Like Netflix, all they have to do is raise their subscription price next year. Those already dependant or addicted, will pay. People complain about the snapshot while ignoring the trend over years.
Clearly they’re tokenmaxing. They, as a collective, deserve a raise and a promotion.
i dont think a leak was necesary for that.
Yeah we didn’t need the documents we already knew that but I suppose it’s nice to have confirmation.
The thing about AI is that the bubble has very little to do with the capability of the technology and everything to do with the overvaluation of the company’s developing it.
Don’t you worry about burning venture capital, let me worry about blank!
https://www.youtube.com/watch?v=-6qIYgwebhM
Blank! Blank!! Your not looking at the big picture.
Who did not know this already?
The real issue is that nobody seems to care… I mean, the biggest IPO in history just took place, valuing SpaceX (which was in reality a tiny bit of SpaceX, entirely composed of Grok) at almost 2 TRILLION dollars after they showed a 5 BILLION loss in the last quarter
Reality is for suckers I guess
And After the IPO they burned 60 billion on a vs code fork that is also hemorrhaging money, but the stock price went up 6%
They replaced the entire market with manufactured vibes.
The market is just finding bagholders right now. Once the guardrails are off of SpaceX, it’s going to crash when insiders cash out.
they are peddling so much AI to BUSINESSes in our area in the form of billboards and conferences. those are the bagholders people are likely to be targeting.
Well, the less money people have, the more of their income they spend. This means that maximum spending would be achieved when all income is equally distributed. Hence, as money concentrates at the top, consumer spending drops, which reduces the number of viable businesses, but at the same makes more capital available, since people tend to invest money they don’t spend.
Since people in general aren’t that good at telling whether an idea will pan out or not, as capital starts concentrating at the top, dumb ideas are more likely to attract a ton of funding. Add to that that spectacular ideas attract more funding, while at the same time tending to be bad ideas.
Essentially, Elon Musk’s businesses are valued so highly because his promises of AGI and space colonization are already being priced in as if they were real, existing things, instead of pipe dreams.
It’s wild we can lose money on this but healthcare or ubi, I bet ubi would help all these businesses/shareholders investing in ai more because ppl would just spend it all every month buying things they don’t need
This is an important point. The folks making “investment” decisions aren’t just greedy, they’re idiots.
The average capitol holder would make bank after UBI, while the government picked up the tab for health costs, and average folks spend the money saved on consumer goods.
But the healthcare industrial complex gives amazing blowjobs or something, to keep the lobbyists acting against most of their own customer’s best interests.
It’s not news that they are losing money, but it is news that they are losing tremendously more money than they were previously losing.
It does weaken the argument that scaling up is the path to profitablity, but of course they’ll just claim more money and scaling is the way to go. If the market remains manic they can get away with it.
Scaling up definitely ain’t the path, every user they get makes them less profitable (source)
They’re both spending more, and losing market share, below 50% for the first time recently.
IKR? Was it supposed to be a secret? The game plan is to bleed out the competition, make businesses dependent on AI, and then raise prices sky high.
The classic bait and switch, the entire tech industry works on this
In most industries it’s known as predatory pricing, and it’s illegal. For software tech\non-physical goods the governments are always just like YOLO.
Los is tremendously profitable companies ran at a deficit for a decade or more. They made their investors a lot of money.
I expect that many companies will realize that an LLM is a tool that can help with certain tasks, but cannot fully replace most workers because there is a ton of context in people’s jobs that cannot be condensed into language. Similarly, many companies are now realizing with token-based pricing that frontier LLMs are not cost effective in many applications. You shouldn’t have a natural gas fired data center in Tennessee running a model to proofread your emails. You can have a local model do so MUCH more cheaply. This will leave the speculative data center companies holding the bag on a lot of hardware and capacity that is not actually needed.
When training ai, I was always confused that they never gave a sht about tokens, like that was never something you picked any model over another for or reviewed, it often says to ignore the length but make note of how long it took, tbh that could be because of reasoning text not shown to the user
That’s interesting to hear. I wish efficiency had been considered from the start. It seems like there has been a ton of waste. They should only do the calculations needed to achieve the user objective. But they were prioritizing market share over efficiency. Maybe they thought they could afford another couple years of subsidizing wasteful use to build market share, but it hasn’t turned out that way.
This kind of feels like a “Duh.” moment. We all know.
Losing BILLIONS a Year? That sounds like TRILLION Dollar Status!
-Wall Street!
“Actually, this is good news, as the amount of money lost shows how much money they have gotten. This means they are very good at getting money.”
Hey Nasdaq, how much can I get for my compulsive gambler uncle?
Probably a lot if you short him.
All aboard the hype train 🚂. Next stop hypeville. Final destination… Who gives a shit.
I always thank the LLM and ask if it wants a cup of tea. Is this my fault?
Billions of dollars they earned? Did they earn those?
Hate on openai all you want but 4xing your revenue over a year is no small feat. Only 4 companies have gone from $1b to $10b in 3 years, Google, Uber, Cheniere and moderna
Not as bad as I thought honestly. Looks like they’re making a profit on inference, it’s just training the models is costing them a shit ton in R&D.
If we hit a plateau and training new models isn’t worth it and they scale back there R&D the business could be profitable. Not enough to justify there absurd evaluation, but not a money pit that some people in this thread would have you believe.
How? They have no moat.
The problem is though that inference by itself is going to end up a low margin utility service that there will be loads of players offering, they’ll never recoup their costs that way.
The only path to profitability I can imagine is to have a model that is vastly superior to what people can get elsewhere that they can somehow lock people into using and then charge them well over the cost of inference alone. None of which looks likely to happen.
It’s not a small feat, but they also 4x’d their expenses, which made them lose significantly more. Long term as you mentioned, if they could entirely drop their R&D, which they’ll never get to $0, but if they did, they’d still be almost -$2 billion in profit. Business modes can change to help accommodate that at that point theoretically though.
I just don’t see them ever getting there. How many years can you lose $20 billion and stay solvent? They’ll raise prices like everyone, but they may lose customers offsetting the gains made, or even if they get more, operating costs will go up too. With all of the DCs being built, I also don’t see R&D going down anytime soon either.
How many years can you lose $20 billion and stay solvent?
As long as investors keep pumping money into it. Uber lost billions a year until relatively recently, and they didn’t have nearly the same queue of investors ready to pour money into them at an insane markup. You underestimate the tolerance for silicon valley vcs to take in years of loss as long as the companies growing.
With all of the DCs being built, I also don’t see R&D going down anytime soon either.
Wouldn’t more data centers reduce there cost? More data centers means more capacity and more competition pushing the price down.
So a quick search shows that over the last 10 years, Uber was down a total of around 30 billion before turning profitable 3 years ago. This OpenAI report shows a 20 billion loss just this past year. They are surely different scales, but that’s a lot more billions lost.
As far as more DCs costing more, well you have to buy for the structures, pay for all of the hardware, and then pay to run the hardware. The more DCs you have the more that’s going to cost. I don’t know how that affects capacity or if it’s more for model training. However, I don’t think there’s a snowballs chance that prices are going down. Currently they’re going up across the board, and seeing how much they are hemmoraging, they can’t afford to go down. These first few years have entirely been about marketshare to build a client base and drive out competition. I can’t think of any service I have ever used that ever dropped in price.
Maybe I’m wrong. We can only speculate at the moment and this wave is fairly unprecedented. I personally hope they all crash and burn. It’s a blight on humanity and the environment. So I really hope I’m right and these companies go under leaving a bunch of bag holders that invested. I want it to hurt for everyone involved.
It is a small feat when you’re already losing money.
Not really, tons of companies in silicon valley burn through billions in cash and never even reach $100M in revenue, much less 4x on billions in revenue, that’s gotta be single digits in the amount of companies.
Snowflake in there prime when they had the largest IPO ever only got 50% yoy growth after $1b in revenue. 4x is insane
I wonder how much of that revenue is the circular contract bullshit. It’s easy to move money around when you have so much of it.
