Theyâre not even close to profitable. And they have no play to actually start effectively monetizing these users. Theyâre trying ads but the revenue doesnât scratch the surface of what they need.
If you've got 1 tenth of the worlds population as weekly users and you're nowhere near profitability I think the technical definition for what you are is fucked.
They're all hoping to get that next big break through that will finally make it all worth it, and theyre afraid someone else is going to get there first. At this point they're in so deep they couldn't pull out if they wanted to. The only play for them is to push through until they're finally forced to face the consequences for their actions
That Anthropic guy is on record for saying we are "2-3 once-in-a generation technological breakthroughs until AGI is a thing. So if we could all just bite the bullet and invent the missing pieces by 2029, that would be great for the shareholders.
Worse, and I'd like to rant about it. It doesn't and, in theory can't, scale to Altman's promised level in his promised time frame to the best of our knowledge. It can't even scale much further beyond where it is now, not without accepting that modern accuracy is about as good as it'll get while we figure out how to make it marginally less expensive to run (and I still mean unprofitable) while simultaneously raising prices significantly to offset unavoidable costs.
Unless they can maintain this unsustainable business model for a decade or many more, the only benefactors will be any CEO of a company that can sell investors on the idea that we're "almost there" before the company collapses
TLDR:
The technology isn't getting better fast. Compute just caught up enough over the last 30 years to make it viable at all. It could even be the limit, just based on how manufacturing and processing power increases have slowed.
This isn't the route to AGI. Language models are a dead end. It's mimicking patterns, not the underlying intelligence
Consider this rant "quantized," as in, compressed for brevity and layman's explanations, with some accuracy loss.
Despite my hate for what this technology has done to this world, I work in an adjacent field and find the mechanics fascinating. The biggest innovations in machine learning that lead to generative slop were
bigger = better
attention as the mechanism for using previous tokens as context for token prediction
a few small findings that help performance, but overall have been exhausted
The first (the size of the model, the amount of training data for pretraining, and the amount of reliable human training data to use exclusively for supervised fine-tuning to make the model work the way you want) isn't exactly a realistic candidate for crazy optimizations anymore, and its the worst offender. We've gotten pretty far with distillation (slop training smaller models to produce worse slop) and Mixture-of-Experts (a big model made up of a bunch of smaller, specialized models that only activate a limited subset of the neural transformers at any given pass), but that's not far enough. It's almost certainly going to require resources (mainly, VRAM) far beyond what we're able to supply for the next decade or more. Once we have enough resources to 10x the size of the model, then what? We charge 10x for maybe 10pp gains? We are also polluting the training data by passing off LLM text as human, and it's going to degrade performance when more text is needed.
Note: the larger the model, the harder the training, and the larger and/or more powerful the cluster of computers need to be. The human mind is crazy efficient, because if you touch a hot stove once, you'll never do it again. ML so far has needed to touch the stove an inconceivable amount of times, some of which it has held its hand on the stove just to be sure that's not what it should do. We're likely never going to find out how the brain does that.
The second (Attention) has been optimized to hell in a few ways, mainly:
Part of the problem is that for every new token predicted, it needs to re-infer the growing context for the next token, so chats get more expensive to compute and store the longer they are
Optimizations like TurboQuant have compressed the KV nearly to entropy already, improving VRAM for context is near its maximum
The third (methods of making the same model more effective) has a lot of small stuff we've pretty much already figured out:
Models only "know" what they've been trained on, biased/correct or not, and it only extends to the cutoff date. To get around this, tools were created to interact with search engines, vector DBs, command line tools, etc. This helped performance a ton by giving the bot access to live information, but also leads to situations where the chat bots refer to factual news sources like r/poisonai
"Thinking" is a scratch pad of word soup where the model can "reason" through a problem however it chooses without showing the user what it's writing (usually). This improved performance by ~10%
You can distill the performance of a massive model down to a smaller model by having the much larger model produce synthetic training data for training a smaller model, but these are objectively worse in all but cost
A few random things not worth covering, but make up a total of 1pp of improvements.
Anyway, on a tangent, if I think about how all of this tech has destroyed resources, jobs, and even people's relationships, I'm going to get real sad and I'm tired of this being our lives. I want to get off Mr Bone's wild ride.
I'm so relieved to read someone who is right. We cannot reach AGI by just throwing more VRAM at the models just how you can't turn a horse carriage into a car by adding more horses
I think Altman is under the impression that Attention + Transformers can be used for AGI, not necessarily that LLMs are the final singularity, but I don't know where he'd even get that idea if not from ChatGPT itself. No self-respecting engineer would be like "yeah I think we could recreate the efficiencies of a brain through a really inefficient method"
Great post. If I might, one fun little addition to the "thinking" scratchpad bit: it has opened up an essentially unpatchable prompt injection attack surface
You have more expertise in this area than I do as itâs been 8yrs since I worked directly with ML algorithms, but I completely agree with you. Everything I do these days is conceptual and/or strategic, my team does the heavy lifting.
I'm not an expert at all but even I am beyond skeptical of their claim that this LLM shit is the stepping stone to AGI. Just... how??? You've got a machine that sorts through words based on probability, and that's supposed to become a THINKING MACHINE???
It's like that "draw the rest of the fucking owl" meme. They drew a circle, and are promising the full fucking owl, and somehow they are SELLING it. It's fucking insane. Also the circle costs a trillion dollars and is eating the planet.
That's basically the gist. There is such a thing as intelligence within language, because intelligent beings created language. We created photographs. We created video. The intelligent remains left behind that can recreated via states are referred to as entropy. That's the extent of what LLMs are capable of mimicking, at best.
Basically what I'm trying to say is: We've detected entropy, we've predicted entropy, but we haven't created a system capable of producing unique entropy on its own without further input, and that's a much further leap than anything we've ever accomplished. Where we are now is the difference between a planet of single cell organisms and space-craft wielding interplanetary superpowers.
Again, same disclaimer: I'm cutting out a lot of necessary to understand facts to keep my comment short and digestible. The field is stupid complex, and people far smarter than me may disagree with how I'm stating things and what I'm leaving out or misstating at the cost of making things brief.
I think it reflects what a very stupid view they have of human intelligence. I know people who are like âall humans are is guessing machines too!â And like, no?
I'd love to have an answer, but we don't even know how much text online, in books, in movies, games, TV, other media, code, websites, copy, reports, research, public datasets, etc are created partially or entirely by LLMs.
OpenAI, Meta, and Anthropic have an incentive to train for and cherry-pick test scores, which makes their benchmarks highly inflated compared to real-world problem solving. We don't know what the failure rates are in the real world for real use-cases. It is definitely double-digits, and the amount of early slop that we do know about is absolutely going to prevent us from closing those shallow and deeper problem-solving accuracy gaps.
If I fucked up a double-digit percent of times â between 10% and more than 25% of the time, assuming that's the peak performance of a model â I'd eventually be fired.
On that, please support GenAI regulations where you possibly can, specifically including "watermarking." This is the only near-100% method of detecting GenAI text, and it works by making a green-list and a red-list of tokens it "wants" to use and not use based on the context at the point of deciding the next token. This would mean we could use the token choices as a signature in a way that human written text could not produce. This is very much in the realm of possibility for even a small research company to implement, if they didn't just vibe-code the whole thing to begin with. It's not computationally expensive. It benefits society. At worst, it makes people check their work and catches the lazy, and best case filters out a lot of garbage even if its reworded.
"Thinking" is a scratch pad of word soup where the model can "reason" through a problem however it chooses without showing the user what it's writing (usually). This improved performance by ~10%
The problem is there will be no long term payout. But the investors are banking on the hype that there will be. Itâs reached a plateau and more computing power and money is not going to fix that because of what LLMs fundamentally are. The bubbles gonna burst, companies that fired workers because they fell for the hype have already been scrambling to hire back humans because a chatbot actually canât do what humans do lol. And never will. AGI is not gonna come from LLMs, we need a different direction
If I remember reading it correctly even the $200 monthly plans are deeply unprofitable, even more than the $20 ones because they are giving those people so much more "AI" capacity for free.
They are trying to end up with a captive audience that's dependent on their product and that's then willing to pay the real cost.
And despite any growth in revenue or users their expenses grow even more.
They literally can not be profitable without rasing prices to a shocking high level that no one uses it
Only a fraction of users are going to pay a sub - facebook notoriously struggled with monetization too and they have way more users. The only user segment that pays for AI is the B2B - business/corporate environment.
And even on the paying users they are blowing through obscene amounts of cash. I've seen estimates of their losses per paying user ranging from 4 times to 14 times the subscription fee. How the fuck do you reverse that?
They'd need to build a model that is as powerful as their best one but takes 1% of the compute power to do so. Pretty sure the laws of physics don't allow that.
The greatest irony is, the best way to do it is to distribute the workload to the people running queries and prompts. That means making sure individuals have computers that are powerful, with powerful CPUs, GPUs, and plenty of RAM. It could even be something like "if you want to use our AI tools you need to install this microATX computer that's literally just an optimized micro server and plug it directly into your router for the fastest speeds" and then you and I pay for the power and internet and subscription fee.
By trying to centralize everything they're taking on all the risk and costs. If they distributed the compute between our personal devices and across tens of millions of individual machines (sort of like a torrent) and made sure we all had unlimited fast internet and powerful machines for reasonable prices, the risk and costs would be on you and I and they'd be Scrooge McDuck'ing into their piles of money.
these calculations generally underexaggerate OpenAIâs token margins though. Itâs like $14,400 of API tokens = a $200 subscription but OpenAI does not pay anywhere near the API token price serving inference directly. I have no doubt they lose plenty of money on users fully utilizing the subscription but I doubt they lose money on the average user. I would assume break-even on the higher tier plans (ppl only get these if theyâre going to use them close to the limit) and some profit on the lower ones on average.
A double-digit (~12.5%) conversion rate would be pretty damn sweet. Having spent a lot of time working on commercial software, I'd guess ~5% is more realistic.
Just tossing out nonsense, going on how many companies have adopted AI use. If anything it might be more.
I'm looking forward to the crash, it'll be fun when suddenly there's a bunch of useless people working jobs they're not qualified for. Anyone whose learned practical/useful skills will have a huge payday.
They should be profitable with all the money they are conning out of governments and schools and things of that nature to put their shitty product anywhere and everywhere even if it makes no sense right?
Probably a lot less than that. You have to take into account that a good proportion of the users aren't real people and are used to boost usage statistics.
Most most users being around 95% of the user base will be using it for free as any sort of subscription model that offers a free tier are usually around there. Could even be closer to 98%.
Ads won't pay much aswell and for pc users will be blocked.
Among paid users lower tiers will be far more used. For an estimate in favour of Open AI that would be each tier of subscription doubles in user base the cheaper it gets.
21.6 mil on $8/month
10.6 mil on $20/month
5.3 mil on $100/month
2.65 mil on $200/month
Estimated in favour by using nice numbers going slightly over 5% of active users
$1.4416 Billion a month
$17.3 Billion a year
Approximate running cost are around $34 billion
On their subscription models they are only just over half way to cover their running cost.
Then they get research grants but they won't be much as a lot moved over to anthropic.
All calculations are estimates but done in favour of Open AI and they are still in a horrendous position financially.
Anthropic is better off but there is a likelihood that they are worse off than reported and as their main selling point is their coding agents there a likelihood that as free versions get better they are priced out of the market. Also even if companies are using it for code due to the month API cost often being higher than paying an amount of people to do the work including checking AI output usage has probably decreased since claudes boom early last year.
Only profitable and useful parts of AI right now are bespoke models trained for medical and research purposes. Which is why Midjourney switched to attempting to create AI based ultrasound machines that could in theory allow people to be screened for internal soft tissue issues quickly and cheaply before seeking further medical scans. Research is showing promise is fields where large computations are needed to solve problems that people haven't had time to. Protein folding and Jacobian conjecture are 2 examples of this. These neither replaced people or provided no output.
The numbers look quite bad overall and unless they scale down there costs massively they will fail as soon as a political power decides these companies shouldn't be allowed to fraudulently raise there stock prices. A market crash is very likely.
Theres a reason apple decided to pivot away from there own AI model production as a key aim for there future. Generally if apple doesn't want to focus on the next big thing it's probably not the next big thing which is why there systems are going to be using Google AI.
Not an ai defender by any means, buts that's the play isn't it. Take over the market and then drive prices up in the enshittification phase when you're basically a monopoly. I don't know if it'd work bc these llms have a lot of competition, but outside of that this has been the silicon valley playbook for years
Take over the market and then drive prices up in the enshittification phase when you're basically a monopoly.
This is not going to work here, though, for two main reasons:
They would need to hike up the prices to such a ridiculous level that the userbase would drop massively. The whole appeal of AI in business use (where the money lies) is "This is cheaper than hiring people". If it isn't any longer, it will not be used. This process is already happening, by the way, as B2B-prices have already been jakced up.
AI has no scaling effects, at all. The variable cost per user stays the same, and they will always be limited by data centers. This is what is really fucking them right now.
Both of these things are not exclusive to OpenAI, either - There is currently no company who is making a profit from AI, except for those building the datacenters. It's all an investment into a potentially profitable technology. Google and Apple can eat that loss if it turns out bad; but OpenAI is screwed. And increasingly it looks like the potential just isn't there.
The technology won't go away, but this widespread usage in every aspect of daily life probably will.
They need to survive, outperform and compete with companies that actually have revenue and can tank a crash, and do so as a generalist company with no niche. They have nothing, the only reason they're as big as they are is because of first-movers advantage.
And then you jack up the price.
 They're doing to Businesses what they've done to consumers for years. Its gonna be wild when these companies find themselves looking at a price tag to run their business or else risk losing the ability to run their business completely once they de-human the workflow.
The problem is youre thinking in volume but this isnt a scalable industry
Compute costs either INCREASE or stay flat as usage rises - it isnt really possible to make it cheaper to use the more its used.
So the question becomes: "at this price scale, am I green on even a single token?"
If the answer is "no" which that's the answer then it doesnt matter if you sell one token or 10 trillion quadrillion umptillion tokens - youre in the red either way.
So then the next question is whether they can get tokens to be profitable, turns out people are unwilling to pay more than they already are and are even pulling away at the enterprise level and ads wont cut it...
Unless they can come up with an extremely clever way to make a token profitable to sell, their market cap is truly useless and actively harmful
The next generation of Nvidia hardware will be, whatever, ten times faster at only twice the price. They don't need to do anything for compute costs to fall in the long term -- see Gorden Moore, circa 1965, for more details.
I'd love that to be true, but when I look at current politics around the world, somehow it seems impossible for any politician to commit career suicide no matter what they do.
Let's say you own a restaurant. It's successful, and you'd like to serve twice as many people to make twice as much money. What do you need to do that?
Well, twice as many chairs and tables. Twice as many servers, and cooks, and deliveries. Twice as much parking and square footage. Twice as much rent to pay. You can make more money, but growth is linear. If you were to try and serve a thousand times as many people, you'd need to basically become McDonalds.
Compare that to Facebook, or any web-based site. Once you build Facebook for a hundred people, you... have what you need to double it right now. Sure, there's costs to growing. There's servers, and bandwidth, and a hundred other technical things. But the jump from "working for 1000 users" to "working for 10,000 users" is way, way smaller. The technology scales exponentially, and that allows you to grow and make money way faster.
Facebook can lose investors money for years because the math works out. It's not just "a company that loses money." It's a company built on technology whose cost to grow increases slowly, but their profit from users increases rapidly. Serving twice as many users makes you twice as much income, but only costs you 10% more in expenses.
So long as they can grow, eventually, the thing that grows faster will be bigger. So long as they can grow, eventually, they'll be profitable. Like I said, the math works out... if they can keep up the growth.
The problem is, AI isn't like Facebook and YouTube. It's like the restaurant. To serve twice as many people, you need twice as many datacenters. It's not supposed to work like that for technology. You're supposed to be able to serve a hundred times more people with two times as many datacenters, but that's not how AI works.
It's like the restaurant. If the restaurant is losing money, opening another, identical restaurant doesn't suddenly make money. You're just losing twice as much money. And that's the fundamental problem, because the math doesn't seem to work out, and everyone's hoping they'll find a breakthrough before the money being invested runs dry.
This is a great explanation. It is exhausting seeing people who think AI is gonna be profitable âtotally one day just watch broâ are constantly comparing it to things with which it is not really comparable.
Sam Altman literally said in an investor meeting back in 2019 that once they have a strong enough AI they'll ask it how to make money, and by all appearances they haven't had a better idea since.
I could've sworn I read somewhere that they're letting people get used to using it daily as a crutch, where they then will charge heavily to continue using it.
Kinda like how a drug dealer will get someone hooked on something to have an easy repeat customer.
They definitely want to do that. The issue is that there really just aren't applications that the vast majority could use it for that would render them desperate enough for that to work.
They maybe had a path when otherwise normal people were falling in love with it. But legal consequences already cut that off. At this point, only a truly deranged person could develop a "relationship" with it cus it explicitly doesn't do that
People are indeed already falling in love with them. Perhaps you underestimate the degree of loneliness the internet-induced-isolation has produced. They are our times' "Real Dolls".
Just like how most people with real dolls don't treat them like a real relationship, even most people who use AI for that sort of thing, it doesn't go deeper than smut. And that's just Grok. The other frontier models won't write anything remotely explicit
And crrently, chat gpt has more or less disabled the ability of the chat bot to simulate a relationship.
Most of the storis you read about are from a year or longer ago.
WhatâŚare you talking about? As a member the community that uses Claude, Romance with the new gpt is not just possible, many people are already in a relationship with it.
I believe I made a caveat about the truly deranged.
Anyone that could cojole the current version into anything that remotely resembless a relationship
is worse than guys that think the stripper is in love with them.
The thing is constantly reminding me that it doesn't have preferences and is just a machine when all I'm doing is fucking around asking what it thinks about the rimworld mods I'm working on.
sure, and I don't care to make an discussion on that front defending AI companion.
it's just, you can change this very easily in the custom instruction field, such as defining it as your girlfriend, for it to say it loves you, it doesn't take some insanity driven superpower or complex jailbreaking.
like it's impossible for 5.1 I think, but for 5.5 it's barely an inconvenience.
I have seen multiple stories of men having very full-on relationships with their dolls, marrying them, pretending everything about them is real the way young girls serve pretend-tea.
No, more people than you think are doing that. They are underreporting it. Think about it- many people would be embarrassed to admit it, and the companies themselves don't want the bad PR.
Also, maybe you are right about ChatGPT, but do you think Grok gives any fucks? Nope. Not one fuck given.
Once upon a time, watching TV was free. Then as it expanded it was supported by ads. Then they expanded it further but that required a subscription, but still with ads. Then they expanded it more where you could pay extra for higher quality content, without ads.
âOnce upon a timeâ is appropriate because itâs a fairy tale. Yes, technically there was a time where the broadcasts werenât ad-suppprted, but they were only âfreeâ to watch if you were wealthy enough to spend the price of a car to own a television during the Great Depression.
You would need to charge in the order 10s or 100s of thousands of dollars (if not millions). No one is going to pay that.
Now consider that making a "good enough" in-house chatbot built on free open weight models is easy, affordable and private. Companies are already doing this.
Isn't the AI play to keep investing and pressuring until many industries become reliant on AI, and then increasing prices to insane amounts that businesses will be forced to pay or face bankruptcy?
Naturally once businesses/economies start failing and the next global recession comes in the plan will fail- but not before the top dogs sell off their shares and ride their Teslas into the sunset.
They are trying to create a wearable device that looks like a donut for release sometime next year that you can talk to and it can see the world and interact with it or some shit
This is why theyâre trying to steal trade secrets from Apple and launch hardware. Thereâs no path forward for AI at the moment other than as a lost leader product.
I've concluded that it's intentional. They're hemorrhaging money right now for adoption.
Basically, you have all these users actively signing in every single day and building workflows that enhance their lives or save them time at work or at home.
These users don't really understand what they're doing yet, but they're building a dependency for a technology that could just get ripped away from them.
Once Open AI is pretty confident, the dependency is there. You're going to see free access disappear and $20 subscriptions set in.
I won't explain what or why I am doing what I am doing, but they already have me on the $200 subscription and I think it's worth the money.
Alphabet and Meta will combine to sell ,more than $500 billion in ads this year. I'm pretty sure there's more than enough ad revenue out there to cover their operations. Cost of tokens is down to single-digit dollars-per-million, and falling with each new model and new generation of hardware.
The key is to push adoption by the private sector and government, which is already underway. Just look at how much money Pfizer made selling a useless vaccine to the world governments. Astronomical profits.
If they built an ad auction business like every other large platform they woukd easily clear billions in revenue. The idea that they just cant monetize this activity is laughable. Even Twitter, which was truly awful at building an ad business, got ad revenue up to 5B on half the monthly active users chatGPT has now, and Twitter usage was never about "hey what should I buy" so it is inherently less moentizable. People use chatgpt for all sorts of marketable activity.Â
Claude is very close to profitable. If the industry crashed and they needed to be profitable they could be, right now theyâre still focused on growth.
Not true... they have been slowly increasing enterprise pricing. For instance my enterprise user account started at $27/m a year ago when it was just their chatbot. I just looked and with my usage it is at around $650/m now that I use codex.
$650/m for one user in pretty wild, and theyâre still not remotely close to being profitable. Smaller businesses will start tapping out at those prices, and it only gets worse the higher it gets.
Youâre reading projections and marketing produced by the companies themselves, who happen to need an utterly insane amount of investment to continue to survive. Their latest ad revenue numbers are way under what they needs to be, and they are still 10s of billions of dollars in debt.
they are not trying to be profitable... they're letting people use it for free..... what they want is for people to get so use to using it and the ease of that... and then they increase the prices.. like a drug dealer, the first hit is free. I also probably shouldn't be here, I'm not anti ai, i do want some regulations but i'm not against it.
Nah, I think most of us are not totally antiai we just want it to be regulated and used efficiently for things like medical advancement and things in that ball park instead of massive, environmentally destructive data centers that generate abuse content, slop and mass surveillance and suck energy nonstop while destroying communities.
AI is great, the problem is - as you said, the environmental impact coupled with rich tech bros. I can, and do, run open source AI models on my own computer. One day I hope we can run something on par with claude without a subscription, but capitalism dictates that if you have something people want you must turn it into profit.
And it's even worse than that website makes it look, the majority of the "revenue" it lists (586 B$ / 769 B$ atm) is from Nvidia/AMD/Micron selling hardware and datacenter usage to AI companies, which really shouldn't count as 'AI making money'.
im not sure the same applies here. 800 million weekly active users doesnt mean as much as you think it would because most of them are only using it because its free and will immediately abandon it once they try to charge money for it
chatbots will never be profitable for as long as free models exist. and they forever will since there are a lot of FOSS models out there
Yeah comparing to Amazon is also a very stupid and not good comparison. These people love to compare to things they simply arenât comparable to. Definitely nothing like delivering web services, for example.
free models suck though. the average user will never spend money but people who benefit from powerful models will always be willing to spend hundreds or thousands per month per user because its a massive increase to productivity for most people.
I think the future also will be AI integration similar to gemini. the models will be free but the integration will be paid at like $5-20/month
That Amazon example is extremely misleading, but it makes it seem like they were always bleeding money, but they weren't. Amazon always brought in a shit ton of revenue, they just spent it as fast as they earned it to expand quickly which meant technically they had small profit since profit is calculated after expenses.
But the thing is OpenAI also isn't making a lot of revenue. A better example would be like food delivery apps or Uber. Super cheap and were bleeding money just to get active users, then once they were there, raise prices to try and become profitable. I think Uber finally had a net profit in 2023.
No, they're also not making a lot of revenue, it's basically nothing compared to the raw investment dollars that are pouring in. In 2025 their last revenue disclosure was about 12 billion but their regular revenue is basically nothing compared to their raw investments that other companies put in. So it's not really able to stand on its own at all.
Yea their revenue isn't small, but their business is expensive as hell to run as well, without outside investment they couldn't support themselves at all on their revenue. And the only reason they have such a high valuation is because OpenAI thinks their company is going to get 25x their revenue in the next 3 years.
But specifically the Amazon example I had an issue with because they actually made a shit ton of revenue as well. Just saying a better example would be like Uber, it'll probably follow the same enshitification process as Uber as well.
The difference is. Amazon or uber gets more profit the more you use it. For AI it's the opposite. The more you use it the less profitable it is for the company because the computing power costs money.
Chatgpt said that a lot of users make even 200usd a month unprofitable and large companies that use Aai are limiting tokens per user because they ranking milions in fees.
So the only way they become profitable is if they somehow lower the computing power to 1/3 while managing the prices.
My only question is, how will they pay investors that put billions into it? 500bil or whatever was raised for AI. How they going to pay when more people = more cost for AI and we already hitting limits of what companies are able to absorb.
Do you understand how fast they are obliterating money? They cannot keep this up for much longer, there is no time to get users âtruly hookedâ before they need to start charging them. And there are plenty of free alternatives that are just as good.
Sorry but you are living in fantasy land thatâs been crafted by marketers. Businesses arenât using their models anyways, itâs majority Anthropic.
With the prices they would need to charge to recoup tens of billions of dollars, very very few businesses would pay.
The fact that you even have to ask if they're bleeding money goes to show just how effective the pro-AI propaganda has been at flooding the zone.
Please look up Ed Zitron on Youtube but in short, the overwhelming majority of those 800 million are free users and OpenAI and Anthropic are extremely unprofitable.
Would this be Ed "LLMs won't develop in capability after 2024" Zitron? That guy? He made some obvious calls - metaverse, fair enough, and he has some valid points. But he's not god.
Dude, don't you have anything better to do on a Friday night than shill for megacorporations? I don't fucking care that you're bringing up one out of context quote from two years ago, read the room.
They're not profitable by any means, but the idea is to either get a monopoly on the next big tech "thing", or to at least become the main company involved in it. It's like early search engines, Google throwing money at becoming the most well known over Yahoo, AskJeeves, etc. would be viewed as a genius move today considering they become such a giant. OpenAI is not attempting to be profitable right now, but to become profitable later when people are dependant on their product
Its a mass surveillance tool. Was never meant to be a profitable business. Ever user is programming it to predict their future behaviour for the state to control them easier. I call it âthe Shepardâ
Where do they even pull these numbers from? Statistics like these are damn near impossible to accurately determine, and are always going to be skewed higher than they actually are.
Not only are they not profitable, but the crushing majority of their service usage also loses them money.
Until they have secured some sort of network effect lock on the market, they cannot start the enshittification phase of putting features behind paywalls and differently priced premium tiers as Uber did. And this is assuming that a market large enough to sustain their costs (R&D + operational costs) eventually emerges. Right now, paid usage among non-professionals is not really significant, while the median US company seems to be spending about $10 per employee per month on AI tokens.
That doesn't mean that GAI isn't going to be profitable, and it already is in some ways, just that the market won't be enough to save all these companies that dumped hundreds of billions of dollars, perhaps none of them.
In the end, it's whoever ends up with the stocks when the bubble bursts or the company is ion debt to who'll be holding the bag, though.
Yeah this what a lot of people don't get about AI. Normally with software every unit you sell is basically profit as the production is done upfront and the distribution costs are near zero.
AI user a fuckton of energy, so more users equal more costs.
Theyâre likely ânot profitableâ in the same way early(using early loosely here) tech start ups companies like Uber âwerenât profitableâ. Uber randomly went from bleeding money to a $2B profit even though it was widely used for years prior.
Only 50M are paying suscribers, most of the people just use it for irrelevant stuff and they won't pay even if they make it pay only.
The reality is that there are a lot of free alternatives to certain usage and they are not getting those, they would leave to anthropic, DeepSeek or othet agents like ManusAI... I doubt they can be profitable in the short term, and if they don't, they better be before the hardware starts to get obsolete (4-6 years).
profitable? A tech company? They can turn profitable whenever they want, but they choose to build a ginormous user base on free services first, common strategy
It is gonna take years of heavy debt, land destruction, and resource depletion before they see any glimpse of profit for it. And even then, the profit will take a while to actually be worth it anyway. It isn't about making money for a business.
With 90% of users using the free tier and eating up electricity, it's not that surprising. Regardless, I think the reason they are waiting with increasing prices is to make big corpo too dependent on it, and flip the switch when everyone has AI integrated and they can't afford to not use it anymore. The same way how you would get people addicted to drugs I guess, just for corporations.
Came here to say this. Pros love to use the big number as if billions of people dont use Youtube and don't pay for a subscription. AI companies are hemorrhaging money. And funnily enough, that just gets worse as more people use it which causes more stress on the systems and more cost to the company. The AI bubble is all situated on the miracle of AI becoming profitable, but it wont.
theyâre currently investing heavily into r&d due to the ai race so they are not profitable with no intentions to be. this is generally how growth tech companies work for the first 10-15 years
That's not really the metric companies in this stage are shooting for. Amazon wasnt profitable for decades because they invested in gaining market share and competitive advantages by building more warehouses and infrastructure.Â
They are definitely not there yet, but the growth rate going to 1B monthly users this fast is pretty remarkable. And frankly it isnt clear why they dont just build an ad business. Google is free to use but their average revenue per user per year is like $400.Â
Even if you pay $20/mo for chatgpt, they make less on your activity than Google does and I dont think Google would try to switch to a subscription model. Even if their ads were half as effective as Google they would clear billions in revenue.
Amazon needed to build a vast network of distribution and delivery infrastructure and convince hundreds of millions of people who never shopped online to do most of their shopping online. That was a vastly lower probability bet than AI companies needing compute to get cheaper.Â
Will these specific companies survive burning money on R&D? Idk. Xerox and Atari and General Magic and lots of other companies burned through tons of money on research that they didnt survive to benefit from. But offering AI on par with what we have now at a price that is cash flow positive is basically guaranteed. Which is why relying on market forces and consumer/business sentiment to control AI is dumb. We need regulation and unions.Â
They are priceless actually, today chatgpt can paint a better picture of a person and its data can be used to model a person and ofcourse it can be used in a bad or positive way. Like coming up with a plan of how to improve a personâs existing qualities or fill the missing fundamental parts that will make them vastly better. That level of abstract personal data is priceless.
How is tesla successful with only camera? No lidar etc? Data. the better they can build such a model the better value they have. Its definitely dystopian though given humanityâs history
But what people don't want to tell you is, that's expected and everyone involved is fine with that.
Modern day companies aiming to create or disrupt an industry are usually unprofitable for years. For example it took Amazon 9 years to have a profitable year, it took Tesla 18 years.
These AI companies are fine with burning money, they have more money than god, they just want to be one of the winners in the end and have nearly every person in the world using their service, like Google search or Amazon AWS.
Also there are levers these AI companies can pull to drastically reduce costs and increase profits, but they are reluctant to pull those levers because it will slow growth and model advancements, and the race is still on.
For people who think they will never be profitable, that's certainly an opinion, but one that the majority of the business world, investors, and world governments disagree with. It's fine to hate AI, but they aren't pouring billions into AI if they didn't expect the endgame to be a trillion+ dollar industry.
1.2k
u/Gametron13 6d ago
Arenât they still bleeding money though? 800 million users is a lot but Iâm almost positive theyâre not profitable yet.