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.
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.
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
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.
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.
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.