The problem is human nature and how we evaluate risk. An analyst who fails to deliver a report on time has failed. An analyst who turns in a report that might be wrong will only fail some of the time. Press the big red “generate report” button and maybe fail or don’t press the button and guarantee failure. Guarantee you’ll be screamed at by a superior or take a small chance of accidentally starting a war? Far too many of us would choose the latter.
this is such a funny comment, we are so tech-pilled that we forgot companies traditionally pay dividends and that’s the reason to invest, to share in the profits, not to speculate
As long as you have an accurate sense of the intrinsic value of your shares at any given time; there is a price at which buybacks destroy more value for continuing shareholders than they would lose to taxes on dividends.
I wish I saw this comment two years ago while the stock price of one of our local company is still cheap. I sold all my shared before the price slightly tanked, earning just around 14% profit. Now two years later the price has gone up ~100% and they paid dividends twice during the time.
Should have treated it the old-fashion way, not the modern day-trading way.
I’m not sure if you’re joking or not but TV license detection vans are a joke, a scare tactic, a meme, they don’t exist. TV license “inspectors” just showed up at houses and asked if they were watching broadcast TV.
Pirate radio would broadcast from the top of buildings and did often get caught.
To be fair TV detector vans actually did exist in the early days of TV, there were just barely any of them because they were expensive and they were just as effective as psychological tactic. The idea was that old televisions would radiate the local oscillator frequency used in the superheterodyne circuit strongly enough it was detectable from the street, where it could be direction-found from the van outside. Ringway Manchester has a decent video on the subject.
This wouldn't work nowadays for obvious reasons, but they still pretend the vans are a thing as far as I know.
You’re from the Matt “WordPress is 45% of websites” school of statistics. WooCommerce is nothing compared to Shopify, barely a blip, inconsequential. WooCommerce is “installed” on millions of websites but it processes perhaps 1% of the volume of Shopify.
WooCommerce isn’t bad, acquiring it was a good call for Automattic, but to put it in the same league as Shopify is pure fantasy.
As for cost control, I’m not sure why you think Shopify is more expensive. Moving from WooCommerce to Shopify is expensive because migrations are expensive but day to day running costs are pretty much equivalent.
And keep in mind most major Shopify users are building out their own front ends so these BuiltWith numbers are underreporting on big Shopify customers, whereas WooCommerce is almost never used without a WordPress front end. These are the most favorable numbers to WooCommerce and they are still bad.
edit: it’s even worse than I thought. Woo’s own stats cite storeleads.app which lists the biggest Woo stores as… some blogs? Shopify has most of the top stores from brands we all recognize. Woo has zero. Woo’s involvement in actual commerce is pitiful, I think 1% of Shopify is optimistic.
edit edit: one of Woo’s most popular stores is billyparisi.com. A recipe website that sells a couple of t-shirts. A WordPress blog that drives all of the traffic and a WooCommerce tacked on for the sake of it. And that’s one of Woo’s best.
I did write a mangled sentence late at night and you are correct to object to it.
But you seem kind of angry and have decided something about me, and are now cherrypicking things off the woocommerce site to try to make me look foolish (as if that site’s gallery is necessarily authoritative?)
Did I explicitly say “shopify is more expensive”, for one thing? You are putting those words in my mouth.
However. I just looked at the numbers. Shopify starts at £19 per month. I could set up a speculative woocommerce store on good hosting for about £40 per year.
Several of the people I have set up stores for over the years have had no certainty that they would make a sale for months and yet needed customisations in their setup that no hosted e-commerce company could offer in their cheap plans.
I have written dynamic product functionality, installed weird extensions, even used Wordpress as the prototype storefront in a multi-vendor, multi-supplier fulfilment network demo.
Woocommerce exists. It functions. It can be rolled out for tiny, tiny money on hosting you control and can customise. It is OK. Not that fun to administer but it’s a complete open source store with a huge ecosystem. It’s exceptionally widely deployed. For people who want to run shoestring customised store experiments or sell on tiny margins or for charities, it’s clearly an option.
> Like isn't WooCommerce an absolute also-ran compared to Amazon, Shopify, Wix, Squarespace, etc?
You said that WooCommerce is more widely deployed than Shopify. Yes, it is installed as a WordPress plugin on more websites than Shopify but that is completely meaningless when discussing whether WooCommerce is an "also-ran" compared to Shopify.
So, if your comment was intended only to explain that WooCommerce is a widely installed Shopify plugin, I apologize for suggesting you have something in common with Matt, but your comment read to me (and I guess everyone else) like you were saying WooCommerce isn't an also-ran and is an important product for online commerce. It isn't, in the context of business, it doesn't belong in the same conversation as Shopify or any other serious commerce business.
(e.g. just this afternoon: Godin guitars. One of the longer-established multi-brand companies in the guitar world.)
And embedded in really odd stuff, like behind member walls — companies selling spare parts for washing machines and hoovers, all of that stuff. It's absolutely the long tail of ecommerce.
I will grant you that in the last year or two some pretty big stores (particularly in the media and music world) have migrated to Shopify (they have a tool for that).
I don't blame them for migrating away and it's not hard to see purely strategic reasons why they would that are tied into all of this nonsense with Matt's very obvious implosion. Like I said in my comment, I'd prefer not to be running WP at all.
But a lot of the work I do is at the very small, very speculative or very custom end of things. I'm looking for various ways out that still let me help individual people.
The majority of revenue comes from API usage. The majority of usage comes from subscriptions. For any of the numbers to make any sense, subscriptions must be subsidized ergo the majority of usage is subsidized. A single $200 subscription can incur upwards of $10,000 in API equivalent usage (and even more when there are frequent resets).
If it were true that Anthropic and OpenAI were profitable on all inference they wouldn’t need to constantly raise so much money. Anthropic regularly announce huge investments in infrastructure but it is all smoke and mirrors, data center build out costs aren’t being paid by OpenAI and Anthropic, they’re financed externally. Google, for example, are backstopping tens of billions of datacenter build outs that are being financed based on commitments but not investment from Anthropic.
You are underestimating the insanity of subscription subsidization. Being profitable on API inference is meaningless when it is such a small proportion of usage and is only going to fall off a cliff as cheap open weight models become more capable.
The absolute majority of tokens are being subsidized and as soon as the subsidies end usage will fall off a cliff, rendering all the data center buildout a terrible waste of money.
The numbers in the article are forecasts but let’s take them as real. That’s $10bn of revenue, the majority from enterprise customers, let’s say 75% from enterprise API usage: $7.5 billion. If the margin on inference is 80% that means of the $7.5bn in enterprise revenue they’re spending $1.5bn on compute. Yet we know that they actually spend over $5bn per month on compute, which includes the $1.25bn per month to SpaceX.
If $7.5bn is their enterprise revenue and it costs just $1.5bn to generate, that leaves $3.5bn in compute costs to account for. Dario previously said that training costs less than inference so training can’t explain it.
If subscriptions aren’t the majority of usage and aren’t subsidized, where is the money going? Anthropic don’t spend money on data centre build out so that can’t be it either.
> If the margin on inference is 80% that means of the $7.5bn in enterprise revenue they’re spending $1.5bn on compute.
I don't think you can reverse this out like this because the 80% rate is before payments to "distribution partners, including Amazon". I think that payment includes the hosting cost for that those model but it's unclear.
> Dario previously said that training costs less than inference
Do you have a source for that?
Are you sure you aren't conflating the statements Dario has made that training costs less than they make on inference (over the life cycle of a model)?
> I don't think you can reverse this out like this because the 80% rate is before payments to "distribution partners, including Amazon". I think that payment includes the hosting cost for that those model but it's unclear.
The "hosting cost" is paid for by Anthropic and is the largest cost. The money Anthropic pay to Amazon for delivering Anthropic models via Bedrock is separate, independent of compute costs, best thought of as commission.
The forecasted / guessed / estimated 80% number is based what customers pay per token minus the projected compute costs, i.e: the people who believe that Anthropic has 80% margins on tokens believe that Anthropic spend $0.20 on inference compute for every $1 of per-token billed-via-the-api revenue.
We know that there are hundreds of thousands of fixed-price subscriptions being used to their absolute maximum, with many people bragging about how many subscriptions they run in parallel. These tokens are not included in the 80% margins, they are acknowledged to be "subsidized". People like @theo on Twitter post almost daily about how much they're milking Anthropic and OpenAI with leaderboards.
Both Anthropic and OpenAI (more so OpenAI) do "resets" where they increase the limits available to people on their fixed price plans. We know that there are people paying $1,000 per month for multiple subscriptions to generate tokens that would cost $50,000 via the API. Even if Anthropic's margins are 80% on compute for per-token billing, that's still $10,000 of cost to Anthropic generating just $1,000 in revenue. Multiply that by tens of thousands or maybe even hundreds of thousands of subscriptions.
Anthropic and OpenAI have raised over $100 billion each and continue to raise. If they're making 80% or even 50% margins on $10 billion in revenue per month they would not need to raise, they would be shouting for the roof tops about how profitable they are, they wouldn't be delaying their IPOs, yet they're only profitable by non-GAAP metrics like WeWork's classic "Community-adjusted EBITDA" or in this case "per-token-adjusted EBITDA" or whatever they will call it in their IPOs.
Yes, they're selling tokens via the API for more than they cost, they are profitable on per-token billed inference, it has positive margins, but those profits are obliterated when you account for all the inference they're paying for out of pocket on fixed price subscriptions, upon which they keep increasing limits because they desperately need to show growth further harming their profitability (consuming all of the money they make from their API).
If Anthropic and OpenAI needed to be profitable tomorrow, they could be, they could kill off all their fixed price subscription plans and charge only for usage via the API, they'd print money, but they'd lose mindshare because nobody except for enterprises can afford to pay the true cost, all the regular people would switch to cost effective good-enough models, and then within months, the enterprises would start to switch too because no longer would their employees be claude-pilled.
Anthropic and OpenAI cannot turn off subsidization, thus, their margins on per-token API billing are not important in any discussion about their long term financial wellbeing. Just look at the large scale customers like Harvey (~15 trillion tokens per month, ~$50m+ in spend) who are, sensibly, investing in building their own specialized models that are cheap to run so they can cut their spend by 90%. That's profitable revenue for Anthropic / OpenAI today, but completely gone soon.
"This week, Noah Smith and Erik Torenberg are joined by Dario Amodei, CEO and Co-founder of Anthropic. Dario talks about the economics of AI development, the comparative advantage of AI companies like Anthropic, AI safety, and his stance on California's SB 1047 bill. They also discuss the impacts of AI on global power dynamics, competition between the US and China, and inequality in an AI-powered world."
At around 12 minutes in:
"I think actually even if such a model is released one thing you know that's a this analogy to to open- Source software is that these big models they're actually very expensive to run on inference the majority of the cost is is inference not necessarily the training of the model so if you have only you know I don't know 10 20% 30% better way to do inference that can kind of negate the effect so the economics are kind of strange yes there's this giant fixed cost that you have to amortise but then there's also the per unit cost of inference and small differences in that can actually again assuming the thing is deployed widely enough make a very big difference so I don't know quite how that's going to play out"
The scales have changed since then with inference costs falling and more being spent on training but the fundamentals are the same. Inference is expensive, in part, because peak usage dictates capacity whereas capacity can dictate training. Anthropic must pay billions of dollars per month to be able to handle peak inference, hence their efforts to try and shape usage by offering discounts / flexible limits at different times of the day. They can train when capacity permits.
> The money Anthropic pay to Amazon for delivering Anthropic models via Bedrock is separate, independent of compute costs, best thought of as commission.
My point is that you can't reverse out the maths like you did without knowing how much this is.
> These tokens are not included in the 80% margins, they are acknowledged to be "subsidized".
No, this isn't correct. Even including these they are claiming 80% margins.
There's nothing at all that indicates subscriptions aren't included in this - it's a simple statement of their running margin.
> these big models they're actually very expensive to run on inference the majority of the cost is is inference not necessarily the training of the model
I don't think you can take this statement to claim that currently they spend more on inference than on training. I think he's saying over the lifetime of a model maybe inference ends up costing more unless they keep finding "better way to do inference that can kind of negate the effect".
> If Anthropic and OpenAI needed to be profitable tomorrow, they could be, they could kill off all their fixed price subscription plans and charge only for usage via the API, they'd print money
My point is that their subscription costs are a lot less than you think because of this statement by Anthropic that they have 80% margins including these subscriptions.
Your version of reality cannot be real because the numbers do not make sense. Anthropic's supposed revenue run rate for 2026 puts December 2026's forecasted revenue at $10 billion. They're only "profitable" according to a non-GAAP measure that excludes all of their costs, they are not cash flow positive, they are not bringing in more money than they are spending.
If their margins are 80%, that means on $10 billion in revenue they're spending just $2 billion. Anthropic's own announcements put their spending at much, much higher, such as the $1.25 billion per month they are paying to SpaceX for compute, and the ~$3.5 billion they're paying to Google each month, and the billions to Amazon each month too.
> We’ve signed an agreement with SpaceX to use all of the compute capacity at their Colossus 1 data center. This gives us access to more than 300 megawatts of new capacity (over 220,000 NVIDIA GPUs) within the month. This additional capacity will directly improve capacity for Claude Pro and Claude Max subscribers.
There's no world in which Anthropic has 80% margins. At their current expenditure on compute it would require at least $20 billion in revenue to be mathematically possible. The 80% figure on compute margins that is widely discussed is based on analysis by SemiAnalysis and refers only to their per-token compute margin (which is calculated comparing hardware costs + electricity costs to what they charge via the API).
The estimated training costs for models like Opus and Astra are ~$1 billion and they're not training multiple frontier models in parallel every month. Training costs cannot explain where billions of dollars per month are disappearing if they have 80% margins. And that's before even considering all the money they're raising and spending. Anthropic raised tens of billions just a few months ago, OpenAI even more.
> The 80% figure on compute margins that is widely discussed is based on analysis by SemiAnalysis
No.
To quote from my link above:
> Anthropic has told its backers it will be profitable this quarter, as it moves to allay investor concerns about the aggressive cash burn of frontier AI companies ahead of its blockbuster initial public offering.
> The company has told a small group of shareholders that its adjusted operating income will be positive for the second consecutive quarter,
[snip]
> Anthropic’s gross margins are above 80 per cent before accounting for revenue shared with distribution partners, including Amazon, and the cost of training its models, according to two of the people.
So this is a direct claim by Anthropic people, not analysis by outsiders.
> If their margins are 80%, that means on $10 billion in revenue they're spending just $2 billion.
Agree - but only spending $2B on inference.
> Anthropic's own announcements put their spending at much, much higher, such as the $1.25 billion per month they are paying to SpaceX for compute, and the ~$3.5 billion they're paying to Google each month, and the billions to Amazon each month too.
I don't believe this compute is sorely dedicated to inference. Only the part dedicated to inference is included in this profit rate calculation.
Do we know that? As I understand it, enterprise customers pay more. Do we know the usage breakdown between monthly subscribers vs enterprise accounts? I agree that it's inevitable that subsidized subscriptions are unlikely to last forever, but that's not the only assumption in your argument.
Edit: I think "enterprise customers pay more" was poorly phrased. I mean that enterprise customers are charged per token, presumably with a profit margin, and thus are not subsidized. While personal accounts are (thought to be) highly subsidized if you consistently max out the quotas. We also don't know what proportion of personal accounts do that though, which is another big question mark.
I think you're also missing a quirk and that is, is everyone on a $200 plan using $10,000 worth of equivalent API spend?
I know people that have the most expensive plan on all the platforms... because
The other side to that is, what is 'cost'? Is cost just inference or are expenses also being taken into account? Because the expenses of these companies are huge to build the models.
There’s an astounding level of arrogance required to believe he is somehow uniquely capable of bringing about a technology especially considering Anthropic came after OpenAI where he worked.
Place yourself at the head of one of like 3 companies the entire rest of the world has been taking about nonstop for 4+ years now. You can move forward or you stop. If you move forward you get to have a hand in how stuff turns out and you make a gajillion dollars. If you stop, it's somebody else's hand in stuff, and you don't get to make a gajillion dollars. And if you shut it all down? Then you just cede to the competition. Everything happens anyway.
the obvious play is to get the government to shut down all the competition, and then make a gajillion dollars while making whatever at the worst level of effort that destroys the world anyways.
----
the real play is using the accumulated power to get socialism and democratic control over the key aspects of the economy, such as where to build data centers, and how many. Nothing says you have to play the corporate game of competition
> I think Dario is genuinely afraid of the inevitability
If someone genuinely believes that an invention will bring about the end of the world as we know it while making him and his friends inconceivably rich, “hey guys let’s uh, stop?” is so profoundly naive that his think pieces aren’t worth the bits they’re written on.
He’s either an idiot or an idiot, does it matter whether or not he genuinely believes this nonsense?
You are cynical but not cynical enough. The idea of a rogue Ai gives plausible deniability when they can blame human hubris, rather than it being seen as a deliberate and calculated attack, the perfect cover story for a sinister scifi plot. Make it look like an accident ehh
I can't even tell whether the poster to whom you're replying is saying that "let's uh, stop" is profoundly naive, or that failing to say it is profoundly naive... I've certainly seen both takes elsewhere.
Vitalik Buterin: “...But currently, I see zero plans for how to deal with an ASI transition that are not naive. Perhaps humanity is stuck with a choice between naive and naive squared (or maybe even naive squared and naive cubed), so I feel inclined to cut some slack to people who are trying.”
Long before generative AI we all knew one absolute truth: ideas don’t matter, it’s the execution. YC marched to the drum. Execution! Execution! Execution! Do things that don’t scale, do the hard things, build something people want.
And then generative AI arrived and suddenly, unless you’re generating the maximum amount of code in the minimum amount of time, you’re going to fail, you’re going to be left behind, programming is dead, do the easy thing, generate! Generate! Generate!
We are years into generative AI and still there is no fundamental change. The most successful businesses are still the businesses doing something well, not businesses doing things easy. Spending hundreds of hours writing every line of code by hand isn’t a competitive weakness, it isn’t foolish, if it creates a good product.
So, I agree, fuck it, type your code line by line. Users don’t care if you spent 1 hour or 100, they care if your product is good, just as they did in 2025, 2020, 2015…
Maybe you’ll get beaten by someone generating a million lines of code. Just as maybe you would have been beaten by someone who typed faster than you in 2020. Nobody worried about increasing WPM in 2020.
But my purse does, as do my investors. I can no longer justify taking a hundred hours to build a product, even if that makes it materially better than that of my competitor, who spent one hour to build theirs and used the other ninety-nine to sell it.
I don't like that either, but it's the reality we live in now.
> And then generative AI arrived and suddenly, unless you’re generating the maximum amount of code in the minimum amount of time, you’re going to fail, you’re going to be left behind, programming is dead, do the easy thing, generate! Generate! Generate!
This reminds me of a different theme in the programming world.
There was always a feeling that development spends time on meetings long past the point when the app could have been finished. And I remember a comment here on HN (which I can't find now) saying how, if you're on a team at IBM working to develop something for a client, you will feel that you could just go ahead and finish whatever functionality you're supposed to be developing.
And if you sneak in after hours and do that, you'll be met with the message that you aren't being helpful, that you've got to wait for the business to determine that that functionality really is what the client wants, that the app needs to be described a certain way to get signoff from other decision makers, etc. Anything annoying that you can imagine.
But the overall takeaway that I saw was that developers tend to be frustrated that business processes are slower than the act of producing the software, and they feel held back by that.
Given that background, it's not clear why generating more code per unit time is valuable at all. That's something developers wanted to do all along, and they were told they shouldn't. More code per developer would make sense, but why more code per time?
> * Donated the WordPress trademark to the nonprofit WordPress Foundation in 2010
Fallen at the first hurdle. The WordPress Foundation is Matt’s personal vehicle used to obscure his control over the WordPress ecosystem. He has misrepresented the foundations role for over a decade, it was only following the WP Engine debacle that the true status of the foundation and Matt’s personal ownership of WordPress.org came to light.
The spirit of Open Source is contributing to the world for the greater good, not building your personal fiefdom. Matt is rare because he’s one of the few people in Open Source who are so desperate to launder their reputation. Most either acknowledge their project as theirs over which they exert absolute control or they hand over control to the community. Matt pretended to be a benevolent steward for decades until his position was threatened. He has long since cashed in all the credit he earned for his Open Source contributions.
You’ll find dozens of examples of tech CEOs that spend some of their corporate budget on sponsorships of open source projects and events. Matt was relatively unique in 2006, but not in 2026.
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