The Chinese models are also creating a bit of a vice for the tier one ai labs. The middle and low end customers that aer price sensitive are gone. The price difference is so huge people have to look at the open source models. The top models are reserved for 10% of the tasks that the Chinese can't do. You can make that a business.
Seemed very good. Much less stress on the troops for target acquisition. It’s also only going to get better. Problem is that for now, there’s only so much we can do from the air. We’ve already blown everything up that we can see from the air and satellites. We also are not trying to escalate anymore. We were pretty successful in killing all their leadership, but that in of itself isn’t really a great goal cause they got plenty of people to run things.
It will only be a matter of time before we have ai drone swarms and have some ender’s game level attack patterns. What a time to be alive.
That’s strategic mistakes because there were no well defined goals. The military industrial complex is doing incredibly well and am achieving great military moves. Unfortunately you need more than military might to achieve things in this world.
Ukraine just trounced US tanks with drones in a war game. The US is manufacturing a lot of weapons but it's not clear they know how to make useful military moves anymore.
if you want to do agentic coding, you don't want to sacrifice performance. they are still not on par with codex/claude for coding. partially from the harness, and partially because these companies are heavily targeting coding ability
for general use and maybe if you aren't employed, its good enough. if you work at a company and they pay you 6 figures, I don't see why anyone would use subpar models to save such a tiny % of what they spend on you. like codex/claud max20x is $200/mo and SWEs pull $10~30k/mo in salary
Eh, yes and no. People who are using Claude Fable or whatever to perform every little tiny task are just wasting resources. Ideally you'd use the big guns as an orchestrator to draw up a roadmap of dozens/hundreds/thousands of small discrete tasks, and then you can slot in a collection of whatever tiny models to code those out. Then maybe at the end you break out fable again to give it a pass over and make sure everything came together as expected.
Lots of harnesses support a workflow like this now, which doesn't move you entirely off of the top of the line models, but certainly eats massively into the profit ceiling for these companies.
100%, and as investment money pulls back you will see more of this. The problem is that in edge cases, automatic discernment of what automation tools will be effective for a given task can be...opaque. So you have to consider "is this worth the time and money to train staff over the course of months to figure out what tools are effective for what?" when the average US employee costs anywhere from $35-$75 an hour for a given business.
So when it's a couple hundred dollars difference a month, sticking with 1 tool isn't a huge issue. It's when your compute costs go into the millions/hundreds of millions that you'll be forced to diversify.
But it will be different for each and every business.
> Ideally you'd use the big guns as an orchestrator to draw up a roadmap of dozens/hundreds/thousands of small discrete tasks, and then you can slot in a collection of whatever tiny models to code those out.
GSD-core
maybe use fable to research or orchestrate but op can do that just fine, sonnet can write the code.
Fable actually i'd use to find the brownfield requirements. That's actually a perfect use case for it, map out the existing repo/codebase, document existing requirements, if dealing with an enterprise app (crm,erp,etc) it can scan through say salesforce docs and your codebase to find existing limits/requirements.
> People who are using Claude Fable or whatever to perform every little tiny task are just wasting resources.
If you make $50/hour Claude Fable can legitimately let you double your productivity for "every little task." You can certainly overuse it but the math works out if you're a company paying software engineers $50/hour (really $250/hour.)
>if you work at a company and they pay you 6 figures, I don't see why anyone would use subpar models to save such a tiny % of what they spend on you. like codex/claud max20x is $200/mo and SWEs pull $10~30k/mo in salary
A few things;
Pricing has changed and that fixed $200/mo no longer exists. Enterprise pricing is now per seat plus per tokens consumed. I dont think anyone offers any included tokens anymore.
The open weight models have all but closed the gap. Prop frontier models - Anthropic, OpenAI, Google, CoPilot?? may perform better at the edges but not many people actually need that. There are other considerations with open weight models but price/performace is strongly in their favor.
I work closely with these models and I have not yet seen anyone really migrate away from the proprietary frontier models yet. But, there is real interest in the open weight models. It's still a risky venture though, not because the models dont perform but geopolitics and ecosystem. It is much easier to get started with Anthropic, OpenAI, Google then any of the open weight options.
Corporate America won't take on that risk yet. Eventually if that risk goes down or goes away and the models comptete on the economics of it the closed models arent able to compete with the open models.
And this is what the vibe coders said six months ago and six months before that, with models that would now under perform the Chinese models.
And in six months, when China catches up to the current American frontier, someone will make the same argument that it's somehow worth it, but that someone is going to be part of an increasingly shrinking pool.
Agreed on all the model feedback, but it seems like the 200 only gets me a ticket to the dance. I burn tokens on a meter, which admittedly isnt significant…but we have to know that price is going to go through the roof soon
$200 per month is pretty low if you’re using Claude for everything. That’s pretty close to my spend and I only use it a couple times per day and I never go out of my way to use loops or multiple agents or anything.
oh wtf my bad i read another comment and somehow thought it was same thread i agree w u. i think the models being ‘commodities’ is over played by non technical ppl. openai cornered math and stem and anthropic enterprise software development
I'm a software engineer working for a large tech company. I've used cheap/free chinese models in personal projects because I'm a cheapskate, and frontier Claude and GPT models at work. My company is choosing to pay 1000x the cost for me to be able to use the latter over models that are 90%+ as good, and correctly so in my opinion. The extra 5-10% matters a lot.
"90% as good" is very misleading, since that 10% often means it takes 20x as long and produces no useful results, or even worse, results that look correct but are in fact wrong.
No, that would hurt China a lot and probably trigger uprising against the ruling party and Xi will loose all his power.
China is boosting an open ecosystem because they want to participate in the AI boom. In an ecosystem controlled by US corporations they will be blocked from participating by the US government.
I think a lot of it is courting the AI researchers. Publishing papers, having open weights and accessible models all make your labs more enticing. If you are trying to hire the best in the world, and you can't compete with the tier-one US labs and their stupidly high salaries, you have to find something else to attract talent.
Why does Xi get credit for anything? I think XI kind of thought AI was a fad, Ironically the Chinese gov not caring that much probably helped their AI industry be more innovative and open.
Yes, a few months ago, the Chinese gov is coming around to it now. Funny thing is if they start to try to lock it down like the US it may give other regions to become the open source hub instead.
It's not even just China that will benefit from these models.. There are plenty of larger businesses in the US that will benefit from commoditized AI offerings that these open AI models will bring.
Maybe they're making the models open source because historically open platforms have done better than closed, walled gardens... (See IBM PC clones vs. Apple, or Android vs. iOS)
The ai labs represent a very small portion of economic activity, though. I believe most of the companies investing in datacenters are model agnostic now.
Edit: Not to mention the sell for a lot of these AI labs isn't the model, but all the external tool integrations that have been developed to enable AI to do things an LLM can't do alone like precise math.
There will be a financial shock, but long term these models are here to stay. Data Warehousing demand probably won't be as big as the values of these companies currently predict though, new models are getting more efficient and powerful all the time.
Even the frontier models still struggle with spatial reasoning. The new models are getting more efficient but I think the frontier will continue to get bigger until they figure out spatial reasoning properly, which could be a while.
Also if 30B parameter models get to be Fable-level I think you'll start seeing the equivalent in the cloud with the extra RAM dedicated to more and more context. 30M-50M tokens of context would be game-changing. Although I kind of suspect you need a trillions-of-parameters model to usefully use that much context.
oh for sure.. but at some point the infinite money dries up and subscriptions won't be subsidized anymore. Businesses will be looking to keep their LLM API costs low by using the correctly sized model for each task.
People want to keep costs down, to be sure, but software engineers cost $10k-$30k a month and quibbling about spending $100/day in tokens is being pennywise and pound-foolish if you're actually developing software that you sell.
Google and Meta certainly aren't "model agnostic," and neither is any other tech company with their own model. To use another one is to admit defeat (which Apple has basically done). Do you think Elon is suddenly going to delete Grok and say, "Nah, we're using ChatGPT now?"
It's highly likely that at least one of the main AI labs will blow up at some point, maybe both OpenAI and Anthropic will, or at least there'll be some sort of crisis followed by unfavourable forced restructuring.
But...
...that in itself isn't unusual, that's what happens in the "gold rush" stage of pretty much every technological breakthrough. A loss-making land grab is common, and has been for 200 years or more. Canal Mania in England in the 1700s had much the same process.
This headline seems to be implying this state-of-affairs is somehow unique.
It is unique because LLMs are uniquely expensive. For some reason, none of the AI boosters will acknowledge this fact. Every comparison to durr Uber or Durr Amazon is underscored by the fact that they don't cost ANYWHERE as much in compute.
As well as the huge compute costs, depreciation of hardware is also another factor that makes the whole gold rush or railway analogy really not really work in my view. It’s not like this stuff will be built out and last for 20 years, or 10 years, or 5.
The data centers and supporting infrastructure (buildings, power, cooling, internet connectivity) will last. The GPU tenants could last more than three years, the idea of that they rapidly depreciate stems from expected further advancements which make them more economical to replace than keep, not that they will all fail at the three year mark.
If the bubble pops, those future advancements may slow and older silicon could be kept online longer.
The thing is, none of these dynamics are new to the industry. The people making these decisions understand all of these things deeply, which isn’t to say things can’t or won’t go sideways, that’s the nature of speculative investment.
Cerebras ChatGPT Sol isn't a flash model, it's the full model running on Cerebras, which means it is more expensive to serve because you're using an entire million-dollar Cerebras chip to serve a single request. (As opposed to the million-dollar servers usually used which are slower but can serve dozens of requests in parallel.)
>It is unique because LLMs are uniquely expensive.
But isn't the potential gold mine at the end for the one that suceeds first uniquely profitable? Following the same general rules the other use is discussing about gold rushes and leading with losses.
How does the cost disparity in the AI sector being magnitudes more than Uber and Amazon make a material distinction in this conversation?
They want it to replace workers and workers are cheaper, especially if the true costs to run these models is passed on to the businesses. Another issue is the accuracy of these models. Would you buy a calculator that was correct 90% of the time? How about if it cost $1000 a month to run it? LLMs are unlike other software in that it isn't right all of the time but it is priced at orders of magnitude more than other software.
Humans make mistakes all the time, but these fall along predictable patterns that have been studied for decades, and robust systems and processes are designed to guard against them.
AI and especially LLM mistakes display quite different patterns and that makes them seem especially egregious or baffling to us humans.
>They want it to replace workers and workers are cheaper
Isn't the gold rush at the end when this is no longer the case?
Same for the other points.
>it isn't right all of the time but it is priced at orders of magnitude more than other software.
Because if those problems can be solved (they believe it can be, regardless) then it will be uniquely profitable in the same regard.
Again, it seems the point is not the magnitudes difference in debt, as the rewards are potentially in the same magnitudes, but rather in the viability.
To use the gold rush anomaly. It's not that there's uniquely more gold in the mine attracting a massive amount of debt/rush to get it ("uniquely expensive"). It's that it's improbable it's minable.
Which is identical to an actual gold rush scenario. its speculative.
No, the gold mine at the end isn’t profitable. What they’re seeing is a 12 trillion dollar TAM of white collar work, the problem is if these companies succeed, that TAM collapse because the cost of work is now much lower
Edit: it isn’t uniquely profitable if you go beyond the simple calculations they’re making
It's absolutely unique. You're right, there's hundreds of examples of SAAS services and other industries making huge losses to grab market share then slowly hike up the price.
The main difference is cost of inference with LLMs. For Amazon or netflix the cost to serve goes down as you increase your market share and build up the infrastructure.
For cloud computing for netflix the more users you have, you actually save money by negotiating smaller contracts with the cloud provider.
As Amazon built more warehouses and acquired more drivers the cost to serve goes down because they can travel shorter distances, improving delivery times.
For AI labs there's a cost to train a model and every time the user uses tokens the AI lab has to pay (in a data centre they may or may not own).
So as market share increases you actually lose more money exponentially. And the current track is the "better" models get, the more expensive they get to serve.
And lastly the SCALE of losses are incomparable. At it's worst Amazon was operating at a 16bn defecit before they turned a profitable year.
AI lab investment currently sits between 1.25 trillion and 1.75 trillion depending on who you ask, for a total revenue return of just over 60 billion in 4 years since gpt1 was released.
It's basically a giant circular financing Ponzi scheme ATM.
> So as market share increases you actually lose more money exponentially.
only if you're selling tokens at a loss, and the evidence anyone is doing that is pretty thin. It looks a lot like the US labs are deliberately spinning the narrative you're talking about so people buy tons of tokens in the mistaken belief that they're getting a huge discount. When in fact the margins on frontier inference are insanely profitable, and it's like any other SAAS in that respect.
Where is the hard evidence inference in profitable? OpenAI lost billions last year, we don’t have any data on anthropic so we can’t trust their public statements or leaks either
There's no hard evidence either way. But the idea that businesses are going to "lose money exponentially" selling inference at a loss is pretty out-there. Seems much more likely they want customers to think like you do so they will spend money exponentially on a profitable product.
The $20/month and $200/month plans are oversold but that doesn't mean they're subsidized - it just means if people used them 100% they would lose money, but they have good control over that situation and don't let people use them 100%.
I never said that’s the case that, but selling inference at a loss isn’t out there. We have proof of these companies doing this. It’s the tech playbook, sell at a loss, gain market share, increase prices with market dominance. We don’t know what’s going on exactly, but it’s equally likely they’re selling some portion of inference at a loss as it is they’re making money. And those costs bare minimum increase linearly.
That's almost 2 trillion dollars. The problem a lot people don't grasp with AI is the sheer scale of the cost. At it's worst, even a giant corporation like Amazon was operating at a $16 billion deficit before they turned a profitable year.
2 trillion dollar is low i feel like they should be valued much higher. if you do frontier work in stem the tech genuinely feels surreal u cant compare it to anything else
Yes and no. Yes, it's correct that lots of businesses in the "gold rush" stage have poor business models that struggle when the euphoria wears off. What's unique in this situation is that the leaders in this industry are the ones losing money. The application layer, the layer facing the end-users, is the layer seeing losses, and that's across the board. I'm not familiar with the economics of the Chinese models, but none of the US AI businesses that are actually building the models themselves are anywhere near profitable. That raises serious questions as to the viability of this entire business.
I'm not a staunch AI skeptic, it will stick around in some form, but what form and how much of the current investment gets completely wiped out is an open question.
> What's unique in this situation is that the leaders in this industry are the ones losing money.
That's not unique at all.
Amazon didn't make a profit for it's first nine years. (To pick just one example).
Losing money until businesses reach a break-even point is standard in these situations. The risks being: how long will it take to get there, and what could change in the meantime to prevent them getting there.
I don’t think people here appreciate how widely used these LMMs have become. I’ve seen first hand the dramatic shift at work but I also know people who have never been tech savvy embracing AI.
I have very mixed feelings about this tech and I’ll be the first to admit that it’s been massively disruptive on so many levels but AI is here to stay. We’re a long way off from knowing who the winners and losers will be.
There's not a lot of evidence it's highly subsidized. I think the initial releases might be roughly at cost, but they quickly optimize and margins are likely more like 90% for most of it.
I actually use Claude a ton, everyday. But my company is lowering usage limits as it adds more users to the pool. And as the models get more capable and the datasets get bigger, I’m hitting my limits faster. And I do believe they will either limit the number of users at some point (which will be difficult as it gets more entrenched in different tasks), or they will limit the amount of data we can have it analyze which will reduce how useful it is.
Sure not saying that companies aren't going to cost cut, we do the same with limits. Just pointing out that at the enterprise tier we're not paying subsided prices.
Is this reddit code for 'I use it all the time because I understand what it can do and what it's limitations are, but dont like telling people that, and I acknowledge that it's overuse has a real effect on everything from the environment to the economy', cause if so I also have mixed feelings about it.
There have been reports of creative accounting, all the circular dealing between the major tech firms, the labs, and Nvidia. Neither of this firms are filling out 10-k's yet. They are self reporting these figures. Also, ARR as a measure is easily manipulated. Sooooo this could literally all be smoke and mirrors to project health and strength to the market, creditors, and competitors.
The problem is that the revenue only looks high if you don’t factor in all of the capex; they are projected to spend $100 billion in infrastructure alone in 2026 and I doubt they make over their total costs for that and everything else this year.
It’s the debt. No other startup was this deep in the hole then succeeded. The only way to pay pack investors and the reason why AI gets so much money is because it’s meant to replace workers on a large scale. If it cannot massively reduce worker numbers, then AI companies will never be able to pay the debt.
>It’s the debt. No other startup was this deep in the hole then succeeded.
I'm agreeing with you. And when debt becomes due will be a major moment. But it's obvious that no other startup was facing this deep of a profit if they are ultimately successful.
So sure, debt is unprecedented, but so is the potential profit. The only question is if it materializes.
There's a massive risk, but the risk isn't how deep the hole is. It's if they are the ones to have the breakthrough.
We’re over ten years in now (Open AI was founded in 2015) and 8 years from when Open AI released its first language model. The scale of their spend is very not normal and the VCs are getting impatient. I don’t believe they have all that much runway left, of course everything rests on the IPO being successful (and not postponed again). I wouldn’t venture to measure how much in months to actual sustainable profitability but people can’t talk about what it’s going to do in 2030 as if that will be soon enough
Amazon finally turned profitable because of AWS, it had to pivot from its original business model. It’s now improved its profitability elsewhere because of jacking up seller fees (which may have a detrimental effect on use the platform) but still in 2024 AWS made up 58% of Amazon’s operating profit https://finance.yahoo.com/news/mystery-inside-amazon-record-profits-010823949.html?guccounter=1
The numbers I see both point to anthropic and openai having a successful ipo and having fairly decent earning for the forseeable future. we also have not seen any scaling wall being hit, which has been pessimisticly predicted on reddit for the past 3 years. the explosion in revenue this year really reflects how powerful coding agents got in latest generation. if progress continues, users/revenue will only go up. we are only a couple doublings from these agents being smarter than pretty much everybody and capable of doing virtually any intellectual task
> Anthropic and openai revenue have both exploded this year - see chart
But where is the revenue coming from? If it's the Microsofts and other tech giants, that stream could dry up if the can't pass those costs along to their clients.
IE if MS is spending say 50B a year on OpenAI, but only can realize 25B from their customers, then they'll start to pull back on their AI spending.
I'm not saying this is going to happen, but if there isn't money to be made by the Microsofts of the world, their investment in AI will decline. The current rates are unsustainable, and we should be prepared for an AI spending pullback at some point.
> 80% from api/enterprise with 300000 business customers
So 80% of their revenue is from customers like Microsoft? I think my position stands that if MS can't get value from their AI spending, then it might pull back.
I've been through the dot.com boom and bust. This feels very much like that. AI will 100% be a game changer going forward, just like the dot.com was in 1999. But I think there will be some blood in the water before it all balances out.
80% spread across 300000 businesses, not one big company. companies are getting value, hence why they are paying for tokens. agentic coding agents are just better than humans 99% of the time now, and it was not true last year. if you are writing software, you want every dev in the company to have a claude subscription or unlimited token access.
I think we both agree that AI is a game changer. The difference is that I think the meteoric rise in (stock) valuations, and revenue isn't sustainable. And we'll see a pull back in the AI space.
My own small org is trying to find ways to cut down on token spending. It's getting too expensive.
This is not about hating LLM or other reasoning technologies, they are transformative indeed. The point is that the current business model will fail. AI services will generally not be expensive, this is just the current stage is expensive. It propelled purely by FOMO.
> Oh there’s also one important note: The Journal adds at the bottom of the article that “...it is unclear what accounting methods Anthropic has used to book revenue and costs, as the company isn’t yet required to follow the financial-reporting requirements of a public company.” That’s right —-- Anthropic is possibly going to be EBITDA profitable for a single quarter, on a non-GAAP basis.
> That’s also interesting. So Anthropic may be profitable very specifically in Q2 2026, but might not be afterward. It’s almost as if it found a way to specifically cut its costs in May and June somehow…
> …because it did! Remember that deal Anthropic signed with SpaceX to take over Colossus-1? Well it’s also taking over some or all of Colossus-2, paying SpaceX $1.25 billion a month starting in May and June… when it’ll have a reduced fee as it ramps up!
> That’s $15 billion a year in compute costs, but reduced to an indeterminately-discounted level for the precise months that Anthropic is using to tell investors and the media that it has an operating profit. That operating profit is a result of accountancy rather than any improvements to its business model.
> While I wouldn’t say this is cooking the books, it’s definitely a shiatsu-grade massaging of the numbers. Anthropic has deliberately leaked a quarterly “profit” where it knows it can suppress its costs, specifically made sure that the journalist gave it the out of “costs might increase,” and released it on the day of NVIDIA’s earnings as a means of keeping the AI bubble inflated.
Correct, and taking it one step further. Any revenue is used to pay off early investors. It’s a textbook Ponzi scheme. Just like private equity - largely what’s going on in private equity right now is a Ponzi scheme and assets that private equity has acquired are worth less today than when they were acquired, meaning private equity can’t unload them. Any sort of revenue private equity is getting is used to pay off early investors at the cost of recent investors.
Everyone needs to buckle up for a crash unfortunately
AI search has increased their search ad revenue, not decreased it. That narrative has proven to be incorrect which is why their stock is up 100% over the past 12 months. Your opinion is about 2 years outdated now.
That's temporary. Ad-buying companies are incensed with it and are already pulling back their ad buys. But it takes awhile to redeploy those ad dollars somewhere else.
Google isn't worth it anymore for them That's a killer.
The people complaining are not their ad customers. The people complaining are like cooking bloggers that run their own ad infested cooking blogs that have seen a dropoff in visitors because ai overview gives you a cookie recipe
The only people complaining are the ones who have their own websites like blogs with ads that relied on blue links to funnel users into their own ad ecosystem. Those people were not Google ad customers to begin with though.
Negative cash flow doesn’t mean the model is not sustainable lol their GCP backlog is $500B. They have to build the data centers to service cloud contacts already signed. It is a perfectly acceptable business model to go negative cash flow of $200B in order to service a revenue backlog of $500B, obviously.
Google was wildly profitable last Q even with negative cash flow and excluding investment gains.
Ok, but every FAANG company hides their AI spend within a different category like "cloud", which is their most profitable segment already. You don't actually know how much they are losing.
Google (and Apple soon) will say they don’t really care. You could claim they also “hide” their spend on email and maps and how those are unprofitable business segments. Google has a business model where their unprofitable software offerings like maps, email and AI are part of an ecosystem of software services underpinned by ad revenue and enterprise cloud solutions.
This is the same argument people made about email being an unsustainable business model.
Email is like what, a few fucking kilobytes? And there's a limit to how large one can be.
LLMs are not like that. A user with a fresh prompt uses all of the VRAM the model uses + some for their starting context window. Someone who pasted a crap ton of code is using far MORE VRAM for the context window, and is costing much more. You can not fight against the near exponential scaling costs of training the model, nor the quadratic (SLOW) attention mechanism of inferencing. LLMs light money on fire.
Yeah the scale is different but the philosophy is the same just with bigger numbers. Google is still making more money than they are spending because they have that ecosystem. Being a hyperscaler while training your own models allows you to be profitable.
BS comment. Revenue is not investment - and the net profits from revenue goes to investors, that’s fine.
Investors buy shares, that’s also fine.
If investors bought shares, and that money went to pay out profits, instead of actually purchasing the shares - that would be a textbook Ponzi scheme, and a massive fraud case.
Not BS comment at all. Go back and educate yourself on what a Ponzi scheme is. Both the AI sector and private equity sector are largely being sustained by Ponzi schemes currently.
Power of the media has always been known, now the trick is the corpos use these AI to manufacture concent and distract the massess, whilst confusing the poltical class... Thats how fascism did it, history repeating itself...
AI companies that use these data centers need to be profitable and have strong demand. Currently, that demand is there, not sure if it will stay strong.
Data centers need to reinvest in new equipment every 2–3 years due to physical wear and improvements in hardware. Some GPUs be still in less demanding tasks
Servers are typically deprecated on paper over 3 years.
In reality with very modest care even servers under heavy load have a 5 to 8 year lifespan.
Now if architectures with the equivilent of huge amounts of VRAM tightly attached to GPU-like processor's start to take over the old ones will quickly become obsolete.
Never confuse "there" (extant) demand with strong (inelastic) demand.
The demand for literal unicorns at $0 is somewhere in the single-digit millions of units, factoring in that they are still horses and have upkeep costs.
The quantity demanded, with consideration for the real biotech development cost, is... maybe one unit? Two? And only because of the obscene skew in wealth distribution.
But of apples and orange comparisons. Some companies are VC funded ventures whose profit will be funded by investors. And not really profit but rather losses. That’s the nature of VC backed companies even at scale.
Some of the companies are well established businesses (even public ones) and they are taking highly speculative bets which are getting funded with debt and future profit (or losses).
One is not the other and they shouldn’t be compared. Both add to respective bubbles but in the case of the public companies there’s an argument to be made they went in deep too soon. That’s a question of bad management.
Unfortunately given the size of both bubbles there is the potential for a serious deflation for some companies.
OpenAI and Anthropic have consistently put out very profitable products. The reason why the companies aren’t profitable is because the huge capital investments they’re making right now are for products that will exist in the future.
It’s kind of like saying that a new NBA team is unprofitable while their $1 billion arena is still under construction and the team isn’t playing yet.
Except the construction in discussion is basically training new models.
And unlike an arena that's reusable in a long term, a model from 2022 is garbage today, not because technology improved, but simply because it lacks four years of context.
When you put it that way, training isn't a one time cost, but a constant operations cost for any LLM provider out there.
who cares? If I open a line of bracelets and one line sells extremely well and the other lines put me 300% in the red who gives a fuck about the unicorn bracelet?
Fascism trying to hedge their capital wealth against the rising socialism and awareness of the inequity and inequality, by speed running the technofuedlism orwellian nightmare of mass surveillance and data driven economic and social control...
SO the math does make sense when you understand how history is in fact repeating itself.
I believe he's an idiot who doesn't know strategic management, typical "economist". Of course they are unprofitable, as they are in the growth/scaling stage. Had they (OpenAI, Anthropic, etc.) chosen overnight to turn a profit, they would have destroyed more than 90% of their value
They could never turn a profit overnight because as soon as they did that the demand would snap out of existence. The models are brutally expensive to train, that is why they are igniting money to the point that crypto-nft-AI bros can't count that high.
Except for a BILLION FUCKING PEOPLE using their services - that's the demand. Do you really think an abuela down in Mexico or a boomer anywhere in the world knows how to set up a local LLM? Even if they did, it could cost thousands of dollars to acquire the necessary computing power for a household to run a decent model. A subscription costs $8 - $20 and offers the best models in the world running on the best inference chips - Cerebras, which you can't even buy as a consumer
And those billion people aren't paying for it. There only is demand if the service is free, there is no demand if people have to pay the actual cost of the service let alone the extra margin required to make it profitable. How little economic sense do you have?
The vast majority of those people are using the free tier. They will not take out a subscription. And even if they did it would not cover the colossal cost of the data centers.
Yes, they use free tiers because it’s perfectly rational for them to do so for now. And yes, the shareholders are financing it, which is also rational for them to do. These companies are very aggressively scaling and trying to steal market share from each other. It’s a ruthless, bloody war between a few clusters of tech companies for a market that will soon be worth a trillion dollars
You're working on the assumption this is life-changing tech for the abuela or boomer. They do not care. It is a funny toy to turn their dog into a secret agent. It could disappear tomorrow and nothing would seriously change. For the majority, there is no chance they're paying money for access to the funny piss-tinted photoshop generator.
If it were so trivially wrong, you could probably say so in a few words rather than resorting to ad hominem.
The user numbers are massively inflated by people who could never support the real cost of continuing to run these models and pay off dev spend, especially when the investor-bankrolled hardware they are currently running into the ground needs to be replaced. Never mind the cost of continuing to iterate (which, mind you, they must do in order to remain afloat, considering their valuation is only sensible under the presumption that they will somehow magick AGI into existence and utterly break economics).
Please defend AI with your own words and not standard industry talking points that everyone is bored of 🥱. Yes a billion people use their services. How many pay for it? See, that's the ultimate issue that you must cope about. How will these companies make money? Even Sam Altman doesn't know. The ads have failed. A year ago he said "we just ask the AI how to make it profitable". You're putting a lot of faith into incredibly unserious "companies".
Weird, I never said anything about local models, so you're obviously on the "I defend only the creepy AI labs cause I don't have an agenda" tree. Like come on.
Oh, and by the way, Cerebras is cool. I know one of the chief scientists there. Too bad OpenAI, the majority of AI demand, needs to turn a profit.
The whole Chinese economy operates by screwing everybody else over through CO2 emissions (poisoning the planet), as well as through slave labor in their concentration camps. The US/EU will never allow the Chinese AI into the Western world, it's a communist country never forget that. If you think else you just don't understand the reality of politics
The rub is that there is no path to profitability. The invests made were to create something that can eliminate workers. That’s not happening. Replacing workers was the only real way they’d make money, yet models are already hitting diminishing returns.
They were still improving at a decent rate but post-harness has been marginal. Opus->Mythos is particularly laughable because it's triple the size and like 5% improvement lol.
I cannot believe I was on the economics subreddit reading all these comments who regurgitate the same Reddit hive mind bullshit without understanding that the entire sector is scaling for long-term profits in the future
This website is fucking cooked, reading comments on this thread makes me remember all the intelligently worded bad advice I've read throughout the years as a lurker
I can absolutely believe that people who have no education in how these models work, think that LLMs are going to become anything but costlier, beefier LLMs. AI is cool. Unfortunately however, LLMs are narrow AI, much closer to a machine learning model that processes vast amounts of data, than actual intelligence. Many in the field are pulling their hair out wondering why we are wasting so much money on fucking LLMs.
So yeah, you fell for industry bait because you don't understand how the technology actually works.
You do know that a GPU only lasts 3 to 4 years at best, right? The buildings and the land are long term investments, but GPUs are a continuous money pit.
What long term profits, the only demand is openAI and anthropic and once either goes down that collapses the house of cards, open source models have effectively made sure there is no long term profitability.
It is embarassing to hear someone titled as a Chief Economist make such an uneducated statement. It demonstrates a complete lack of understanding of business models.
Sorry this is a stupid argument. The compute isn't being built for Claude, OpenAI or any other "chat" application. It's the infrastructure on which the next layer of AI will be built, and that infrastructure needs to exist before those applications.
Microsoft, Alphabet and Amazon can't afford to fall behind in building it. Their future growth increasingly depends on their cloud infrastructure businesses, and if one of them doesn't make these investments while the others do, it risks handing its competitors an enormous structural advantage.
I'm constantly surprised that smart people fail to see this.
You'd still still want that infrastructure investment to at some point be paid for by actual future customer revenue. That seems unlikely at the current scale. It won't hit datacenter builders and cloud services as much as the AI companies taking on long-term commitments.
Alphabet reported Google Cloud backlog of about $514 billion at Q2 2026, up more than $50 billion sequentially from Q1. Alphabet said the increase was driven by strong demand for enterprise AI offerings, and that just over half of the backlog should be recognised as revenue over the next 24 months.
Microsoft reported $678 billion of commercial remaining performance obligations at FY2026 Q4, up 84% year-on-year. Microsoft said all of the sequential RPO growth in the quarter came from customers outside frontier-model companies; excluding OpenAI, RPO was still up 25%. About 30% is expected to convert to revenue over the next 12 months.
Amazon reported approximately $496 billion of remaining performance obligations at 30 June 2026, primarily related to AWS. Its long-term contracted obligations had a weighted-average remaining life of 6.4 years. AWS itself was running at roughly a $169 billion annualised revenue rate in Q2, after quarterly AWS sales rose 37% year-on-year to $42.2 billion.
Sorry, i think you accidentally copy/pasted something with many numbers in it over your own argument.
Probably you wanted to use these numbers somehow, e.g. relate them to costs? Maybe take out the infra revenue coming in from deep-in-the-red AI companies? And argue that these companies might then be candidates to get workable business models going, even outside the frontier model cash burn?
Maybe you can get that argument together again, would be interested.
You don’t seem to be getting that these massively profitable companies with dozens of healthy revenue streams can afford the capital expenditures associated with the AI buildout without needing to show a profit right this second. They’re making the investment because they anticipate future growth related to AI, and the demand will obviously be there, because this technology has already changed the world even if it never advances further at all.
You’re thinking too small and if all executives thought like you, the economy would never grow and new industries would never be created.
I read it, now I'm waiting for what you make out of it. It's not clear what that is.
I mean, on the surface, we can summarize your pasted text as "projected revenues of big companies involved in AI infra and enterprise AI are rising due to AI".
To which my answer would be: "Well, duh?"
But does it pay off for them, and more importantly does it pay off for the companies from which they generate that revenue (so it will keep coming)?
yes well i can give you the record profits of those three companies over the last year as well as their projected orders, so you'd see that they are in fact making money hand over fist - you can attribute some of that money to the investments into OpenAI and Anthropic and the forward purchasing of compute but that's only a proportion of the current revenue, profit and order book, and OpenAI and Anthorpic both have significant revenue, c$25 and $30bn so far this year
That is a logical explanation. I wish this logic could have been applied to green energy tech but for some reason the administration is actively harming that sector. It could have been part of the AI data center energy sector.
Fibre stays operable for decades with relatively little monetary investment required for maintenance. Most of the fibre laid down during the dot com bubble is still in use today. GPUs they've got in a data centre now will need replacement by 2030 if not earlier, if there is not enough demand to fund that replacement the datacentre becomes useless.
It is, but there are two counter points to consider:
Fiber has an operational lifespan of 30 odd years so was still as valuable in 2004 as it was when it was laid in 2000. Cutting edge gpus will no longer be cutting edge in two years time so you have to factor in significant depreciation on this infrastructure. Not saying it won't still have value, but I doubt that we'll be creating the 2035 ai revolution on 2025 hardware.
The people who made money on that fiber were in many (dare I say most) cases not the people who fronted the cost but more the people who were at the firesale. This won't phase Microsoft, Google or Amazon who have more cash than they know what to do with, but OpenAI and Anthropic need to take note.
Giving GPUs a 2 year lifespan is a little hyperbolic. They're not useful as long as fiber no doubt, but cloud companies traditionally continue to offer lower performance options on older hardware. Most of these GPUs will get at least 5 years of use.
Hell, Meta recently developed a method to use DDR4 memory in modern servers to get around the memory shortage.
Not to mention a huge portion of their investment is in tangables with significantly longer usable life. Like the land, rezoning, buildings, utilities, mechanical equipment, etc.
People you thought were tech literate have become luddites. People who didn’t know what a data center was a year ago and had never attended a zoning hearing, are descending on zoning hearings in a rage.
And people who you thought understood the concept of a loss leader are calling TOD on AI as a whole, because it’s not profitable while it’s still in its absolute infancy.
Or people who understand the mechanics behind the laughably inefficient Transformer architecture realize that all the chucklefucks hyping up the word prediction machine (yes, that is what they are. Cope about it.) are falling for the biggest rug pull in history?
LLMs are a dead end tool and scaling is showing diminishing returns already (Fable and Opus 5, but Fable cost 3x as much as a 10 trillion parameter model and is marginally better). So the next model needs another 5 billion in addition to the cost of the previous model? Like come the fuck on, anyone with a brain who hasn't succumbed to AI psychosis can see how goofy this shit is.
"Maybe we shouldn't be shaping our economy around something with no proven way to generate profit while stacking up insane amounts of debt in a giant circlejerk"
Here I am with nearly every new Open Source model on my desktop, a CS degree with ML concentration under my belt, and yet because I don't worship the creepy fuckers in Silicon Valley who want us all to eat dirt, I am also a luddite to these people.
The issues is that it’s taken on so much debt that there is no way to pay back investors unless it does something like major workforce replacement. Which isn’t going to happen with current AI. In addition we’ve already hit diminishing returns.
What was said is technically true but the framing is ridiculous. Investor funded profits is literally the name of the game. Some of these current and future AI companies will eventually be hugely profitable and many will lose 100% of their investors’ money. No, the bubble isn’t going popping tomorrow, not next week, not when clueless “economists” still write about it being a bubble. I’d be worried when the bubble talk stopped or die down.
Profits implies these AI entities are profitable. We know they are wildly unprofitable. Insiders are very profitable with massive compensation packages paid for with mountains of bad debt though.
Why do people bring this up as if this hasn’t always been the case with the 21st century generation of major startup companies?
What the article states also describes Uber, DoorDash, Lyft, and a bunch of other ultra successful companies.
Investors have plentifully long leash with these companies and will continue to cover their deficits because they think the upside will be extremely huge.
Also, as a side note, for Anthropic specifically, it is operationally profitable. If they wanted to cease all investments and taking in investor money and just try to coast on current revenues, they’d be able to do so profitably. But a company like Anthropic has much larger ambitions than their current state.
If even the medium case projections are correct, we’re looking at many ultra valuable companies.
What exactly is the hopium here? I’m just explaining why investors are glad to pour money into AI companies and using past cases as to why it might work.
Investors are happy to pour money into a technology that is hyped to hell and back simply because they do not understand the machine learning concepts and flaws ($$$) that define the architecture.
Uber is a SaaS app with a map. An LLM requires a large amount of VRAM to store the model, then a large amount of VRAM to store the user's context. The cost isn't consistent and is a logistical nightmare.
Anthropic is literally operationally profitable. If it stopped investing the hoards of cash it does to expand its infrastructure and further develop its models, it would literally be a profitable business.
Your talking points are so ill-informed it’s hilarious and frankly out of date.
Reminds me of all of the goobers confidently predicting and making video essays about how SpaceX would never make money with Starlink and hoe the economics of DoorDash and Uber made it so that they could never actually become profitable lmao
> because they do not understand the machine learning concepts and flaws
Yes, nobody investing into AI knows how anything works, everyone is dumb (except u/Olangotang, he knows better than everyone).
I don't know why you people try when it's immediately obvious you don't know what the fuck you are talking about. Plenty of people who understand the technology have called it out in this thread that you are all chucklefucking for the most unserious firms to exist.
I mean dude, you are repping fucking SpaceX, which everyone from the illiterate MAGA to the ivory tower liberal know is a scam.
All you are doing is wasting time on the Internet making yourself look stupid.
Also:
> An LLM requires a large amount of VRAM to store the model, then a large amount of VRAM to store the user's context. The cost isn't consistent and is a logistical nightmare.
This ain't a talking point, dummy. It is quite literally... No wait, not quite it IS... Oh hold on, I'm losing my train of thought like an AI booster in psychosis, give me a minute.
IT IS HOW THE MODELS WORK. The fact that you clowns have to cope so much that you deny how the models function just proves how sad you boosters are to be cucked by Dario and Altman 😂 .
While your points are valid, the way I see it is that the scale here is the main issue. No one would mind AI as an enterprise if it didn't siphon money from left and right, and its success wasn't disproportionately tied to the future of the US (world?) economy.
“siphon money from left and right”… you mean from investors… seeking returns… as they have for all eternity?
And no, AI is not disproportionately tied to the future of the US and world economy. Without it, the world economy is fine. AI investments made up a disproportionate share of economic growth in 2025 and this year because the Trump administration is actively harming the US economy. If they weren’t, we’d have the best of both worlds working in tandem.
just to add, API pricing is wildly profitable. Their subscription tiers, on the other hand….
But they could just lower the limits and be profitable tomorrow. But for now, users would flock to other subsidized service, which sells them $1000 tokens for $100. But if they slowly lower the limits in tandem with one another (which will happen once investors start demanding profits), so you got nowhere else to go, subscriptions will be profitable too
> But they could just lower the limits and be profitable tomorrow.
Where do y'all come up with this? 😂
If they lowered the limits demand would drop like a rock. There is also no evidence API is profitable, that was a one-off hypothetical note from Dorkio a year ago. Each model costs more money and the cost rises exponentially. Also, they are still being heavily subsidized. There is no viable business model.
it is known fact that API pricing is much more expensive than subscription
Anthropic is now EBIDTA profitable - meaning they make enough money to cover compute costs and more with their revenue.
If they are barely-profitable overall and API hypothetically lose them money, where do they make their profit from?
The only possible answer is API
If they lowered the limits, demand would drop because people would move to other services which subsidize their subscriptions more. But once investor money dries up for everybody and nobody can afford to subsidize subscription, there is nowhere to go for users.
And there is no chance in hell that developers will stop using AI, neither does marketing and many other industries that are deep in AI work already, with many more joining every month.
They don't make any profit. Are you seriously going to use the same dug and buried up 700x talking point of "lol Anthropic is profitable because the other creepy fucker gave them compute in a quarter so we can ignore the CAPEX"? Oh yeah, multiply it by 12 to get the non-gaap cope run rate. Give me a break. You bring a lot of finance bro terms but no ML bro terms.
> And there is no chance in hell that developers will stop using AI, neither does marketing and many other industries that are deep in AI work already, with many more joining every month.
So do you not read the news like at all? Half of the companies using AI don't know why the fuck they are using AI. It does make a lot of sense that crypto-nft-AI bros live under a rock, far from society I guess.
Man it's crazy, y'all know literally fuck all about this stuff, but will repeat numbers you don't understand over and over and over again.
who hurt you?
I may be biased, but I don’t know single developer that isn’t relying on AI anymore.
Sure, there are a lot of AI projects that fail (especially amongst the early ones, where almost all of them failed), but AI is quickly becoming normal tool for more and more office workers every day. This year, it is already exploding in scale, some sectors faster than others. You can see AI everywhere. And it’s not going away, even if the price doubled.
And I am not going into debate, who can insult other party more
I literally don't care. I don't know how you people don't have the self awareness to realize that you don't convince ANYONE because you all use the same talking points for years in a row. It gets boring. It gets stale. It's fucking weird and disturbing. It's like, why try if you aren't getting paid for this!?
I'm not even going to go into the fires AI is causing behind the scenes at the companies that are deepthroating LLMs. Why would I? The audience is already on my side, it's a waste of time.
I just hope that one day, when you realize your mistakes, I hope that it will make you more humble and more willing to discuss, instead of trying to insult others who don’t agree with you.
Some people take it badly and become even more hostile and unwelcoming of any other opinion or facts that don’t agree with them - I hope that won’t be your case.
Have a good day, mate! Hope to have the same discussion with you in a year!
Well yea, that’s how new business works. You don’t have positive cash flow on your enormous capital expenses for a while. It’s a bet on future cash flows.
A lot of the speculation on AI is based on recursive self improvement
(RSI) happening to a meaningful degree.
If your not taking that into account then you'll have no hope of understanding investors.
If we get RSI it's the most powerful and impactful technology ever and valuations are actually far too low. If we don't then it's still very useful tech but over valued, potentially severely.
Yeah yeah yeah. We're been hearing the AI bubble narrative for years now, but it's still ongoing, and AI development and user base keeps increasing. Keep dreaming.
i feel like these articles talking about the doom of AI are just clickbait and ignoring reality. consider that gemini alone already has over a billion monthly active users and 350M paid
subscribers. add to this over 8M enterprise accounts and you have
substantial usage (despite what people say about AI only being slop).
taking that 350M alone - ignoring the active 650M users who aren't
currently paying (but it is fair to think many will convert) and the 8M
enterprise users - the pro plan is $20/month. 350M x $20 x 12 (to
annualize) is nearly
a hundred billion. this number
could easily double as non-paying users convert and i'm sure the
enterprise accounts can give similar sizable gains.
it isn't a stretch to say gemini will soon account for a quarter of a trillion dollars in revenue per year based on today's activity alone (AI will only continue to get better and more integrated). i don't know how this "AI math doesn't make sense" - it is obvious this will be a major product going forward and a cash cow for the hyperscalers.
It is absolutely not fair to assume "many will convert" when the average "users" are just googling for local restaurants and getting an AI summary about it for some reason. If anything, we should expect the users to go down as the real prices get pushed onto them instead of the heavily subsidized ones.
The math doesn't make sense because you just made a bunch of things up in order to get to the end goal of "AI is profitable somehow, actually."
"People were wrong this one time, so they must be wrong this time" isn't really an argument, but alright.
Cloud computing's invention did not require the industry jerking itself off into a debt spiral for several years before seeing a pathway to profitability.
Software as a Service is not new to us anymore. "AI" is just a shitty software as a service that's propping up our economy while we go through collective mania.
The math doesn't make sense because if you understand fuck all about Transformers, you would realize that making bigger and bigger LLMs is lighting money on fire for little gain in the long run.
retiredcheapskate | 8 hours ago
The Chinese models are also creating a bit of a vice for the tier one ai labs. The middle and low end customers that aer price sensitive are gone. The price difference is so huge people have to look at the open source models. The top models are reserved for 10% of the tasks that the Chinese can't do. You can make that a business.
True_Joke_5248 | 8 hours ago
What tasks can't the Chinese models do tho
The_Blip | 7 hours ago
US defence and security contracting is the one I know.
dcuhoo | 4 hours ago
Judging by use of AI the Iran war, the US models can't do many of the tasks very well either.
elbow8075 | 4 hours ago
Shots fired!
azkxv | 3 hours ago
Direct hit on the elementary girls school!
ensui67 | 2 hours ago
Seemed very good. Much less stress on the troops for target acquisition. It’s also only going to get better. Problem is that for now, there’s only so much we can do from the air. We’ve already blown everything up that we can see from the air and satellites. We also are not trying to escalate anymore. We were pretty successful in killing all their leadership, but that in of itself isn’t really a great goal cause they got plenty of people to run things.
It will only be a matter of time before we have ai drone swarms and have some ender’s game level attack patterns. What a time to be alive.
dcuhoo | 2 hours ago
They blew up a school full of children.
ensui67 | 2 hours ago
Mistakes happen in war. Important thing is they tend to learn from their mistakes and it will be improved over time.
FlyingBishop | an hour ago
Hegseth and Trump are making the same mistakes over and over.
ensui67 | an hour ago
That’s strategic mistakes because there were no well defined goals. The military industrial complex is doing incredibly well and am achieving great military moves. Unfortunately you need more than military might to achieve things in this world.
FlyingBishop | an hour ago
Ukraine just trounced US tanks with drones in a war game. The US is manufacturing a lot of weapons but it's not clear they know how to make useful military moves anymore.
ThePensiveE | 6 hours ago
Don't worry we'll let the Russians do that for us.
Available-Street4106 | 5 hours ago
You mean Israel?
ThePensiveE | 5 hours ago
Well whoever pays the first family most on any given week really.
clervis | 5 hours ago
Because they're not allowed to be used in those spaces.
The_Blip | 5 hours ago
I'm hoping the people on this sub didn't need that spelled out for them.
clervis | 4 hours ago
I wasn't sure if you were talking about the ban or their actual performance, which is also a valid argument depending on the use case.
the_pwnererXx | 6 hours ago
if you want to do agentic coding, you don't want to sacrifice performance. they are still not on par with codex/claude for coding. partially from the harness, and partially because these companies are heavily targeting coding ability
for general use and maybe if you aren't employed, its good enough. if you work at a company and they pay you 6 figures, I don't see why anyone would use subpar models to save such a tiny % of what they spend on you. like codex/claud max20x is $200/mo and SWEs pull $10~30k/mo in salary
Great_Northern_Beans | 4 hours ago
Eh, yes and no. People who are using Claude Fable or whatever to perform every little tiny task are just wasting resources. Ideally you'd use the big guns as an orchestrator to draw up a roadmap of dozens/hundreds/thousands of small discrete tasks, and then you can slot in a collection of whatever tiny models to code those out. Then maybe at the end you break out fable again to give it a pass over and make sure everything came together as expected.
Lots of harnesses support a workflow like this now, which doesn't move you entirely off of the top of the line models, but certainly eats massively into the profit ceiling for these companies.
wubwubwubwubbins | 3 hours ago
100%, and as investment money pulls back you will see more of this. The problem is that in edge cases, automatic discernment of what automation tools will be effective for a given task can be...opaque. So you have to consider "is this worth the time and money to train staff over the course of months to figure out what tools are effective for what?" when the average US employee costs anywhere from $35-$75 an hour for a given business.
So when it's a couple hundred dollars difference a month, sticking with 1 tool isn't a huge issue. It's when your compute costs go into the millions/hundreds of millions that you'll be forced to diversify.
But it will be different for each and every business.
Willing_Activity_855 | 3 hours ago
> Ideally you'd use the big guns as an orchestrator to draw up a roadmap of dozens/hundreds/thousands of small discrete tasks, and then you can slot in a collection of whatever tiny models to code those out.
GSD-core
maybe use fable to research or orchestrate but op can do that just fine, sonnet can write the code.
Fable actually i'd use to find the brownfield requirements. That's actually a perfect use case for it, map out the existing repo/codebase, document existing requirements, if dealing with an enterprise app (crm,erp,etc) it can scan through say salesforce docs and your codebase to find existing limits/requirements.
FlyingBishop | an hour ago
> People who are using Claude Fable or whatever to perform every little tiny task are just wasting resources.
If you make $50/hour Claude Fable can legitimately let you double your productivity for "every little task." You can certainly overuse it but the math works out if you're a company paying software engineers $50/hour (really $250/hour.)
6158675309 | 4 hours ago
>if you work at a company and they pay you 6 figures, I don't see why anyone would use subpar models to save such a tiny % of what they spend on you. like codex/claud max20x is $200/mo and SWEs pull $10~30k/mo in salary
A few things;
Pricing has changed and that fixed $200/mo no longer exists. Enterprise pricing is now per seat plus per tokens consumed. I dont think anyone offers any included tokens anymore.
The open weight models have all but closed the gap. Prop frontier models - Anthropic, OpenAI, Google, CoPilot?? may perform better at the edges but not many people actually need that. There are other considerations with open weight models but price/performace is strongly in their favor.
I work closely with these models and I have not yet seen anyone really migrate away from the proprietary frontier models yet. But, there is real interest in the open weight models. It's still a risky venture though, not because the models dont perform but geopolitics and ecosystem. It is much easier to get started with Anthropic, OpenAI, Google then any of the open weight options.
Corporate America won't take on that risk yet. Eventually if that risk goes down or goes away and the models comptete on the economics of it the closed models arent able to compete with the open models.
austinwiltshire | 4 hours ago
And this is what the vibe coders said six months ago and six months before that, with models that would now under perform the Chinese models.
And in six months, when China catches up to the current American frontier, someone will make the same argument that it's somehow worth it, but that someone is going to be part of an increasingly shrinking pool.
G1uc0s3 | 6 hours ago
Agreed on all the model feedback, but it seems like the 200 only gets me a ticket to the dance. I burn tokens on a meter, which admittedly isnt significant…but we have to know that price is going to go through the roof soon
BH_Gobuchul | 2 hours ago
$200 per month is pretty low if you’re using Claude for everything. That’s pretty close to my spend and I only use it a couple times per day and I never go out of my way to use loops or multiple agents or anything.
DarkSkyKnight | 5 hours ago
They’re still terrible at math.
Dedelelelo | 2 hours ago
lol no way sol 5.6 pro is cracked
DarkSkyKnight | 2 hours ago
Since when is Sol a Chinese model
Dedelelelo | 2 hours ago
oh wtf my bad i read another comment and somehow thought it was same thread i agree w u. i think the models being ‘commodities’ is over played by non technical ppl. openai cornered math and stem and anthropic enterprise software development
polar_nopposite | 3 hours ago
I'm a software engineer working for a large tech company. I've used cheap/free chinese models in personal projects because I'm a cheapskate, and frontier Claude and GPT models at work. My company is choosing to pay 1000x the cost for me to be able to use the latter over models that are 90%+ as good, and correctly so in my opinion. The extra 5-10% matters a lot.
FlyingBishop | an hour ago
"90% as good" is very misleading, since that 10% often means it takes 20x as long and produces no useful results, or even worse, results that look correct but are in fact wrong.
polar_nopposite | 43 minutes ago
I don't think you read what I wrote. You're essentially saying the same thing I did.
circuitloss | an hour ago
[ Removed by Reddit ]
loaferuk123 | 7 hours ago
Absolutely. Xi is making Chinese models open source because he knows it will crash the economic growth in the US.
nullmove | 6 hours ago
They have their own AI aspirations and ideals. The framing that everything they do revolves around undermining US is narcissistic as fuck.
Dirty_Rapscallion | an hour ago
I'm so tired of my fellow Americans thinking China is just Xi and some cronies in a room.
Mundane-Light6394 | 7 hours ago
No, that would hurt China a lot and probably trigger uprising against the ruling party and Xi will loose all his power.
China is boosting an open ecosystem because they want to participate in the AI boom. In an ecosystem controlled by US corporations they will be blocked from participating by the US government.
saynay | 5 hours ago
I think a lot of it is courting the AI researchers. Publishing papers, having open weights and accessible models all make your labs more enticing. If you are trying to hire the best in the world, and you can't compete with the tier-one US labs and their stupidly high salaries, you have to find something else to attract talent.
Illustrious-Lime-878 | 6 hours ago
Why does Xi get credit for anything? I think XI kind of thought AI was a fad, Ironically the Chinese gov not caring that much probably helped their AI industry be more innovative and open.
oursland | an hour ago
AI is a major component of the 15th 5-year plan that was approved a few months ago.
Illustrious-Lime-878 | 26 minutes ago
Yes, a few months ago, the Chinese gov is coming around to it now. Funny thing is if they start to try to lock it down like the US it may give other regions to become the open source hub instead.
oursland | 14 minutes ago
The AI industry in China is more regulated than in the US. They're still strong advocates for open source and mass adoption.
kappi2001 | 3 hours ago
It's not even just China that will benefit from these models.. There are plenty of larger businesses in the US that will benefit from commoditized AI offerings that these open AI models will bring.
circuitloss | an hour ago
Maybe they're making the models open source because historically open platforms have done better than closed, walled gardens... (See IBM PC clones vs. Apple, or Android vs. iOS)
Sryzon | 8 hours ago
The ai labs represent a very small portion of economic activity, though. I believe most of the companies investing in datacenters are model agnostic now.
Edit: Not to mention the sell for a lot of these AI labs isn't the model, but all the external tool integrations that have been developed to enable AI to do things an LLM can't do alone like precise math.
Olangotang | 7 hours ago
They may be model agnostic but the demand is literally just OpenAI and Anthropic. If OpenAI fails, the whole thing blows up.
flappysack- | 3 hours ago
When it fails*
kappi2001 | 3 hours ago
There will be a financial shock, but long term these models are here to stay. Data Warehousing demand probably won't be as big as the values of these companies currently predict though, new models are getting more efficient and powerful all the time.
FlyingBishop | an hour ago
Even the frontier models still struggle with spatial reasoning. The new models are getting more efficient but I think the frontier will continue to get bigger until they figure out spatial reasoning properly, which could be a while.
Also if 30B parameter models get to be Fable-level I think you'll start seeing the equivalent in the cloud with the extra RAM dedicated to more and more context. 30M-50M tokens of context would be game-changing. Although I kind of suspect you need a trillions-of-parameters model to usefully use that much context.
kappi2001 | an hour ago
oh for sure.. but at some point the infinite money dries up and subscriptions won't be subsidized anymore. Businesses will be looking to keep their LLM API costs low by using the correctly sized model for each task.
FlyingBishop | an hour ago
People want to keep costs down, to be sure, but software engineers cost $10k-$30k a month and quibbling about spending $100/day in tokens is being pennywise and pound-foolish if you're actually developing software that you sell.
circuitloss | an hour ago
Google and Meta certainly aren't "model agnostic," and neither is any other tech company with their own model. To use another one is to admit defeat (which Apple has basically done). Do you think Elon is suddenly going to delete Grok and say, "Nah, we're using ChatGPT now?"
Sryzon | 58 minutes ago
Microsoft's entire schtick is Copilot being a multi-model system that uses whatever model is appropriate for a particular task.
xAI already started leasing their excess compute to Google and Anthropic.
The majority of AWS's and Google's revenue and future compute commitments is for leasing compute.
Meta isn't even trying to sell their model. Their strategy is to improve advertising on their platforms using AI.
Apple never earnestly tried in the first place.
Dreadsin | 5 hours ago
To add to this, Chinese models may not be the best but they do almost everything for a fraction of the price. Good enough is all you need sometimes
Osiris_Raphious | 2 hours ago
The rich get richer, and poor pay the price... hmm china and US be doing the same thing, and not with just AI, but with capital wealth, housing etc.
Dedelelelo | 2 hours ago
i promise u no one outside of reddit uses chinese models lol
Soft_Walrus_3605 | 2 hours ago
You promise, do you?
https://openrouter.ai/rankings#leaderboard-table
Dedelelelo | 2 hours ago
bro no one cares about consumer. there’s not a single entreprise that will ever use deepseek internally
hu6Bi5To | 7 hours ago
It's highly likely that at least one of the main AI labs will blow up at some point, maybe both OpenAI and Anthropic will, or at least there'll be some sort of crisis followed by unfavourable forced restructuring.
But...
...that in itself isn't unusual, that's what happens in the "gold rush" stage of pretty much every technological breakthrough. A loss-making land grab is common, and has been for 200 years or more. Canal Mania in England in the 1700s had much the same process.
This headline seems to be implying this state-of-affairs is somehow unique.
Olangotang | 6 hours ago
It is unique because LLMs are uniquely expensive. For some reason, none of the AI boosters will acknowledge this fact. Every comparison to durr Uber or Durr Amazon is underscored by the fact that they don't cost ANYWHERE as much in compute.
Maybe_Human0_0 | 5 hours ago
As well as the huge compute costs, depreciation of hardware is also another factor that makes the whole gold rush or railway analogy really not really work in my view. It’s not like this stuff will be built out and last for 20 years, or 10 years, or 5.
supercargo | 4 hours ago
The data centers and supporting infrastructure (buildings, power, cooling, internet connectivity) will last. The GPU tenants could last more than three years, the idea of that they rapidly depreciate stems from expected further advancements which make them more economical to replace than keep, not that they will all fail at the three year mark.
If the bubble pops, those future advancements may slow and older silicon could be kept online longer.
The thing is, none of these dynamics are new to the industry. The people making these decisions understand all of these things deeply, which isn’t to say things can’t or won’t go sideways, that’s the nature of speculative investment.
HowdyDiarrhea | 2 hours ago
>The people making these decisions understand
Yes but that doesn't mean they have any level of regard for it. They persist in spite of it.
bmc2 | 2 hours ago
The datacenters themselves aren't the huge cost. The hardware they're buying to fill them with is. And that lasts 2-3 years.
TheRencingCoach | 3 hours ago
Compute costs problems apply to players purchasing compute (OpenAI, Anthropic)
Depreciation of hardware problems apply to players purchasing hardware (cloud hyperscalers)
For the most part, different companies in this space have different problems.
WallaceCorpPC | 6 hours ago
LLMs are getting cheaper to serve, and more expensive to train. OpenAI just released a flash mode on Cerebras that's serving 14x faster.
Freud-Network | 5 hours ago
And in a month DeepSeek will duplicate it with open source, making OpenAI's model worthless.
Dedelelelo | 2 hours ago
no f500 company is ever sending their data over to deepseek i would literally bet my entire life savings
rabouilethefirst | 4 hours ago
That’s like saying China duplicated the iPhone and now Apple is useless. Hundreds of millions will still choose Apple
Equivalent-Bus-4336 | 4 hours ago
But China has never duplicated anything close to an iPhone in quality
WallaceCorpPC | 5 hours ago
DeepSeek has done that multiple times, lagging the frontier models by ~3 months, but still OpenAI's revenue still grows massively YoY
InitiatePenguin | 5 hours ago
Via inventors, not customers.
WallaceCorpPC | 3 hours ago
I think you mean "investors" not inventors, but also incorrect these are growing revenues from customers, their S-1 SEC filing has confirmed this
madhewprague | 5 hours ago
No, these opensource models still suck so much compared to even 1 year old openai and anthropic models. They cant compare
FlyingBishop | an hour ago
Cerebras ChatGPT Sol isn't a flash model, it's the full model running on Cerebras, which means it is more expensive to serve because you're using an entire million-dollar Cerebras chip to serve a single request. (As opposed to the million-dollar servers usually used which are slower but can serve dozens of requests in parallel.)
aznzoo123 | 4 hours ago
That would be an interesting area of research is our investment in LLMs uniquely expensive vs railroads, canals, and other historical booms and busts
Freak-Of-Nurture- | 4 hours ago
there’s an article that compared them a few weeks back
Successful-Money4995 | 6 hours ago
Weren't all those very expensive at the time, too? What about the dotcom bubble?
MajesticComparison | 5 hours ago
It’s the magnitude of debt. Other companies were expensive but the debt to revenue ratio of AI companies is 100x worse
InitiatePenguin | 5 hours ago
>It is unique because LLMs are uniquely expensive.
But isn't the potential gold mine at the end for the one that suceeds first uniquely profitable? Following the same general rules the other use is discussing about gold rushes and leading with losses.
How does the cost disparity in the AI sector being magnitudes more than Uber and Amazon make a material distinction in this conversation?
Snapingbolts | 4 hours ago
They want it to replace workers and workers are cheaper, especially if the true costs to run these models is passed on to the businesses. Another issue is the accuracy of these models. Would you buy a calculator that was correct 90% of the time? How about if it cost $1000 a month to run it? LLMs are unlike other software in that it isn't right all of the time but it is priced at orders of magnitude more than other software.
pemb | 2 hours ago
Humans make mistakes all the time, but these fall along predictable patterns that have been studied for decades, and robust systems and processes are designed to guard against them.
AI and especially LLM mistakes display quite different patterns and that makes them seem especially egregious or baffling to us humans.
InitiatePenguin | 4 hours ago
>They want it to replace workers and workers are cheaper
Isn't the gold rush at the end when this is no longer the case?
Same for the other points.
>it isn't right all of the time but it is priced at orders of magnitude more than other software.
Because if those problems can be solved (they believe it can be, regardless) then it will be uniquely profitable in the same regard.
Again, it seems the point is not the magnitudes difference in debt, as the rewards are potentially in the same magnitudes, but rather in the viability.
To use the gold rush anomaly. It's not that there's uniquely more gold in the mine attracting a massive amount of debt/rush to get it ("uniquely expensive"). It's that it's improbable it's minable.
Which is identical to an actual gold rush scenario. its speculative.
Smooth-Ad8030 | 54 minutes ago
No, the gold mine at the end isn’t profitable. What they’re seeing is a 12 trillion dollar TAM of white collar work, the problem is if these companies succeed, that TAM collapse because the cost of work is now much lower
Edit: it isn’t uniquely profitable if you go beyond the simple calculations they’re making
SoggyMattress2 | 5 hours ago
It's absolutely unique. You're right, there's hundreds of examples of SAAS services and other industries making huge losses to grab market share then slowly hike up the price.
The main difference is cost of inference with LLMs. For Amazon or netflix the cost to serve goes down as you increase your market share and build up the infrastructure.
For cloud computing for netflix the more users you have, you actually save money by negotiating smaller contracts with the cloud provider.
As Amazon built more warehouses and acquired more drivers the cost to serve goes down because they can travel shorter distances, improving delivery times.
For AI labs there's a cost to train a model and every time the user uses tokens the AI lab has to pay (in a data centre they may or may not own).
So as market share increases you actually lose more money exponentially. And the current track is the "better" models get, the more expensive they get to serve.
And lastly the SCALE of losses are incomparable. At it's worst Amazon was operating at a 16bn defecit before they turned a profitable year.
AI lab investment currently sits between 1.25 trillion and 1.75 trillion depending on who you ask, for a total revenue return of just over 60 billion in 4 years since gpt1 was released.
It's basically a giant circular financing Ponzi scheme ATM.
FlyingBishop | an hour ago
> So as market share increases you actually lose more money exponentially.
only if you're selling tokens at a loss, and the evidence anyone is doing that is pretty thin. It looks a lot like the US labs are deliberately spinning the narrative you're talking about so people buy tons of tokens in the mistaken belief that they're getting a huge discount. When in fact the margins on frontier inference are insanely profitable, and it's like any other SAAS in that respect.
Smooth-Ad8030 | 52 minutes ago
Where is the hard evidence inference in profitable? OpenAI lost billions last year, we don’t have any data on anthropic so we can’t trust their public statements or leaks either
FlyingBishop | 45 minutes ago
There's no hard evidence either way. But the idea that businesses are going to "lose money exponentially" selling inference at a loss is pretty out-there. Seems much more likely they want customers to think like you do so they will spend money exponentially on a profitable product.
The $20/month and $200/month plans are oversold but that doesn't mean they're subsidized - it just means if people used them 100% they would lose money, but they have good control over that situation and don't let people use them 100%.
Smooth-Ad8030 | 39 minutes ago
I never said that’s the case that, but selling inference at a loss isn’t out there. We have proof of these companies doing this. It’s the tech playbook, sell at a loss, gain market share, increase prices with market dominance. We don’t know what’s going on exactly, but it’s equally likely they’re selling some portion of inference at a loss as it is they’re making money. And those costs bare minimum increase linearly.
wiseduckling | 3 hours ago
Anthropic and OpenAi would get bailed out by the US gov or taken over before they went bust. AI is too arms racy.
NotMeekNotAggressive | 3 hours ago
That's almost 2 trillion dollars. The problem a lot people don't grasp with AI is the sheer scale of the cost. At it's worst, even a giant corporation like Amazon was operating at a $16 billion deficit before they turned a profitable year.
Dedelelelo | 2 hours ago
2 trillion dollar is low i feel like they should be valued much higher. if you do frontier work in stem the tech genuinely feels surreal u cant compare it to anything else
egotistical-dso | an hour ago
Yes and no. Yes, it's correct that lots of businesses in the "gold rush" stage have poor business models that struggle when the euphoria wears off. What's unique in this situation is that the leaders in this industry are the ones losing money. The application layer, the layer facing the end-users, is the layer seeing losses, and that's across the board. I'm not familiar with the economics of the Chinese models, but none of the US AI businesses that are actually building the models themselves are anywhere near profitable. That raises serious questions as to the viability of this entire business.
I'm not a staunch AI skeptic, it will stick around in some form, but what form and how much of the current investment gets completely wiped out is an open question.
hu6Bi5To | 57 minutes ago
> What's unique in this situation is that the leaders in this industry are the ones losing money.
That's not unique at all.
Amazon didn't make a profit for it's first nine years. (To pick just one example).
Losing money until businesses reach a break-even point is standard in these situations. The risks being: how long will it take to get there, and what could change in the meantime to prevent them getting there.
AtomWorker | 5 hours ago
I don’t think people here appreciate how widely used these LMMs have become. I’ve seen first hand the dramatic shift at work but I also know people who have never been tech savvy embracing AI.
I have very mixed feelings about this tech and I’ll be the first to admit that it’s been massively disruptive on so many levels but AI is here to stay. We’re a long way off from knowing who the winners and losers will be.
pork_fried_christ | 5 hours ago
But the costs are still highly subsidized. If the full price was being borne by the users, usage may look a lot different.
FlyingBishop | an hour ago
There's not a lot of evidence it's highly subsidized. I think the initial releases might be roughly at cost, but they quickly optimize and margins are likely more like 90% for most of it.
ishboo3002 | 5 hours ago
On the personal side yes, but typically on the enterprise side you're being changed api rates for usage maybe at a slight discount based on scale.
pork_fried_christ | 4 hours ago
I actually use Claude a ton, everyday. But my company is lowering usage limits as it adds more users to the pool. And as the models get more capable and the datasets get bigger, I’m hitting my limits faster. And I do believe they will either limit the number of users at some point (which will be difficult as it gets more entrenched in different tasks), or they will limit the amount of data we can have it analyze which will reduce how useful it is.
Not to mention, it’s really dumb sometimes…
ishboo3002 | 4 hours ago
Sure not saying that companies aren't going to cost cut, we do the same with limits. Just pointing out that at the enterprise tier we're not paying subsided prices.
VariousAir | 4 hours ago
> I have very mixed feelings about this tech
Is this reddit code for 'I use it all the time because I understand what it can do and what it's limitations are, but dont like telling people that, and I acknowledge that it's overuse has a real effect on everything from the environment to the economy', cause if so I also have mixed feelings about it.
the_pwnererXx | 6 hours ago
Anthropic and openai revenue have both exploded this year - see chart
https://www.wsj.com/tech/ai/mind-blowing-growth-is-about-to-propel-anthropic-into-its-first-profitable-quarter-7edbf2f4?eafs_enabled=false
And the numbers say they are selling inference at anywhere from a 50~100% markup
I know you guys hate ai and want it to fail, so I expect to be downvoted for sharing these economic facts
dmadSTL | 6 hours ago
There have been reports of creative accounting, all the circular dealing between the major tech firms, the labs, and Nvidia. Neither of this firms are filling out 10-k's yet. They are self reporting these figures. Also, ARR as a measure is easily manipulated. Sooooo this could literally all be smoke and mirrors to project health and strength to the market, creditors, and competitors.
HouseofMarg | 6 hours ago
The problem is that the revenue only looks high if you don’t factor in all of the capex; they are projected to spend $100 billion in infrastructure alone in 2026 and I doubt they make over their total costs for that and everything else this year.
Anthropic’s quarterly numbers look better than Open AIs (which are so bad they postponed their IPO when those got leaked) but it’s because they got a favourable compute deal from Musk because so few people are using Grok that he needed to offload it https://www.fastcompany.com/91537990/groks-usage-is-so-low-they-can-sell-compute-to-anthropic
Everyday_ImSchefflen | 6 hours ago
Extremely common for tech companies to be unprofitable in early stages. Literally happens to every tech company
MajesticComparison | 5 hours ago
It’s the debt. No other startup was this deep in the hole then succeeded. The only way to pay pack investors and the reason why AI gets so much money is because it’s meant to replace workers on a large scale. If it cannot massively reduce worker numbers, then AI companies will never be able to pay the debt.
InitiatePenguin | 5 hours ago
>It’s the debt. No other startup was this deep in the hole then succeeded.
I'm agreeing with you. And when debt becomes due will be a major moment. But it's obvious that no other startup was facing this deep of a profit if they are ultimately successful.
So sure, debt is unprecedented, but so is the potential profit. The only question is if it materializes.
There's a massive risk, but the risk isn't how deep the hole is. It's if they are the ones to have the breakthrough.
HouseofMarg | 5 hours ago
We’re over ten years in now (Open AI was founded in 2015) and 8 years from when Open AI released its first language model. The scale of their spend is very not normal and the VCs are getting impatient. I don’t believe they have all that much runway left, of course everything rests on the IPO being successful (and not postponed again). I wouldn’t venture to measure how much in months to actual sustainable profitability but people can’t talk about what it’s going to do in 2030 as if that will be soon enough
Everyday_ImSchefflen | 5 hours ago
That's really not an accurate way to look at it since the spending didn't blow up until about 3 years ago.
If you are using founding date, Amazon was founded in 94 and wasn't profitable until 20 years later.
HouseofMarg | 4 hours ago
Amazon finally turned profitable because of AWS, it had to pivot from its original business model. It’s now improved its profitability elsewhere because of jacking up seller fees (which may have a detrimental effect on use the platform) but still in 2024 AWS made up 58% of Amazon’s operating profit https://finance.yahoo.com/news/mystery-inside-amazon-record-profits-010823949.html?guccounter=1
the_pwnererXx | 6 hours ago
The numbers I see both point to anthropic and openai having a successful ipo and having fairly decent earning for the forseeable future. we also have not seen any scaling wall being hit, which has been pessimisticly predicted on reddit for the past 3 years. the explosion in revenue this year really reflects how powerful coding agents got in latest generation. if progress continues, users/revenue will only go up. we are only a couple doublings from these agents being smarter than pretty much everybody and capable of doing virtually any intellectual task
HouseofMarg | 5 hours ago
Your first comment seems serious but this reads very booster-y. You’re welcome to this opinion of course
Xoron101 | 6 hours ago
> Anthropic and openai revenue have both exploded this year - see chart
But where is the revenue coming from? If it's the Microsofts and other tech giants, that stream could dry up if the can't pass those costs along to their clients.
IE if MS is spending say 50B a year on OpenAI, but only can realize 25B from their customers, then they'll start to pull back on their AI spending.
I'm not saying this is going to happen, but if there isn't money to be made by the Microsofts of the world, their investment in AI will decline. The current rates are unsustainable, and we should be prepared for an AI spending pullback at some point.
the_pwnererXx | 6 hours ago
openai pays microsoft 20% of revenue
half of openais revenue is consumer subscription, the other half is from businesses
anthropic is 20% consumer, 80% from api/enterprise with 300000 business customers
Honestly, no idea why you think your opinion is worth a cent when you have no idea what the facts are and just make stuff up to fit your bia
Xoron101 | 6 hours ago
> 80% from api/enterprise with 300000 business customers
So 80% of their revenue is from customers like Microsoft? I think my position stands that if MS can't get value from their AI spending, then it might pull back.
I've been through the dot.com boom and bust. This feels very much like that. AI will 100% be a game changer going forward, just like the dot.com was in 1999. But I think there will be some blood in the water before it all balances out.
the_pwnererXx | 6 hours ago
80% spread across 300000 businesses, not one big company. companies are getting value, hence why they are paying for tokens. agentic coding agents are just better than humans 99% of the time now, and it was not true last year. if you are writing software, you want every dev in the company to have a claude subscription or unlimited token access.
Xoron101 | 5 hours ago
I think we both agree that AI is a game changer. The difference is that I think the meteoric rise in (stock) valuations, and revenue isn't sustainable. And we'll see a pull back in the AI space.
My own small org is trying to find ways to cut down on token spending. It's getting too expensive.
EDIT: "This time it's different" - No it isn't
SoggyMattress2 | 5 hours ago
ARR is almost meaningless. Nobody knows the markup.
What we do know is 1.25 trillion has been spent or invested with these AI labs for around 100bn in revenue.
You can spin that however you like but operating at a scale of loss we've literally never seen before is not going to continue.
Open ai and anthropic are the two worst companies in human history for cost to serve to profit ratios.
biblioprof | 6 hours ago
Go live next to a data center then get back to us
the_pwnererXx | 6 hours ago
I live in a first world country with zoning laws
bk7f2 | 5 hours ago
This is not about hating LLM or other reasoning technologies, they are transformative indeed. The point is that the current business model will fail. AI services will generally not be expensive, this is just the current stage is expensive. It propelled purely by FOMO.
Dedelelelo | 2 hours ago
they’re not normal businesses there’s a national security aspect to it also
VEMODMASKINEN | 5 hours ago
That article you link to was mostly BS and you'd known that if you did any sort of research instead of just trusting the headline.
https://www.wheresyoured.at/anthropics-profitability-swindle/
> Oh there’s also one important note: The Journal adds at the bottom of the article that “...it is unclear what accounting methods Anthropic has used to book revenue and costs, as the company isn’t yet required to follow the financial-reporting requirements of a public company.” That’s right —-- Anthropic is possibly going to be EBITDA profitable for a single quarter, on a non-GAAP basis.
> That’s also interesting. So Anthropic may be profitable very specifically in Q2 2026, but might not be afterward. It’s almost as if it found a way to specifically cut its costs in May and June somehow…
> …because it did! Remember that deal Anthropic signed with SpaceX to take over Colossus-1? Well it’s also taking over some or all of Colossus-2, paying SpaceX $1.25 billion a month starting in May and June… when it’ll have a reduced fee as it ramps up!
> That’s $15 billion a year in compute costs, but reduced to an indeterminately-discounted level for the precise months that Anthropic is using to tell investors and the media that it has an operating profit. That operating profit is a result of accountancy rather than any improvements to its business model.
> While I wouldn’t say this is cooking the books, it’s definitely a shiatsu-grade massaging of the numbers. Anthropic has deliberately leaked a quarterly “profit” where it knows it can suppress its costs, specifically made sure that the journalist gave it the out of “costs might increase,” and released it on the day of NVIDIA’s earnings as a means of keeping the AI bubble inflated.
the_pwnererXx | 5 hours ago
nobody is reading your zitron slop
since your article was posted, revenue increased another 50%
VEMODMASKINEN | 5 hours ago
Cope. Sure it did.
I can link some AI slop instead, maybe that's easier to digest for you AI bros.
copperblood | 8 hours ago
Correct, and taking it one step further. Any revenue is used to pay off early investors. It’s a textbook Ponzi scheme. Just like private equity - largely what’s going on in private equity right now is a Ponzi scheme and assets that private equity has acquired are worth less today than when they were acquired, meaning private equity can’t unload them. Any sort of revenue private equity is getting is used to pay off early investors at the cost of recent investors.
Everyone needs to buckle up for a crash unfortunately
watusiwatusi | 7 hours ago
But what’s the hedge when data centers are the entire market now
thekbob | 5 hours ago
Island bunkers and PMCs.
Keeltoodeep | 7 hours ago
The only ai lab that has a sustainable business model is Google.
Bodine12 | 6 hours ago
But their AI business model is fueled by setting fire to their search business model.
Keeltoodeep | 6 hours ago
AI search has increased their search ad revenue, not decreased it. That narrative has proven to be incorrect which is why their stock is up 100% over the past 12 months. Your opinion is about 2 years outdated now.
Bodine12 | 6 hours ago
That's temporary. Ad-buying companies are incensed with it and are already pulling back their ad buys. But it takes awhile to redeploy those ad dollars somewhere else.
Google isn't worth it anymore for them That's a killer.
https://www.businesswire.com/news/home/20260518322756/en/New-Research-Googles-AI-Overviews-Now-Cost-Websites-58-of-Their-Clicks
I_Am_AI_Bot | 5 hours ago
This is a well expected outcome. I just dont understand why their ad customers couldn't realise it earlier right after the overview function launched.
Keeltoodeep | 5 hours ago
The people complaining are not their ad customers. The people complaining are like cooking bloggers that run their own ad infested cooking blogs that have seen a dropoff in visitors because ai overview gives you a cookie recipe
jellyhessman | 4 hours ago
And the companies paying Google large sums of money so those ads are there are pissed they aren't getting the impressions they paid for.
Keeltoodeep | 3 hours ago
That's not correct at all lol they are spending more.
https://www.marketingdive.com/news/googles-ads-biz-gets-boost-from-world-cup-hype-gemini-improvements/826008/
Google's business partners are spending more because their ad impressions are better not worse.
https://www.adgully.com/post/18360/google-ad-revenue-surges-as-search-grows-17-and-youtube-climbs-13-on-ai-momentum
The only people complaining are the ones who have their own websites like blogs with ads that relied on blue links to funnel users into their own ad ecosystem. Those people were not Google ad customers to begin with though.
Hegemonikon138 | 7 hours ago
Do they? They are lighting cash on fire just like the rest of them and are now negative cash flow.
The only thing that might be sustainable about it is they can subsidize a chunk of it from the profitable side of the business.
Sustainable business model means profitable.
Keeltoodeep | 7 hours ago
Negative cash flow doesn’t mean the model is not sustainable lol their GCP backlog is $500B. They have to build the data centers to service cloud contacts already signed. It is a perfectly acceptable business model to go negative cash flow of $200B in order to service a revenue backlog of $500B, obviously.
Google was wildly profitable last Q even with negative cash flow and excluding investment gains.
Olangotang | 7 hours ago
Ok, but every FAANG company hides their AI spend within a different category like "cloud", which is their most profitable segment already. You don't actually know how much they are losing.
Keeltoodeep | 7 hours ago
Google (and Apple soon) will say they don’t really care. You could claim they also “hide” their spend on email and maps and how those are unprofitable business segments. Google has a business model where their unprofitable software offerings like maps, email and AI are part of an ecosystem of software services underpinned by ad revenue and enterprise cloud solutions.
This is the same argument people made about email being an unsustainable business model.
Olangotang | 6 hours ago
Email is like what, a few fucking kilobytes? And there's a limit to how large one can be.
LLMs are not like that. A user with a fresh prompt uses all of the VRAM the model uses + some for their starting context window. Someone who pasted a crap ton of code is using far MORE VRAM for the context window, and is costing much more. You can not fight against the near exponential scaling costs of training the model, nor the quadratic (SLOW) attention mechanism of inferencing. LLMs light money on fire.
Keeltoodeep | 6 hours ago
Yeah the scale is different but the philosophy is the same just with bigger numbers. Google is still making more money than they are spending because they have that ecosystem. Being a hyperscaler while training your own models allows you to be profitable.
PlanetCosmoX | an hour ago
Too bad then that Google has the dumbest AI of the lot with a focus of lying to push product as opposed to return actual information.
Keeltoodeep | an hour ago
Per AA benchmarks tweet:
Google has released Gemini 3.7 Flash, improving 4 points over Gemini 3.6 Flash and reaching the Intelligence vs. Time per Task Pareto frontier
Google just released a frontier model yesterday.
snowrazer_ | an hour ago
BS comment. Revenue is not investment - and the net profits from revenue goes to investors, that’s fine.
Investors buy shares, that’s also fine.
If investors bought shares, and that money went to pay out profits, instead of actually purchasing the shares - that would be a textbook Ponzi scheme, and a massive fraud case.
copperblood | an hour ago
Not BS comment at all. Go back and educate yourself on what a Ponzi scheme is. Both the AI sector and private equity sector are largely being sustained by Ponzi schemes currently.
snowrazer_ | 53 minutes ago
I explained to you exactly why this is not a Ponzi scheme and you explained nothing except ‘go ask AI’. I live in idiocracy.
copperblood | 52 minutes ago
Awww MAGA dat you?? 🤣🤡
Historical-Tough6455 | 5 hours ago
Right now most of ai is monitoring and injecting fake comments and content in social media
The payoff is turning America into a religious dictatorship
Osiris_Raphious | 2 hours ago
Power of the media has always been known, now the trick is the corpos use these AI to manufacture concent and distract the massess, whilst confusing the poltical class... Thats how fascism did it, history repeating itself...
KoseteBamse | 8 hours ago
AI companies that use these data centers need to be profitable and have strong demand. Currently, that demand is there, not sure if it will stay strong.
Data centers need to reinvest in new equipment every 2–3 years due to physical wear and improvements in hardware. Some GPUs be still in less demanding tasks
WTFwhatthehell | 7 hours ago
Servers are typically deprecated on paper over 3 years.
In reality with very modest care even servers under heavy load have a 5 to 8 year lifespan.
Now if architectures with the equivilent of huge amounts of VRAM tightly attached to GPU-like processor's start to take over the old ones will quickly become obsolete.
Ithirahad | 6 hours ago
Never confuse "there" (extant) demand with strong (inelastic) demand.
The demand for literal unicorns at $0 is somewhere in the single-digit millions of units, factoring in that they are still horses and have upkeep costs.
The quantity demanded, with consideration for the real biotech development cost, is... maybe one unit? Two? And only because of the obscene skew in wealth distribution.
Holbrad | 5 hours ago
>to be profitable and have strong demand.
I think it's literally impossible for there not to be strong demand for good AI models.
joepez | 4 hours ago
But of apples and orange comparisons. Some companies are VC funded ventures whose profit will be funded by investors. And not really profit but rather losses. That’s the nature of VC backed companies even at scale.
Some of the companies are well established businesses (even public ones) and they are taking highly speculative bets which are getting funded with debt and future profit (or losses).
One is not the other and they shouldn’t be compared. Both add to respective bubbles but in the case of the public companies there’s an argument to be made they went in deep too soon. That’s a question of bad management.
Unfortunately given the size of both bubbles there is the potential for a serious deflation for some companies.
datums | 4 hours ago
OpenAI and Anthropic have consistently put out very profitable products. The reason why the companies aren’t profitable is because the huge capital investments they’re making right now are for products that will exist in the future.
It’s kind of like saying that a new NBA team is unprofitable while their $1 billion arena is still under construction and the team isn’t playing yet.
ThinkingWinnie | 3 hours ago
Except the construction in discussion is basically training new models.
And unlike an arena that's reusable in a long term, a model from 2022 is garbage today, not because technology improved, but simply because it lacks four years of context.
When you put it that way, training isn't a one time cost, but a constant operations cost for any LLM provider out there.
DFX1212 | 2 hours ago
And that arena has a lifespan of 3-5 years.
Zvenigora | 4 hours ago
It's more like building the arena when you don't even have any players and have no path to being granted a franchise.
cejmp | 2 hours ago
who cares? If I open a line of bracelets and one line sells extremely well and the other lines put me 300% in the red who gives a fuck about the unicorn bracelet?
Osiris_Raphious | 2 hours ago
Fascism trying to hedge their capital wealth against the rising socialism and awareness of the inequity and inequality, by speed running the technofuedlism orwellian nightmare of mass surveillance and data driven economic and social control...
SO the math does make sense when you understand how history is in fact repeating itself.
Rambok01 | 8 hours ago
I believe he's an idiot who doesn't know strategic management, typical "economist". Of course they are unprofitable, as they are in the growth/scaling stage. Had they (OpenAI, Anthropic, etc.) chosen overnight to turn a profit, they would have destroyed more than 90% of their value
Olangotang | 7 hours ago
They could never turn a profit overnight because as soon as they did that the demand would snap out of existence. The models are brutally expensive to train, that is why they are igniting money to the point that crypto-nft-AI bros can't count that high.
Rambok01 | 7 hours ago
Except for a BILLION FUCKING PEOPLE using their services - that's the demand. Do you really think an abuela down in Mexico or a boomer anywhere in the world knows how to set up a local LLM? Even if they did, it could cost thousands of dollars to acquire the necessary computing power for a household to run a decent model. A subscription costs $8 - $20 and offers the best models in the world running on the best inference chips - Cerebras, which you can't even buy as a consumer
Paradoxjjw | 6 hours ago
And those billion people aren't paying for it. There only is demand if the service is free, there is no demand if people have to pay the actual cost of the service let alone the extra margin required to make it profitable. How little economic sense do you have?
antiquemule | 7 hours ago
The vast majority of those people are using the free tier. They will not take out a subscription. And even if they did it would not cover the colossal cost of the data centers.
Rambok01 | 7 hours ago
Yes, they use free tiers because it’s perfectly rational for them to do so for now. And yes, the shareholders are financing it, which is also rational for them to do. These companies are very aggressively scaling and trying to steal market share from each other. It’s a ruthless, bloody war between a few clusters of tech companies for a market that will soon be worth a trillion dollars
Dense-Comment-5938 | 7 hours ago
You're working on the assumption this is life-changing tech for the abuela or boomer. They do not care. It is a funny toy to turn their dog into a secret agent. It could disappear tomorrow and nothing would seriously change. For the majority, there is no chance they're paying money for access to the funny piss-tinted photoshop generator.
Rambok01 | 6 hours ago
Krugman moment
Ithirahad | 6 hours ago
If it were so trivially wrong, you could probably say so in a few words rather than resorting to ad hominem.
The user numbers are massively inflated by people who could never support the real cost of continuing to run these models and pay off dev spend, especially when the investor-bankrolled hardware they are currently running into the ground needs to be replaced. Never mind the cost of continuing to iterate (which, mind you, they must do in order to remain afloat, considering their valuation is only sensible under the presumption that they will somehow magick AGI into existence and utterly break economics).
Rambok01 | 6 hours ago
I don't have to do anything. AI agents will do it for me
Dense-Comment-5938 | 6 hours ago
Very insightful, and definitely not a sign you have no idea what you're talking about.
You're falling for inflated numbers on a bad pitch-deck.
Olangotang | 7 hours ago
Please defend AI with your own words and not standard industry talking points that everyone is bored of 🥱. Yes a billion people use their services. How many pay for it? See, that's the ultimate issue that you must cope about. How will these companies make money? Even Sam Altman doesn't know. The ads have failed. A year ago he said "we just ask the AI how to make it profitable". You're putting a lot of faith into incredibly unserious "companies".
Weird, I never said anything about local models, so you're obviously on the "I defend only the creepy AI labs cause I don't have an agenda" tree. Like come on.
Oh, and by the way, Cerebras is cool. I know one of the chief scientists there. Too bad OpenAI, the majority of AI demand, needs to turn a profit.
I_Am_AI_Bot | 7 hours ago
Before OpenAI or Anthropic make profit, the Chinese labs would reduce the token prices to the level making them non-competitive.
Rambok01 | 6 hours ago
The whole Chinese economy operates by screwing everybody else over through CO2 emissions (poisoning the planet), as well as through slave labor in their concentration camps. The US/EU will never allow the Chinese AI into the Western world, it's a communist country never forget that. If you think else you just don't understand the reality of politics
I_Am_AI_Bot | 6 hours ago
Trump will definitely ban them sooner or later but EU and the rest of the world will not. See what is happening to Chinese EV export.
MajesticComparison | 7 hours ago
The rub is that there is no path to profitability. The invests made were to create something that can eliminate workers. That’s not happening. Replacing workers was the only real way they’d make money, yet models are already hitting diminishing returns.
Ithirahad | 6 hours ago
They hit diminishing returns a year or more ago.
Olangotang | 6 hours ago
They were still improving at a decent rate but post-harness has been marginal. Opus->Mythos is particularly laughable because it's triple the size and like 5% improvement lol.
Gaglardi | 7 hours ago
I cannot believe I was on the economics subreddit reading all these comments who regurgitate the same Reddit hive mind bullshit without understanding that the entire sector is scaling for long-term profits in the future
This website is fucking cooked, reading comments on this thread makes me remember all the intelligently worded bad advice I've read throughout the years as a lurker
Olangotang | 7 hours ago
I can absolutely believe that people who have no education in how these models work, think that LLMs are going to become anything but costlier, beefier LLMs. AI is cool. Unfortunately however, LLMs are narrow AI, much closer to a machine learning model that processes vast amounts of data, than actual intelligence. Many in the field are pulling their hair out wondering why we are wasting so much money on fucking LLMs.
So yeah, you fell for industry bait because you don't understand how the technology actually works.
hw999 | 7 hours ago
You do know that a GPU only lasts 3 to 4 years at best, right? The buildings and the land are long term investments, but GPUs are a continuous money pit.
Paradoxjjw | 7 hours ago
What long term profits, the only demand is openAI and anthropic and once either goes down that collapses the house of cards, open source models have effectively made sure there is no long term profitability.
Dense-Comment-5938 | 3 hours ago
There is a shocking number of you guys that would have absolutely fallen for Theranos.
Alone-Supermarket-98 | 4 hours ago
It is embarassing to hear someone titled as a Chief Economist make such an uneducated statement. It demonstrates a complete lack of understanding of business models.
cbawiththismalarky | 8 hours ago
Sorry this is a stupid argument. The compute isn't being built for Claude, OpenAI or any other "chat" application. It's the infrastructure on which the next layer of AI will be built, and that infrastructure needs to exist before those applications.
Microsoft, Alphabet and Amazon can't afford to fall behind in building it. Their future growth increasingly depends on their cloud infrastructure businesses, and if one of them doesn't make these investments while the others do, it risks handing its competitors an enormous structural advantage.
I'm constantly surprised that smart people fail to see this.
solarpanzer | 8 hours ago
You'd still still want that infrastructure investment to at some point be paid for by actual future customer revenue. That seems unlikely at the current scale. It won't hit datacenter builders and cloud services as much as the AI companies taking on long-term commitments.
cbawiththismalarky | 8 hours ago
Alphabet reported Google Cloud backlog of about $514 billion at Q2 2026, up more than $50 billion sequentially from Q1. Alphabet said the increase was driven by strong demand for enterprise AI offerings, and that just over half of the backlog should be recognised as revenue over the next 24 months.
Microsoft reported $678 billion of commercial remaining performance obligations at FY2026 Q4, up 84% year-on-year. Microsoft said all of the sequential RPO growth in the quarter came from customers outside frontier-model companies; excluding OpenAI, RPO was still up 25%. About 30% is expected to convert to revenue over the next 12 months.
Amazon reported approximately $496 billion of remaining performance obligations at 30 June 2026, primarily related to AWS. Its long-term contracted obligations had a weighted-average remaining life of 6.4 years. AWS itself was running at roughly a $169 billion annualised revenue rate in Q2, after quarterly AWS sales rose 37% year-on-year to $42.2 billion.
solarpanzer | 8 hours ago
Sorry, i think you accidentally copy/pasted something with many numbers in it over your own argument.
Probably you wanted to use these numbers somehow, e.g. relate them to costs? Maybe take out the infra revenue coming in from deep-in-the-red AI companies? And argue that these companies might then be candidates to get workable business models going, even outside the frontier model cash burn?
Maybe you can get that argument together again, would be interested.
zerg1980 | 7 hours ago
You don’t seem to be getting that these massively profitable companies with dozens of healthy revenue streams can afford the capital expenditures associated with the AI buildout without needing to show a profit right this second. They’re making the investment because they anticipate future growth related to AI, and the demand will obviously be there, because this technology has already changed the world even if it never advances further at all.
You’re thinking too small and if all executives thought like you, the economy would never grow and new industries would never be created.
cbawiththismalarky | 8 hours ago
if it's too much to read for you i totally understand
solarpanzer | 7 hours ago
I read it, now I'm waiting for what you make out of it. It's not clear what that is.
I mean, on the surface, we can summarize your pasted text as "projected revenues of big companies involved in AI infra and enterprise AI are rising due to AI".
To which my answer would be: "Well, duh?"
But does it pay off for them, and more importantly does it pay off for the companies from which they generate that revenue (so it will keep coming)?
cbawiththismalarky | 7 hours ago
yes well i can give you the record profits of those three companies over the last year as well as their projected orders, so you'd see that they are in fact making money hand over fist - you can attribute some of that money to the investments into OpenAI and Anthropic and the forward purchasing of compute but that's only a proportion of the current revenue, profit and order book, and OpenAI and Anthorpic both have significant revenue, c$25 and $30bn so far this year
FoogYllis | 8 hours ago
That is a logical explanation. I wish this logic could have been applied to green energy tech but for some reason the administration is actively harming that sector. It could have been part of the AI data center energy sector.
cbawiththismalarky | 8 hours ago
I mean it is elsewhere, and I totally agree
Lithgow_Panther | 8 hours ago
Just like all that fibre had to be laid before the dot com era worked out for investors
cbawiththismalarky | 8 hours ago
All that fibre is being used isn't it?
Paradoxjjw | 7 hours ago
Fibre stays operable for decades with relatively little monetary investment required for maintenance. Most of the fibre laid down during the dot com bubble is still in use today. GPUs they've got in a data centre now will need replacement by 2030 if not earlier, if there is not enough demand to fund that replacement the datacentre becomes useless.
phoenixbouncing | 8 hours ago
It is, but there are two counter points to consider:
cbawiththismalarky | 7 hours ago
OpenAI is 30% owned by Microsoft, Google has a significant minority stake in Anthropic probably about 10-14%
Sryzon | 7 hours ago
Giving GPUs a 2 year lifespan is a little hyperbolic. They're not useful as long as fiber no doubt, but cloud companies traditionally continue to offer lower performance options on older hardware. Most of these GPUs will get at least 5 years of use.
Hell, Meta recently developed a method to use DDR4 memory in modern servers to get around the memory shortage.
Not to mention a huge portion of their investment is in tangables with significantly longer usable life. Like the land, rezoning, buildings, utilities, mechanical equipment, etc.
NinjaLanternShark | 8 hours ago
AI has made lots of smart people dumb.
People you thought were tech literate have become luddites. People who didn’t know what a data center was a year ago and had never attended a zoning hearing, are descending on zoning hearings in a rage.
And people who you thought understood the concept of a loss leader are calling TOD on AI as a whole, because it’s not profitable while it’s still in its absolute infancy.
solarpanzer | 8 hours ago
Maybe you're confusing scepticism about the financial viability of companies in the market and their business models with general tech scepticism?
Valuations are extreme, as are costs, and just from a financial math perspective, it can't end well for all the companies participating in the race.
Olangotang | 7 hours ago
Yep. AI can be the most amazing, blowjob giving tool, and yet once the corps hit their debt refinancing window with nothing left. 📉
Olangotang | 7 hours ago
Or people who understand the mechanics behind the laughably inefficient Transformer architecture realize that all the chucklefucks hyping up the word prediction machine (yes, that is what they are. Cope about it.) are falling for the biggest rug pull in history?
LLMs are a dead end tool and scaling is showing diminishing returns already (Fable and Opus 5, but Fable cost 3x as much as a 10 trillion parameter model and is marginally better). So the next model needs another 5 billion in addition to the cost of the previous model? Like come the fuck on, anyone with a brain who hasn't succumbed to AI psychosis can see how goofy this shit is.
Dense-Comment-5938 | 7 hours ago
"Maybe we shouldn't be shaping our economy around something with no proven way to generate profit while stacking up insane amounts of debt in a giant circlejerk"
"LUDDITE!!!!!!!!!!!!!!"
Olangotang | 6 hours ago
Here I am with nearly every new Open Source model on my desktop, a CS degree with ML concentration under my belt, and yet because I don't worship the creepy fuckers in Silicon Valley who want us all to eat dirt, I am also a luddite to these people.
MajesticComparison | 7 hours ago
The issues is that it’s taken on so much debt that there is no way to pay back investors unless it does something like major workforce replacement. Which isn’t going to happen with current AI. In addition we’ve already hit diminishing returns.
_ii_ | 5 hours ago
What was said is technically true but the framing is ridiculous. Investor funded profits is literally the name of the game. Some of these current and future AI companies will eventually be hugely profitable and many will lose 100% of their investors’ money. No, the bubble isn’t going popping tomorrow, not next week, not when clueless “economists” still write about it being a bubble. I’d be worried when the bubble talk stopped or die down.
Famous-Decision-1017 | 5 hours ago
Profits implies these AI entities are profitable. We know they are wildly unprofitable. Insiders are very profitable with massive compensation packages paid for with mountains of bad debt though.
notintelligentidiot | 8 hours ago
Why do people bring this up as if this hasn’t always been the case with the 21st century generation of major startup companies?
What the article states also describes Uber, DoorDash, Lyft, and a bunch of other ultra successful companies.
Investors have plentifully long leash with these companies and will continue to cover their deficits because they think the upside will be extremely huge.
Also, as a side note, for Anthropic specifically, it is operationally profitable. If they wanted to cease all investments and taking in investor money and just try to coast on current revenues, they’d be able to do so profitably. But a company like Anthropic has much larger ambitions than their current state.
If even the medium case projections are correct, we’re looking at many ultra valuable companies.
Dadoftwingirls | 8 hours ago
Keep huffing the hopium!
notintelligentidiot | 8 hours ago
What exactly is the hopium here? I’m just explaining why investors are glad to pour money into AI companies and using past cases as to why it might work.
Some of y’all are weird (and dumb).
Olangotang | 7 hours ago
Investors are happy to pour money into a technology that is hyped to hell and back simply because they do not understand the machine learning concepts and flaws ($$$) that define the architecture.
Uber is a SaaS app with a map. An LLM requires a large amount of VRAM to store the model, then a large amount of VRAM to store the user's context. The cost isn't consistent and is a logistical nightmare.
notintelligentidiot | 5 hours ago
Anthropic is literally operationally profitable. If it stopped investing the hoards of cash it does to expand its infrastructure and further develop its models, it would literally be a profitable business.
Your talking points are so ill-informed it’s hilarious and frankly out of date.
Reminds me of all of the goobers confidently predicting and making video essays about how SpaceX would never make money with Starlink and hoe the economics of DoorDash and Uber made it so that they could never actually become profitable lmao
> because they do not understand the machine learning concepts and flaws
Yes, nobody investing into AI knows how anything works, everyone is dumb (except u/Olangotang, he knows better than everyone).
Olangotang | 54 minutes ago
I don't know why you people try when it's immediately obvious you don't know what the fuck you are talking about. Plenty of people who understand the technology have called it out in this thread that you are all chucklefucking for the most unserious firms to exist.
I mean dude, you are repping fucking SpaceX, which everyone from the illiterate MAGA to the ivory tower liberal know is a scam.
All you are doing is wasting time on the Internet making yourself look stupid.
Also: > An LLM requires a large amount of VRAM to store the model, then a large amount of VRAM to store the user's context. The cost isn't consistent and is a logistical nightmare.
This ain't a talking point, dummy. It is quite literally... No wait, not quite it IS... Oh hold on, I'm losing my train of thought like an AI booster in psychosis, give me a minute.
IT IS HOW THE MODELS WORK. The fact that you clowns have to cope so much that you deny how the models function just proves how sad you boosters are to be cucked by Dario and Altman 😂 .
mandingo_climbs | 7 hours ago
While your points are valid, the way I see it is that the scale here is the main issue. No one would mind AI as an enterprise if it didn't siphon money from left and right, and its success wasn't disproportionately tied to the future of the US (world?) economy.
notintelligentidiot | 5 hours ago
You guys really just say shit lol
“siphon money from left and right”… you mean from investors… seeking returns… as they have for all eternity?
And no, AI is not disproportionately tied to the future of the US and world economy. Without it, the world economy is fine. AI investments made up a disproportionate share of economic growth in 2025 and this year because the Trump administration is actively harming the US economy. If they weren’t, we’d have the best of both worlds working in tandem.
Tupcek | 8 hours ago
just to add, API pricing is wildly profitable. Their subscription tiers, on the other hand….
But they could just lower the limits and be profitable tomorrow. But for now, users would flock to other subsidized service, which sells them $1000 tokens for $100. But if they slowly lower the limits in tandem with one another (which will happen once investors start demanding profits), so you got nowhere else to go, subscriptions will be profitable too
Sad-Plankton-1225 | 7 hours ago
Or China will continue funding open source cheap models and users can flock there.
rpctaco1984 | 7 hours ago
Most users will just go to cheaper open source models that can do 95-99% of what the expensive models can do at less than 1/10 of the price.
Intelligent-Pear-783 | 7 hours ago
Bittensor ahem ahem
notintelligentidiot | 5 hours ago
And yet, Anthropic has $75 billion ARR and likely racing past $100 billion by the end of the year… so clearly, you’re wrong lol
Olangotang | 7 hours ago
> But they could just lower the limits and be profitable tomorrow.
Where do y'all come up with this? 😂
If they lowered the limits demand would drop like a rock. There is also no evidence API is profitable, that was a one-off hypothetical note from Dorkio a year ago. Each model costs more money and the cost rises exponentially. Also, they are still being heavily subsidized. There is no viable business model.
Tupcek | 6 hours ago
it is known fact that API pricing is much more expensive than subscription
Anthropic is now EBIDTA profitable - meaning they make enough money to cover compute costs and more with their revenue.
If they are barely-profitable overall and API hypothetically lose them money, where do they make their profit from?
The only possible answer is API
If they lowered the limits, demand would drop because people would move to other services which subsidize their subscriptions more. But once investor money dries up for everybody and nobody can afford to subsidize subscription, there is nowhere to go for users.
And there is no chance in hell that developers will stop using AI, neither does marketing and many other industries that are deep in AI work already, with many more joining every month.
Olangotang | 6 hours ago
They don't make any profit. Are you seriously going to use the same dug and buried up 700x talking point of "lol Anthropic is profitable because the other creepy fucker gave them compute in a quarter so we can ignore the CAPEX"? Oh yeah, multiply it by 12 to get the non-gaap cope run rate. Give me a break. You bring a lot of finance bro terms but no ML bro terms.
> And there is no chance in hell that developers will stop using AI, neither does marketing and many other industries that are deep in AI work already, with many more joining every month.
So do you not read the news like at all? Half of the companies using AI don't know why the fuck they are using AI. It does make a lot of sense that crypto-nft-AI bros live under a rock, far from society I guess.
Man it's crazy, y'all know literally fuck all about this stuff, but will repeat numbers you don't understand over and over and over again.
Tupcek | 6 hours ago
who hurt you?
I may be biased, but I don’t know single developer that isn’t relying on AI anymore.
Sure, there are a lot of AI projects that fail (especially amongst the early ones, where almost all of them failed), but AI is quickly becoming normal tool for more and more office workers every day. This year, it is already exploding in scale, some sectors faster than others. You can see AI everywhere. And it’s not going away, even if the price doubled.
And I am not going into debate, who can insult other party more
Olangotang | 6 hours ago
I literally don't care. I don't know how you people don't have the self awareness to realize that you don't convince ANYONE because you all use the same talking points for years in a row. It gets boring. It gets stale. It's fucking weird and disturbing. It's like, why try if you aren't getting paid for this!?
I'm not even going to go into the fires AI is causing behind the scenes at the companies that are deepthroating LLMs. Why would I? The audience is already on my side, it's a waste of time.
Tupcek | 6 hours ago
I just hope that one day, when you realize your mistakes, I hope that it will make you more humble and more willing to discuss, instead of trying to insult others who don’t agree with you.
Some people take it badly and become even more hostile and unwelcoming of any other opinion or facts that don’t agree with them - I hope that won’t be your case.
Have a good day, mate! Hope to have the same discussion with you in a year!
ucmecheng | 3 hours ago
Well yea, that’s how new business works. You don’t have positive cash flow on your enormous capital expenses for a while. It’s a bet on future cash flows.
Holbrad | 5 hours ago
A lot of the speculation on AI is based on recursive self improvement (RSI) happening to a meaningful degree.
If your not taking that into account then you'll have no hope of understanding investors.
If we get RSI it's the most powerful and impactful technology ever and valuations are actually far too low. If we don't then it's still very useful tech but over valued, potentially severely.
technocraticnihilist | 5 hours ago
Yeah yeah yeah. We're been hearing the AI bubble narrative for years now, but it's still ongoing, and AI development and user base keeps increasing. Keep dreaming.
Equivalent-Bus-4336 | 4 hours ago
It’s the only thing we’ve got now, just gotta keep pumping it up and hope it works out in the end
2ManyCatsNever2Many | 7 hours ago
i feel like these articles talking about the doom of AI are just clickbait and ignoring reality. consider that gemini alone already has over a billion monthly active users and 350M paid subscribers. add to this over 8M enterprise accounts and you have substantial usage (despite what people say about AI only being slop). taking that 350M alone - ignoring the active 650M users who aren't currently paying (but it is fair to think many will convert) and the 8M enterprise users - the pro plan is $20/month. 350M x $20 x 12 (to annualize) is nearly a hundred billion. this number could easily double as non-paying users convert and i'm sure the enterprise accounts can give similar sizable gains. it isn't a stretch to say gemini will soon account for a quarter of a trillion dollars in revenue per year based on today's activity alone (AI will only continue to get better and more integrated). i don't know how this "AI math doesn't make sense" - it is obvious this will be a major product going forward and a cash cow for the hyperscalers.
Dense-Comment-5938 | 7 hours ago
It is absolutely not fair to assume "many will convert" when the average "users" are just googling for local restaurants and getting an AI summary about it for some reason. If anything, we should expect the users to go down as the real prices get pushed onto them instead of the heavily subsidized ones.
The math doesn't make sense because you just made a bunch of things up in order to get to the end goal of "AI is profitable somehow, actually."
2ManyCatsNever2Many | 6 hours ago
that is basically the same argumnt said when these companies built out a cloud business - investors spoke of doom and their profit skyrocketed.
Dense-Comment-5938 | 6 hours ago
"People were wrong this one time, so they must be wrong this time" isn't really an argument, but alright.
Cloud computing's invention did not require the industry jerking itself off into a debt spiral for several years before seeing a pathway to profitability.
Software as a Service is not new to us anymore. "AI" is just a shitty software as a service that's propping up our economy while we go through collective mania.
2ManyCatsNever2Many | 6 hours ago
"i don't understand all the revenue sources so it must be destined to fail" ain't much of an argument either.
Dense-Comment-5938 | 6 hours ago
I understand the theoretical ones. I also understand they're theoretical, because none of them are actually making money.
Paradoxjjw | 6 hours ago
If they were anywhere near profitable they wouldn't need to hide their AI expenses and revenues in other business segments to obfuscate the damage
Olangotang | 7 hours ago
The math doesn't make sense because if you understand fuck all about Transformers, you would realize that making bigger and bigger LLMs is lighting money on fire for little gain in the long run.
disposablemeatsack | 6 hours ago
Enlighten us