[criley2]

$11 billion revenue in 2025, but how much in costs?

In 2024, they are projected to bring in $3.4 billion in revenue and lose $5 billion dollars.

They just had a massive fundraising round for $6.6 billion which at the current costs and growth is what, 6-8 months of spend?

If they bring in $11 billion in 2025, I expect them to lose at least $18 billion dollars. Good luck!

[bryanlarsen]

I imagine that OpenAI's operating revenue highly exceeds their operating costs. They spend virtually all their money on training and R&D salaries, not inference and operating salaries.

There are three likely outcomes:

1. AI plateaus. OpenAI slashes the R&D budget to become profitable with revenue in double digit billions and profit in single digit billions. Valuation likely similar to today's.

2. AI doesn't plateau. OpenAI makes a killing. (Hopefully metaphorically, not literally)

3. Scenario 1 or 2, but it's a company other than OpenAI that wins.

[throwaway314155]

Bold of you to assume AI plateauing would be somehow intrinsically obvious to everyone, or even to the minds at OpenAI. Tunnel vision is common in tech, particularly when your salary (or funding) depends upon it.

[enragedcacti]

> I imagine that OpenAI's operating revenue highly exceeds their operating costs.

The Information estimates that OpenAI is spending $4 billion just to run ChatGPT and their APIs, along with $3 billion in training and $1.5 billion in salaries.

https://www.axios.com/2024/10/03/openai-investors-profit-mon...

[tempusalaria]

Don’t agree. Inference costs have been in a race to the bottom for a while and it’s likely imo that OpenAI is gross profit negative on inference right now

[sottol]

If AI were to plateau, OpenAI would be one of many providers without a clear edge, they'd lose market share. Companies might even start competing on price. Imo, it's not clear any of the software providers would really do that well in an "AI is commodity" scenario, HW companies might though.

I'm running Phi3, Llama 3.2 and Mistral Nemo locally and they're decent enough for many things.

[__loam]

That's delusion, not imagination. Inference is far and away more expensive than R&D and training. It dominates the cost at these companies because it represents most of the unit economics. If OpenAI is not profitable, it's because each marginal customer costs more than they bring in. That's especially true for heavy users since OpenAI charges a fixed amount per customer per month.

Couple that with a lack of pricing power thanks to all the other similar products in the market.

[patwolf]

How will they continue to operate into the future with those kinds of losses? More rounds of funding? Loans? Charge more? Most companies with losses that big would be bankrupt, e.g. GM in 2009.

[silver_silver]

The true believers seem to think the compute and energy requirements will drop by an order of magnitude in the near future

[caeril]

Inference is super cheap, and getting progressively cheaper.

Greenlighting training a new foundation model is very expensive, but is also a human decision that can be postponed based on available capital.

[jckahn]

That didn’t go well for crypto.

[gerikson]

Crypto (at least proof-of-work) is purposefully designed to have rising per-unit production cost.

[matwood]

Why do you think cost would expand linearly with revenue? That's typically not how technology companies work. Compute gets cheaper over time and R&D expenses eventually cap out.

[criley2]

We're in the "add billions in dollars of datacenters" and "spin up nuclear power plants" level of infrastructure needed for their growth, so if anything, I might be underestimating the costs if they grow as much as Sam claims they can.

Didn't Sam ask TSMC to spend $7 trillion on new fabs? By comparison, $18 billion/yr spend seems very small.

[jazzyjackson]

But OpenAIs R&D isnt going to level off until they reach AGI