But how does that detract from the overall point that Open AI is losing billions of dollars? If there's an insatiable demand for AI compute, where's the profit?
First and foremost, it's about competent reporting. You can think a company is doomed and still expect people to report on it accurately.
Zitron continually presents things in ways that create a hyperbolic narrative. Turning routine consolidation accounting into an unexplained mystery hinting at some sort of fraud is the perfect example of that. He does it so often and in such a way that I truly believe he just doesn't understand accounting.
It doesn't take a rocket scientist to understand that OpenAI is losing money. But the question ("where's the profit?") assumes that profit is the thing being optimized for. It isn't.
There are basically three buckets here: cost of serving a query, cost of training and capex for capacity.
The first one is unit economics. The other two are bets on the future that get expensed against present revenue. A company can serve every query at a healthy gross margin (OpenAI has improved margins considerably) and still have a $9 billion loss because it spent $12 billion training a model that generates $0 this year.
Zitron constantly blends everything into a pithy "they lose money on everything" narrative, which just isn't accurate. The thing is that OpenAI could have a very different P&L if it chose to, say, stop training the next model.
The problem, obviously, is that if you stop training the next model, the competition might eat you. So right now you have a situation where the the frontier model you spent $12 billion on depreciates in about 18 months, the GPUs depreciate on a schedule nobody agrees on, and you seemingly can't stop the cycle without risking your position in the market.
This is the legitimate bear case, but the problem with Zitron is that he doesn't make it using an argument that is coherent and honest as far as the accounting is concerned. And the accounting is everything.
High growth companies often have significant negative cashflow during the early high growth era, followed by positive cashflow in the years later down the line.
This phenomenon is known as the J-curve[1], and Uber is a good example of how this can turn out absolutely fine. To some extent, the entire Venture Capital industry exists to finance precisely this dynamic!
Nb. I'm not suggesting OpenAI is fairly valued, or that they will definitely become profitable, but "OpenAI is losing billions of dollars" doesn't really mean anything in and of itself.
High growth companies often have significant negative cashflow during the early high growth era, followed by positive cashflow in the years later down the line.
Uber is the antithesis of OpenAI, it’s not a good example. Uber was burning money on acquiring customers. OpenAI is burning money to provide their service (and the R&D they need to continue to have valuable models). They cannot just stop and turn profitable like Uber. The money they burn isn’t invested, it won’t yield a multiple of revenue in the future. It’s consumed for compute and that’s it loo
If the leaked data is to be believed, OpenAI is spending 40% of revenue on sales and marketing, which is not the OPEX profile of a product-led technology company
Broadly speaking, companies that spend 40%+ of revenue on sales and marketing end up being a bit of a drag on society. Eg. Salesforce’ product quality is far lower than winners in other sectors that sit closer to 10-15% of revenue on sales and marketing
Maybe - just as how the city of Sao Paolo implemented a ban on billboards - we can implement a law where a 3 year rolling average of sales and marketing spend cannot exceed 20% of revenue in that period
They cannot just stop and turn profitable like Uber.
Of course they can. They could just stop training new models and milk the existing ones. A billion users check in ChatGPT weekly. Software developers wouldn't stop using Codex.
OpenAI is not unlike any other startups who try to build their marketshare early on. No matter how much money they lose, they would be fine as long as they could raise more money than they spend. Uber is exactly the same. HN during 2015-2020 were full of comments predicting Uber's demise.
I don’t think you understand how bad OpenAI economics are. The company is burning billions just to operate. They cannot stop the training treadmill due to competitive pressure, but assuming they do that would only reduce their expanses, not increase their revenue. They would still be in the negative. We are talking about a company that has more than >$750B of infrastructure expenditure commitment for 2030.
The number of users they have checking weekly is irrelevant, most of them are free users, unless they find a way to make money from them, but their ads business has been a flop so far.
For context: Uber losses were $12B over 5 years. AWS was $5B invested over 7y.
OpenAI is projected to lose more than $14B just this year!!!
Uber burned through roughly $32 billion in cumulative losses before reaching sustained profitability.
The rough timeline:
- Founded 2009, and lost money every year for about 14 years
- Biggest single-year losses: ~$8.5 billion in 2019 (the IPO year) and ~$9.1 billion in 2022
- 2023 was its first full year of net profitability, earning about $1.9 billion
- Uber has a market cap of $153bn as of today (at a P/E of 16.5)
OpenAI has received substantially more funding than Uber, so its losses will be substantially higher (spending investor money shows up as a loss on your P&L), but again that doesn't mean anything in and of itself.
Comments
But how does that detract from the overall point that Open AI is losing billions of dollars? If there's an insatiable demand for AI compute, where's the profit?
First and foremost, it's about competent reporting. You can think a company is doomed and still expect people to report on it accurately.
Zitron continually presents things in ways that create a hyperbolic narrative. Turning routine consolidation accounting into an unexplained mystery hinting at some sort of fraud is the perfect example of that. He does it so often and in such a way that I truly believe he just doesn't understand accounting.
It doesn't take a rocket scientist to understand that OpenAI is losing money. But the question ("where's the profit?") assumes that profit is the thing being optimized for. It isn't.
There are basically three buckets here: cost of serving a query, cost of training and capex for capacity.
The first one is unit economics. The other two are bets on the future that get expensed against present revenue. A company can serve every query at a healthy gross margin (OpenAI has improved margins considerably) and still have a $9 billion loss because it spent $12 billion training a model that generates $0 this year.
Zitron constantly blends everything into a pithy "they lose money on everything" narrative, which just isn't accurate. The thing is that OpenAI could have a very different P&L if it chose to, say, stop training the next model.
The problem, obviously, is that if you stop training the next model, the competition might eat you. So right now you have a situation where the the frontier model you spent $12 billion on depreciates in about 18 months, the GPUs depreciate on a schedule nobody agrees on, and you seemingly can't stop the cycle without risking your position in the market.
This is the legitimate bear case, but the problem with Zitron is that he doesn't make it using an argument that is coherent and honest as far as the accounting is concerned. And the accounting is everything.
High growth companies often have significant negative cashflow during the early high growth era, followed by positive cashflow in the years later down the line.
This phenomenon is known as the J-curve[1], and Uber is a good example of how this can turn out absolutely fine. To some extent, the entire Venture Capital industry exists to finance precisely this dynamic!
Nb. I'm not suggesting OpenAI is fairly valued, or that they will definitely become profitable, but "OpenAI is losing billions of dollars" doesn't really mean anything in and of itself.
[1] https://www.uark.vc/blog/breaking-down-the-j-curve-the-journ... (many other similar such articles exist)
Uber is the antithesis of OpenAI, it’s not a good example. Uber was burning money on acquiring customers. OpenAI is burning money to provide their service (and the R&D they need to continue to have valuable models). They cannot just stop and turn profitable like Uber. The money they burn isn’t invested, it won’t yield a multiple of revenue in the future. It’s consumed for compute and that’s it loo
If the leaked data is to be believed, OpenAI is spending 40% of revenue on sales and marketing, which is not the OPEX profile of a product-led technology company
Broadly speaking, companies that spend 40%+ of revenue on sales and marketing end up being a bit of a drag on society. Eg. Salesforce’ product quality is far lower than winners in other sectors that sit closer to 10-15% of revenue on sales and marketing
Maybe - just as how the city of Sao Paolo implemented a ban on billboards - we can implement a law where a 3 year rolling average of sales and marketing spend cannot exceed 20% of revenue in that period
Of course they can. They could just stop training new models and milk the existing ones. A billion users check in ChatGPT weekly. Software developers wouldn't stop using Codex.
OpenAI is not unlike any other startups who try to build their marketshare early on. No matter how much money they lose, they would be fine as long as they could raise more money than they spend. Uber is exactly the same. HN during 2015-2020 were full of comments predicting Uber's demise.
I don’t think you understand how bad OpenAI economics are. The company is burning billions just to operate. They cannot stop the training treadmill due to competitive pressure, but assuming they do that would only reduce their expanses, not increase their revenue. They would still be in the negative. We are talking about a company that has more than >$750B of infrastructure expenditure commitment for 2030.
The number of users they have checking weekly is irrelevant, most of them are free users, unless they find a way to make money from them, but their ads business has been a flop so far.
For context: Uber losses were $12B over 5 years. AWS was $5B invested over 7y.
OpenAI is projected to lose more than $14B just this year!!!
Uber burned through roughly $32 billion in cumulative losses before reaching sustained profitability.
The rough timeline:
- Founded 2009, and lost money every year for about 14 years
- Biggest single-year losses: ~$8.5 billion in 2019 (the IPO year) and ~$9.1 billion in 2022
- 2023 was its first full year of net profitability, earning about $1.9 billion
- Uber has a market cap of $153bn as of today (at a P/E of 16.5)
OpenAI has received substantially more funding than Uber, so its losses will be substantially higher (spending investor money shows up as a loss on your P&L), but again that doesn't mean anything in and of itself.