attestations, you are taking his wager and reinterpreting it to give it some kind of legitimacy that it never originally held. The entire point of the wager was to justify belief in the absence of sufficient evidence, by appealing to the asymmetry between infinite reward and finite cost. If your now arguing that Christianity is more credible because of historical evidence, so be it and stick to it but you've abandoned Pascal's wager and moved on to an entirely different argument.
> by appealing to the asymmetry between infinite reward and finite cost
The supposed asymmetry only holds in a framework that assumes the Christian God as the only possibility. The point is that it's possible for there to be a god that isn't Yahweh, and that god might sentence you to eternal torment for believing in Yahweh, so in fact believing in Yahweh can result in infinite cost, destroying the value of the wager.
>The asymmetry holds whenever the other possibilities don't introduce an opposing infinite penalty for belief.
Or in a stronger argument. It only works when you're the only possible infinity that exists with the set of possible requirements. The moment another infinity exists that has even a single conflicting requirement then it falls apart.
Using language we can create infinite conflicting infinities which makes Pascals wager a weak argument in a generalized set.
Now, if someone vibe coded up Roko's basalisk into a real entity that was copying humans and torturing them for eternity that's a different story, at least until someone made a second incompatible basalisk.
I agree Pascal's wager is generally weak. But I think the strongest reason it's weak is because people in other worldviews, particularly Islam, have a tremendous amount to lose if they convert to Christianity but it turns out Islam is true.
If this claim was in writing then it's legally binding in most U.S. states. Technically it's legally binding even if it's not written but in those cases it's harder to prove.
It's a misleading number, the 500 billion in revenue is needed over a 10 year period, it's not a yearly figure. Anthropic isn't paying 500 billion a year for the commitments that OP posted, it's paying 500 billion between now and 2036.
The OP post is misleading because it makes you think Anthropic has to earn 500bn per year in revenue, but those commitments listed are not yearly commitments, they're commitments over 10 years with contracts that run until 2036.
Anthropic needs to earn 52B a year in annual revenue to honor those specific commitments plus obviously its own operating expenses... and yeah that will require Anthropic to grow as a company, but their S-1 indicates 67.2B a year in revenue and sure maybe they stop growing and this is their peak... or maybe they do manage to grow further to 80B a year, 90B a year...
are those 67.2B revenue or profit? Because you know there are costs associated with running the business, so of those 67B if they only keep 30, they they're in the red, no?
These commitments aren't annual though, most of them amount to 10 billion a year commitments for 10 years. Put another way Anthropic has committed 52 billion dollar a year to these companies and their S-1 indicates they earn 67.2B a year in revenue.
I'm not going to predict whether Anthropic succeeds or fails, just that it's very misleading to claim that Anthropic needs to grow to $500b in revenue without making it clear that it's $500B in revenue per decade rather than $500B in revenue per year which is what most people reading such a number would assume.
That is wild. What if there is a huge break-through in LLM models where they can reduce compute by 90%? All of those data centers would suddenly crater (many customers cancel) and go bankrupt. I feel it could go either way.
Surely the thing the AI giants fear the most in this respect must be the possibility that competitive open models and locally available hardware reach the point of viability for most people. If that happens then where is the moat for the giants?
If progress with frontier models doesn't continue at the same pace then the investments and funny money deals might start to look very fragile.
If progress does continue then that progress might be towards smaller models more than quantum steps up in quality or capability that would increase the risk of the scenario above.
All of this is set against a backdrop of public hostility and political problems that I can only imagine increasing in the near term as well.
This feels like an unusually high stakes game of poker. I don't think I'd want to bet on Big AI right now if I had a few billion lying around. Then again - maybe that's why I don't have a few billion lying around!
Well, they are ensuring that hardware prices stay extremely high by buying all the flash memory at a premium, so at least they've got that aspect kinda under control?
I've made that same point myself in the past. It's more of an accidental moat though - and not one they can defend for very long if they're no longer getting value out of those components themselves.
I saw an interesting observation the other day that Jensen Huang has played this game the best because his company is the one actually selling real products and making real money in return. If all the AI giants are buying up huge amounts of hardware speculatively because they assume they will need those data centres in the future and then the bottom falls out of the market then it's the AI companies left holding the baby. And if we do get to a point where local models are competitive then the OpenAIs and Anthropics of the industry might face real difficulties but it would just be a different market for Nvidia to also be selling real hardware and still in exchange for real money.
Training costs haven’t plummeted like they have for inference afaik and the efficiencies are just translated into running larger and longer training. Basically Jevon’s paradox in action just like on the inference side.
That's already happened. It's one reason prices have dropped so much lately (n.b. in the quarter that's not in their S-1, I think!) They've been able to improve model efficiency a lot through better algorithms and training models to be less verbose.
Jevon’s paradox would apply. If I can use order(s) of magnitude more AI for the same price, I would absolutely do that. It would also unlock many use cases that are currently gated by model pricing, which is largely dictated by the price of compute + frontier intelligence markup.
And thats just the inference side of things. For training, the big players like Anthropic would still be able to benefit from cheaper compute, by generating more RL rollouts, running more RL environments, and thus still providing frontier intelligence that would justify the markup.
Many customers cancelling would only be a risk if the compute expenditure was more decentralized. But its not
The question is, how're those datacenters build outs coming along? two reasons for Anthropic to cancel those contracts. A) They don't need the capacity because they have capacity elsewhere, or b) they don't need the capacity because no one is using Claude. (I guess c) they don't need the capacity because theyre running Claude more efficiently is also technically possible.) For B to happen, they've got the demand in the form of contracts, and models don't really seem like they're shrinking, though there's a lot of non-public info, Astra > insize than sol, and Opus > insize than a Sonnet. So then we're looking at situation A), and the think to look at is SpaceX has the vertical integration to be able to plonk down datacenters and get them powered with literal jet/rocket engines/turbines that they make from scratch because they're a space rocket company when no on else can. So, personally, I don't think it's that big a risk to SpaceX's revenue. Or rather, is cancelable in 90 days, but smart money is going to see those cancelations coming from a lot longer away, if you're tracking datacenter construction. (Disclaimer, I picked up some SPCX; not financial advice, etc)
> "SpaceX has the vertical integration to be able to plonk down datacenters and get them powered with literal jet/rocket engines/turbines that they make from scratch"
At this point, you can get the chips you just can't get the power. So in typical elon fashion, he just "solves" the bottleneck. Long term, no, that is not the strat. Thus the pivot to space.
That's the equivalent of more than EIGHT 10-GW AI computing campuses operating around the clock.
Lastly, a significant amount of natural gas is produced alongside crude oil. When producers can't economically capture or transport that gas, some of it is burned off through a process called flaring. Those flames you sometimes see at oil and gas facilities are an example, although refinery flares also serve important safety functions.
Seems like you just like to say snarky things about Elon, but can't be asked to do any actual math.
Thank you for doing the math. North Dakota "solved" flaring by making it illegal and fined companies for flaring just a bit more than it would take companies to capture the flared off gas, thus making it economical to capture it.
I do agree and understand we flare a lot of natural gas, waste because there's just not the economics to transfer it elsewhere. I definitely agree, it would be nice for that to be put to some economic use if we're pulling it out of the ground.
> Texas produces nearly twice as much natural gas as it consumes domestically.
And it exports that other half it doesn't consume domestically. It's not like half of what is produced just sits around forever. We've massively scaled up LNG exports. We export to surrounding states. But hey just act like we've got billions of cubic feet lying around doing nothing ready to go for datacenters.
> approximately 80.7 GW of continuous electrical generation.
Ooh wow. There's 420.8 GW of demand sitting in the ERCOT connection queue specifically for data centers today. All that "extra" and we'll cover like 20%. A good gas power plant will do better than 50%, but that's still not enough. And I imagine there will be even more datacenter demand coming soon. And that's just at the grid connection levels, not behind-the-meter generation like what we're talking about.
I've also lived through continued cost increases of natural gas in Texas. What does adding an additional 420GW of demand for just datacenters do to our rates? How much more am I going to spend to heat my home this winter? How much more will I spend on my electric bill next summer?
I've also lived through the collapse of natural gas supplies in 2021. I wonder if these datacenters will turn off their turbines or let people freeze it something similar happened again?
Seems like you make a big point about doing the math but only doing half of it. Keep going, see where it takes you.
420.8 GW is alot of compute... like an ungodly amount. A vera rubin rack is like 220KW.. so 1.9m racks. a rack is 72 GPU's per rack so 420.8GW of power is 137.7M GPU's. So lets say about 60% of the power goes to infra, we get 55.08M GPU's. So, with each GPU costing around 55k, that gives us a final cost of compute for the 420GW is 3.0294 trillion.
Obviously that is not real... Eithier double booked, or fake corps making a bunch of requests from thousand different vectors to resell access.
Also, companies like Base are making a killing off taking all the excess energy generated by wind at Night and selling it back to the grid.
So in final, we can support around a $6T AI buildout in Texas just on our exported Natural Gas alone before we really need to start expanding LNG supply.
And yeah, supposedly it's over $1T in computer capacity allegedly planned to be built.
> just on our exported Natural Gas alone before we really need to start expanding LNG supply.
That's natural gas which already has a buyer though. We're now adding a buyer who isn't batting an eye at spending over a trillion dollars. What price of natural gas do they stop buying at? What price will the people of Texas, surrounding states, and our international customers pay for gas until we can't afford it and freeze?
So yeah, if we do build out anything close to this I hope we manage to increase energy capacity similarly. Because I doubt I can spend as much to heat my home as these hyperscalers can spend to power their chips.
That's kind of the whole point of my "sucks the natural gas pipes dry". I'm not saying the gas pressure of the line going to my house is literally going to zero, but if it's so expensive I can't afford for it to flow it might as well be.
Also, your number of 72 GPUs per rack is a dated figure. They're targeting >500 per rack these days. That's also assuming GPUs. What's the same math on TPUs?
Edit: OKay... you are right, never mind. Redid the math and data centers will consume all of the natural gas exports of texas by 2033... lol. 77.6 Billion feet per day by 2033.... Jesus we are cooked.
Ahhhhh, Makes sense now. Page 7 of your slideshow, Key Takeaway: Solar and Energy Storage account for approximately 72% of the amount of generation seeking
interconnection in the ERCOT grid.
Remember i mentioned Base earlier? Those interconnects are for peps selling or arbing in energy. Not to pull energy out of it.
Yeah I mean it's yet to be seen how much of that really gets built. I imagine some of it will never get built. Who knows how much though.
All I'm certain of is all this new demand willing to pay any price means things will be more expensive just to try and not melt or freeze in the Texas weather.
FWIW I'm far from an AI detractor. But we need to make sure we're putting these costs where they belong, and some of these plans do seem insane.
I'm at Texas A&M for mech e, I fly my drone sometimes at some of the data centers being built around here/ The Tesla construction up in Austin. The scale is... unbeleivable. I guess i never really realized how much money these companies (Google, microsoft, etc.) have... I just made an Excel sheet based off the slides you showed. It's around $1.55T in GPU's alone...? WTF? With a fucking T! Google is generating $476B forward a year tho...
What happens when companies have more GDP than the united states? Because i though the two would be correlated since American companies, but i guess if you can sell to a global market and the government can only tax it's citizens, that's kinda the inevitable outcome.
It's not even just how much money they have, which is an insane amount in and of itself. It's also how much money they're able to raise with debt.
These hyperscalers are issuing so much debt and investors are certain enough of returns they're upending global bond markets (among other factors, it's not just AI). Tons of large countries are having to mess with interest rates because the groups who used to buy their debt are already tossing their money at AI datacenters at a massive scale.
> JPMorgan Chase estimated in June that $4.1 trillion in AI-related debt will be issued through 2030, as data center companies and others tied to the AI boom race to build up capacity.
And once again that's just the debt. They're also all making many billions of dollars every quarter in revenue already, they're planning on that increasing rapidly, and dumping that cash into building as fast as they can.
So yeah, your napkin math of them spending trillions on datacenter builds you used to try and illustrate how impossible that could be...yeah...that's been the plan for a while. It's an insane number, but that's the number.
We'll be forgiven for expecting the new overlords will take over in the bang of boiling oceans, as we miss the significant whimper of a cold Texan winter.
I honestly think that the whole Memphis/Colossus debacle is what lead to the datacenter backlash. Before then I'd just hear rumblings from people complaining about bitcoin miners, but data centers in general were not seen as an odious land use.
Then Elon goes to Memphis, buys a warehouse and fires up 30 jet turbines in the parking lot, and you start getting reports about the incessant noise and being able to smell it from 5 miles away.
It seems like there's a fundamental problem with realizing other people have agency and if you fuck them hard enough they will fight back.
Not the whole turbine, but they are manufacturing turbine blades in bastrop texas. The turbines are available right away, but the blades are 12-18 month lead time, so Elon built a foundry. From what i heard they've only gotten a couple proto's out of the foundry/ no idea the grain quality. But they are doing it.
I'd imagine all of the vendors have an incentive to keep their main customer a float, while there might be penalties etc. for missed targets - it doesn't make sense for any of these vendors to ride the contract into chapter 11.
This is so important in analyzing these commitments. Anthropic's commitments will make them a Top 10 customer at many of their vendors. (Even at Google/Amazon, how many other customers do they have with $100B+ committed?)
Those vendors would very much like to retain as much of that business as possible. If the space goes sideways, I would very much expect some kind of renegotiation/work out.
On a side note, these are pretty hefty portions of the total revenue of these companies. 161B with Broadcom over 5 years is about 32B/year; that's fully half of their 2025 revenue. 120B with SpaceX over 3y is 40B a year, more than double their 2025 revenue and almost triple 2024. 114B with Google over 7 years is about 3% of their total revenue and about 1/4 of all Cloud revenue. 110B with Amazon is about 9% of their AWS revenue.
If Anthropic's revenue story doesn't materialize and the AI bubble bursts, these companies are in a world of hurt. It's probably not fatal for Google or Amazon but would be a major drag on the stock price (perhaps why Google has dropped from 400 to 315 over the last couple months as the AI story soured), and it could be company-ending for Broadcom or SpaceX if they end up building out infrastructure to service these commitments.
I remember before I left Google, one of the TGIF questions (which are now AI syntheses of many peoples' individual opinions) was "What happens if AI is a bubble and it bursts?" His response was "If that happens, the whole industry is in trouble." I see now what he meant.
SpaceX will just use the compute directly if they don't have buyers. They are already talking about the data center shortage as well because they can't get capacity elsewhere either. It's a weird problem to not be able to use your own data centers because you rented them out.
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.
A software product you can access via website or app being faster growing than cars, rockets, and satellites is not an indication of it being any good. It takes a lot less to convince a consumer to use it vs buying a car or starlink.
A lot of things. The UX for non-code related activities is excellent. They've removed the friction from setting things up by giving each agent their own machine which can give you remote desktop. The process of creating and working with each agent is as simple as naming it and then explaining it's job. You can keep feeding them information, ask them to train themselves, etc.
They can access anything you can, whether there's an MCP/CLI/API or not. I create speciality bots for each 3rd party tool that I use at this point. The bots can talk to each other, have group chats. You can give them access to the machines that you're running the software on and give specific bots permission to do things on certain machine (like an Obsidian bot that writes logs of daily bot activity on a specific machine with a Dropbox folder shared). I've got a Security Scan bot that downloads anything that a bot wants to download to it's personal machine at SpaceX and runs a slew of security scanners before the other bots can work with it.
I got locked out of one machine while I was travelling and I asked Grok Bot on another machine if it could get into that one over SSH, so it sent me a temporary authorization link via Tailscale, connected to the machine and restarted the stuck process for me.
The usability is off the charts. It's really like having a team of people working for you. I've run a conference for the last few years and was getting completely overloaded. Now I have 14 bots specialized just for the conference helping me do it better than ever and participating in architectural discussions to build a system that help long term.
If you find yourself trying to juggle a lot in your life and work, it's a gift.
No the biggest problem will be investors will demand much higher dividends aka cash return..... how will alphabet continue to fund its projects with ever decreasing internal cash flows available after dividends? If the founders decide not to come good on this - the stock price will crash. If much of your employees compensation is stock based...? i have bad news for you
Their current stock price is pricing in these contracts, which have already been announced but have not been fulfilled (or booked as revenue) yet. So Broadcom's 2025 revenue was 63B; note that this is already up almost double from its 2023 revenue of 35B, largely on AI contracts. If Anthropic spends another $32B in 2026, that's in addition to their declared revenue; investors expect they'll be making $100B+ in 2026. Broadcom's operating margins are pretty good, so a lot of this flows through to the shareholders as earnings, and so investors are valuing it on the assumption that these contracts result in tangible cash flow.
If the AI companies go tits-up, that introduces counterparty risk, the revenue doesn't materialize as cash, and suddenly their earnings take a nose-dive. If they've staffed up significantly to design and sell these AI accelerators and suddenly there's no market, they could be in a lot of hurt.
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.
I'm sure there are others here that are experts on this topic, but my 2 cents on this is that Broadcom specialise in custom / specialised AI chips, and their collaboration with Google to manufacture the TPUs is a pretty solid revenue moat over the next several years.
That's helpful, but 2026 isn't cancelable, nor is at least half of 2027. Also, I think some of these numbers are off. Only SpaceX is cancelable but the above shows declines for years outside of the SpaceX commitment (assuming it does get cancelled, and in full).
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.
If we assume none of it is front-loaded (which seems, uhhhh unlikely) we're looking at ~$100 billion a year for the first 4 years of commitment. That's significant.
> 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.
Thanks for clarifying, that’s a huge difference. Obviously they will have other revenue sources, but will likely make a small portion of their revenue. If we approximate their growth rate by these numbers, it is quite a slowdown.
You're right that my numbers are imprecise, but I did mean $500b in revenue annually.
This is just the compute, which primarily covers training + inference. They still have to run the rest of the business. If you think AI should look like SaaS and spend 10% of their revenue on compute, that's $1T in revenue. If you think it's a hardware business, that's 30% margins and perhaps $200b in revenue. I went with something in the middle at $500b.
They won't disappear as a company at $200b in revenue, but I don't think that's their aspiration. These commitments imply to me that they're confident they can do much better.
> 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.
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%
> Put another way Anthropic has committed 52 billion dollar a year
Idk where you got this figure from, but the actual figure are very different from that:
It's 120B over four years for SpaceX alone and 120B for Broadcom over 6 years. These two players, representing less than half of the total commitment, already give you an annual commitment above 50B.
Good point. Although they also need to make a profit. To justify an eventual PE ratio of 25 and a current valuation of $1 trillion they need to make an annual profit $40 billion. And then lets assume $40 billion in other expenses. So they need revenue of $50 + $40 + $40 = $130 billion revenue annually.
But if you buy them today at a $1 trillion valuation, and they only make $40 billion in annual profit, your investment will go nowhere. They need to be growing profits at 20% per annum to justify a PE OF 25.
And then you have the competition problem. The cheap open weight models are good enough for many (most?) tasks.
And then you have the problem that LLMs may not be that useful outside of programming, customer support and law (and doing homework).
We have examples today of companies that don't need to justify an eventual PE ratio of 25 so why would this be a thing all the sudden? I think you all are misunderstanding vague notions of market fundamentals as some kind of rules by which the market works.
Yeah, it's a crazy number, but they got the AI business right, just like Google got internet marketing right 25 years ago, as long as they keep the momentum (and prices).
> google launched at i dunno a 1bn market cap and grew as the internet grew
Google closed its first trading day "worth more than $25 billion" [1] with $1.5bn revenues, up 234% from 2002's $440mm [2]. That's a 16x revenue multiple, 0.07 growth adjusted [3].
On a similar revenue multiple, Anthropic's $16.3bn half-year earnings are worth $543 billion. Adjust for Anthropic's 1,400% YoY growth and you're well over $3 trillion.
Obviously, it's a lot harder to grow at a thousand percent from a $16bn baseline versus a few billion. But purely on a multiple basis, Anthropic is in a similar ballpark as Google.
As another check, SpaceX is trading at ~62x sales with a growth rate in the 30% range. Assigning the same sales multiple puts Anthropic at ~$2T market cap. Add in a factor for much faster growth (and non-GAAP profitability) and $3T is a really easy place to end up.
Sure, you can throw any numbers around, if you wish to get any valuation you want.
In reality, a valuation based on revenue (sales) is bonkers to begin with, but even worse when you consider that Anthropic has so much debt that it doesn't have positive equity value, it's in a deficit ("When liabilities attached to an asset exceed its value, the difference is called a deficit and the asset is informally said to be "underwater" or "upside-down""). At least SpaceX has more assets than liabilities.
There are a set of mistakes in what you wrote, but
> SpaceX has more assets than liabilities.
is definitely a choice thing to write on the day SpaceX announced a $40B debt deal to purchase compute to run other companies' models. Based on available information, this will put SpaceX into a place where it has more liabilities than assets.
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.
But the question is not so much if they can IPO at those prices but rather if the valuations are sustainable over a couple of years. If they are priced to perfection there isn't much left for public investors besides huge risk that something might not work out 100% as expected.
Well not exactly. It's quite different this time since most other tech companies used to IPO way earlier. So their valuations weren't based on everyone assuming that they will continue growing exponentially, corner the entire market and effectively become monopolies. You used to have much more uncertainty and therefore potential upside for investors. I mean Anthropic can do great by the standards of pretty much every other public company and still catastrophically underperform the current expectations.
> Some people will benchmark Anthropic vs. SpaceX, that doesn't make it a smart approach.
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.
> I am saying benchmarking against peers is what investors commonly do.
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.
> You are benchmarking against an outlier stock with a cult following (Elon Musk) and diversified sources of revenue
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!
> So in this case, diversified revenue is a drag on SpaceX because all the non-AI revenue is growing considerably slower.
Your argument is like saying that having gearbox in a car is a drag on speed, why not remove it? Just take out the transmission and the windshield while you're at it too.
> 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
None of those companies are AI labs, you're just cherry picking random expensive stocks and doing the whole price/sales nonsense again. All of them have positive shareholder equity (Anthropic has shareholder deficit).
> But you are correct that investors will use a basket of stocks.
That's your approach, I was just quoting it.
> 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.
At this point you're either being silly or arguing in bad faith. Your best case scenario is for Anthropic to trade like a stock with cult-like following and your worst case scenario is for it to trade like a ketchup stock. Completely ignoring the most obvious tech companies that are traded publicly and also provide models of their own. This conversation became so absurd that it's not worth answering anymore.
The mental gymnastics you're doing here are appalling.
Someone on a different forum fed the S-1 in Fable and it said "Shows a massive “loss” on paper, but that’s mostly an accounting effect from the company’s value going up"
Stock markets made a whole lot more sense before the internet and broad interconnectivity. It was really only one of the reliable ways for companies to broadly raise money to grow and expand. Now everything just feels like a mixture of gambling and pump and dump.
Like is there going to be anybody, whatsoever, who's genuinely aiming to go long on Anthropic? It just feels like this massive collusion that 'everybody' is in on where we all know it's going to crater but the whole game is to pump it as much as possible and just try not to be the last guy holding the bag.
Obviously LLMs are going to revolutionize the world, and they arguably already have, but there are open weight models available for free with frontier level performance, and the price to run these models keeps plummeting which, in turn, is already driving token costs down. Like many things now a days, this is all highly entertaining, yet absolutely insane.
Did they get it right? I'm geniunly curious because from my point of view the only company to get AI right so far is Microsoft. This is from the point of view of an EU energy company married to Microsoft services mind you, but Microsoft is the only AI company which actually sells AI to us in a manner that can be considered useful. 7 months ago I thought Copilot (the m365 one, not the github one) was useless. Now I think the chat part is as good as what you'll get on the smaller subscriptions to ChatGPT or Claude, and it's Cowork is very good.
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.
> Put another way Anthropic has committed 52 billion dollar a year to these companies and their S-1 indicates they earn 67.2B a year in revenue.
A very large part of that revenue is paying for inference. There’s not enough leftover for the committed outlays. So it has to come from smucks I mean investors.
Jonathan Blow made his own language and compiler because C++ was slow and miserable.
He recently released an indie game using that very language using his own 3D engine. The reviews on Steam are Overwhelimgly Positive and sales have so far significantly exceeded expectations.
>The only benefit of them seems to be slightly better error messages if someone misuses a template class/function.
The error messages are arguably worse with concepts than without them but it's really just a trade-off. Without concepts you got long "stack-traces" of raw syntax errors that could dig deep into nested functions. With concepts you get long stack-traces of concept failures where concept A fails because concept B fails because concept C isn't satisfied and then you need to dig through this chain of concepts to figure out what's actually needed.
Traits in more principled languages like Haskell/Rust don't have this issue whatsoever because traits are semantic requirements in those languages while concepts in C++ just perform a "will it compile" kind of check.
The primary benefit of concepts in C++ is overload resolution, they allow you to write multiple functions with the same name, and same number of parameters, but where the types of the parameters are required to satisfy certain properties.
It's not even that though. Looks like public utilities are only offered in areas where those utilities are cheap to provide or abundant, and private utilities fill in a gap in harder to reach areas.
The study even points this out as a foot-note but then focuses on rate of price increase versus nominal price. It should not come as a surprise that in areas where utilities are less abundant the price will increase faster than in areas where that same utility is plentiful.
That’s roughly the opposite of the development of electric utilities in the US. The IOUs owned dense urban areas and refused to electrify further out. It was only the rise of public municipal utilities that got them to go to the states, implement the regulatory compact, be granted rate of return, etc., and then they began building out more.
That is the historic situation yes. However it doesn't change how things are today. the municipal utilities that remain have lower costs because they don't have the more expensive structures.
It's amazing and at this point, absolutely no surprise that HN has worse moderation of genAI than the cpp subreddit. The conflict of interest with AI has hit HN like 9/11.
> It's amazing and at this point, absolutely no surprise that HN has worse moderation of genAI than the cpp subreddit.
I don't think this is a fair assessment. Submissions from specific sources are more frequent in niche forums, as this helps them stand out. So once a blog is found to be spamming, it's easier to target the blog and not individual submissions.
This is much harder to do on generalist forums such as HN.
Sure, sure, but they've already won by even having a policy against AI slop articles and posts, which, to my knowledge, HN seems steadfast in refusing to do so. After all, the public is fiercely divided into mostly one side in favor of banning said articles. HN is apparently just going to ride this out with only a policy banning LLM comments.
At this point, my only reason for still being around on here is because I simply don't know of any place that I find strictly better. Most of the popular alternatives to HN are annoying in ways that I find equally hard or even harder to tolerate.
If every single SIGTRAP was caused by an INT3 instruction, then this would work, but SIGTRAP can also be generated by single stepping where subtracting 1 would be incorrect.
GDB already compensates for breakpoints it inserts itself because it knows their locations, so it subtracts 1 as you suggest. It could also recognize embedded INT3 instructions but that requires distinguishing their traps from other causes of SIGTRAP which is much more complicated. So instead GDB generally leaves the instruction pointer unchanged for embedded INT3 instructions.
Here's a discussion of precisely this issue from the GDB developers:
reply