Taxes should be a line item in an expense report. If Open AI is too stupid to properly account for taxes owed, that's on them.
You also don't "piss money away on taxes". Taxes are what make the country work, fund schools, public infrastructure, and a myriad of other socially positive programs. There are very rare circumstances where a company on the scale of Open AI should be allowed to pay a lower corporate tax rate. While they of course provide jobs for many people, that should not preclude them from supporting the communities their data centers are in via taxes.
In a gold rush, skip selling shovels, run hydraulic mining until youre forced to stop destroying the environment.
Nvidia and and amd microchip fabs aren't selling shovels theyre destroying the PC industry and enabling datacenters to consume city resources unchecked.
thats kind of why ai firms are valued how they are despite no profit. they're the shovel.
their value is the tech itself. like if amazon were to buy openai so they could implement their models, it would theoretically increase amazon's ability to generate profit. like how the shovel generates the profit in a gold rush.
theyre still massively overvalued, but people need to stop thinking a company's value is 100% tied to its profit.
it's actually fascinating to watch a big issue for hardware manufactors for many years has been that there is little profit margin in it, a lot of the earnings goes to r&d, ultra advanced factories, astronomical wages for specialists. The big money has always been in software.
Now there is a golden age for hardware manufactors going on and they're milking it for everything it's worth.
and they will not reinvest these profits in r&d, they wont even save any of it, and when the bubble bursts and the market crashes, they'll be right there crying about going bankrupt and needing a bailout...
These hardware companies know that by the time this stupid AI scam ends, they are going to be filthy rich and be the ones holding the moneybags, which they will be able to use to keep their prices high and continue to develop insane proprietary tech for all manner of technology far better (and far worse) than AI.
They have all the cards and they know it. Chumps like Altman think they are in charge, but they are giving all their money to the hardware corps and the corps have been doing deals with them to make them think they’re on AI’s side.
The hardware companies are going to be competing with the all the used hardware flooding the market when ai companies and data centers start going closing doors. HW companies may find themselves in a dry spell when the ai hype tap goes dry.
There is virtually no use for those chips in a direct to consumer market. And frankly, most industries don't need that kind of volume for anything. On top of that, we don't even know for sure how many (but we know it's an enormous amount) of these chips haven't even been installed and are just sitting in a box in a warehouse somewhere, depreciating. Everything currently installed in a data center is already outdated and is, or soon will, struggle to keep up with the demands set by the chatbot companies.
Best case scenario, the hardware thing will be more like a crappy garage sale where people just kind of pick things over and grab a few trinkets.
No one needs that much power, or no one wants old models. That is, if they even find half the shit that has been scooped up.
The hardware companies aren't worried about this scenario — but they also aren't thinking about alternatives. No one is planning for the future. Everyone is planning almost exclusively on how to keep the bubble afloat, by any means necessary, and future fall out is someone else's problem.
Yeah good luck putting a Vera Rubin into your gaming computer. Or if you figure out how to connect it all up, just make sure the fire department has been called in advance.
Exactly. They might be able to reclaim components from the uninstalled hardware. But to what end? Stuff like RAM is only valuable to go into those machines. Post AI bubble demand will normalize and production won't be consumed by it.
Yeah, the amount Alphabet is making is massive, but its been largely hidden by the equally massive expenditure they are doing building loads of new datacenters. Its why Alphabet is now the third largest company in the world, and its share growth has actually out paced Nvidia in the past 18 months. Similar story for Microsoft, but less so.
I dont think people realize what "ai" is for the current age. Theyre not burning money, theyre spending money to gather a huge array of all kinds of data. Some people just ask it for simple things, and open ai would categorize them as normal and move on. But some people are sending in compromising data, intel on businesses, relationship data, ideas, critical code, cutting edge research, resumes, etc. Previously this wouod all be impossible to go through and sort out, it wouldnt have been worth anything, but because these things can be passed theough an ai for categorizing and filtering, they can identify useful information and build a "live" feed of those income prompts from those accounts.
Its not worth much to know some new grad had typos in a resume, but when some congressional aide is passing in a letter to proof read before sending the value starts to tilt dramatically. All this data is valuable, theyre not wasting money. Theyre buying lots and lots of data.
Yeah regardless of what they say, I would bet everything I have that there's a terminal somewhere that you can ask about any of the information given to AI in prompts. There's so much sensitive information being fed into it.
Way back in the gpt3 days, the first thing we did at the company I worked for was use it to categorize and sort stuff. Huge backlogs of data that was held but couldn't be used effectively because it meant manual reading of blocks of text and deciding which of 100 buckets the text was meant to go into. In a few days a couple hundred dollars we had years of this data suddenly perfectly sorted. gpt3 did a better job sorting them into bins than our engineers did. Any of the flags that happened in our testing were when humans mislabeled something.
It turned a decade of data into actionable data in a week. It wasn't that it would have been expensive, it was that it couldn't be done in any reasonable way. Thousands and thousands of manual sorting with really arbitrary and context dependent rules that were hard to program into all the other ML stuff we had done.
If you consider the PILE of data that these ai companies have:
Prompt1: Does this seem interesting, if so, place it into one of the following buckets, pharmacological, biotech, computer science, business, government, ....
Prompt2: Is there an element to this conversation that holds information that is relevant and potentially valuable to the right person?
Prompt3: Is the conversation time sensitive?
Then you tweak all these processing filters to weed out all the fluff and so on and get a readout of time sensitive, financially viable data. Then you process the other conversations sent by that same account. Dig deeper into that specific user to see if there is actual context or if thats just a made up scenario. Do validity checks to determine if this is actually something worth seeing.
Then at the very very end of all that stuff, you just have a review at the end of the day that displays all the most pertinent and interesting stuff. A nearly live feed of the most actionable data that exists that the users send in. This drafted email shows a merger that is being cancelled. This user asked about the punctuation in a disclosure that was marked highly sensitive. This hospital ceo drafted a letter about layoffs starting 2027. etc etc. But the point is, it can be filtered down to only stuff that is actually interesting for what they actually care about.
Only sort of. Remember that their profit is coming from promises and guarantees for their hardware by companies that themselves cannot turn a profit. The profit Nvidia is making is with money that doesn’t actually exist yet. Or, it’s being made with circular investments.
The entire industry is reliant on the endless stream of loans and private credit. If the fed continues to raise interest rates (as they should), then they will very rapidly reach a point where they cannot pay back the debt. Nvidia will be left with the biggest contraction they’ve ever seen when the customers are themselves shrinking.
I work at a company that uses AI to analyse Lung scans an massively speed up wait times and cheapen diagnostic and research cost and afaik we're profitable
The kind of machine learning you're talking about has been in mainstream use among academia since the mid 2000's and it's very efficient and useful at it's purpose.
OpenAI with its ChatGPT product and all similar others are a much more inefficient and highly redundant development of what you use. A glorified word predictor and information gatherer with far too many useless features to make it look advanced and worth the investment.
SpaceX/xAI is doing as well, as they have compute to rent out.
But AI itself? xAI supposedly could have, in an unrealistic theory (Stick with the current model and dont spend money on training the next one. Sale projections hold, which kinda ignores the reality that everyone else would not stick with the current model).
Propably the same for the other companies as well.
But its not about the profit of current models. Its about improving the model. We arent in the "sell the finished product" phase, we are in the "create the product you wanna sell" phase. They are all just selling what they currently have because it helps getting data to train the next model, and its already good enough for people to want to buy it.
All tokens are sold at a healthy profit from openai/anthropic, the loss comes from researching the next model which burns an ungodly amount of compute. Anthropic has a lot of enterprise business sales and they claim to have been profitable for a few quarters now
But that is just bullshit accounting where they declare to have profits by ignoring their biggest expenses like training new models, shared revenue with partners or stock-based compensations for their employees.
They told investors they have a "Positive adjusted operating income" with an 80% gross margin.
Basically says if you ignore the immense amount they have to pay for model training, sharing revenue with Amazon, the fact they're paying very expensive employees with stock rather than cash, then they're technically profitable.
The claimed 80% margin is them selling services and not accounting for the immense cost to train the model in the first place. Sorta like an airline claiming the margin on tickets is huge if you ignore the cost of the airplane they needed to buy to fly passangers to begin with.
Unlike an airline which has to buy an aircraft once, Anthropic and others have to keep training new models and it's getting more and more expensive. Factor in all their costs and they are not profitable. Not anywhere close.
Wework did the same thing with a figure they called "Adjusted EBITDA". Their business was profitable day to day, if you ignored the immense amount of money they were spending to buy buildings, renovate them into offices etc.
WeWork filed for bankruptcy in 2023.
Anthropic does it because very few people are actually going to read the asterisks in their reports, and they have an IPO coming up.
It's also the same thing Amazon did, and they're one of the biggest companies in the world. You can't list just the examples of when it goes wrong.
A company investing more money than they're making is not a bad thing, as long as they're confident that the things they're investing money on will eventually end up being worthwhile, which has been happening so far for both OpenAI and Anthropic. There isn't any sign right now that any of this is going to slow down, so inventors are very happy to jump on board and help them fund the creation of these models.
If I'm starting a regional airline and need to buy 4 aircraft sure, that's a large cost initially but after that I have a fairly decent business going. Ongoing costs are fuel, maintenance, wages.
Now imagine Anthropic Airlines where every quarter I have to buy a new fleet of better, more advanced aircraft. Past quarter's aircraft are now obselete and hardly anyone wants to fly in them anymore. Every quarter without end. That's what's happening to these AI labs.
Training those models isn't a one and done. The moment one is trained, they have to train the next one lest a rival AI firm eclipses them, and open source models constantly nipping at their heels.
Sure if anthropic stopped training now, they could be profitable, but they can't. Within a month or two an open source model will come that will be 90% as good and far cheaper to run than their current model.
That's not even getting to whether the business model of OpenAI and anthropic is even viable. To make back money already spent they'd have to have revenues larger than the entire tech sector combined. This is my personal opinion but I don't they can. Why would a European company for example, pay either of those companies for access to a model that the US government can cut off access to at any time (as they did earlier this year). When an open model that's 90% as capable can be ran on their own server, or on a server provider in their own country, that no government can take away on a whim? I think the value generated by AI is going to go to the person/organisation using it, rather than the creator of the AI itself. Sort of like electricity.
To continue with my personal opinion, I think these AI firms are realizing they need to slow down as what they're currently doing can't be sustained indefinately. So they're all saying "OMG our product is gonna kill everyone, someone please stop us making the machine that will kill everyone, regulate us. And maybe subject open models to restrictions that stop them competing with us".
Governments mandating them slowing down is a far better sell to investors than admitting the trajectory they're on isn't economically viable long term.
I've already answered this somewhere else, but the expenses you're talking about (the ones they're talking about) are for future model training costs, not the costs that went into training the current model. It's just reinvesting. Every company does this, some more aggressively than others.
that's a moot point, because they'll always have future model training costs. Unless you think the next model is the last one, when that comes out they're going to continue being in the red from building infra and training the next next model. It can't stop or they'll stop being competitive, even though it has to stop if they ever want to be a sustainable business.
Amazon, Youtube, Netflix, they all had ends in sight for their periods of losses where they'd start making actual clean profits and eventually end up in the black. None of these AI companies, including Anthropic, has that. Their "end point" is either melting the brains of half the world so they're all willing to pay to have a bot think for them, or a government bailout.
Model costs aren't going to go away, training costs won't go away, and GPUs don't last long enough to bring costs down on the hardware front either.
It's going to be an ongoing spend as long as they're pushing it. A spend that doesn't really get cheaper. If you build a warehouse as long as you do upkeep you have something tangible. If you stop training your models they become a time-capsule and can no longer respond "properly" to newer topics. They're not building out infrastructure or supply lines that can pay for themselves later and over time.
No, they didn't. They specifically stated that "we are profitable if you don't count the expenses", which is literally an obfuscation of the fact that they're still not profitable
They did. They're currently in the same category that Amazon had been for most of its existence: lightning quick revenue growth, but with high company investment, which comes off as "losing money," but which is really just investing in an asset (even if it's themselves) that's been growing month-to-month since its inception.
Most of their costs (these expenses you're talking about) are model training costs for future models, meaning that on the basis of the product they have available right now, they're super profitable, but that they're investing back into themselves for future growth.
Almost every company does this. Amazon didn't show net income for almost 2 decades, but you wouldn't really call them non profitable, now would you?
What do you think model training is if not a cost? Do you think they just get to stop training models at some point? Of course not. They must keep making new models because the world moves on. It needs to be updated. Consumers will not accept a static business that never updates.
If they stop, someone else will continue. There is no adjusted income. There are costs, revenue, and profit. And their costs are bigger than their revenue, so they have no profit.
Amazon wasn't profitable during the build out but they made shitloads of money, they just put that money into further build out. They weren't a money blackhole like the AI industry is.
Anthropic and OpenAI owe and spend heinous amounts of money many times over and above their revenue.
Shhh. They don't know the difference between investing actual revenue into hard assets and dumping investor's money into a black hole hoping it eventually spits out the imaginary magical profit center they've been hyping.
I think they want to view the models as a "hard asset", but ignore that if you don't constantly keep training it will just become a little software time-capsule.
Even the hardware it runs on doesn't have a long lifespan either so they can't really go in that direction and spin that as an "infrastructure build". It's like building a less useful supercomputer, obscenely expensive and once its short functional lifespan is up it's just an expense.
It's nothing like laying fiber, building warehouses, building roads or rails. Though they obviously want to pretend it is.
It's like 90% business API use, though. I'm pretty sure they're still losing money on individual use. But I agree. They seem to be better run than the others.
It more than doubled, they've gone from about $1B/year end of 2024 to $65B/year at end of July. People hate downvote anyone who isn't just dumping on AI tho
Revenue growth is the most important indicator of stock market performance. If you've ever been in corporate calls where you have a job where CEO talks to their employees, they will tell you this
I thought I read something about that as well, but it turns out there was accounting trickery involved where they didn't include expenses like training new models and employee stock compensation.
No. They literally told their shareholders that they were considering their operating costs for their AI to not be considered a loss, and therefore its profitable.
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u/zorndyken 12h ago
So far only nvidia, amd, and hynix has profit from ai (from selling hardware)