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Comment by bryanlarsen | Hacker News Reader

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.

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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.

> 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...

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

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.

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.

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